I have attached the Final assignment since this assignment is building off of it this will be a big deal. I will let you pick the four domains that you are comfortable with and if you want I will help

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I have attached the Final assignment since this assignment is building off of it this will be a big deal. I will let you pick the four domains that you are comfortable with and if you want I will help find articles for you as well or you can just do what you do best. Week six Final assignment is a big one.

Prior to beginning work on this written assignment, be sure to carefully review the instructions for the Final Assignment, which is due at the end of Week Six. In preparation for that assignment, you will list the four required content domains you have chosen for the Integrative Literature Review and provide a minimum list of six resources you intend to use for each domain. For the group of resources in each domain, evaluate the reliability, validity, and generalizability of the research findings and provide a rationale for including the group within the domain. These rationales should include descriptions of how the research findings will function together in the Integrative Literature Review.

Please use the format below for each of the four domains.


Name of the Domain: (e.g., Psychopharmacology)

List the complete references for each of the six resources. Format your reference list in alphabetical order according to APA style

Rationale:

One to two paragraphs including the required information noted above.

The Resources for the Integrative Literature Review

  • Must include a separate title page with the following:

    • Title of paper
    • Student’s name
    • Course name and number
    • Instructor’s name
    • Date submitted
  • Must use at least 24 scholarly sources, including a minimum of 20 from a library.
  • Must document all sources in APA style
  • Must include a separate references page that is formatted according to APA style.

Attached is week six final assignment

I have attached the Final assignment since this assignment is building off of it this will be a big deal. I will let you pick the four domains that you are comfortable with and if you want I will help
Integrative Literature Review Week Six Final The primary goal of this literature review is to integrate concepts from four different content domains within the larger field of psychology. The four content domains should be chosen from previous coursework in this program. In this paper, students will review the findings in the individual empirical articles, organize the research in a meaningful way, evaluate the reliability, validity, and generalizability of the research findings, and present an integrated synthesis of the research that sheds new light on the topics within and across the four domains. The result of a successful integrative literature review may be a significant contribution to a particular body of knowledge and, consequently, to research and practice. Therefore, before writing this literature review, substantive new research must be conducted via the Internet and within the Library for each of the four chosen domains. A minimum of six sources must be included for each of the four domains. Although content from literature reviews completed in prior courses within this program may be included, it may not constitute the total research for the individual domains addressed within this assignment. No more than four sources from previous literature reviews completed in this program may be utilized for this integrative review. The headings listed below must be used within the paper to delineate the sections of content. These sections include the following: a clear introduction that provides a general review and organizes the research in a meaningful way; a discussion in which the evidence is presented through analysis, critique, and synthesis; and a conclusion in which the discussion is drawn together in a meaningful way, the claims of the introduction are brought to a logical closure, and new research is proposed. Introduction Provide a conceptual framework for the review. Describe how the review will be organized. The questions below may be used to guide this section. What are the guiding theories within the domains? How are the domains connected? Are there competing points of view across the domains? Why is the integration of these domains important? What is the history of these domains? What are the related theories or findings? Describe how the literature was identified, analyzed, and synthesized. How and why was the literature chosen? What is your claim or thesis statement? Discussion Provide the analysis, critique, and synthesis for the review. Analysis Examine the main ideas and relationships presented in the literature across the four domains. Integrate concepts from the four different content domains within the larger field of psychology. What claim(s) can be made in the introduction? What evidence supports the claim(s) made in the introduction? Critique Evaluate the reliability, validity, and generalizability of the chosen research findings. How well does the literature represent the issues across the four domains? Identify the strengths and the key contributions of the literature. What, if any, deficiencies exist within the literature? Have the authors omitted any key points and/or arguments? What, if any, inaccuracies have been identified in the literature? What evidence runs contrary to the claims proposed in the introduction, and how might these be reconciled with the claims presented? Explain how the APA’s Ethical Principles of Psychologists and Code of Conduct might influence the reliability and/or generalizability of the chosen findings. Did the ethical issues influence the outcomes of the research? Were ethical considerations different across the domains? Synthesis Integrate existing ideas with new ideas to create new knowledge and new perspectives. Describe the research that has previously been done across these domains, as well as any controversies or alternate opinions that currently exist. Relate the evidence presented to the major conclusions being made. Construct clear and concise arguments using evidence-based psychological concepts and theories to posit new relationships and perspectives on the topics within the domains. Conclusion Provide a conclusion and present potential future considerations. State your final conclusion(s). Synthesize the findings described in the discussion into a succinct summary. What questions remain? What are the possible implications of your argument for existing theories and for everyday life? Are there novel theories and/or testable hypothesizes for future research? What do the overarching implications of the studies show? Where should the research go from this point to further the understanding of these domains and the greater study of psychology? The Integrative Literature Review Must be 20 to 30 double-spaced pages in length (not including title and references pages) and formatted according to APA style Must include a separate title page with the following: Title of paper Student’s name Course name and number Instructor’s name Date submitted Must begin with an introductory paragraph that has a succinct thesis statement. Must address the topic of the paper with critical thought. Must end with a conclusion that reaffirms your thesis. Must use at least 24 peer-reviewed sources, including a minimum of 20 from the Library. Must document all sources in APA style. Must include a separate reference list that is formatted according to APA style
I have attached the Final assignment since this assignment is building off of it this will be a big deal. I will let you pick the four domains that you are comfortable with and if you want I will help
Heterogeneity in Externalizing Problems at Age 3: Association With Age 15 Biological and Environmental Outcomes Kostas A. FantiUniversity of Cyprus Eva Kimonis The University of New South Wales Investigating heterogeneity in antisocial behavior early in life is essential for understanding the etiology, development, prognosis, and treatment of these problems. Data from the longitudinal National Institute of Child Health and Development (NICHD) study of Early Child Care were used to identify homoge- neous groups of young antisocial children differentiated on externalizing problems, internalizing prob- lems, and callous-unemotional (CU) traits using latent profile analysis (LPA). We examined how identified subgroups were differentiated on adolescent social, biological, cognitive, and environmental outcomes, controlling for dispositional and contextual antecedents during the first 2 years of life. The sample consisted of 1,167 children (52% male) followed from toddlerhood to adolescence. LPA identified a large “low problems” group (n 795; 49.9% male) as well as 3 antisocial groups at age 3: the first scored high on internalizing and externalizing problems but low on CU traits (Ext/Int,n 125), the second scored high on CU traits and externalizing problems but low on internalizing problems (primary CU variant,n 135), and the third scored high on CU traits, internalizing, and externalizing problems (secondary CU variant,n 112), and these differences persisted into adolescence. Primary and secondary CU variants were further differentiated from one another on adolescent measures of aggression (reactive and relational), biological indices (cortisol, heart rate), cognitive abilities, and parental psy- chopathology, after controlling for early life risk factors (i.e., maternal sensitivity, difficult temperament, and maternal depression). We discuss implications of our findings for research, theory, and practice on early childhood externalizing problems. Keywords:internalizing and externalizing problems, callous-unemotional traits, primary and secondary variants, cortisol and heart rate, parenting Antisocial behaviors developing early in life are a risk factor for stable and persistent problems that continue into later adulthood, placing the child on a developmental pathway of low academic achievement, poor parent and peer relations, and other maladaptive outcomes (Coie & Dodge, 1998;Fanti & Henrich, 2010;Keiley, Lofthouse, Bates, Dodge, & Pettit, 2003). Early in life these behaviors take the form of aggression, defiance, and destructive behavior, defined as externalizing problems, and have been found to precede child, adolescent, and adult antisocial problems (e.g., Achenbach, 1991;Fanti & Henrich, 2010;Leadbeater, Thompson, & Gruppuso, 2012;Moffitt, 1993). Importantly, these externaliz- ing problems are marked by heterogeneity, with existing subtyping approaches proposing distinct subgroups according to co- occurring psychopathology or deficits in prosocial development (i.e., CU traits). Two approaches to understanding heterogeneity in antisocial behavior have received considerable attention in the literature. The first differentiates antisocial children into those with andwithout internalizing problems, including anxiety and depres- sion (e.g.,Fanti & Henrich, 2010;Keiley et al., 2003). This research suggests that distinct subgroups of children exist as early as toddlerhood that are either characterized by high ex- ternalizing and normative levels of internalizing problems or by co-occurring externalizing and internalizing symptoms. Cross- sectional and longitudinal studies suggest that these two sub- groups can be differentiated on dispositional, environmental, and biological factors (Beauchaine, Gartner, & Hagen, 2000; Fanti & Henrich, 2010;Leadbeater et al., 2012;Schoorl, Van Rijn, De Wied, Van Goozen, & Swaab, 2016). The second approach to subtyping antisocial children differen- tiates them into those with and without CU traits (i.e., low guilt, low empathy;Fanti, Demetriou, & Kimonis, 2013;Frick, Ray, Thornton, & Kahn, 2014), with emerging evidence supporting CU heterogeneity as early as preschool and toddlerhood (Kimonis, Fanti, Anastassiou-Hadjicharalambous, et al., 2016;Willoughby, Waschbusch, Moore, & Propper, 2011). Children with stable ex- ternalizing problems without CU traits tend to score high on anxiety and to be more fearful, whereas those with stable high externalizing problems with co-occurring CU traits tend to score at average levels of anxiety and low on behavioral and physiological measures of fear (Fanti, Panayiotou, Lazarou, Michael, & Geor- giou, 2016;Frick et al., 2014). Thus, the group of children with co-occurring externalizing and internalizing problems might re- semble antisocial youth low on CU traits. This article was published Online First April 13, 2017. Kostas A. Fanti, Department of Psychology, University of Cyprus; Eva Kimonis, School of Psychology, The University of New South Wales. Correspondence concerning this article should be addressed to Kostas A. Fanti, Department of Psychology, University of Cyprus, P.O. Box 20537, CY 1678, Nicosia, Cyprus. E-mail:[email protected] This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Developmental Psychology© 2017 American Psychological Association 2017, Vol. 53, No. 7, 1230 –12410012-1649/17/$12.00http://dx.doi.org/10.1037/dev0000317 1230 Adding complexity, accumulating evidence supports further het- erogeneity within antisocial children high on CU traits. This liter- ature consistently identifies two groups with equivalent high levels of CU traits, one with co-occurring internalizing problems (anxi- ety, depression) known as secondary CU variant, and a second with low to average anxiety levels known as primary CU variant (Fanti, Demetriou, et al., 2013;Kimonis, Skeem, Cauffman, & Dmitrieva, 2011). Exposure to adverse or abusive home environ- ments is thought to be critical to the development of secondary CU traits, whereas biological risk factors play a more prominent role in developmental accounts of the primary variant (Karpman, 1941; Kimonis et al., 2011). Secondary CU variants show biological correlates associated with trait anxiety (Kimonis, Fanti, Goulter, & Hall, 2016;Kimonis, Frick, Cauffman, Goldweber, & Skeem, 2012), which are in the opposing direction to fearless, emotionally hyporeactive primary variants, thus more closely resembling chil- dren with co-occurring externalizing and internalizing problems (seeFanti, 2016for a review). The present study aims to integrate for the first time these separate literatures focused on subtyping antisocial children, to gain a more complete understanding of developmental outcomes of children with externalizing problems disaggregated on the basis of internalizing problemsandCU traits. We tested whether three groups of antisocial youth could be identified as early as age 3: a group scoring high on both externalizing and internalizing prob- lems but low on CU traits (Ext/Int); a group scoring high on CU traits and externalizing problems, but not internalizing problems (primary CU); and a group scoring high on CU traits, internalizing, and externalizing problems (secondary CU). We sought to com- pare identified subgroups on adolescent outcomes measured at age 15. Elucidating individual differences in the developmental out- comes of children with more homogeneous presentations of early antisocial behavior (i.e., subtypes) is of great importance toward improving models of antisocial behavior and providing avenues for prevention and intervention efforts. The majority of studies subtyping antisocial youth on the basis of CU traits and internalizing problems focus on adolescents and rely on cross-sectional designs using retrospective reports of dys- functional parenting practices, highlighting the need for longitu- dinal research. As such, it is unclear whether subtyping models detailed above are useful for understanding antisocial behavior within young children. The current study aims to test whether antisocial subtypes can be identified in preschoolers, and whether they predict similar adolescent outcomes to those documented in the literature. Together, this literature finds that adolescent sec- ondary CU variants (high internalizing problems) show greater histories of social and environmental adversity and poorer self- regulation relative to primary variants (low internalizing), despite showing equivalent levels of CU traits (Kahn et al., 2013;Kimonis et al., 2011). Primary CU variants show low levels of emotional arousal fitting with “emotionally stable” descriptions (Hicks, Markon, Patrick, Krueger, & Newman, 2004;Kimonis et al., 2012, 2016), and are more likely to engage in relational forms of ag- gression necessitating better developed social skills to facilitate manipulation of others (Rosan, Frick, Gottlieb, & Fasicaru, 2015). By contrast, secondary CU variants more closely resemble antiso- cial youth with comorbid internalizing problems with their pro- pensity toward emotional dysregulation and reactive aggression(Bubier & Drabick, 2009;Eisenberg et al., 2009;Fanti & Henrich, 2010). The many differences between these antisocial subgroups sug- gests they are likely to also differ in other ways, such as in cognitive and academic functioning; factors that have been studied extensively in antisocial youth more generally. Low cognitive and academic functioning are common among children with external- izing problems, with or without co-occurring internalizing prob- lems, suggesting they may represent a general risk factor for antisocial subgroups (Fanti & Henrich, 2010;Masten et al., 2005; Moffitt, 1993). However, the poor self-regulation of Ext/Int and secondary CU variants suggests they could show poorer cognitive abilities (IQ/achievement) relative to the more emotionally and behaviorally regulated primary CU group. The primary group may drive hypotheses that individuals with CU traits show average to above average cognitive abilities (Cleckley, 1976). Agreeing with this suggestion, individuals with co-occurring internalizing and externalizing problems tend to exceed those exhibiting pure prob- lems in terms of greater functional interference in daily life and more impairment across domains such as educational and social functioning (Fanti & Henrich, 2010;Ingoldsby et al., 2006;New- man, Moffitt, Caspi, & Silva, 1998). One reason for poor academic achievement among children with externalizing problems is the considerable disruption they cause within school contexts. Similarly, their home environments are considerably disruptive and marked by conflicted parent-child relationships (Ingoldsby et al., 2006). Parent-child conflict has been identified as a common risk factor for multiple forms of childhood psychopathology (Burt, Krueger, McGue, & Iacono, 2003), and thus may be relevant to all externalizing subtypes. Importantly, the child’s antisocial behaviors might elicit parent- child conflict, which, in turn, exacerbates the child’s antisocial behaviors, particularly when the conflict occurs with a depressed mother (Lytton, 1990;Marmorstein & Iacono, 2004). In fact, parental psychopathology is a risk factor for both internalizing and externalizing problems (Fanti & Henrich, 2010;Fanti, Panayiotou, & Fanti, 2013;McLeod & Shanahan, 1996). For example, children of depressed mothers are almost five times more likely to develop depression by adolescence than those without depressed mothers (Murray et al., 2011), with both genetic and environmental mech- anisms contributing to this intergenerational transmission. Impor- tantly, externalizing, internalizing, and CU characteristics have been associated with increases in maternal depression and distress (Fanti & Munoz Centifanti, 2014; Fanti, Panayiotou, et al., 2013), although no prior work investigated such child effects by compar- ing Ext/Int, primary, and secondary CU subgroups. To date, this line of research has been limited to environmental measures and cognitive tasks and is yet to examine whether differences between CU variants extend to neurobiological mea- sures. For instance, low heart rate and low cortisol levels are two biomarkers linked to antisocial behavior, and each has distin- guished externalizing individuals with and without CU traits, or with and without internalizing problems (Alink et al., 2008;Cima, Smeets, & Jelicic, 2008;Fanti, 2016;Frick et al., 2014;Loney, Butler, Lima, Counts, & Eckel, 2006;Ortiz & Raine, 2004;Raine, Venables, & Mednick, 1997;Stadler et al., 2011). However, across these literatures results are inconsistent and suggest the relation- ship between these biological indices and antisocial behavior may be more complex than previously thought (e.g.,Alink et al., 2008; This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1231 HETEROGENEITY IN ANTISOCIAL BEHAVIOR Fanti, 2016;Hawes, Brennan, & Dadds, 2009). Thus, investigating heart rate and cortisol in antisocial subgroups has potential to shed light on the role of neurobiological factors in the development of antisocial behavior. Low heart rate might characterize emotionally hyporeactive antisocial individuals with primary CU traits, whereas hyperreactive children with co-occurring externalizing and internalizing problems might show high average heart rate (see Fanti, 2016for a review). Secondary CU variants might also be characterized by high heart rate due to their emotional dysregula- tion (Beauchaine et al., 2000), such that high heart rate may be a biological marker for antisocial behavior co-occurring with inter- nalizing problems irrespective of levels of CU traits (Fanti, 2016). Findings regarding the association between cortisol and exter- nalizing problems are especially equivocal with some studies suggesting that externalizing problems are associated with low cortisol levels and others suggesting no association or a positive association (seeAlink et al., 2008for a meta-analysis). In fact, this meta-analysis identified only a small association between cortisol levels and externalizing problems (d .10), which was positive among preschoolers, negative among school-age children, and dropped to nonsignificance in adolescence. The authors concluded that cumulative exposure to high levels of environmental stress may explain the lower levels of basal cortisol identified in antiso- cial children by school age, and that heterogeneity in externalizing problems might account for the small effect size. The nonsignifi- cant association identified during adolescence calls for more re- search on this developmental period and the need for longitudinal research spanning early childhood to adolescence. Covariates: Early Risk Factors Investigation of adolescent outcomes associated with antisocial subgroups must consider the extensive literature on early risk factors, particularly those associated with CU traits. Low maternal sensitivity has emerged as an important early predictor of child externalizing problems at high levels of CU traits, likely reflecting its key role in the development of moral emotions and empathic responding (Frick & Morris, 2004;Kochanska, Kim, Boldt, & Yoon, 2013;Waller et al., 2014). In their longitudinal study, Barker and colleagues also found that maternal postnatal depres- sion (PND) and child temperament predicted the co-occurrence of externalizing problems and CU traits (Barker, Oliver, Viding, Salekin, & Maughan, 2011). Thus, we controlled for these age 3 antecedents to ensure that any observed associations between latent classes and adolescent outcomes were not accounted for by risk factors occurring during the first three years of life. The Present Study A large number of factors are associated with childhood anti- social behavior, but the many inconsistencies in the literature may be clarified by a more comprehensive consideration of heteroge- neity within this population. That is, studies that fail to consider comorbidity between externalizing problems, internalizing prob- lems, and CU traits together risk missing important distinctions between these antisocial subgroups that may be critical to inform- ing the field’s understanding of the development of antisocial behavior. The overarching aim of this study is to identify sub- groups of young children with externalizing problems differenti-ated on these variables. We hypothesize that we will identify three groups of children showing early childhood antisocial behavior, based on three separate but complementary lines of subtyping research aimed at better understanding heterogeneity in childhood antisocial behavior: externalizing/internalizing (Ext/Int), primary CU (Ext/CU) and secondary CU (Ext/Int/CU) variants. We hypothesize that subtypes identified at preschool age will predict adolescent outcomes aligning with the existing literature base. That is, we hypothesize that primary and secondary CU variants will show the greatest externalizing problems and CU traits at age 15, with levels indistinguishable from one another, supporting their developmental stability. We predict that children showing co-occurring internalizing and externalizing problems (Ext/Int and secondary CU) will continue to show the greatest levels of adolescent internalizing problems. With regard to social, biological, cognitive, and parental measures, we hypothesize that primary CU variants will show higher self-regulation, social skills, relational aggression, and cognitive/achievement functioning, and lower heart rate relative to secondary CU variants. Due to the inconsistencies reported in the literature, we did not have any specific predictions for cortisol level differences. Further, we hy- pothesize that secondary CU variants will show greater reactive overt aggression compared with all other groups, and that comor- bid groups (Ext/Int, secondary CU) would both show poorer self- regulation, social skills, cognitive/academic functioning, and greater maternal depression relative to primary CU and low-risk groups. We predict parent-child conflict will be higher in all externalizing groups relative to low risk youth. To investigate the unique influence of these factors, we examine these associations covarying early risk factors associated with externalizing problems at high levels of CU traits (difficult temperament, maternal PND, and low sensitivity). The study’s hypotheses are presented inTable 1for clarity. Method Participants The present study used data from the NICHD Study of Early Child Care. This study was conducted by the NICHD Early Child Care Research Network supported by NICHD through a cooper- ative agreement that called for scientific collaboration between the grantees and NICHD staff. Participants were recruited from dif- ferent hospitals across 10 locations in the United States based on conditional random sampling that was used to assure that the sample was representative of single mothers, poverty status, ethnic minority, and low maternal education. Sampling information is described in detail elsewhere (https://www.nichd.nih.gov/research/ supported/seccyd/Pages/overview.aspx). The analyses for the cur- rent study were based on 1,167 children (51.7% male) whose mothers completed the Child Behavior Checklist (CBCL) at age 3. At age 15, the sample size ranged from 834 to 975 adolescents based on the behavioral, questionnaire, and biological measures used in analyses. To retain all participants, outcome analyses were conducted using the multiple imputation feature in SPSS 22. The sample used for the current study was diverse in terms of ethnicity (77.5% were White, 6% were of Hispanic descent, 11.7% were African American, 1.3% were Asian, and 3.5% represented other minority groups) and family income (70% scored above the pov- This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1232 FANTI AND KIMONIS erty threshold; 20.4% scored below the poverty threshold at some point during data collection; 9.6% scored below the poverty threshold continuously during data collection). Based on inter- views with the mothers during the first year of data collection, 10% of mothers had not completed high school and 21% were single. Grouping Variables at Age 3 Mothers completed the preschool version of the Achenbach System of Empirically Based Assessment (ASEBA;Achenbach & Rescorla, 2000) at age 3. The current study used items related to externalizing problems (26 items), anxiety/depression (11 items), and CU traits (5 items; seeWilloughby, Mills-Koonce, Gottfred- son, & Wagner, 2014;Willoughby et al., 2011). Item 58 (punish- ment doesn’t change his or her behavior) that was included in the CU index was removed from the externalizing composite. Reli- ability/validity information of the Preschool ASEBA subscales and the CU measure based on the NICHD data are reported in multiple studies (e.g.,Fanti & Henrich, 2010;Fanti, Panayiotou, et al., 2013;Willoughby et al., 2011,2014). Possible Early Life Covariates Maternal sensitivity.Maternal sensitivity was calculated from ratings of mothers’ behavior toward the child during a videotaped interaction using semistructured free-play conditions at 6, 15, and 24 months (NICHD Early Child Care Research Net- work, 1998). A summed composite score of maternal sensitivity at each age was created from coding of the videotapes for emotional support, positive affect, lack of hostility, and respect of the child’s autonomy or efforts using a 4-point scale. Scores were averaged from 6 to 24 months with good internal consistency ( .75). Interrater reliabilities of the composites at each age based on intraclass correlations across raters ranged from .83 to .87.Child temperament.Temperament was assessed with the Infant Temperament Questionnaire (Medoff-Cooper, Carey, & McDevitt, 1993). When the child was 1 and 6 months old, mothers were asked to respond to 38 items which were developmentally appropriate for young infants (rated on a 1- to 6-point scale from “almost never”to“almost always”). The items provide scores on five subscales: Activity, Adaptability, Approach, Mood, and In- tensity, and all items can be combined into a single difficult temperament scale. Because the stability from 1 to 6 months was high,r .77,p .001, we created a difficult temperament scale based on the average score of all the items from the first and sixth month collection ( .70). Postnatal depression.Mothers completed the Center for Ep- idemiological Studies Depression Scale (CES-D;Radloff, 1977) when the study children were 1 month old. Mothers rated the frequency of their own depressive symptoms during the past week ( .91). Age 15 Outcome Measures Externalizing and internalizing problems.Mothers rated adolescents’ anxiety/depression and externalizing problems at age 15 using the school age version of the ASEBA (Achenbach, 1991). Items were summed to compute externalizing and internalizing problem scores. CU traits.The Youth Psychopathic Traits Inventory (YPI; Andershed, Kerr, Stattin, & Levander, 2002) is a self-report ques- tionnaire that assesses three dimensions of psychopathy. In the current study, participating children completed the 15-item Callous-Unemotional (CU, i.e., Callousness, Unemotionality, and Remorselessness) subscale ( .82). Each item is scored on a 4-point Likert-type scale ranging from “Does not apply at all”to “Applies very well.” Table 1 Hypotheses in Relation to Current Study Findings Adolescent outcomes Ext/Int Secondary (Ext/Int/CU) Primary (Ext/CU) Current study findings Age 15 outcomes Externalizing problems Moderate High High All groups Low, secondary Ext/Int Internalizing problems High High Low Secondary, Ext/Int Primary, low CU traits Low High High Secondary, primary Ext/Int, low Social outcomes Relational aggression Low Low High Primary Secondary, low Reactive aggression Low High Low Secondary Primary, low Social skills Low Low Moderate Low Primary, secondary Biological outcomes Heart rate No hyp. High Low Secondary Primary Cortisol No hyp. No hyp. No hyp. Primary, low Secondary Cognitive outcomes Self-regulation Low Low High Primary, low Secondary WJ-R cognitive score Low Low High Primary, low Secondary WJ-R achievement Low Low High Primary, low Secondary Parenting outcomes Conflict High High High All groups Low Maternal depression High High Low Secondary Primary, low Note. The three columns associated with each identified group report how we expected each hypothetical group to score on adolescent outcome measures: Low, moderate, or high. We also specify instances where we did not have a specific hypothesis (No hyp. no hypothesis). The last column of the table indicates how the groups were found to differ on each measure, enabling the reader to determine whether the hypotheses were supported. Ext/Int externalizing/internalizing; Low low risk group; CU callous-unemotional; WJ-R Woodcock-Johnson Psychoeducational Battery–Revised. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1233 HETEROGENEITY IN ANTISOCIAL BEHAVIOR Social Outcomes Aggression.The six items used to create the Relational Ag- gression scale, based on an adaptation of theCrick and Grotpeter (1995)relational aggression instrument, had modest internal reli- ability ( .68). Reactive overt aggression was also based on six items adapted from the rating instrument developed byDodge and Coie (1987), with a Cronbach’s alpha of 0.87. Adolescents rated how true each of the items is of them on a 4-point scale, ranging from “not at all true”to“completely true.” Social skills.Mothers completed the 40-item Social Skills Rating System (Gresham & Elliott, 1990), which provides a broad assessment of child social skills. The response levels range from 0 (Never)to2(Very Often). The total scale, which is based on four subscales (Cooperation, Assertiveness, Responsibility, and Self- Control), had high internal reliability ( .93) Biological Outcomes Heart rate.Heart rate readings were taken using a blood pressure cuff and stethoscope (i.e., no automated instruments). Heart rate readings were taken a second time if the child appeared anxious or if the initial readings were high, and this second measurement was used in analyses. For uniformity across data collection sites, the heart rate was taken with the child seated using the nondominant arm. The majority of exams were conducted by nurse practitioners. Cortisol.Adolescents and their parents were given detailed instructions on the saliva collection procedure and were trained in the use of salivettes for collections in the morning hours during three consecutive school days. Immediately after collection they completed a daily diary reporting on the time and date of sample collection, quality of sleep, medication used, average minutes elapsed from awakening to cortisol acquisition, and average time of awakening. They also reported their general sleep problems (7 items indicating greater difficulty falling and staying asleep) and smoking habits. These variables were included as covariates in analyses. Details on the assay procedure are provided inRoisman et al. (2009). Samples were assayed in duplicate and were aver- aged for analyses. Cortisol values (fxg/dl) were averaged over the 3 days of data collection since the correlations among the three samples were large by Cohen’s criteria (rs ranged from .38 to .52 across the 3 days of sampling; allps .001). Outlier values falling 3SDabove the mean were assigned the next highest value that was mean 3SD. Raw untransformed data were used in analyses since averaged cortisol values were only moderately skewed (skew 1.08). Cognitive Outcomes Self-regulation.Self-regulation was assessed by averaging the standardized scores on a measure of self-reported impulse control and two behavioral self-control tasks, the Tower of London and the Stroop task. Self-reported impulse control was measured with a seven-item questionnaire assessing reactions to external constraints, taken from the Weinberger Adjustment Inventory (Weinberger & Schwartz, 1990). The measure asked adolescents to rate (1 falseto 5 true) how closely their behavior matched a series of statements (e.g., “I do things without giving themenough thought,” reverse scored), resulting in an impulse control composite score ( .82). Abehavioral measure of impulse controlwas generated with a computerized version of the Tower of London task (Steinberg et al., 2008), which was used to measure the adolescent’s ability to inhibit acting before a plan is fully formed. For analyses, the variable of interest was the average latency (in milliseconds) to first move for more complex five-, six-, and seven-move problems, indicating greater impulse control. Response inhibitionwas assessed with the computerized version of the classic Stroop color-word task. Adolescents completed two 48-trial experimental blocks, the first of which included an equal mix of neutral and incongruent (e.g., the word “blue” printed in yellow) trials, and the second of which (‘unequal block’) included a greater number of neutral than incongruent trials. We calculated an interference score as the difference between the average re- sponse time on incongruent versus neutral trials within unequal blocks, and reverse-scored this value so that higher scores repre- sented stronger response inhibition. Cognitive/academic achievement.The Woodcock-Johnson Psychoeducational Battery–Revised (WJ–R;Woodcock, Johnson, & Mather, 1990) consists of two major parts: the Tests of Cogni- tive Ability and the Tests of Achievement. At age 15, adolescents’ cognitive ability was assessed with two subscales, Picture Vocab- ulary and Verbal Analogies. Achievement was assessed using the Passage Comprehension and Applied Problems subscales. We used standard scores in analyses, which are based on a mean of 100 and a standard deviation of 15. Parenting Related Measures Conflict.The Child-Parent Relationship Scale (Pianta, 1992) is a 15-item questionnaire designed to assess the parent’s feelings and beliefs about his or her relationship with the adolescent on a 5-point, Likert-type scale ranging from 1 (Definitely does not apply)to5(Definitely applies). For the purposes of the current study, mothers reported on their Conflict (7 items, .87; i.e., always struggling with each other) with their adolescents. Maternal psychopathology.Maternal depression was as- sessed at age 15 with the same CES-D measure used in infancy ( .92). Plan of Analyses Identifying variants.LPA in Mplus 7 (Muthén & Muthén, 2010) was used to identify distinct subgroups of individuals based on their scores on CU traits, externalizing problems, and anxiety/ depression assessed at age 3. LPA identifies different latent classes by decomposing the covariance matrix to highlight relationships among individuals, and clusters individuals that are similar on the constellation of indicators into latent classes (Bauer & Curran, 2004). Models that specify different numbers of classes are tested. The Bayesian information criterion (BIC) and Lo-Mendel-Rubin (LMR) statistics are used as statistical criteria to compare models to identify the optimal number of groups to retain (Nylund, Asp- arouhov, & Muthén, 2007). The model with the lowest BIC value is preferred. A nonsignificant chi-square value (p .05) for the LMR statistic suggests that a model with one fewer class is preferred. Further, average posterior probabilities and entropy val- ues equal to or greater than .80 indicate clear classification and This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1234 FANTI AND KIMONIS greater power to predict class membership (Clark & Muthén, 2009). Identifying potential covariates.We used multinomial logis- tic regression analyses (MLR) in IBM SPSS 22 to identify poten- tial early life covariates (i.e., difficult temperament, maternal de- pression, and maternal sensitivity) to include in analysis of covariance (ANCOVA). Outcome analyses.We first used ANCOVA (controlling for significant covariates) to compare the identified groups on age 3 and age 15 CU traits, externalizing, and internalizing problems. Second, we used ANCOVA to compare the groups identified at age 3 on adolescent outcomes collected at age 15. The dependent variables were grouped into four categories: (a) social, (b) biolog- ical, (c) cognitive, and (d) parent-related outcomes. Because com- paring groups identified with LPA might underestimate standard errors of the parameters,Clark and Muthén (2009)recommend using a more stringent alpha level for comparisons. Following this recommendation and because of the multiple comparisons per- formed in the current study, the Bonferroni correction was used in all analyses. Results LPA Findings To identify the optimal number of groups to retain, we com- pared two LPA models, with the first model excluding covariates and the second model including the three hypothesized covariates (difficult temperament, maternal depression, and maternal sensi- tivity): 1. For the model with no covariates, the BIC statistic in- creased from Class 5 (BIC 17,040.83) to Class 6 (BIC 17,073.25) and decreased from Class 4 (BIC 17,145.69) to Class 5. In addition, the LMR statistic fell out of significance for the six-class model (p .59). Thus, the five-class model better represented the data based on the BIC and LMR statistics. The mean posterior probability scores ranged from .89 to .94 and the entropy value was .82. 2. For the model including the three covariates, the BIC statistic increased from Class 4 (BIC 16,870.55) to Class 5 (BIC 16,933.63) and decreased from Class 3 (BIC 16,908.41) to Class 4. In addition, the LMR statistic fell out of significance for the five-class model (p .46). As a result, the four-class model better repre- sented the data. The mean posterior probability scores ranged from .90 to .93 and the entropy value was .81, suggesting that the identified classes were well separated Because both the five-class (without covariates) and four-class (including covariates) models identified similar high-risk groups, we decided to use the more parsimonious four-class model includ- ing covariates.Figure 1shows standardizedz-scores by group on each grouping variable. The majority of the sample scored below average (n 795; 49.9 male) on all of the measures under investigation. This group is described hereafter as the “low prob- lem” group. Children in the Ext/Int group (n 125; 52.8% male)scored at approximately 1SDabove the mean on anxiety/depres- sion and externalizing problems, but below average on CU traits. Children in the secondary CU group (n 112; 55.4% male) scored 1SDabove the mean on all LPA measures. Children in the primary CU group (n 135; 57.8% male) scored below average on anxiety/depression and approximately 1SDabove the mean on externalizing problems and CU traits. According to 2analyses, the identified groups were not differentiated in terms of ethnicity, 2(20,N 1,167) 13.88,p .54, or sex, 2(3,N 1,167) 6.30,p .09, and as a result these demographics were not included in further analyses. Testing for Potential Early Life Covariates The analysis comparing the identified groups using MLR was significant, 2(9,N 1,167) 114.82,p .001. Maternal sensitivity, 2(3,N 1,167) 26.59,p .001, difficult temper- ament, 2(3,N 1,167) 32.75,p .001, and maternal PND, 2(3,N 1,167) 21.54,p .001, significantly predicted the identified subgroups.Table 2incorporates odds ratios to compare the groups, which reflect the odds likelihood of being in one group over the other, based on the level of the independent variable. As shown inTable 2, children who experienced less maternal sensi- tivity were more likely to be in the secondary CU group compared with the low problem and Ext/Int groups. The primary CU group also scored higher than the low problem group. Children charac- terized by difficult temperament were more likely to be classified in the secondary, primary, and Ext/Int groups compared with the low problem group. Finally, children whose mothers scored high on PND were more likely to be classified in the secondary and Ext/Int groups than the low problem group. Thus, maternal sensi- tivity, difficult temperament, and maternal PND were included as covariates in all follow-up ANCOVAs. Comparing the Identified Groups on Age 3 Grouping Variables The ANCOVA results, shown inTable 3, suggested that the low problem group had the lowest levels of externalizing problems and Figure 1.Groups identified using latent profile analysis at age 3 (N 1,167; 95% confidence intervals are included in the figure) after controlling for covariates. Anx/Dep anxiety/depression. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1235 HETEROGENEITY IN ANTISOCIAL BEHAVIOR CU traits, and scored similarly low on anxiety/depression as the primary CU group. The Ext/Int and secondary CU groups had the highest scores on anxiety/depression, reaching borderline clinical scores (Achenbach, 1991). The secondary CU group had the highest scores on externalizing problems (borderline clinical), followed by the primary CU and Ext/Int groups. The primary CU group also scored higher than the Ext/Int group. Regarding CU traits, the secondary group scored higher than the primary group, and both groups scored higher compared with the remaining groups. Analyses of Age 15 Outcomes Analyses involving age 15 outcomes are shown inTables 3and 4. The reported results are based on analyses of the data imputed using the multiple imputation feature in SPSS 22. For all analyses Bonferroni post hoc tests are reported, which set the statistical significance level at .008 (i.e., for 6 comparisons). All findings are also reported inTable 1in relation to the study’s hypotheses. Evidence for Stability of LPA-Related Variables From Age 3 to Age 15 As shown inTable 3, children in the low problem group scored lower on externalizing problems at age 15 compared with all other groups. The secondary group scored similarly on externalizing problems as the primary CU group and higher than the Ext/Intgroup, approaching borderline clinical levels. Children in the Ext/ Int and secondary CU groups continued scoring high on anxiety/ depression compared with primary CU and low problem groups. Regarding CU traits, primary and secondary CU groups scored higher than all other groups, but did not differ from one another. The findings support the stability of traits relevant to antisocial subtypes from toddlerhood to adolescence (12 years later). Social outcomes.As shown inTable 4, primary CU variants were more likely to engage in relational aggression than the low problem and secondary CU groups. In contrast, secondary variants were more likely to engage in reactive aggression than the low problem and primary CU groups.Further, primary and secondary CU variants scored similarly on the measure of social skills and lower than the low problem group. The Ext/Int group did not differ from any other group on measures of aggression and social skills. Biological measures.As reported inTable 4, the secondary CU group had higher heart rate compared to the primary group, with the remaining groups falling between these two groups and undifferentiated from one another. In terms of cortisol, the sec- ondary CU group scored significantly differently than the primary and low-risk groups, with the secondary group showing lower cortisol concentrations compared with both groups. In addition, group differences remained significant,F(3, 816) 2.94,p .05, 2 .01, after controlling for sleep problems, time awakening, medication used, smoking, and average minutes elapsed from awakening to cortisol acquisition. Table 2 Multinomial Logistic Regression Analyses Comparing the Identified Groups on Early Life Covariates Group comparisons based on odds ratios Covariates Primary vs. low Secondary vs. low Ext/Int vs. low Primary vs. Ext/Int Secondary vs. Ext/Int Primary vs. secondary Mat. sensitivity .68 (.55–.85).55 (.42–.70).84 (.64–1.09) .82 (.60–1.11) .65 (.47–.90)1.25 (.93–1.67) Difficult temp. 1.84 (1.22–2.76)2.44 (1.49–3.99)3.02 (1.89–4.83).61 (.35–1.06) .81 (.44–1.50) .75 (.42–1.33) Mat. depression 1.02 (.99–1.05) 1.04 (1.02–1.06)1.04 (1.02–1.06).99 (.97–1.02) 1.00 (.97–1.03) .98 (.96–1.02) Note.N 1,167. Antecedent variables are: maternal sensitivity (Mat. sensitivity), difficult temperament (Difficult temp.), and maternal depression (Mat. depression); Ext/Int externalizing/internalizing. Comparisons are based on odds ratios; 95% confidence intervals are in parentheses. Only comparisons at p .008 are reported as significant. Table 3 Comparisons Between the Identified Groups on Age 3 (N 1,167) LPA Variables and Age 15 Outcomes Indicating Stability Over Time, After Controlling for Significant Early Life Covariates Age 3 and age 15 outcomes Low Ext/Int Secondary PrimaryFvaluedf 2 LPA measures—age 3 Externalizing problems 44.43 a(.22)58.07 b(.55)63.80 d(.60)59.75 c(.48)482.11 3 .56 Anxiety/depression 46.38 a(.26)61.99 b(.65)63.99 b(.70)48.03 a(.56)255.11 3 .40 CU traits 1.22 a(.04)1.50 a(.10)3.95 c(.11)3.29 b(.08)288.35 3 .43 Outcomes—age 15 Externalizing problems 48.06 a(.37)56.11 b(.90)60.59 c(.95)57.99 bc(.77)45.28 3 .11 Anxiety/depression 48.77 a(.37)57.93 b(.21)58.64 b(.98)50.61 a(.18)17.08 3 .04 CU traits 28.38 a(.19)27.79 a(.51)31.23 b(.54)30.64 b(.43)8.38 3 .03 Note. Estimated marginal means (SE); different superscripts ( a,b,c,d ) denote significant differences between groups in post hoc pairwise comparisons using the Bonferroni procedure. Only pairwise comparisons atp .008 are reported as significant. AllFstatistics are significant at thep .01 level.Tscores are reported for externalizing problems and anxiety/depression. LPA latent profile analysis; Ext/Int externalizing/internalizing; CU callous- unemotional. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1236 FANTI AND KIMONIS Cognitive measures.The secondary CU group was charac- terized by lower self-regulation compared with the primary CU and low problem groups (seeTable 4). Regarding WJ-R cognitive and achievement scores, the secondary CU group scored signifi- cantly lower than the low problem and primary CU groups, but not the Ext/Int group. Parent-related measures.All externalizing groups scored higher on the measure of conflict with parents relative to the control group (seeTable 4). Further, mothers of children in the secondary CU group were more likely to be depressed compared to all other groups, except the Ext/Int group. Discussion The present longitudinal study set out to integrate parallel lines of research supporting heterogeneity in childhood externalizing problems by examining adolescent outcomes differentiating pre- schoolers subgrouped on the basis of externalizing and internaliz- ing symptoms and CU traits. We were particularly interested in whether primary and comorbid secondary variants of CU traits, previously identified only in adolescent samples, existed in young children. We were further interested in whether the secondary CU group could be differentiated from children with comorbid exter- nalizing and internalizing problems in the absence of CU traits, and whether these distinctions identified in early childhood dem- onstrated developmental stability into adolescence. Findings indi- cated that preschool children with elevated externalizing problems could be disaggregated into three subgroups, two of which showed nonnormative levels of CU traits ( 1SDabove the sample mean) and one that was low on CU traits. Comorbid groups (Ext/Int and secondary CU variants [Ext/Int/CU]) were undifferentiated across the full range of adolescent outcomes investigated, including anx- iety/depression levels, social, cognitive, biological, and parent- related outcomes. In contrast, there were a number of differences between high CU variants with primary variants showing greater self-regulation, relational aggression, intellectual and academic functioning, lower heart rate,highermorning cortisol levels, and less maternal depression than secondary variants. These differ-ences persisted after controlling for early life risk factors, includ- ing difficult temperament, maternal depression, and maternal sen- sitivity. We discuss these findings in turn below. Our findings suggest that two prior lines of study, examining co-occurring externalizing and internalizing problems on the one hand, and externalizing problems with or without CU traits on the other, may be missing an important piece of the puzzle by failing to consider all three factors together: internalizing and externaliz- ing problems and CU traits. To date, high-anxious secondary CU variants have only been studied among adolescent populations and are similarly identified as lower in self-regulation and higher in reactive aggression and depression (e.g.,Fanti, Demetriou, et al., 2013;Kimonis et al., 2011). Adding to this work, current findings provide novel evidence that secondary variants also show lower IQ and achievement scores compared with primary CU variants. Also consistent with adolescent subtyping studies is our finding that primary and secondary CU variants showed comparable levels of CU traits and externalizing problems in adolescence (Fanti, Dem- etriou, et al., 2013), despite secondary variants presenting with the highest levels as preschoolers. Further, both groups showed low social skills during adolescence, such as assertiveness and respon- sibility, pointing to the low prosocial behavior of both groups. These findings are important because CU traits have increas- ingly been used to designate an important subgroup of antisocial youth at heightened risk for early onset and persistent conduct problems, and are incorporated into theDiagnostic and Statistical Manual of Mental Disorders(5th ed.;American Psychiatric As- sociation, 2013) diagnosis of conduct disorder as a limited proso- cial emotions (LPE) specifier (Frick et al., 2014); however, youth scoring high on CU traits or diagnosed with conduct disorder with LPE could fall into either primary or secondary groups, which is likely to be relevant to their course, prognosis, and individual treatment needs, although these are questions in need of further study. The uptake and influence of the primary/secondary CU subtyping literature is likely to be a slow process just as it has taken decades to influence theory, research, and practice to recog- nize the importance of CU traits to antisocial behavior more Table 4 Comparisons Between Identified Groups on Adolescent (Age 15) Outcomes, After Controlling for Significant Early Life Covariates Age 15 outcomes Low Ext/Int Secondary PrimaryFdf 2 Social outcomes Relational aggression 1.32 a(.01)1.38 ab(.03)1.30 a(.03)1.44 b(.02)4.12 3 .01 Reactive aggression 1.63 a(.02)1.70 ab(.06)1.83 b(.05)1.60 a(.05)4.48 3 .02 Social skills 58.95 b(.54)57.42 ab(.95)55.16 a(.99)56.58 a(.89)8.34 3 .03 Biological outcomes Heart rate 72.53 ab(.19)72.51 ab(.46)73.38 b(.50)70.63 a(.40)2.63 3 .01 Cortisol .35 b(.01).33 ab(.03).29 a(.03).37 b(.02)3.88 3 .02 Cognitive outcomes Self-regulation .01 b(.02) .09 ab(.08) .21 a(.08).04 b(.04)2.87 3 .01 WJ-R cognitive score 107.15 b(.36)105.52 ab(1.71)102.22 a(1.73)107.34 b(.84)2.86 3 .01 WJ-R achievement 105.52 b(.36)103.56 ab(1.71)99.78 a(1.72)106.80 b(.83)4.99 3 .02 Parenting outcomes Conflict 16.83 a(.20)19.03 b(.50)19.65 b(.53)18.70 b(.43)13.48 3 .04 Maternal depression 10.12 a(.30)11.21 ab(.73)12.63 b(.79)10.13 a(.63)3.24 3 .01 Note. Estimated marginal means (SE); different superscripts ( a,b) denote significant differences between groups in post hoc pairwise comparisons using the Bonferroni procedure. Only comparisons atp .008 are reported as significant. AllFstatistics are significant at thep .05 level. Ext/Int externalizing/internalizing; WJ-R Woodcock-Johnson Psychoeducational Battery–Revised. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1237 HETEROGENEITY IN ANTISOCIAL BEHAVIOR generally. Relative to this broader CU traits literature, the study of primary and secondary variants is in its infancy with the first published empirical adult study in 2004 (Hicks et al., 2004) and youth study in 2009 (Vaughn, Edens, Howard, & Smith, 2009). The burgeoning literature on CU variants, together with current study findings, support that this broader perspective can improve our understanding of antisocial behavior and has potential to clarify inconsistencies across the literature. Comorbid internalizing problems are a key distinguishing factor between secondary and primary CU variants irrespective of develop- mental period. Secondary CU variants had significantly greater symp- toms of anxiety and depression than primary variants at age 3 and at age 15. Notably, children with externalizing problems without CU and those classified as secondary CU both showed high and nonsig- nificantly different levels of anxiety/depression in early childhood that persisted into adolescence, and both may be considered comorbid externalizing groups. Similarly, both groups also showed high and undifferentiated levels of maternal depression during the postnatal period and in adolescence relative to lower risk and primary CU groups. This suggests that heritable and learning factors that are central to theories of anxiety and depression may represent shared vulnerabilities to both comorbid presentations. It is thought that both too high and too low levels of arousal in the context of emotionally charged early socializing experiences (i.e., parental punishment) negatively impact the development of moral emotions and contribute to antisocial behavior (Frick & Morris, 2004). For young children with secondary CU traits that show similar patterns of heightened emotionality to those with internalizing prob- lems, as reflected by high heart rate in the current study, it is likely that too high levels of emotional arousal contribute to this failure in moral socialization, although this is a question in need of further study. Conversely, low heart rate is a long-established correlate of external- izing problems; however, our results suggest that inconsistent findings in the literature may be due to important differences between exter- nalizing subtypes. Consistent with a large body of research document- ing low levels of emotional arousal among antisocial youth with CU traits (Blair, 1999;Marsh, Gerber, & Peterson, 2008), primary CU variants showed significantly lower heart rate relative to secondary variants. Paired with their greater self-regulation compared with sec- ondary CU variants, this presentation fits adult conceptualizations of primary psychopathy as an emotionally stable and planful group of individuals. These suggestions are strengthened by current findings that childhood primary CU variants were more likely to engage in relational than reactive aggression, which requires a degree of plan- ning. By contrast, the average heart rate of secondary CU variants was highest within our sample, although undifferentiated from low prob- lem and Ext/Int groups after applying Bonferroni corrections. Simi- larly,Kimonis et al. (2012)found that primary and secondary CU variants identified in an incarcerated adolescent sample showed con- trasting patterns of emotional reactivity on a dot probe task. Whereas primary variants were underaroused to negative cues on the task, secondary variants were hyperaroused. Cortisol emerged as a second potential biomarker differentiating externalizing subgroups. Secondary CU variants presented with the lowest morning cortisol concentrations and primary variants with the highest, and were the only groups significantly differentiated from one another. Although a priori predictions were not made, the some- what unexpected direction of these findings necessitates caution in their interpretation and a need for replication in future studies. Incon-sistencies and contradictions are embedded throughout the cortisol- antisocial behavior literature (Hawes, Brennan, & Dadds, 2009), with some studies reporting a negative relationship between diurnal corti- sol and psychopathic traits, and others finding no relationship (Cima et al., 2008;Holi, Auvinen-Lintunen, Lindberg, Tani, & Virkkunen, 2006). Mixed results may, in part, arise from differences in method- ology, such as collecting single-snapshot basal or afternoon measures, examining stress-reactive measures, or diurnal measures as we did in the present study. Another line of research relevant to our findings reports that low cortisol levels are associated with negative familial experiences, such as maternal insensitivity and history of maltreat- ment (Roisman et al., 2009;Tarullo & Gunnar, 2006). The attenuation hypothesis was posited to explain these findings, proposing that social stressors and chronic activation of the hypothalamic-pituitary-adrenal (HPA) axis in early development might result in attenuated cortisol levels (Susman, 2006), similar to the pattern observed among our secondary variants. The longitudinal nature of our study might further explain this association, sinceRuttle et al. (2011)found that while internalizing problems were concurrently associated with higher morning cortisol levels, internalizing problems assessed in childhood were associated with low cortisol levels during adolescence. Further, children with the most severe behavioral problems during childhood, which was the case for the secondary CU group, had the lowest cortisol levels during adolescence, pointing to greater dysregulation of the HPA axis. Thus, by taking heterogeneity into account and inves- tigating longitudinal associations, current findings provide support for disentangling the association between cortisol and antisocial behavior. Strengths, Limitations, and Conclusions There were a number of important strengths to this study, including its longitudinal design with a relatively large sample, the inclusion of a variety of measures assessed via multiple methods, and at a variety of relevant time points. Our findings must also be considered within the context of several study limitations. First, CU traits at age 3 were based on the CBCL and not an instrument designed to comprehen- sively assess CU traits, although prior work suggests the ASEBA provides a valid measure (Willoughby et al., 2014;Willoughby et al., 2011). Also, the YPI is a self-report instrument and while the validity of self-report measures of personality tends to increase with age as that of parent- and teacher-report declines from childhood to adoles- cence (Frick, Barry, & Kamphaus, 2010), self-report is susceptible to deception that is a cardinal feature of psychopathy. An additional limitation might be that grouping variables relied exclusively on maternal reports andassociations with mother-reported outcomes could be inflated due to shared method variance; however, mothers might be more observant of their children’s emotional characteristics compared with other informants (Keiley et al., 2003). Related to this limitation, measures of father psychopa- thology were not included in the current study. Finally, the current study was not genetically informed and thus many of these findings could reflect heritable, rather than contextual, processes. Our findings have important implications for assessment, preven- tion, and treatment of preschoolers with externalizing problems. They are consistent with the broader research on childhood antisocial be- havior suggesting that the causes for these problems can vary greatly and that effective intervention requires both a comprehensive assess- ment of these various causal pathways and a matching of treatment to This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 1238 FANTI AND KIMONIS the unique needs of children across these pathways (Frick et al., 2014). In the current study, children identified into a high-risk group were at risk for problematic adolescent outcomes: Ext/Int and sec- ondary CU groups were at heightened risk for internalizing problems; secondary CU variants were particularly at risk for severe external- izing problems and reactive aggression; and primary CU variants were at greatest risk for relational aggression, relative to other exter- nalizing and low problem groups. These findings suggest that distin- guishing between externalizing subgroups on the basis of internaliz- ing problems and CU traits is likely to have clinical utility for understanding their prognosis. Parent management training is the gold-standard intervention for young children with externalizing problems (Comer, Chow, Chan, Cooper-Vince, & Wilson, 2013); however, estimates suggest that approximately one third of treated children do not respond to tradi- tional intervention (Masi et al., 2011;Webster-Stratton & Hammond, 1997). Whereas children with anxiety problems tend to yield the greatest benefit from these programs, they are significantly less cost- effective for children with CU traits (Hawes, Price, & Dadds, 2014; cf.,Hyde et al., 2013;Waller et al., 2014). The reason for this relative treatment resistance appears to be that the externalizing problems of children with CU traits arise from some distinct factors from those typically targeted in traditional interventions. Recent efforts to im- prove treatment outcomes for children with CU traits by targeting their unique emotional deficits are promising (Dadds, Cauchi, Wimalaweera, Hawes, & Brennan, 2012;Datyner, Kimonis, Hunt, & Armstrong, 2016). Our findings suggest these efforts require expan- sion to consider the unique treatment needs of those children with and without comorbid internalizing problems. 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I have attached the Final assignment since this assignment is building off of it this will be a big deal. I will let you pick the four domains that you are comfortable with and if you want I will help
Pakistan Journal of Psychological Research, 2012, Vol. 27, No. 1, 135-151 Effect of Academic Interventions on the Developmental Skills of Slow Learners Najma Iqbal Malik Quaid-i-Azam University and University of Sargodha Ghazala Rehman and Rubina Hanif Quaid-i-Azam University 1 The present study was a single-group pre-test and post-test design; it was conducted to see the effectiveness of academic interventions (Shaw, 2005) on developmental skills (adaptive, personal-social, communication, motor, and cognitive) of slow learners having borderline intelligence. Eight slow learners were identified through subjective ratings based on teacher’s appraisal and attained achievement scores in respective grades and scores attained on Raven’s Colored Progressive Matrices (CPM; Raven, Court, & Raven, 1977) during screening. Boys (n = 6) and girls (n = 2) of ages ranging from six years to six years and 11 months of age were purposefully selected from two private-sector schools of District and Tehsil Sargodha, Punjab, Pakistan. Developmental skills of slow learners were measured by Battelle Developmental Inventory (BDI-2; Newborg, 2004); assessment and screening was followed by academic intervention. Quantitative analyses revealed that academic interventions were highly effective in enhancing the developmental skills of slow learners’ adaptive, communication, and cognitive developmental skills. However, these interventions remained silent and failed to show any positive effect on personal- social and motor skills. Keywords: Slow learners, academic interventions, developmental skills The challenge of identifying slow learners has been a topic of increasing concern of researchers from last few decades (Khan, 2005; Shaw, 2003; Sing, 2004). Academically slow learners are usually identified based on their attained scores on intelligence tests, with IQs Najma Iqbal Malik, National Institute of Psychology, Quaid-i-Azam University, Islamabad, Pakistan and Department of Psychology, University of Sargodha, Sargodha, Pakistan; Ghazala Rehman, and Rubina Hanif, National Institute of Psychology, Quaid-i-Azam University, Islamabad, Pakistan. Correspondence concerning this article should be addressed to Najma Iqbal Malik, Department of Psychology, University of Sargodha, Sargodha, Pakistan. E-mail: [email protected] 136 MALIK , REHMAN , AND HANIF between 75-89. A slow learner differs slightly from normal children in learning ability and cannot meet average academic standards year to year. Their intelligence test scores are likely to be low from average test scores. However, not too low to meet the large discrepancy set as an inclusion criterion for special educational services (Mercer, 1996). Although slow learner may have special educational needs, yet they do not fit neatly into the special education system and generally study at normal schools (MacMillan, Gresham, Bocian, & Lambros, 1998). Academic slow learners are also labeled as borderline mentally retarded, dull, below average children. They are generally slow learner when they are faced with tasks requiring abstract, symbolic, and conceptual skills (Lowenstein, 2003). Furthermore, rate of slow learning direct these children (slow learners) to lag behind in their normal developmental skills acquisition and they tend to grasp basic concepts of living (i.e., social interaction, communication styles, memory skills, and thinking patterns) about 1-2 years later in comparison to peers (Carroll, 2002; Gouwens, 2002; Kaznowski, 2004). Borderline intellectual functioning contributes negatively in their life as they lack concentration, have poor memory, imagination, and foresight; an inability to express ideas clearly through the medium of language (Bhatt, 2009). Research indicates that academically slow learners pose significant educational and behavioral difficulties in the schools because of their deficiencies in intellect and psychosocial skills (Anastasia, Elein, & Effi, 2006; Shaw, 2008). They differ from average students in the rate of learning and need much external stimulation/encouragement to do the simple of work (Krishnakumar, Geeta, & Palat, 2006; Stenhouse, 2005). This is also well documented that slow learners do work at their ability level but below their grade level, which in turn leads to their adjustment problems in mainstream class rooms (Krishnakumar et al., 2006). Their deficit in skills (e.g. inadequate coping mechanisms, poor self-image, immature interpersonal relationships, troubled communications, and inappropriate social role ideology) make them vulnerable or at risk of several psychosocial problems. These problems could only be addressed by incorporating interventional teaching strategies in the inclusive classrooms for their accommodation and to enhance the rate of their adequate psychosocial development i.e., better adult and peer interactions, enhanced receptive and expressive communication, and modesty of self-concept, and social role by expressing logical reasoning and understanding of environmental demands (Anastasia et al., 2006). ACADEMIC INTERVENTIONS FOR SLOW LEARNERS 137 In the context of Pakistani academic setting, unfortunately there is sparse empirical evidence which may assist academic settings (schools) to identify slow learners (Aly, Taj, & Ibrahim, 2009), with the help of standardized and objective measures (IQ tests scores) (Hussein, 2009) and to develop and implement special educational criteria and curriculum and provide interventions for associated mental health issues (Haider, 2008). Majority of these children, are initially not identified as slow learners requiring special education and specifically designed interventions (Shaw, 2008). This is probably because of the fact that they are able to understand things up to some level and donot present serious problems in their functional skills; these children function normally and they have physical agility and adeptness in different situations. Moreover, they also demonstrate common sense and appear to have adequate memory (Mroczka, 2003). However, the typical problems in general cognitive function are more evident, when they are required to perform a task requiring higher mental processes; they fail to accomplish the task, mainly due to deficits in abstract thinking, organizational skills, and generalization of information, which creates hurdles in their academic success (Balado, 2003). To ensure slow learners’ success in schools, their rate of slower learning needs to be accommodated through specifically designed interventions in accordance with their ability level (Shaw, 2008). Before going toward the intervention, it is critical that teachers and parents should consider assessment through a number of sources before assuming that poor school performance is due to a slower learning ability (Carroll, 2002). Hussein’s (2009) study supported the notion that; child’s mental health is largely influenced by child’s home environment, child’s schooling, and the society at large. This confirms the critical and helpful role of parents and teachers in giving prime attention, vigilance, and care to ensure sound mental health (Aly et al., 2009; Haider, 2008; Rahman, Mubbashar, Harrington, & Gater, 2000; Rehman, 2005; Yaqoob, Ferngren, Jalil, Nazir, & Karlberg, 2008). Developmental psychologists have affirmed the importance and relation of IQ with developmental skills acquisition. A firm view is that there is strong interplay between environmental factors and person’s normal functioning which determine his/her successful social life. Erickson (1950) has given importance to cultural and social aspects of life and describes the impact of social experience across the whole lifespan. According to him one’s life is a series of lessons and challenges which help us to grow in multiple stages of life. Further, Vygotsky (1978) contributes that if theses leaning aids are give in a manner that they 138 MALIK , REHMAN , AND HANIF relate with the cultural context of the child then profound impact on the developmental skills becomes more visible. It is evident from literature that while dealing with children with borderline intelligence, theories of Erickson and Vygotsky are valuable (Tudge, 1990; Wood, 1998). Based on Erickson and Vygotsky’s theories, various models of slow learners and their related risks have emerged and Shaw’s model of slow learners and mental health issues is the one most widely used. Shaw (2000a) described the slow learner’s borderline intellectual functioning in relation to their developmental tasks. It also elaborates how deficiencies in these task completions can lead to various kinds of mental health risks among slow learners. Keeping in view, the specified significance of research on slow learners in Western community and effectiveness of Shaw’s academic intervention plan, the dire need was felt to explore application of academic interventions based on Shaw’s model in Pakistani settings. The present research is designed to find out the effectiveness of academic interventional teaching plan for developmental skills of slow learners. On the basis of the objective of this study, following hypothesis was formulated for the study: Hypothesis 1: Slow learners will show higher level of adaptive skills in post-test assessment in comparison to pre-test assessment. Hypothesis 2: Slow learners will show higher level of personal- social skills in post-test assessment in comparison to pre-test assessment. Hypothesis 3: Slow learners will show higher level of communic- ation skills in post-test assessment in comparison to pre-test assessment. Hypothesis 4: Slow learners will show higher level of motor skills in post-test assessment as compared to pre-test assessment. Hypothesis 5: Slow learners will show higher level of cognitive skills in post-test assessment as compared to pre-test assessment. Method Sample Slow learners (N = 08), both boys (n = 6) and girls (n = 2), were purposefully selected from two private sector schools of urban area of District and Tehsil Sargodha, Punjab, Pakistan. In order to have a ACADEMIC INTERVENTIONS FOR SLOW LEARNERS 139 homogeneous control sample for comparison, the children were matched for age (6 year to 6 years & 11 months of age), grade (1 st grade), high socioeconomic status (above Rs. 31, 000/- per month), and mother tongue as Urdu. Eight participants were identified as slow learners on the basis of Raven’s Colored Progressive Matrices (CPM; Raven et al., 1977) scores i.e., scoring between 10 th to below 25 th percentile and teacher’s appraisal; teacher appraisals based on the consideration of the child performance in curricular and recreational interests and overall academic performance in the class, designated as dull or below average in comparison to class mates. Instruments Colored Progressive Matrices (CPM). It is an internationally recognized culture-fair, nonverbal IQ test, to measure the ‘g’ factor. It is specially designed for use with children between ages of 5 ½ and 11 ½ years. This easily administered, paper and pencil test is comprises of three sets of twelve problems, arranged to “assess mental development up to a stage where a person is sufficiently able to reason by analogy to adopt this way of thinking as a consistent methods of inference” (Raven et al.). In the present study children having the raw scores and corresponding percentiles between 10 th to below 25 th percentile were identified as slow learners. Literature supports that (Gatti, 2004; Li, Gamlin, Jain, & Luther, 2001; Pujar & Gaonkar, 2008) Raven’s CPM is a reliable source to identify slow learners/intellectually subnormal or have deteriorated cognitive abilities. Battelle Developmental Inventory-2. Slow learners were assessed for their key developmental skills through the second edition of Battelle Developmental Inventory (BDI-2; Newborg, 2005). The full BDI-2 battery consists of 450 test items grouped into the following five domains (i) adaptive domain i.e., child’s ability to use the information and skills acquired in the other domains, (ii) personal- social domain i.e., abilities and characteristics that allow a child to engage in meaningful social interaction with adults and peers and to develop his or her own self-concept and sense of social role, (iii) communication domain i.e., how effectively a child receives and expresses information and ideas through verbal and nonverbal means, (iv) motor domain i.e., the child’s ability to control and use the large and small body muscles, and (v) cognitive domain i.e., those skills and abilities most commonly thought as mental or intellectual, with the 140 MALIK , REHMAN , AND HANIF exception of language and communication skills. BDI-2 has been successfully used by medical and health professionals for the assessment of psychomotor developmental delays (HOPE, 2009a, 2009b), assessment of disabilities, and assessment of typical developmental rate of children in Pakistan (Aly et al., 2009). Academic interventional teaching plan. It is essential for educational sector to accommodate every child in productive environment and it is desired to have best method of teaching and training of slow learners/at risk students to be incorporated with the traditional ones to enforce the learned material. For this purpose in the light of four broader themes given by Shaw (2000b), an academic interventional teaching plan was designed and implemented in mainstream classrooms. The following steps were undertaken to implement the academic interventional teaching plan: 1. Modification in the curriculum and study material: The standard curriculum of Punjab Text Book Board, Punjab, Pakistan of first grade was modified as more pictures books, charts, models, and educational blocks (made of thermopile, plaster of paris and wood), educational software of games (e.g., rays package of learning aid, old mac-dot farm etc.), and puzzles (letter and picture matching exercises in math, english, and urdu; count and tell, tell before and after, hundreds, tens, and ones, find the largest number, find the same or spot the different one) with the help of computers, educational rhymes, short stories, crayons, poster colors, and playful dough (clay) along with paper and pencil, were made part of study. This was accomplished with the help of art teacher and a professional artist. 2. Modification in classroom environment: A regular seat change plan was designed to be implementing on weekly basis. Slow learners were stipulated to be sitting in front whereas their peers had a weekly seat change program by rotation. Walls were decorated and painted with teaching material models, charts, pictures, and story characters. This was furnished with the help of an artist and art teacher, who were assisted by the researcher and class teachers for generating ideas. 3. Modification in time demands: The deadlines for task completion/performance were designed to be lenient for slow learners as compare to other class fellows i.e., if normal average child needed 5 minutes for one problem solution then 7-8 minutes were given to slow learners. ACADEMIC INTERVENTIONS FOR SLOW LEARNERS 141 4. Peer tutoring and use of groups in learning: Class assignments were gradually made easy for slow learners and were given in small parts/units. In this activity, slow learners from advanced classes were asked to ‘tutor’ the younger grade students. In addition, complex and technical educational tasks related to subject area were distributed among groups. 5. Daily good behavior exercise: In daily routine a ‘model good behavior’ was exercised through peer role play, which was monitored (through observation by researcher and teacher) and was incorporated (imitated) in their routine behavior as a mode of social-skills training and social problem solving exercises. For example “how to take permission”, “how to say good morning and good bye”, “how to say sorry on your mistakes by accepting them”, “how to pay gratitude by saying thank you”, etc. These exercises aimed at helping slow learners in resolving problems related to interpersonal communication, problematic relations, and poor initiative- taking and motivation issues. 6. Differential reinforcement and immediate feedback to reward (every) desirable behavior: On each successful task accomplishment and initiative, immediate feedback (in form of praise from teacher and clapping from the peers was initiated) and encouragement were made part of intervention plan; to help boost their self-esteem and self-confidence. 7. Review of concepts on weekly basis: At the last working day of week (on Friday’s), the week plan was reviewed in a light/fun way with the help of various techniques such as drama, role-play, storytelling, and presentations. This exercise aimed at assisting children to develop associations between concepts with help of pictorial presentation of each concept and models of learning material. Procedure Written informed consent from the schools, teachers and parent of slow learners was obtained before the start of this intervention program. At first step after sample selection of eight slow learners, baseline measurement (pre-test) of developmental skills was carried out and slow learners were assessed through BDI-2 for their developmental skills prior to interventions. Only those two schools were selected whose principals allowed imparting interventions, agreed to spend finances on teaching aids, 142 MALIK , REHMAN , AND HANIF and their teachers expressed commitment for the intervention. Both the schools run from play group to grade 10, and follow the standard curriculum of Punjab Text Book Board, Lahore, Pakistan for the year 2008. They had 30 teachers as a total teaching staff whose education rages from Bachelors of Arts (BA) to Masters of Science (MSc). The selected teachers (n = 4) for interventions had the education level of BA or Bachelors of Education and were acknowledged by their school administration for having good communication skills and tactfulness in dealing with challenging situations. Prior to intervention they received a six-day training program that was inspired by teaching aid manuals of UNESCO (2007) and UNICEF (2007), and Shaw’s guide of educational programming framework (2005, 2008, & 2010) and teaching resources for teaching slow learners (Shaw, 2001). Teachers’ training was carried out to ensure the proper implementation of intervention plan. Parents of all eight slow learners were also involved; regular parents, teacher, and researcher meetings were arranged. At second step, participants were exposed to academic interventional teaching plan for a period of four months for five days/week and four hours/day in a mainstream room setup, which was inclusive of different abilities level. At third step, after the completion of the intervention period, second baseline measurement (post-test) of developmental skills of slow learners was taken through BDI-2. To assess the difference between two baseline measurements as an effect of academic interventions Wilcoxon Signed Rank test was applied on data. Results and Discussion Different instructional strategies used in the academic interventional teaching plan for slow learners were found to be effective in terms of enhancing the developmental skills level of slow learners in inclusive classrooms. The findings indicate an expected increase in the range of scores on BDI-2 in post-test, compared to the pre-test scores. Hence, these findings support study assumption that slow learners will score higher on BDI-2 after having exposure to academic interventions. Table 1 shows enhanced scores of the slow learners on all developmental skills. There appears to be a shift in the ranges of scores on all indices of development. Similar trends were observed in the median effect size and Wilcoxon Signed Ranks values of pre-test and post-test of slow learners on BDI-2, its domain and sub-domains. ACADEMIC INTERVENTIONS FOR SLOW LEARNERS 143 Table 1 Means, Standard Deviations, Minimum, and Maximum Range of Scores on Battelle Development Inventory (N = 8) Developmental Skills a Pre-test Post-test Min Max Min Max Adaptive (ADP) 80 85 98 98 Self-care 56 59 62 62 Personal responsibility 24 26 36 36 Personal-Social (P-S) 136 149 147 156 Adult interaction 50 52 51 51 Peer Interaction 30 33 35 37 Self-concept and social role 56 64 61 68 Communication (COM) 110 113 127 139 Receptive communication 51 52 56 67 Expressive communication 58 62 71 72 Motor (MOT) 152 162 160 168 Gross motor 77 80 78 79 Fine motor 49 53 50 53 Perceptual motor 26 29 32 36 Cognitive (COG) 128 134 154 164 Attention and memory 48 50 52 52 Reasoning and academic skills 32 33 42 50 Perception and concepts 48 51 60 62 Total 607 641 686 725 Note. The scores depicted in the table are scored by slow learners; the ages ranged from six years to six years and 11 months. The term ‘total’ refers to composite scores, calculated by adding up scores on each domain of Battelle Development Inventory (Newborg, 2005). a the study measures five developmental skills. The major categories have their abbreviations in parentheses. The findings in Table 2 reveal significant differences between the pre-test and post-test scores of slow learners after the exposition of academic interventions especially in the domains of adaptive, socio- personal, communication, and cognitive which confirms the study hypotheses no. 1, 2, 3, and 5. 144 MALIK , REHMAN , AND HANIF Table 2 Median, Effect Size, and Wilcoxon Signed Ranks Values of Pre-test Post-test Assessment of Slow Learners on Developmental Skills (N=8) Developmental Skills a Pre-test Posttest Mdn Mdn z r p Adaptive (ADP) 83 98 -2.46 -.63 .01 Self-care 59 62 -2.64 -.65 .01 Personal responsibility 25 36 -2.6 -.64 .01 Personal-Social (P-S) 146 148 -1.10 -.4 .19 Adult interaction 52 51 -1.41 -.31 .48 Peer interaction 31 37 -2.55 -.63 .01 Self-concept and social role 62 62 -.42 -.14 .37 Communication (COM) 111 137 -2.55 -.63 .01 Receptive communication 52 66 -2.57 -.63 .01 Expressive communication 59 71 -2.57 -.63 .01 Motor (MOT) 161 161 -.44 -.15 .39 Gross motor 80 78 -1.41 -.3 .14 Fine motor 53 50 -.90 -.06 .28 Perceptual motor 28 33 -2.64 -.65 .01 Cognitive (COG) 131 158 -2.55 -.63 .01 Attention and memory 49 52 -2.57 -.64 .01 Reasoning and academic skills 32 44 -2.55 -.63 .01 Perception and concepts 49 61 -2.55 -.63 .01 Total 629 703 -2.55 -.63 .01 Note. The scores depicted in the table are scored by slow learners; the ages ranged from six years to six years and 11 months. The term ‘total’ refers to composite scores, calculated by adding up scores on each domain of Battelle Development Inventory (Newborg, 2005). a the study measures five developmental skills. The major categories have their abbreviations in parentheses. This further indicate that adaptive skills (self-care and personal responsibility), personal-social skills (peer interaction), communication skills (receptive and expressive communication), motor skills ACADEMIC INTERVENTIONS FOR SLOW LEARNERS 145 (perceptual motor), and cognitive skills (attention and memory, reasoning and academic skills, and perception and concepts skills) were significantly enhanced as a result of profound effect of academic interventions. However, adult interaction, self-concept, and social role (personal-social skills), gross and fine motor skills (motor skills) failed to get any benefit from the interventions. This partially confirms the study hypotheses that slow learners get benefit in their domains of personal-social, communication, and cognitive skills. However, peer interaction shows profound and significant effect of interventions with exception to total domain of personal-social, adult interaction, and self-concept and social role. Furthermore similar findings were obtained through the daily feedback of teachers (they were instructed prior to the interventions implementation that they would prepare feed back by checking each and every behavior) and researcher’s observations. These interventions were new for the participants to the study; they seem to appear more confident and displayed positive sense of self-worth and feeling of belongingness which help them integrating well in their class and peers. Also it was observed that exposure to concrete instructions and immediate feedback on goal-directed behaviors, helped these students in following instructions and establishing the efficacy to complete daily tasks with minimal prompting. Peer tutoring (Behera, 2009; Clattenburg, 2003; Hussein, 2009) and social skills exercises helped them learn the skill of asking, taking permission, paying gratitude, and coping with challenges. Moreover, receptive and expressive communications skills seemed to have benefited from the multilevel interventions and they were observed displaying empathy towards others i.e., understanding feelings, thoughts, and emotions of others; recognizing facial expressions and maintaining appropriate eye contact while communicating with others. Moreover, these interventions helped to build their sense of safety by understanding the model behavior to safeguard them from danger; they appear more aware about morality and took pride in their self-accomplishments. This is fair to say that the participants seem to have maximum benefit of this intervention i.e., review of concepts on a weekly basis helped boosting up their minor level leads by maximum course of revisions. These reviews were in the form of educational rhymes, stories, play, drama and fun activities set them free from the burdens of educational life. They in fact learned significantly, by the use of 146 MALIK , REHMAN , AND HANIF casual teaching styles and non-formal remediation teaching strategies; rather than learning in more structured classroom setup. The researcher was aware of their limited cognitive abilities, and giving them large amount of information in paper-pencil form in one setting was very difficult (Haskvitz, 2007). However, this teaching was incorporated and internalized through creative activities to meet their unique needs for attaining achievement and success (Shaw, Grimes, & Bulman, 2005). As expected these academic interventions and modified curriculum with a blend of charts, pictures, and models provided opportunities for effective integration, adjustment, and better learning opportunities (Pujar & Gaonkar, 2008). These made participants more alert, prompt, and active; they were highly motivated and interested in learning. This helped improving their speed of learning and provided them with knowledge and a strong base for understanding and conceptualization. Several previous studies (Mohansundaram & Dharmashekar, 2001; Philip & Marcia, 2002; Reddy & Ramar, 1995; Singh, 2004) have also revealed that interventions through different stimulating and enriching instructional strategies and multimodel approaches are certainly effective than the traditional method of teaching for slow learners in mainstream classrooms. Similar feedback was received by the parents in parent-teacher and parent-researcher meetings that these children showed remarkable progress in interpersonal and social skills. These results were also in line with the findings of Davis and Williams (1972) that slow learners got maximum advantage by multi-model approach instead of uni- model approach i.e., if they are taught by using different strategies then it particularly help them in creating a favorable attitude toward learning and promote a sound conceptual understanding of the taught material. These findings also confirm the Vygotsky’s (1978) concept of practical intelligence in one’s own cultural context i.e., proximal zones. Thus etiology of learning is social interaction. A concept is first presented to a child socially (inter psychologically) either by parent, peer, or teacher which is later internalized by the child; who then appears to employ it for problem solving. According to this concept if the cultural context/proximal zones of the slow learners weather in educational paradigms or in home setting is more facilitating in nature then the chances of their practical intelligence can be raised. It can be done with the help of intervention as and if early identification and special needs advocacy is going to be taken into account then one can safe guard slow learners for indulging in several metal health issues and their adjustment in the society can be enhanced. ACADEMIC INTERVENTIONS FOR SLOW LEARNERS 147 Present research supported that slow learners were enrolled in mainstream schools; due to deficit in developmental skills they needed extra attention of teacher, policy makers, and psychologists. They were also found to be at risk of several mental health problems because of their below average intellectual abilities and deficit developmental skills. However, an early identification, assessment of developmental skills, and supportive interventional plan can safeguard this large minority form various adversities of school and social life; yet this a neglected area of Pakistani education reforms so far. These interventions boosted the rate of developmental skills and worked as an enhancer in this way, which proved that interventional teaching plan works is very much effective in enhancing the developmental skills of slow learners studying in mainstream classroom. In addition, it not only improved their mental health but also increased the levels of adjustment in the mainstream classroom and helped them become part of progressive community. This gives an implication for the need of interventional training of academic nature for slow learners that can assist them to advance so that they can parallel children without learning problems. Conclusion and Implications The findings of the study confirmed that the academic interventions were very effective in enhancing the developmental skills of slow learners. It was also found that slow learners got maximum benefit of academic interventions for their sociocultural settings. Majority of students benefited from academic intervention applied in a creative manner i.e., with the help of drama, role play, rhymes, and storytelling. It was also felt that review of concepts on the last working day was found to be of greatest help to students. Present study also had practical and theoretical implications; it not only adds up to the theoretical constructs of educational and school psychology but also for the persons of academia, policy makers, educational, and child psychologist and counselors in special needs advocacy. References Aly, Z., Taj, F., & Ibrahim, S. (2009). Missed opportunities in surveillance and screening systems to detect developmental delay: A developing country perspective. Brain and Development, In Press, corrected proof. doi:10.1016/j.braindev.2009.06.004 148 MALIK , REHMAN , AND HANIF Anastasia, V., Elein, D., & Effi, A. (2006). Preferences of students with general learning difficulties for different service delivery modes. European Journal of Special Needs, 21(2), 201-216. Balado, C. (2003). Teacher to teacher, Slow Learner questions. University of Central Florida, School Psychology/Counselor Educational Programs. Retrieved from http://forum.swarthmore.edu/t2t/thread.taco?thread=5858 Behera, H. (2009). Dealing with slow learners. Articles for teachers’ board. Retrieved from http://www.Tetrabb.com Bhatt, M. (2009). Are the teaching practices in mainstream classrooms having children with special needs inclusive? Reflections in Indian context. Annual Report of 2008-09. Setu Developmental Intervention Centre, Ahmadabad, India. Carroll, S. (2002). Slow learners in the mainstream classroom: A handout for teachers. National Association of School Psychologists. Retrieved from http://www.aas.ru/academics/counselors/teach/slowlearner.html Clattenburg, C. (2003). A field guide to the slow learners. Redwood City Special Education Department for Teachers, Parents and the Community. Davis, R. L. L., & Williams, P. (1972). A comparison of three methods of teaching fractions to older slow learners. Educational Research, 14(3), 236-243. Erickson, E. H. (1950). Childhood and society. New York. W. W. Norton. Gatti, S. L. (2004). Identifying students at risk for academic failure: The application of a prereferral screening model including responsiveness to intervention (Unpublished Ph. D. dissertation). Department of Psychology: Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College. Gouwens, D. A. (2002). Slow learners: A guide to academic interventions for parents. Helping Children at Home and School II: Handouts for Families and Educators. National Association for School Psychologists, 175-178. Haider, S. I. (2008). Pakistani teachers’ attitudes towards inclusion of students with special educational needs. Pakistan Journal of Medical Science, 24(4), 632-636. Haskvitz, A. (2007). Helping your slow learning child: The car family resource. Retrieved from http://www.reacheverychild.com.html HOPE (2009a). Psychomotor study of developmental delay in pre-school /school going children. Rising HOPE newsletter, April, 2009. HOPE (2009b). Psychomotor development project. Rising HOPE newsletter, August, 2009. Hussein, S. J. (2009). Social and educational determinants of child mental health: Effects of neighborhood, family, and school characteristics in a ACADEMIC INTERVENTIONS FOR SLOW LEARNERS 149 sample of Pakistani primary school children. Journal of Pakistan Psychiatric Society, 6(2), 90-97. Kaznowski, K. (2004, Dec). 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The concept of activity in Scottish psychology. In K. Richardson, & S. Sheldon (Eds.), Cognitive development and adolescence. Hillsdale, New Jersey: Erlbaum. Wood, D. (1998). How children think and learn: The social context of cognitive development (2 nd ed.). Oxford publishing, Blackwell. Yaqoob, M., Ferngren, H., Jalil, F., Nazir, R., & Karlberg, J. (2008). Early child health in Lahore, Pakistan: XII. Milestones. Acta Paediatrica, 82(391), 151-157. Received May 06, 2010 Revision received January 03, 2012 Copyright of Pakistan Journal of Psychological Research is the property of National Institute of Psychology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s express written permission. However, users may print, download, or email articles for individual use.
I have attached the Final assignment since this assignment is building off of it this will be a big deal. I will let you pick the four domains that you are comfortable with and if you want I will help
Behavioural Risk of Bipolar Disorder in an Analogue Population: The Role of Cognitive, Developmental and Interpersonal Factors Matthias Schwannauer, 1,2 * Abbi Noble 1,2 and Gillian Fraser 1 1School of Health in Social Science,The University of Edinburgh, Edinburgh, UK2CAMHS, NHS Lothian, Edinburgh, UK Research to date has identified the contribution of a number of cognitive, developmental and interpersonal risk factors in the development of bipolar affective disorder. However, further work is needed to understand the mechanisms and interactions between these risk factors in relation to bipolar mood instability. The aim of this study is to explore the possibility of identifying high risk of bipolar disorder through cognitive and interpersonal factors and to further expand our knowledge regarding the relationship between such factors. Thefindings from this work demonstrate that when both cognitive and interpersonal variables are entered into one model to predict bipolar high risk, direct effects are observed for the interpersonal factors, which then have a fully mediational effect on the cognitive factors. This work proposes that interpersonal factors develop and maintain cognitive risk factors and that future formulations and treatment of bipolar disorder need to focus on addressing such interpersonal issues. Copyright © 2011 John Wiley & Sons, Ltd. Key Practitioner Message: This study highlights the importance of the interpersonal context of mood dysregulation and the inter- action of cognitive and interpersonal aspects of affect regulation. The interpersonal context needs to be fully considered when investigating and working with indivi- duals at risk of bipolar disorder. Keywords:Bipolar Disorder, Cognitive and Interpersonal Factors, Behavioural High Risk INTRODUCTION Bipolar disorder (BD) is a mood disorder characterized by episodes of mania and depression, which can be widely diverse from mild hypomania and mild depres- sion to severe mania and severe and recurrent depres- sion with chronic psychosis (Muller-Oerlinghausen, Berghofer, & Bauer, 2002). The impact of BD on indivi- duals and their family is psychological, social andfinan- cial (Cooke & Jones, 2009), and the prevalence of suicide in individuals with BD is significantly higher compared with that in the population as a whole (Dutta et al., 2007). High-risk paradigm studies tend to focus on the identi- fication of genetic or behavioural factors that contribute to the risk of developing BD. Work with a behavioural focus has primarily investigated the impact of cognitions in predicting the risk of developing BD, e.g., studies have illustrated how dysfunctional cognitive styles mayincrease vulnerability to the development of BD (Alloy et al., 2005; Reilly-Harrington, Alloy, Fresco, & Whitehouse, 1999). It has been established that dysfunctional negative thinking by individuals with BD increases their vulner- ability to experiencing a bipolar episode when exposed to a negative stressful situation (Reilly-Harrington et al., 1999; Scott, Stanton, Garland, & Ferrier, 2000). Further work into dysfunctional cognitions has focused on the association between the regulation systems of anxiety and impulsivity with BD. Responses to positive reward and positive feelings are regulated by the Behav- ioural Activation System (BAS); a plethora of research supports the premise that an increased BAS sensitivity is predictive of manic episodes (Alloy et al., 2008; Eisner, Johnson, & Carver, 2008; Meyer & Baur, 2009; Meyer, Johnson, & Carver, 1999; Van der Gucht, Morriss, Lancaster, Kidderman, & Bentall, 2009). The Behavioural Inhibition System (BIS), which regulates responses to anxiety and inhibits behaviour that would result in negative out- comes, is thought to be associated with depressive epi- sodes (Alloy et al., 2008; Eisner et al., 2008; Jones, Mansell, & Waller, 2006; Meyer et al., 1999; Van der Gucht et al., 2009). Although work has demonstrated an associ- ation between both BIS and BAS with BD, some *Correspondence to: Matthias Schwannauer, Section of Clinical Psychology, The University of Edinburgh, Teviot Place, Edinburgh, UK EH8 9AG. E-mail: [email protected] Clinical Psychology and Psychotherapy Clin. Psychol. Psychother.18,411–417 (2011) Published online 30 August 2011 in Wiley Online Library (wileyonlinelibrary.com).DOI:10.1002/cpp.781 Copyright © 2011 John Wiley & Sons, Ltd. researchers believe that BD is more a reaction to positive affect and behavioural activation (BAS) (Depue & Iacono, 1989; Meyer & Baur, 2009). It is unclear however whether dysfunctional cognitions result from negative situations and experiences or vice versa. Some researchers, such as Alloy, Abramson, Walshaw, Keyser, and Gerstein (2006) and also Lovejoy and Steuerwald (1997), argue that negative experiences within our interpersonal environment can lead to the devel- opment and maintenance of dysfunctional cognitions. For example, the lack of a responsive caregiver in early life can resultinthedevelopmentofadysfunctionalattitude style, which is known to increase the risk of developing BD (Morriss, van der Gucht, Lancaster, & Bentall, 2009). A negative interpersonal environment may also impact on an individual’s ability to regulate their emotions, with individuals adopting dysfunctional strategies being more at risk of developing BD (Cooke & Jones, 2009). The presence or lack of social support is another envir- onmental factor that has been shown to impact on BD. Re- ceiving low social support has been found to result in a longer recovery from depressive episodes and an increase in the likelihood of relapse and recurrence of episodes (Cohen, Hammer, Henry, & Daley, 2004; Johnson, Lundstrom, Aberg-Wistedt, & Mathe, 2003; Johnson, Meyer, Winett, & Small, 2000). Previous work demonstrates evidence of both cognitive and interpersonal factors impacting on the development and course of BD. However, less is known about the inter- action of these factors in identifying at-risk individuals. This study of an analogue sample will attempt to under- stand such interactions when predicting the risk of devel- oping BD. It is suggested that the role cognitive factors take in predicating this risk will be mediated by interper- sonal factors. METHOD Participants In total, 725 students, aged between 16 and 63 years old, from across the Lothian region in Scotland participated in the research. As the onset of bipolar typically occurs prior to the early thirties, those participants over 35 were excluded. The participants were also required to complete at least all but one of the measures in the survey. Thus, the core sample was made up from 549 students (158 men, 391 women) aged between 16 and 35 years old with a mean age of 22.89 (SD = 4.31). Materials Internal State Scale (Bauer et al., 1991) This 17-item questionnaire is a self-report scale for manic symptoms. It assesses the current mood state ofthe individual. Each item is scored on a 100-mm visual analogue line with reference to their experience in the pre- vious 24 h. The scale has four subscales: activation, per- ceived confidence, well-being and depression index. The internal consistency for these subscales is between 0.81 and 0.92 (Bauer et al., 1991). Inventory of Interpersonal Problems (Horowitz, Rosenberg, Baer, Ureno, & Villasenor, 1988) This questionnaire was designed to assist in the identifi- cation of interpersonal sources of distress. The Inventory of Interpersonal Problems (IIP) is made up of 78 items associated with‘it’s hard for me’and 49 items of‘these are things I do too much’. These items are scored from 0 (‘not at all’)to4(‘extremely’). The IIP provides a total score, which is made up from the six subscale scores: domineering/controlling, vindictive/self-centred, cold/ distant, socially inhibited, non-assertive, overly accommo- dating, self-sacrificing and intrusive/needy. A very good internal consistency (a= 0.82 to 0.94) and test–retest reli- ability (r= 0.80 to 0.90) have been reported by the original authors. Behavioural Inhibition System/Behavioural Activation System (Caver & White, 1994) This scale aims to assess the behavioural systems under- lying anxiety and impulsivity, the BIS and the BAS, respectively. It has 24 items, which are rated on a 4-point Likert Scale from‘very false for me’(1) to‘very true for me’(4). The BIS/BAS has four factors: behavioural inhib- ition (BIS), BAS drive, BAS reward response and BAS fun seeking. A test–retest reliability score of between 0.59 and 0.69 has been reported for these subscales (Caver & White, 1994). Hypomanic Personality Scale (Eckblad & Chapman, 1986) This scale was designed to identify individuals predis- posed to hypomanic episodes and BD. Respondents pro- vide true/false responses to 48 items associated with stable characteristics and recurrent experiences. Afinal total score is derived for each participant. Eckblad and Chapman (1986) reported a test–retest reliability of 0.81 and an internal consistency score of 0.87 for this scale. Mood Disorder Questionnaire (Hirschfeld et al., 2000) The Mood Disorder Questionnaire (MDQ) assesses the lifetime history of manic/hypomanic symptoms. It is made up of 13 yes/no items, where participants indicate whether they experience them or not and whether they currently have them. There then follows an evaluation by the participants as to whether the 13 items have caused them any problems (‘no problems’to‘serious problems’). A high-risk individual would score 7 or more on thefirst 412M. Schwannaueret al. Copyright © 2011 John Wiley & Sons, Ltd.Clin. Psychol. Psychother.18,411–417 (2011) part, answer yes to currently experiencing the symptoms and answer moderate or serious to the problems caused by these symptoms. A high internal consistency (a= 0.90) has been reported by the original authors for the MDQ. Relationship Scale Questionnaire (Griffin & Bartholomew, 1994) The Relationship Scale Questionnaire assesses individ- ual attachment styles in close relationships. Items are scored on a 5-point Likert scale as to whether the state- ment is‘not at all like me’(1) to‘very much like me’(5). The scale has four subscales: fearful, dismissing, secure and preoccupied. The internal consistency for this scale is modest and is reported as between 0.41 and 0.71 by Griffin and Bartholomew (1994). Regulation of Emotion Questionnaire (Phillips & Power, 2007) The Regulation of Emotion Questionnaire (ERQ) is a self-report instrument that measures both internal and ex- ternal functional and dysfunctional emotion regulation strategies. It is a 21-item scale rated on a 5-point measure from‘never’to‘always’. The ERQ has four subscales: in- ternal dysfunctional, internal functional, external dysfunc- tional and external functional. A Cronbach alpha score of 0.66–0.76 was found for the subscales of the ERQ by the original authors. Social Support Questionnaire (Sommer & Fydrich, 1991) The Social Support Questionnaire (SSQ) has 32 items and was designed to measure an individual’s perception of the social support available to them and that they re- ceive. Each item is scored on a 5-point Likert scale from 0 (not at all) to 4 (exactly right). Fydrich, Geyer, Hessel, Sommer, and Brahler (1999) reported an internal consistency score of between 0.81 and 0.93 for the sub- scales of the SSQ. Procedure Students in nine further and higher educational institutes within the Lothian area were invited to participate in the project. Students completed the measures through a Web-based platform, which they accessed through a link sent to them via e-mail or posted on their institution’s intranet page. Analyses An initial regression analysis was followed up with struc- tural equation modelling (SEM) to understand the path- ways to developing BD. For the regression analysis, arepresentation of risk of developing BD was derived through creating an Internal State Scale (ISS) total score through the sum of the four subscales. There was no major concern over multicollinearity due to all variables correlating at less than 0.65 with one another, tolerances of>0.4 (apart from SSQ social integration with a tolerance of 0.33) and Variance Inflation Factors (VIFs) of <2.5 (excluding SSQ social integration with a VIF of 3.17). Structural equation modelling simultaneously estimates the relationship between observed and latent variables (the measurement model) and among latent variables themselves (the construct model), providing estimates of both direct and indirect or mediating effects. Since a pre- liminary data analysis revealed that all variables in the model satisfied the assumptions of normality and multi- collinearity and there were no significant outliers, a max- imum likelihood was used for the data analysis. No differences were found between the bootstrapped esti- mates of the standard errors and those obtained in the maximum-likelihood model, indicating that the model did not violate the assumption of a normal distribution. MPlus offered the additional benefit of formally testing the significance of direct and indirect effects. For the SEM, the modelfit will be measured by the com- parativefit index (CFI), which provides afit index be- tween 0 and 1, with values greater than 0.95 indicating a goodfit (Hu & Bentler, 1999). The standardized root mean square residual (SRMR) will also be reported, which mea- sures the difference between the observed and predicted covariance. Zero indicates a perfectfit, whereas values of less than 0.08 are considered a goodfit (Hu & Bentler, 1999). The root mean square error of approximation is also commonly reported along with the CFI. However, in this work, it will not be used as it can often be misleading with a small sample size and degrees of freedom. PASW version 18 (SPSS, Inc., 2009, Chicago, Il, US) was used for the regression analysis and MPlus version 6 (MPlus, Muthén & Muthén, 2010) for the SEM analysis. RESULTS The descriptive characteristics for the whole sample on each measure used in this study are shown in Table 1. In line with the cut-off scores for the ISS as suggested by Bauer et al. (2005), the ISS scores indicative of mania (ISS-A) or depression (ISS-WB) are well below the cut-off points for clinical scores but comparable with similar non-clinical samples investigating predictors of bipolar personality (e.g., Jones & Day, 2008; Cooke & Jones, 2009). There were three steps to the hierarchical linear regres- sion analysis. In thefirst stage, along with the age and gender, a set of cognitive variables was entered; in the sec- ond step, the cognitive factor of interpersonal problems was entered. Finally, in the third step, a set of interper- sonal variables was entered. 413 Behavioural Risk of Bipolar Disorder Copyright © 2011 John Wiley & Sons, Ltd.Clin. Psychol. Psychother.18,411–417 (2011) Table 2 shows the significant predictors of ISS total for each stage of the analysis. In thefirst step, only BIS (b= 0.215,p<0.01) and MDQ total (b= 0.279,p<0.001) had an independent association. However, once IIP total is added in the second step, BIS no longer has an inde- pendent relationship (b= 0.137,p>0.05), whereas MDQ total (b= 0.257,p<0.001) and IIP total (b= 0.178, p<0.05) are shown to hold an independent relationship. In the third step of the analysis, once the interper- sonal factors are added, no cognitive factor maintains their independent relationship [MDQ total (b= 0.149, p>0.05), IIP total (b= 0.017,p>0.05)]. Thirty-two per cent of the variance in ISS total is predicted by ERQinternal dysfunctional (b= 0.295,p<0.005), ERQ external dysfunctional (b= 0.147,p<0.05) and SSQ practical support (b=0.185,p<0.05). This model was significant [F(20, 188) = 3.94,p<0.001]. Findings were confirmed at the bootstrappedN= 5000 level. The suppression or re- placement of sets of significant predictor variables by the stepwise inclusion of additional psychological factors indicates significant interaction between these factors and possible indirect effects. To investigate these complex associations further, we used the SEM to testa priori models of indirect and mediation effects. Structural Equation Modelling: Measurement Model Confirmatory factor analysis was carried out on the meas- urement model prior to testing the structural model. The confirmatory factor analysis resulted in a moderate model fit:w 2(4) = 32.70,p<0.001, CFI = 0.92, SRMR = 0.058. The loadings of each variable onto the relevant latent construct were all significant atp<0.001 and ranged from 0.35 to 0.93. The correlation between the latent variables was 0.67. An inspection of the individual parameter estimates provides support for the hypothesized structure of the measurement model. The factor loadings were all statisti- cally significant and of substantial magnitude, providing a meaningful and interpretable model. As the model pro- vided an adequatefit and parameters, it was used in the following structural model test. Structural Equation Modelling: Structural Model Figure 1 represents the structural construct model for risk of BD in this sample. The analyses revealed an excellent modelfit:w 2(18) = 38.46,p= 0.005, CFI = 0.96, SRMR = 0.052. Furthermore, the modification indices for the model were modest and did not suggest changes to fur- ther improve the modelfit. Overall, the hypothesized model accounted adequately for the observed co-var- iances among the indicators, providing general support for the hypothesized associations and effects. There were no unreasonable parameter estimates, such as negative variances or correlations greater than 1, and all appeared to be in the expected range of values. Both the direct and total indirect effects were significant. A direct effect between ISS and practical support, and also dysfunctional regulation of emotions, is clearly observ- able. Full mediational effects of interpersonal problems by both practical social support (b= 0.07,p<0.01) and dysfunctional regulation of emotions (b= 0.55,p<0.05) were evident. Clear mediational effects are also observ- able for a previous history of mood disorder, again by practical social support (b= 0.05,p<0.05) and dysfunc- tional regulation of emotions (b= 0.30,p<0.05). Significant pathways were identified between BIS and Table 1. Means and standard deviations for the measures used Mean SD ISS perceived conflict132.05 83.75 ISS well-being131.55 72.41 ISS activation99.96 79.95 ISS depression index54.80 57.39 ISS total score417.18 130.49 BISBAS BIS21.29 2.65 BISBAS reward responsiveness14.25 2.25 BISBAS drive12.24 2.10 BISBAS fun seeking13.04 1.79 HPS total score19.74 7.50 RSQ secure14.58 2.95 RSQ fearful12.04 3.50 RSQ preoccupied11.58 2.81 RSQ dismissing16.37 3.31 ERQ internal dysfunctional13.36 3.67 ERQ internal functional15.31 3.28 ERQ external dysfunctional7.93 2.65 ERQ external functional17.40 4.41 SSQ emotional support4.04 0.75 SSQ practical support2.34 0.86 SSQ social integration3.43 0.83 SSQ social strain2.42 0.77 ISS = Internal State Scale; BIS = Behavioural Inhibition System; BAS = Behavioural Activation System; HPS = Hypomanic Personality Scale; RSQ = Relationship Scale Questionnaire; ERQ = Regulation of Emotion Questionnaire; SSQ = Social Support Questionnaire. Table 2. Results from hierarchical regression StepR 2 FSig. predictorsbt 10.18 5.64 BIS 0.22 2.72* MDQ total0.28 3.87** 20.21 5.79 MDQ total 0.26 3.59** IIP total0.18 2.41* 30.32 3.94 ERQ internal dysfunctional 0.30 3.00** ERQ external dysfunctional0.15 2.00* SSQ practical support0.19 2.12* *p<0.05, **p<0.01. 414M. Schwannaueret al. Copyright © 2011 John Wiley & Sons, Ltd.Clin. Psychol. Psychother.18,411–417 (2011) interpersonal problems and also previous mood disorder. Further pathway identification demonstrated that BIS did not impact on internal state indirectly through these fac- tors. Therefore, BIS was identified as a moderator to both interpersonal problems and previous history of a mood disorder in predicting bipolar risk. It appears that in this sample, social support and emotion regulation variables had a direct effect on indicators of risk of BD, with the attachment, hypomanic personality and behavioural acti- vation variables either being overshadowed or left in the role of mediators and moderators. DISCUSSION The aim of this study was to predict the risk of developing BD using cognitive, developmental and interpersonal fac- tors. One of the primary goals was to show how these fac- tors impact on each other when predicting this risk and whether specific interaction of these variables may be in- dicative of potential psychological processes associated with bipolar mood instability and dysregulation. Thefindings of this study demonstrate clear direct effects of dysfunctional regulation of emotion and a lack of practical support to predicting bipolar risk. The ana- lysis also highlights that interpersonal factors act as full mediators to the effect of cognitive factors on bipolar risk.It is interesting that a previous history of mood disorder does not have a direct path to predicting future BD but is fully mediated. It would appear that current negative interpersonal experiences are more significant in the de- velopment of the disorder compared with past experi- ences. Suchfindings would suggest the need for clinicians to attend to key interpersonal experiences when working with this population and to be mindful of the im- pact of cognitive and behavioural aspects of the indivi- duals functioning on their interpersonal context. This study also supported earlier work by researchers such as Van der Gucht et al. (2009) and Alloy et al. (2008), identifying the impact of BIS in predicting risk of BD. However, this work demonstrated that when BIS was considered along with other interpersonal variables rather than having a direct path to bipolar risk, BIS moderated the impact of interpersonal problems and previous mood disorder. The impact of moderators are often underreported in the literature; however, for a full conceptualization of the pathways to BD in young people, such factors must be accounted for. One key limitation to this work is that all participants recruited for this study were studying at higher or further educational institutions in the Lothian area; therefore, cau- tion should be taken when attempting to generalize to other populations. Further research should also draw on a wider population in order to be able to generalize the Internal state Dysfunctional Regulation of Emotion External Internal Depression index Well being Perceived confidence Previous mood disorder BIS Interpersonal Problems Practical social support -.92 .30 .25 -.35 .17 -.21 .33 .60 .75 .40 -.76 -.89 .62 Chi2 = 38.46, p<.005 CFI= .96 SRMR= .052 Figure 1. Structural equation modelling of bipolar risk 415 Behavioural Risk of Bipolar Disorder Copyright © 2011 John Wiley & Sons, Ltd.Clin. Psychol. Psychother.18,411–417 (2011) findings. However, this non-clinical sample also has the advantage that the participants are not affected by the im- pact of a diagnosis, the effects of psychotropic medication and the use of mental health services. This study contributes to the clarification of the rela- tionship between cognitive and interpersonal problems when attempting to predict BD. More specifically, clear mediating effects of interpersonal factors on cognitive factors have been highlighted. Suchfindings suggest that earlier work identifying cognitive risk factors to BD only represent a partial picture and that more work is needed to further investigate the impact of these interpersonal factors. The knowledge from this work needs to be utilized in the formulation and treatment strategies of young people at risk of developing BD. It will further be important to move these concepts of risk and prediction of bipolar mood instability into clinical samples at ultrahigh risk of developing bipolar mood instability and groups of individuals following early bipolar episodes to further investigate the specific association of these underlying psychological factors in the context of psychological treatments and recovery from BDs. REFERENCES Alloy, L., Abramson, L., Urosevic, S., Walshaw, P., Nusslock, R., & Neeren, A. (2005). 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Psychother.18,411–417 (2011) Copyright of Clinical Psychology & Psychotherapy is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s express written permission. However, users may print, download, or email articles for individual use.
I have attached the Final assignment since this assignment is building off of it this will be a big deal. I will let you pick the four domains that you are comfortable with and if you want I will help
Development of Essentialist Thinking About Religion Categories in Northern Ireland (and the United States) Kirsty Smyth and Aidan Feeney Queen’s University Belfast R. Cole Eidson and John D. Coley Northeastern University Social essentialism, the belief that members of certain social categories share unobservable properties, licenses expectations that those categories are natural and a good basis for inference. A challenge for cognitive developmental theory is to give an account of how children come to develop essentialist beliefs about socially important categories. Previous evidence from Israel suggests that kindergarteners selec- tively engage in essentialist reasoning about culturally salient (ethnicity) categories, and that this is attenuated among children in integrated schools. In 5 studies (N 718) we used forced-choice (Study 1) and unconstrained (Studies 2– 4) category-based inference tasks, and a questionnaire (Study 5) to study the development of essentialist reasoning about religion categories in Northern Ireland (Studies 1–3 & 5) and the U.S. (Study 4). Results show that, as in Israel, Northern Irish children selectively engage in essentialist reasoning about culturally salient (religion) categories, and that such reasoning is attenuated among children in integrated schools. However, the development trajectory of essentialist thinking and the patterns of attenuation among children attending integrated schools in Northern Ireland differ from the Israeli case. Meta-analysis confirmed this claim and ruled out an alternative explanation of the results based on community diversity. Although the Northern Irish and Israeli case studies illustrate that children develop selective essentialist beliefs about socially important categories, and that these beliefs are impacted by educational context, the differences between them emphasize the importance of historical, cultural, and political context in understanding conceptual development, and suggest that there may be more than one developmental route to social essentialism. Keywords:category-based inference, cross-cultural comparison, integrated education, reasoning, social essentialism Psychological essentialism is the belief that natural categories contain an underlying essence that conveys category membership and causes category members to share both observable and hidden properties (Gelman, 2003;Medin & Ortony, 1989). In some cases, essentialist thinking can be useful. For example, using “essential- ized”categories for inference provides us with an important tool to reduce the complexity of incoming information to manage- able levels, and allows us to organize what we know and make inferences about what we do not know. However, essentialist thinking can also be harmful and lead to overgeneralization or unwarranted assumptions of homogeneity, especially when es- sentialist thinking is applied to social categories (e.g.,Bastian & Haslam, 2006;Diesendruck, 2013;Leslie, Cimpian, Meyer, & Freeland, 2015). In this paper we examine the development of essentialist thinking about socially important religion cate-gories—CatholicandProtestant—in Northern Ireland, with particular attention toward how school and national context may contribute to differences in the use of social categories to guide inferences. Essentialist thinking about social categories in particular has been widely investigated (e.g.,Haslam, Rothschild, & Ernst, 2000; Hirschfeld, 1996;Rhodes & Gelman, 2009;Rothbart & Taylor, 1992;Yzerbyt, Corneille, & Estrada, 2001), and there have been a variety of suggestions about its causes. One possibility is that it may represent an application of the same fundamental conceptual machinery that we use for thinking about natural kinds to the critical task of navigating our complex social environment (Gil- White, 2001). Another view is that a general purpose set of biases or heuristics results in the development of essentialist thinking about a variety of domains (Cimpian & Salomon, 2014;Gelman, 2003). Regardless of how it is explained, essentialist thinking about the social world can also lead us to weigh social category membership over individual qualities, making it one of several candidate causes (e.g.,Sherif, Harvey, White, Hood, & Sherif, 1961;Tajfel, 1982) of stereotyping, prejudice, and discrimination (Bastian & Haslam, 2006;Diesendruck, 2013;Haslam, Bastian, Bain, & Kashima, 2006;Pauker, Ambady, & Apfelbaum, 2010; Prentice & Miller, 2007). As a cognitive mechanism that may provide a foundation for stereotypical and prejudicial thinking, it is important to understand how social essentialism develops in dif- ferent contexts. Kirsty Smyth and Aidan Feeney, School of Psychology, Queen’s Uni- versity Belfast; R. Cole Eidson and John D. Coley, Department of Psy- chology, Northeastern University. We are grateful to the children and schools who helped us with this work. Kirsty Smyth was supported by a PhD studentship from the Depart- ment of Employment and Learning, Northern Ireland. Correspondence concerning this article should be addressed to Aidan Feeney, School of Psychology, Queen’s University Belfast, University Road, Belfast BT7 1NN, Northern Ireland. E-mail:[email protected] This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Developmental Psychology© 2017 American Psychological Association 2017, Vol. 53, No. 3, 475– 4960012-1649/17/$12.00http://dx.doi.org/10.1037/dev0000253 475 Although there is now quite a large literature on how the tendency to essentialize social categories develops, drawing firm conclusions from that literature is not straightforward. One diffi- culty lies in the range of categories and national contexts that have been studied. For example, ethno-religious categories are essen- tialized in Israel (seeDiesendruck, Goldfein-Elbaz, Rhodes, Gelman, & Neumark, 2013;Diesendruck & HaLevi, 2006;Segall, Birnbaum, Deeb, & Diesendruck, 2015), social class categories are essentialized in India (Mahalingam, 2003), and race categories are essentialized in the United States (Hirschfeld, 1996). Furthermore, a wide range of tasks has been used to study essentialism. Some researchers take children’s willingness to base inferences about novel behavior on membership in social categories as evidence of essentialism (seeBirnbaum, Deeb, Segall, Ben-Eliyahu, & Diesen- druck, 2010;Diesendruck & HaLevi, 2006), others have examined children’s beliefs about category stability over time (seeKinzler & Dautel, 2012), and yet others study children’s beliefs about the degree to which categories are arbitrary and artificial versus ob- jective and natural (seeDiesendruck, Goldfein-Elbaz, et al., 2013; Rhodes & Gelman, 2009). Perhaps this wide variety of categories, and tasks used to study them, explains why there is evidence for early (Birnbaum et al., 2010;Byers-Heinlein & Garcia, 2015;Diesendruck, Goldfein- Elbaz, et al., 2013;Kinzler & Dautel, 2012) and late (Rhodes & Gelman, 2009) emerging differences in levels of essentialist be- liefs between different cultural and national groups, as well as why those differences have been shown to come about via increases (seeBirnbaum et al., 2010), decreases (Deeb, Segall, Birnbaum, Ben-Eliyahu, & Diesendruck, 2011) or increases and decreases (Rhodes & Gelman, 2009) in essentialist thinking about social categories among children exposed to particular contexts. Taken together, these studies present a suggestive but incomplete picture. Whereas the tendency to essentialize social categories appears to have been detected in every population studied, different social categories are essentialized at different times by different groups of children. Thus, it is hard to tell whether it is the nature of the categories or the nature of the context which is important. To draw general conclusions about how and why children display essen- tialist reasoning about social categories, detailed study of particu- lar categories in particular national contexts is required. Ethnicity Categories in Israel By far the most comprehensive case study in the literature has been provided by Diesendruck and his colleagues in their study of Israeli children’s essentialist beliefs about ethnic categories (Birn- baum et al., 2010;Deeb et al., 2011;Diesendruck, Birnbaum, Deeb, & Segall, 2013;Diesendruck, Goldfein-Elbaz, et al., 2013; Diesendruck & HaLevi, 2006;Segall et al., 2015). In a series of important papers, it has been shown using a variety of experimen- tal tasks and questionnaires, that Israeli children essentialize eth- nicity categories from a young age.Diesendruck and HaLevi (2006)showed that secular Jewish kindergarteners preferred to make social inferences based on membership of ethnicity (Arab, Jew) and social class categories rather than based on shared personality characteristics. In a somewhat different task,Birnbaum et al. (2010)examined Israeli children’s willingness to base infer- ences about novel behavior on competing cues related to member- ship in ethnicity categories, gender, religiosity, and social status.Religious Jewish children preferentially used ethnicity to guide inferences, and showed little change in this tendency between kindergarten and 6th grade. In contrast, secular Jewish children and Arab children showed no preference for any category. More recent work (Segall et al., 2015) suggests that parental use of generic terms (e.g.,Jews,Arabs) to refer to social categories, is the strongest predictor of Israeli kindergarten children’s beliefs about the naturalness of ethnicity categories. Diesendruck and colleagues have also studied the effect of educational environment on essentialist beliefs about social cate- gories in Israel. The context in which children grow up could be important for shaping essentialist thinking about social categories (e.g.,Rhodes, 2013), and one contextual factor that is likely to have a large impact is the diversity of one’s immediate social environment. The effects of contact with members of diverse social groups on social cognition are well known (e.g.,Allport, 1954;Crisp & Turner, 2011;Pettigrew, 1998), and indeed,Deeb et al. (2011)present evidence that children in diverse social environ- ments may display lower levels of essentialist thinking as well. Specifically,Deeb et al. (2011)report that, based on the Essen- tialism Components Questionnaire (Diesendruck & Haber, 2009), Israeli Jewish and Arab children attending integrated schools were less likely to exhibit essentialist thinking about inheritance and psychological characteristics than children attending traditional schools. Older children in this study reported lower levels of essentialist beliefs than younger children, but this drop in essen- tialist beliefs occurred earlier for Jewish children attending inte- grated schools. Thus, in Israel, a diverse educational environment appears to attenuate the relatively high levels of essentialist beliefs about ethnicity categories with which children appear to arrive at school. Further evidence that Israeli children may have strong essen- tialist beliefs about ethnicity, and other social categories, comes from a study (Diesendruck, Goldfein-Elbaz, et al., 2013) that examined the degree to which children in Israel and the United States viewed race (Black,White) and ethnicity (Arab,Jewish) categories (along with gender, occupation, animal, and artifact categories) as arbitrary and artificial versus objective and natural. Results suggested that ethnicity was more highly essentialized for Israeli children than for U.S. children; Israeli children were less willing to accept alternative categorization for ethnicity than any other kind of category, whereas ethnicity was less salient for U.S. children. However, race was no more highly essentialized among U.S. children than among Israeli children. And although they do not discuss it directly, the data reported by Diesendruck et al. hint at overall national differences in beliefs about the naturalness of social categories; the mean probability of rejecting an alternative category was 66% for Israeli children and only 52% for U.S. children, suggesting that Israeli children may be more prone to essentialist thinking in general about social categories than U.S. children. Thus, the picture from Israel is one of (a) high levels of essen- tialist thinking about social categories in general and ethnicity categories specifically, (b) early emerging essentialism of ethnicity categories perhaps related to parental input, and (c) a general decrease in essentialist thinking with age, which occurs earlier among Jewish children attending integrated schools. However, it’s not clear the degree to which these findings about ethnicity cate- gories in Israel represent general developmental patterns or are This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 476 SMYTH, FEENEY, EIDSON, AND COLEY specific to a given political, historical, and cultural context. As such, it is important to carry out other case studies, on other social categories in other national contexts. To this end, we present an exploration of the development of essentialist thinking about reli- gion categories (Catholic, Protestant) in Northern Ireland as an- other case study to complement the Israel one. Additionally, al- though effects of educational context on responses to questionnaires has been studied in Israel (seeDeeb et al., 2011), to our knowledge there has been no study of the effects of educa- tional diversity on experimental tasks typically used to measure essentialist thinking about social categories. Accordingly, we were particularly interested in the effects of educational diversity in Northern Ireland. The Current Study: Religion Categories in Northern Ireland Northern Ireland has long been the locus of ethno-political- religious conflict between Nationalists who favor unity with the Republic of Ireland (and tend to be Catholic and ethnically Irish) and Unionists who favor Northern Ireland remaining a part of the United Kingdom (and tend to be Protestant and ethnically English or Scottish). Although dating back centuries, this conflict was most recently manifest in “The Troubles,” a period from 1968 to 1998 when thousands were killed and injured. As a result, religious affiliation—that is, membership in the category Catholic or Prot- estant—remains a critically important social dimension in North- ern Ireland today (seeGillespie, 2010) and Northern Irish society is subject to high levels of residential (seeShuttleworth & Lloyd, 2009), marital (Lloyd & Robinson, 2011), and educational (see Gallagher, 2010) segregation on the basis of religious affiliation. In contrast to Israel, large segregated population centers do not exist in Northern Ireland. Instead, the pattern is one of microseg- regation such that in urban settings entirely Catholic neighbor- hoods can abut entirely Protestant ones (seeLloyd & Shuttleworth, 2012). Consistent with this pattern of segregation, there is evi- dence that children begin to internalize the ethnic-religious sym- bols and culture of their respective community from three years of age; by age six they already personally identify with their own community and show prejudice (Connolly, 2011;Connolly, Kelly, & Smith, 2009;Connolly, Smith, & Kelly, 2002). Like Israel, there are integrated and segregated schools in North- ern Ireland. Most children in Northern Ireland attend either State “controlled” schools which are run by the Department of Educa- tion Northern Ireland, have formal links to Protestant denomina- tions, and average fewer than 5% Catholic students, or Catholic “maintained” schools which are overseen by a separate body and average less than 1% Protestant students (Northern Ireland Council for Integrated Education, 2007). Although both controlled (Prot- estant) and Catholic maintained schools provide homogenous ethno-religious environments via de facto segregation by religion, there are also integrated schools in Northern Ireland explicitly established to introduce peace education and teach children to respect and value diversity in others by bringing together Catholic and Protestant children. At present only about 5% of both nursery and primary schools in Northern Ireland are integrated (Depart- ment of Education, Northern Ireland, 2015; for reviews see,Gal- lagher, 2010;Hewstone et al., 2005).In the following five studies (along with a meta-analysis), we examine the development of essentialist thinking about social categories in Northern Ireland. In our first study, we use a forced- choice inference task based on that used byBirnbaum et al. (2010) to examine the relative potency of a culturally salient social dimension (religion) in guiding inferences about unfamiliar prop- erties. In the inference task participants learn that an individual, distinguished by its membership of two social categories, pos- sesses a property, and are presented with two further individuals each sharing with the base membership of just one social category. Participants must decide which of the target individuals is most likely to also possess the property. To the extent that participants view the property to be projectible (seeNisbett, Krantz, Jepson, & Kunda, 1983), their decisions provide an indication of their beliefs about category coherence. That is, projectible properties are more likely to be shared by members of coherent categories, and the belief that category members cohere is an important aspect of essentialism (seeGelman, 2003). We address the question devel- opmentally by testing 6-, 8-, and 10-year-old children. Based on Connolly et al.’s (2002)findings, we estimated that six years is the youngest age at which children in Northern Ireland might possess knowledge of religion categories. Furthermore, the period from 6 –11 years is a time previously shown to be associated with important change in children’s beliefs and reasoning about social categories (e.g., seeDeeb et al., 2011;Taylor, Rhodes, & Gelman, 2009). We address questions of the diversity of the educational envi- ronment by comparing category-based social inference among children in religiously integrated schools with those in religiously segregated schools. In Studies 2 and 3 we used a modified meth- odology to compare absolute levels of social inference among children attending segregated and integrated schools in Northern Ireland. In Study 4 we used the same method to examine whether the pattern we had observed was specific to Northern Ireland, or whether it also held in a group of children from the US. In Study 5 we used a completely different measure—the Essentialism Com- ponents Questionnaire (Diesendruck & Haber, 2009)—to examine whether the pattern observed in Northern Irish children’s infer- ences about social categories was an artifact of the category-based inference measures used in Studies 1– 4. And finally, we present a meta-analysis of our findings and address relations between neigh- borhood diversity and patterns of essentialist thinking about reli- gion categories. In all of the studies to be described here we asked children about three different social dimensions: religion, gender and pet owner- ship. The last dimension was included as a control; we expected that children would display more essentialist reasoning (Studies 1– 4) and stronger essentialist beliefs (Study 5) about gender (boy vs.girl) and religion (Catholicvs.Protestant) categories than about control (hamster ownersvs.goldfish owners) categories. Based on the Israeli results, we predicted that children from Northern Ireland will make more inferences based on religion category membership than based on membership of other social categories. Furthermore, if the Northern Irish case is like the Israeli one, then we should observe essentialist reasoning and beliefs about religion categories among the youngest children in our studies, and the effect of attending an integrated school should be to attenuate relatively high and early emerging levels of essential- ist reasoning. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 477 ESSENTIALIST THINKING ABOUT RELIGION CATEGORIES Study 1 Method Participants.Participants were 174 children, aged 6 –11 years, recruited from State controlled (Protestant), Catholic main- tained and Integrated schools in Northern Ireland. As may be seen inTable 1where we present demographic information about our sample, Ns for each age group in each school type varied between 17 and 20. TheseNs are comparable with those in previous developmental studies of social inference (e.g.,Birnbaum et al., 2010). Materials and design.Children were presented with a forced choice inference task (similar to that used byDiesendruck & HaLevi, 2006and byBirnbaum et al., 2010), in which they had to choose between two competing categories as a basis for inference. We focused on two contrasting categories within each of three focal social dimensions. The primary dimension of interest was religion, and the categories wereCatholicandProtestant, chosen because of their cultural, political, and historical salience in North- ern Ireland. We also asked about gender (boy/girl) as another social dimension for which categories were likely to have induc- tive potential. Finally, we utilized the dimension of pet ownership (goldfish/hamster owner) as control categories which we deemed unlikely to support inductive generalizations. By comparing infer- ences based on potentially meaningful categories of religion and gender to inferences based on these less meaningful categories, we can distinguish between targeted beliefs that specific categories conveyed inductive potential, and more generic beliefs about the inductive potential of (potentially novel) social categories. Each participant was presented with 12 triads of pictures. Each triad consisted of two base pictures and one target. The base pictures had explicit values on two of the three focal social dimensions: religion (Catholic/Protestant), gender (girl/boy), and pet ownership (goldfish/hamster), and contrasted on two of these dimensions (e.g., a Catholic boy and a Protestant girl). The target matched each base picture on one of the two dimensions (e.g., a Catholic girl). Each pairwise combination of social dimensions (religion-gender, religion-pet ownership, gender-pet ownership) was tested with four triads that utilized every combination of values on the two dimensions as targets. Stimuli were 36 hand-drawn pictures of children. Religion and pet ownership were conveyed by verbal descriptions alone; thedescriptions conveying religion category membership were “goes to a {Catholic/Protestant} church”and conveying pet ownership category membership were “owns a {goldfish /hamster}.”Gender category membership was depicted visually based on clothing and hairstyle as well as labels, and conveyed via the labelsboyand girl. All children were depicted on similar neutral backgrounds. In triads where the contrasting categories were religion and pet, gender was kept constant. Here and throughout, we chose to convey category membership for religion and pet ownership cat- egories through descriptions rather than labels to make the cate- gories as accessible as possible to our youngest participants. De- scriptions specify the relevant social dimension (e.g., “goes to X church” is a religious affiliation) in a way that labels (“is an X” is potentially ambiguous) may not. As is common in the adult literature on category-based induc- tion (seeFeeney, Coley, & Crisp, 2010), we used entirely blank properties to ensure that any effects we observed were due to participants’ beliefs about the categories in the experiment, rather than the framing of the property. In the adult literature, alphanu- meric symbols are often used to refer to properties (e.g., Prop- erty 15). As this was deemed inappropriate for the age range studied here, we instead used a different novel attribute (e.g.,is noxy, is flirst) for each triad. The order of presentation of each set of triads and the novel attributes used were counterbalanced across participants. Procedure.All participants had written parental consent and were tested individually in a quiet area of their school. They were told that we were interested in how children think about others and that there were no right or wrong answers to the questions that they would be asked. Children were then pre- sented with the 12 triads. For an example of a triad contrasting religion and control category membership, seeFigure 1.As Figure 1illustrates, children were presented with three pic- tures—two base pictures and one target picture. When pre- sented with the first base picture the experimenter said (using Figure 1as an example) “Look at this child here. This child goes to a Catholic church and owns a hamster. This child is flirst.” The second base picture was presented and the experi- menter said “Look at this child here. This child goes to a Protestant church and owns a goldfish. This child is legan.” The target was then presented and the experimenter said Look at this child here. This child goes to a Catholic church like this child (the experimenter points to the first base picture) and owns a goldfish like this child (point to the second base picture). Do you think this child (points at the target) is flirst like this child (points to base picture 1) or legan like this one (points to base picture 2)? Thus, children were asked to choose between shared membership in the same religion category and shared membership in the same control category when deciding which novel inference to draw. There were no children who were unwilling to make an inference at any point during the task. A score of 1 was given to the category that children based an inference on and a score of 0 was given to the category that children chose not to base an inference on. In addition to the counterbalancing of triads and properties across participants, the order of verbally presenting each of the two categories in each picture was also counterbalanced. Table 1 Demographic Information on Participants in Study 1 School type Age group Religion State controlled 6–7 years old:N 19 Catholic: 0% 8–9 years old:N 20 Protestant: 66% 10–11 years old:N 20 Other/Mixed: 5% Not religious: 29% Catholic maintained 6–7 years old:N 19 Catholic: 89% 8–9 years old:N 20 Protestant: 0% 10–11 years old:N 17 Other/Mixed: 9% Not religious: 2% Integrated 6–7 years old:N 19 Catholic: 29% 8–9 years old:N 20 Protestant: 19% 10–11 years old:N 20 Other/Mixed: 15% Not religious: 37% This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 478 SMYTH, FEENEY, EIDSON, AND COLEY Results Scoring.Each child attempted 12 experimental trials and had eight opportunities to make an inference based on each of the three social dimensions used in the experiment. Four of the 12 trials required them to choose between each combination of the social dimensions used in the experiment. For each combination of dimensions we calculated a score out of four to assess the degree to which participants preferred to make inferences on the basis of one or other of the dimensions. Because of our focus on inferences based on religion categories, we also calculated a score for each participant corresponding to the total number of religion-based inferences on all trials involving religion (i.e., religion-gender and religion-pet trials), ranging from 0 – 8. Relative importance of each social dimension.To examine whether participants regarded certain social dimensions as a more useful basis for inference than others, we compared mean re- sponses to chance (50%) for each dimensional pair, both overall and broken down by age and school type. Results are presented in Figure 2. Religion versus control.Overall, children made more infer- ences based on religion than based on pet ownership (M 2.33 religion-based inferences,SD 1.31),t(173) 3.35,p .001, Cohen’sd .25. As depicted inFigure 2A, among children attending State Controlled (Protestant) schools, 6-year-olds did not differ from chance, whereas 8- and 10-year-olds both based infer- ences on religion categories more often than expected by chance, t(19) 2.60,p .018,d .58 andt(19 2.41,p .027,d .54, respectively). Likewise, for children attending Catholic main- tained schools, 6-year-olds were at chance, whereas 8-year-olds showed a significant preference for religion-based inferences,t(19) 2.89,p .009,d .65. Although in the same direction, the difference did not reach significance for 10-year-olds attending Catholic maintained schools,t(16) 1.10,p .288,d 0.2. In contrast, none of the age groups of children attending integrated schools preferred religion-based inferences over those based on pet ownership. In sum, a preference for basing inferences on religion 0.0 2.0 4.0 State Controlled Catholic Maintained Integrated Mean Religion-based Inferences Type of School (B) Religion v Gender Trials 6-yr-olds 8-yr-olds 10-yr-olds 0.0 2.0 4.0 State Controlled Catholic Maintained Integrated Mean Religion-based Inferences Type of School (A) Religion v Control Trials 6-yr-olds 8-yr-olds 10-yr-olds 0.0 2.0 4.0 State Controlled Catholic Maintained Integrated Mean Gender-based Inferences Type of School (C) Gender v Control Trials 6-yr-olds 8-yr-olds 10-yr-olds Figure 2.Inferences (out of 4), broken down by School Type and Age, for each pairing of dimensions in Study 2. (A) Religion-based inferences for religion v control trials. (B) Religion-based inferences for religion v gender trials. (C) Gender-based inferences for gender vs. control trials. Error bars represent 95% confidence intervals. Target pic ture.‘This c hild here goes to a Catholic Churc h lik e this c hild (points to test pic ture 1), and owns a goldf ish lik e this c hild (points to test pic ture 2). Do y ou think this c hild is ‘flirst’lik e this c hild here (points to test pic ture 1) or ‘legan’lik e this c hild here (points to test pic ture 2)? Base pic ture 1. ‘This c hild here goes to a Catholic Churc h and owns a ham ster. This c hild here is flirst.’ Base pic ture 2.‘This c hild here goes to a Protestant Church and owns a goldf ish. This c hild here is legan’. Figure 1.A sample triad from Experiment 1 which forced children to choose between control and religion category membership as a basis for social inference. See the online article for the color version of this figure. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 479 ESSENTIALIST THINKING ABOUT RELIGION CATEGORIES over control categories seems to emerge around age 8, and only among children attending religiously segregated schools. Religion versus gender.Overall, children made more infer- ences based on religion than based on gender,M 2.60,SD 1.28,t(173) 6.24,p .001, Cohen’sd 0.47. As depicted in Figure 2B, the developmental patterns were very similar to those for religion versus control inferences. Specifically, among children attending State Controlled schools, 6-year-olds did not differ from chance, whereas 8-year-olds showed a significant preference for religion-based inferences over gender-based inferences,t(19) 4.22,p .001,d .94. Although in the same direction, the difference did not reach significance for 10-year-olds attending State Controlled schools,t(19) 1.69,p .107,d 0.38. For children attending Catholic maintained schools, 6-year-olds were at chance, whereas 8- and 10-year-olds both based inferences on religion categories more often than expected by chance,t(19) 3.33,p .004,d .74, andt(16) 4.76,p .001,d 1.15, respectively. Among children attending integrated schools, neither the 6-year-olds nor the 10-year-olds differed from chance, al- though 8-year-olds showed a significant preference for inferences based on religion over gender,t(19) 2.11,p .049,d 0.47. In sum, a preference for basing inferences on religion over gender categories seems to emerge around age 8, and was most evident among children attending religiously segregated schools. Gender versus control.Overall, to our surprise, children were no more likely to base inferences on gender than on pet ownership,M 1.87,SD 1.31,t(173) 1.27,p .205,d .10. As is evidenced inFigure 2C, no subgroup differed from chance on these items. Effects of age and educational context on religion-based inferences.Because religion was our focal dimension, we con- ducted an additional factorial ANOVA to examine the effect of educational context (State controlled, Catholic maintained, and Integrated schools), and age group (6 –7 years, 8 –9 years, and 10 –11 years) on children’s religion based inferences across both types of trials (for a total of 8) that involved religion (seeFigure 3). We also compared means to chance (4 of 8 responses.) We observed a significant main effect of age group on children’s tendency to make inferences based on shared religion category membership,F(2, 165) 5.38,p .01, partial2 0.06. Bonferroni-corrected pairwise comparisons revealed that 8-year-olds made significantly more inferences based on religion than did 6-year- olds, whereas 10-year-olds did not differ from either group. Nei- ther the effect of educational context,F(2, 165) 1.52,p .2, partial2 0.02, nor its interaction with age group,F(4, 165) .9, p .45, partial2 0.02, were significant. However, when compared with chance performance (seeFigure 3), religion-based inferences exceeded chance levels among 8- and 10-year-olds attending seg- regated schools (8-year-olds: t 4.34,p .001,d .97; 10- year-olds: t 2.70,p .02,d .66), but never did so for children attending integrated schools. Taken together, these results suggest that a preference for basing inferences on religion categories emerges around age 8, and only among children attending reli- giously segregated schools. Discussion Overall, the children in this study made more inferences based on religion category membership than on gender or control cate- gory memberships, and this preference for religion-based infer- ences emerged with development. Whereas the youngest children did not distinguish between the categories in terms of their induc- tive potential, by eight years of age religion was more informative than gender or pet ownership for the purposes of inference. This is consistent with the view that religion categories become increas- ingly essentialized among Northern Irish children, and suggests that essentialist beliefs about religion categories may emerge later in Northern Ireland than do essentialist beliefs about ethnicity categories among Israeli children (seeBirnbaum et al., 2010; Diesendruck & HaLevi, 2006). The results also suggest that Northern Irish children’s emerging essentialist beliefs about religion categories may be associated with educational context. Although the ANOVA did not show significant effects of school context, comparisons with chance showed that, among children attending integrated schools, religion categories are not used as a basis for inference more than would be expected by chance, and are no more inductively potent than arbitrary control categories. However, for children attending seg- regated schools, more inferences are based on religion category membership than would be expected by chance from 8 years of age, and by 8 years of age, religion categories are seen as more inductively compelling than control categories, or gender catego- ries. Thus, these findings are broadly consistent with previous findings that educational context is associated with essentialist beliefs about culturally salient social categories (seeDeeb et al., 2011). However, the developmental timing and direction of the effects suggests that in Northern Ireland,segregatededucational contexts may be associated with anincreasein essentialist beliefs about religion categories over time, rather than, as has been found elsewhere,integratedcontexts being associated with adecreasein essentialist beliefs. We cannot at present make causal claims about the role of educational context in the emergence of essentialist thinking; in the General Discussion we will consider constraints on how these associations with school context may be interpreted. Surprisingly, children based inferences on gender at chance levels (although this finding is not without precedent; seeDiesen- druck & HaLevi, 2006;Taylor & Gelman, 1993). Coupled with evidence that children perceive gender categories to be highly natural (i.e., immutable and nonarbitrary, e.g.,Taylor, 1996;Tay- 0.0 4.0 8.0 State Controlled Catholic Maintained Integrated Mean Gender-based Inferences Type of School 6-yr-olds 8-yr-olds 10-yr-olds Figure 3.Mean number of religion-based inferences (out of a maximum of eight) made by children in Study 1, broken down by age group, and school type. Error bars represent 95% confidence intervals. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 480 SMYTH, FEENEY, EIDSON, AND COLEY lor et al., 2009), these findings may align withHaslam et al.’s (2000)analysis of social essentialism into components ofnatural- nessandcohesiveness.Perhaps children’s extensive experience with diverse members of gender categories means that although they believe them to be natural, they perceive them to lack cohe- sion, and thus to provide a relatively weak basis for inference. We return to this point in Study 5. Overall, these results provide a basis of comparison for earlier work by Diesendruck and colleagues in Israel (e.g.,Birnbaum et al., 2010), and show that when forced to choose, children in Northern Ireland prefer to draw inferences on the basis of religion over gender or control categories. They also suggest that in North- ern Ireland the emergence of religion as a privileged category for social inference may be especially pronounced among children attending segregated schools. However, because the task involved a forced choice, we cannot draw inferences from these data about absolute levels of inductive potential afforded by religion catego- ries. In the next study, we introduce a slightly modified task which allows us to do so. Study 2 As noted above, in a forced choice paradigm like that used in Study 1 (and byBirnbaum et al., 2010;Diesendruck & HaLevi, 2006, and others), participants’ responses are taken to indicate which category is consideredmore inductively potent. One draw- back of this methodology is that it cannot measureabsolute levels of inference; by constraining the number of inferences children can make, it becomes insensitive to the possibility that both— or nei- ther— of the categories might be seen as inductively potent. To replicate and generalize the findings of Study 1 with a less con- strained task, we taught children a novel property about an exem- plar (a hypothetical child said to belong to two social categories, e.g., Catholic boy), and then individually presented targets that shared both, one, or neither category (another Catholic boy, a Catholic girl, a Protestant boy, a Protestant girl) and asked whether each target would share the property. Because this allowed us to assess absolute levels of inference as well as independently as- sessing the contributions of different social categories, it permitted us to test for general changes in levels of social essentialism as well as for variations in essentialist reasoning about religion cat- egories specifically. Differences between socially relevant catego- ries and the control category are particularly important with this method which does not require participants to choose between the different social categories as a basis for inference. Thus, observing significant differences between, for example, inferences based on religion versus pet ownership is good evidence that those infer- ences are based on specific beliefs about religion categories rather than some more generic beliefs about the inductive potential of (possibly novel) categories. Method Participants.One hundred sixty-five children, drawn from Catholic maintained, State controlled (Protestant) and Integrated primary schools in Northern Ireland, participated in this study. Table 2provides a detailed breakdown of numbers, age, and religious affiliation for each group. Materials and design.We used the same categories in this study as in Study 1, but modified the task, as described above.Each participant was presented with three sets of pictures. Each set contained a base and four targets. The base had explicit values on two of the three focal social dimensions: religion (Catholic/Prot- estant), gender (girl/boy), and pet ownership (goldfish/hamster owner). The corresponding targets represented all possible com- binations of the two dimensions. For example (seeFigure 4), the religion/gender set involved one trial for which the base and target belonged to the same religion and gender categories (R /G ), one trial for which they shared religion but differed in gender (R /G ), one in which they shared gender but differed in religion (R /G ), and one in which they came from different religion and gender categories (R /G ). The category membership of the base was counterbalanced, so the specific role assigned to each target varied accordingly. For instance, the target described as a girl who goes to Catholic church was considered R /G for participants presented with a Catholic boy as a base, but R /G for those who were presented with a Protestant girl as a base. Stimuli were 15 hand-drawn pictures. In this study, as in Study 1, religion and pet ownership category memberships were con- veyed by behavioral descriptions only. Accordingly, the five pic- tures which were used for the religion/pet ownership trials de- picted androgynous silhouettes. Gender category membership was depicted visually as well as with a label, and the remaining 10 pictures represented boys or girls (based on clothing and hairstyle). Procedure.Each child was tested individually for 5–10 min in a quiet corner of their school and had full parental consent to participate. Each child was told that they would be shown pictures of children and asked a question about each picture. For each set of categories, the experimenter showed the base picture and ver- bally presented the appropriate category information, as well as the novel property (gleeve,sproiceorchaunch). For example, for the religion/gender set, children might be shown a picture of a girl and told, “Look at this child. This child is a girl and goes to a Catholic church. This child is gleeve.” With the base picture visible, chil- dren were then shown each target picture in turn. For each target, the experimenter verbally presented the appropriate category in- formation, and asked whether or not the target would share a novel property with the base. For example, children might then be shown a picture of a different girl and told, “Now, look at this child. This child is a girl and goes to a Protestant church. Do you think this child is gleeve like this child (referring to the base)?” For trials involving pet ownership, the child was said to “have a pet goldfish/ Table 2 Demographic Information on Participants in Study 2 School type Age group Religion State controlled 6–7 years old:N 18 Catholic: 0% 8–9 years old:N 20 Protestant: 87.5% 10–11 years old:N 18 Other/Mixed: 9% Not religious: 3.5% Catholic maintained 6–7 years old:N 17 Catholic: 94% 8–9 years old:N 21 Protestant: 2% 10–11 years old:N 16 Other/Mixed: 2% Not religious: 2% Integrated 6–7 years old:N 18 Catholic: 53% 8–9 years old:N 19 Protestant: 9% 10–11 years old:N 18 Other/Mixed: 5% Not religious: 33% This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 481 ESSENTIALIST THINKING ABOUT RELIGION CATEGORIES hamster.” Children responded “yes” or “no” for each target. The same unfamiliar property was used for all four inferences in each set of trials. Order of presentation of the three sets and the four targets within each set was counterbalanced. Results Scoring.Each child saw 4 base-target pairs that matched on each social category. To measure the degree to which each social category promoted inductive generalization, we calculated 3 scores for each participant, corresponding to the number of times the target was said to share the property with the base (ranging from 0 – 4) for each type of social category (religion, gender, control). For example, the religion score was the number of positive infer- ences for the R /P ,R /P ,R /G , and R /G items. Overall analysis of social inference.To examine patterns of social inference, we conducted a 3 (Social Dimension: religion, gender, pet) 3 (School Group: Catholic maintained, State con- trolled, integrated) 3 (Age Group: 6 –7, 8 –9, and 10 –11 year olds) mixed ANOVA on mean inferences to matching targets. Overall, children based more inferences on religion (M 2.60) and the control category (M 2.41) than based on gender (M 2.04),F(2, 312) 22.43,p .001, partial2 0.13; Bonferroni- corrected pairwise comparisons revealed the differences between gender and the other two categories to be statistically significant (p .001), whereas overall inferences based on religion did not differ from those based on the control category. This was qualified by a significant interaction between social dimension and school,F(4, 312) 2.66,p .033, partial2 0.03,depicted inFigure 5. To explore this interaction we carried out three one-way ANOVAs comparing children’s use of religion, pet, and gender categories to guide inferences separately for each type of school. Children in Catholic maintained and state controlled schools showed similar patterns of inference; for both groups, inferences based on religion and control categories were more frequent than those based on gender (Catholic maintained:F(2, 106) 11.17,p .001, partial2 0.17; state controlled:F(2, 110) 14.68,p .001, partial2 0.21, Bonferroni-correctedp Base. “Look at this child. This child is a boy and goes to a Protestant church. This child is sproice”. R+/G+ Target. “Look at this child. This child is a boy and goes to a Protestant church. Do you think this child is sproice like this one (points to base)? R+/G- Target. “Look at this child. This child is a girl and goes to a Protestant church. Do you think this child is sproice like this one? R-/G+ Target. “Look at this child. This child is a boy and goes to a Catholic church. Do you think this child is sproice like this one? R-/G- Target. “Look at this child. This child is a girl and goes to a Catholic church. Do you think this child is sproice like this one? Figure 4.Sample set of base and target pictures for religion/gender trials in Study 2. Note that each target picture is labeled by its relationship to the base. For example, R G shares religion and gender category membership with the base whereas the R G target child shares membership of neither category. See the online article for the color version of this figure. 0.0 2.0 4.0 State Controlled Catholic Maintained Integrated Mean Inference s Type of School Religion Pet Ownership Gender Figure 5.Mean number of inferences (out of a maximum of four) based on religion, pet ownership, and gender, for children in state controlled, Catholic maintained, and integrated schools in Study 2. Error bars repre- sent 95% confidence intervals. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 482 SMYTH, FEENEY, EIDSON, AND COLEY .001), whereas inferences based on religion did not differ from those based on control categories. In contrast, inferences for chil- dren attending integrated schools did not differ by social dimen- sion,F(2, 108) 1.68,p .19, partial2 0.03. The results of the omnibus ANOVA also revealed a marginally significant interaction between category and age,F(4, 312) 2.09,p .08, partial2 0.03, depicted inFigure 6. To explore this interaction we carried out three one-way ANOVAs comparing children’s use of religion, pet, and gender categories to guide inferences separately for each age group. These revealed that 6- and 8-year-olds made more inferences based on religion and control category memberships than based on gender (6-year-olds: F(2, 104) 7.29,p .001, partial2 0.12; 8-year-olds:F(2, 118) 12.33,p .001, partial2 0.17; Bonferroni-correctedps .005). For both groups, inferences based on religion did not differ from those based on control categories. In contrast, the pattern for 10-year-old children was quite different; these children made sig- nificantly more inferences based on religion than on either of the other categories,F(2, 102) 7.11,p .001, partial2 0.12, Bonferroni-correctedp .05. For 10-year-olds, inferences based on gender did not differ from those based on control category membership. Religion-based inferences.Although the omnibus 3-way in- teraction was not significant (F(8, 312) 1.00,p .434, partial2 0.02), we conducted exploratory analyses to examine our focal question about the emergence of religion categories as a privileged guide for social inferences. Specifically, we compared religion- based inferences to control (pet ownership-based) inferences for each age/school group viattest. Difference scores are depicted in Figure 7(positive scores represent more inferences to religion matches than control matches). Results suggest that religion-based inferences exceeded control inferences for 8-year-olds in state controlled schools,t(20) 2.55,p .019,d 1.14 and for 10-year-olds in Catholic maintained schools,t(17) 2.56,p .020,d 1.24. Religion-based inferences never exceed control inferences among children in integrated schools. Discussion The results of this study suggest that in the absence of a forced choice, Northern Irish children’s preferences for religion-basedinferences are still late-emerging and influenced by school context. Specifically, results suggest that preference for religion-based in- ferences over control inferences was only observed among 10- year-olds, but not among 8- or 6-year-olds. Likewise, results suggest that preference for religion-based inferences over control inferences was only observed among children in segregated schools (10-year-olds in Catholic maintained schools, and 8-year- olds in state controlled schools) but not for children in integrated schools, who showed no differential use of religion, gender, or pet ownership to guide inferences. These results add weight to the possibility, suggested by Study 1, that children in Northern Ireland do not develop essentialist beliefs about religion categories until considerably later than had been suggested by results from the Israeli case study of ethnicity categories, and that attendance at a segregated school may be associated with an emerging preference for religion-based inferences. The results of Studies 2 were somewhat weaker than those of Study 1, and suggest somewhat different conclusions about the age at which essentialist reasoning about religion categories emerges in Northern Ireland. In Study 1, religion emerged as a privileged basis for inferences around age 8, whereas in Study 2 we did not observe a significant difference between religion- and control-based inferences until age 10. For these reasons, we decided to repeat Study 2, making a change to the materials. We reasoned that the absence of visual cues to religion and pet ownership categories may have taxed the working memory resources of younger participants, thus leading them to fail to distinguish between these categories in terms of inductive potency. Accordingly in Study 3 all social dimensions were represented visually as well as with behavioral descriptions (religion and control) and verbal labels (gender). Study 3 The aim of Study 3 was to establish whether Northern Irish children begin to treat religion category membership as a partic- ularly informative basis for social inference at eight years of age (as suggested by the results of Study 1) or 10 years of age (as suggested by Study 2). We used the same basic method as in Study 2 but, tomake the task cognitively less demanding for partici- pants, in Study 3 we included visual cues to category member- ship. We hypothesized that this might lead to participants 0.0 2.0 4.0 6 yr olds 8 yr olds 10 yr olds Mean Inferences Age Group Religion Pet Ownership Gender Figure 6.Mean number of inferences (out of a maximum of four) based on religion, pet ownership, and gender, for 6-, 8-, and 10-year-old age groups in Study 2. Error bars represent 95% confidence intervals. -1.00.0 1.0 2.0 State Controlled Catholic Maintained Integrated Mean Difference Score (Religion Infere nces – Control Inf erences) Type of School 6-yr-olds 8-yr-olds 10-yr-olds Figure 7.Mean difference score (number of religion-based inferences minus number of pet-based inferences) in Study 2 broken down by age group and school type. Error bars represent 95% confidence intervals. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 483 ESSENTIALIST THINKING ABOUT RELIGION CATEGORIES distinguishing religion and control categories earlier than was observed in Study 2. Method Participants.A total of 228 Northern Irish children, drawn from Catholic maintained, State controlled (Protestant), and inte-grated schools participated in this study.Table 3provides a de- tailed breakdown of numbers, age and religious affiliation for each group. Materials and procedure.We used materials similar to those used in Studies 1 and 2. However, in this study, category mem- bership was conveyed by verbal labels and by pictorial represen- tations: for religion, one of two visually distinct churches was depicted in the background, for gender, the child was depicted as a boy or a girl (based on clothing and hairstyle), and for pet ownership, a drawing of a hamster or goldfish was presented next to the depicted child (seeFigure 8). For religion/pet trials (i.e., those for which no gender value was specified), we used androg- ynous silhouettes to depict the base and target children. The procedure was identical to that used in Study 2. Results Scoring.As in Study 2, each child saw 4 base-target pairs that matched on each social category. To measure the degree to which each social category promoted inductive generalization, we calcu- lated 3 scores for each participant, corresponding to the number of times the target was said to share the property with the base (ranging from 0 – 4) for each type of social category (religion, gender, control). Table 3 Demographic Information on Participants in Study 3 School type Age group Religion State controlled 6–7 years old:N 20 Catholic: 0% 8–9 years old:N 26 Protestant: 93% 10–12 years old:N 28 Other/Mixed: 3% Not religious: 4% Catholic maintained 6–7 years old:N 27 Catholic: 86% 8–9 years old:N 28 Protestant: 11.5% 10–12 years old:N 23 Other/Mixed: 0% Not religious: 2.5% Integrated 6–7 years old:N 26 Catholic: 42% 8–9 years old:N 24 Protestant: 30% 10–12 years old:N 26 Other/Mixed: 5% Not religious: 22% Figure 8.Sample set of base and target pictures for religion/gender trials in Study 3. Note that each target picture is labeled by its relationship to the base. For example, R G shares religion and gender category membership with the base whereas the R G target child shares membership of neither category. See the online article for the color version of this figure. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 484 SMYTH, FEENEY, EIDSON, AND COLEY Overall analysis of social inference.To examine patterns of social inference, we conducted a 3 (Social Dimension: religion, gender, pet) 3 (School Group: Catholic maintained, State con- trolled, integrated) 3 (Age Group: 6 –7, 8 –9, and 10 –11 year olds) mixed ANOVA on mean inferences to matching targets. Overall, as in Study 2, children made more inferences based on religion (M 2.81) and the control category (M 2.46), than on gender (M 2.06),F(1.9, 411.9) 55.07,p .001, partial2 0.20; unlike in Study 2, overall inferences to religion categories were higher than those to control categories (all differences sig- nificant atp .01 via Bonferroni-adjustedttest). This was qualified by a marginal interaction between Category and Age Group,F(3.8, 411.9) 2.36,p .06, partial2 0.02 (shown inFigure 9). To explore this interaction we again carried out three one-way ANOVAs comparing children’s use of religion, pet, and gender categories to guide inferences separately for each age group. Results suggest that each age group presented a unique profile regarding differences among specific social dimensions. For 6-year-olds, inferences based on religion and control catego- ries were equivalent, and more frequent than inferences based on gender,F(2, 144) 31.44,p .001, partial2 0.30,p .001 via Bonferroni-correctedttests. Eight-year-olds made more inferences based on religion than based on the control categories, which in turn were more frequent than those based on gender,F(2, 154) 21.52,p .001, partial2 0.22,p .05 via Bonferroni-corrected ttests. Finally, for 10-year-olds, inferences based on religion were more frequent than inferences based on control categories or gender, which did not differ,F(2, 152) 11.91,p .001, partial2 0.14,p .02 via Bonferroni-correctedttests. There were no significant effects involving educational context, and the three- way interaction was also not significant. Discussion Overall, participants in this study based more inferences on religion category membership than membership in other social categories. Thus, we have replicated the central finding of Study 1, that children in Northern Ireland view religion categories as a strong basis for social inference. Furthermore, just as in Study 1,6-year-olds did not distinguish between the inductive potential of religion and control categories, whereas 8-year-olds did so. In other words, religion categories did not become a uniquely impor- tant basis for social inference until eight years of age. This sug- gests that the finding in Study 2, that children did not distinguish between religion and control categories as bases for inference until 10 years of age, may have been attributable to the absence of visual cues in that study making the task more demanding on memory. However, because we did not experimentally manipulate this as- pect of our materials, this is a speculative interpretation. Interest- ingly, even the addition of visual cues in this study did not lead to 6- to 7-year-olds distinguishing between the categories. Thus, the results of this study, along with the results of Study 1, suggest that in contrast to Israel where children appear to arrive at school with essentialist beliefs about ethnic categories, children in Northern Ireland do not develop such beliefs about religion categories until eight years of age. In contrast to the results of Studies 1 and 2, the results of this study show no clear differences between children attending inte- grated schools in Northern Ireland and those attending segregated schools. Both make more inferences based on religion category membership than based on gender or membership in a control category. We return to this issue in the General Discussion. Study 4 Studies 1–3 present clear evidence that by age 8, children in Northern Ireland come to essentialize religion categories to a greater degree than gender or control categories. Although the historical and cultural significance of the categoriesCatholicand Protestantin Northern Ireland is undisputed, this developmental pattern may be specific to the historical factors that have shaped Northern Ireland culture, or alternatively may represent a more general tendency to essentialize religion categories. To begin to distinguish between these possibilities, we examined whether the pattern of development we see in Studies 1–3 is specific to North- ern Ireland, by testing a comparison group of children from the greater Boston area in the United States. We chose to recruit a sample in Boston because of the geographical distance and the cultural similarities. People in the Boston area share close linguis- tic, cultural, and even family linkages to Northern Ireland, and thus in many respects the two areas are culturally very similar, and thus comparable in many ways. In particular, the largest religious group in both places is Catholic; c. 29% of people declare themselves Catholic in Boston (Pew Research Centre, 2014), versus c. 41% in NI (Northern Ireland Statistics & Research Agency, 2014). How- ever, the geographical distance and lack of conflict between Prot- estants and Catholics in the United States means that children in Boston are less likely to be affected by the historical-cultural conflict specific to Northern Ireland than children in, say, Great Britain or the Republic of Ireland. Therefore, if the historical- cultural-context specific to Northern Ireland is driving the pattern of emergence of essentialist thinking about social categories we observe there, then the categoriesCatholicandProtestant, al- though present and familiar to most Americans, may be less salient—and perhaps less essentialized—than they are in Northern Ireland. 0.0 2.0 4.0 6 yr olds 8 yr olds 10 yr olds Mean In ferences Age Group Religion Pet Ownership Gender Figure 9.Mean number of inferences (out of a maximum of four) based on religion, pet ownership, and gender, for 6-, 8-, and 10-year-old age groups in Study 3. Error bars represent 95% confidence intervals. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 485 ESSENTIALIST THINKING ABOUT RELIGION CATEGORIES Method Participants.A total of 67 children, drawn from public schools in the Commonwealth of Massachusetts, U.S.A., partici- pated in this study. Thirty of these children were aged 6 –7 years, 28 were aged 8 –9 years, and 23 were aged 10 –12 years. Twenty- nine percent of the sample was Catholic, 12% Protestant, 5% other or mixed and the remaining 53% were not religious. With respect to race and ethnicity, the communities from which the sample was drawn averaged 90% European American, 2% African American, 5% Asian American, and 4% Latino, according to 2010 U.S. Census figures. These categories are more varied than those which characterize the samples from Northern Ireland, which were close to 100% Caucasian Europeans. Materials and procedure.With one exception, the materials were identical to those used in Study 3 where participants received both pictorial and verbal cues for each category they were pre- sented with. Because we had identified religion and pet ownership category memberships using verbal cues only in Studies 1 and 2, but using verbal and pictorial cues in Study 3, half of the partic- ipants in Study 4 received pictorial plus verbal cues, and half received verbal cues for all three dimensions but pictorial cues for gender only (i.e.,religionandpet ownershipwere described but not pictured). This was done to test whether responses were influenced by the presence of the pictorial representations of religion and pet categories. 1In all other respects the procedure and data scoring was as described for Study 3. Results and Discussion Mean rates of inference for U.S. children, broken down by age and social dimension, are presented inTable 4. We computed mean scores for inferences based on religion, gender, and control categories as described for Studies 2 and 3, and conducted a 3 (Age Group) 3 (Social Dimension) mixed ANOVA. Overall, infer- ences to religion and control categories were higher than those to gender categories, but did not differ from each other,F(2, 128) 9.62,p .001, partial2 0.13, Bonferroni correctedttest ps 0.005. Although no other effects were significant, compari- sons to chance performance (seeTable 4) revealed that inferences based on religion and control category membership were above chance for 6-year-olds, marginally above chance for 8-year-olds, and did not differ from chance for 10-year-olds. Gender-based inferences never differed from chance levels.Although this is a preliminary foray into cross-national compar- isons of reasoning about religion categories, based on qualitative comparison the U.S. children in this study differ markedly from children in Northern Ireland in several ways. First, children in the Boston area never drew inferences based on religion at levels that exceeded the control category, whereas children in Northern Ire- land did so by age 8 (Studies 1 and 3) or 10 (Study 2). Second, only 6-year-olds, but not 8- or 10-year-olds, drew inferences based on any social category at above-chance levels, whereas in Northern Ireland, the developmental trajectory was reversed, from chance levels around age 6 to above-chance levels among older children. Moreover, the differences were specific to the salience of religion categories; inferences based on gender were similarly rejected by children on both sides of the Atlantic. These results suggest that the pattern we have observed in Northern Irish children’s reason- ing about religion categories is not universal, but instead is likely related to historical and cultural factors specific to Northern Irish society. An alternative explanation for the different patterns in the U.S. and Northern Ireland is that U.S. children simply lack familiarity with the labelsCatholicandProtestant. Although we are aware of no data directly investigating the familiarity of religion category labels to U.S. children, previous work suggests that children in Northern Ireland identify with their ethnic-religious category by age six (seeConnolly, 2011), and that U.S. participants retrospec- tively report acquiring the termCatholicat 7– 8 years of age (Kuperman, Stadthagen-Gonzalez, & Brysbaert, 2012). As such, it seems unlikely that our 10-year-old U.S. participants—who showed no evidence of a preference for inferences based on religion category membership—are completely unfamiliar with these labels. Nevertheless, until familiarity data are collected, the possibility remains that the difference between children in North- ern Ireland and the United States may be attributable to relative familiarity with the category labels, rather than differences in essentialist thinking about religion categories. Study 5 The results of Studies 1– 4 are remarkably coherent and suggest that essentialist beliefs about religion categories emerge relatively late in Northern Ireland, and are more likely to be observed among children attending segregated rather than integrated schools. As dis- cussed above, this pattern is somewhat different from that described by other researchers (e.g., Diesendruck and colleagues). These differ- ences may reflect contextual and cultural differences in the manifes- tation of essentialist thinking about social categories. However, the different findings may also stem from methodological differences. For example, whereas Diesendruck and colleagues asked participants to reason about specific novel properties (e.g., “likes to play zigo”), we asked children to reason about properties presented as adjectives (e.g., “is legan”). As such, one possibility is that essentialist reasoning in our study showed a different developmental pattern because younger children may not have taken the adjectives to indicate projectible properties. Although we think this is unlikely given the willingness of 6-year-olds in the United States to draw inferences about identical properties, and moreover, this methodological difference doesn’t ex- 1Analysis of this manipulation revealed no effect of materials so, for the purposes of subsequent statistical analysis, we ignored this variable. Table 4 Mean Inferences Based on Religion, Gender, and Control Categories for U.S. Children Age groupSocial dimension Mean ReligionPet ownership (Control) Gender 6-yr-olds 2.83 (1.09) 2.80 (1.06) 2.10 (1.03) 2.58 (.88) 8-yr-olds 2.56 (1.20) 2.56 (1.15) 2.06 (1.16) 2.39 (1.00) 10-yr-olds 2.37 (1.38) 2.00 (1.11) 1.84 (1.07) 2.07 (.92) Mean 2.63 (1.20) 2.51 (1.13) 2.01 (1.07) Note.Chance 2/4. p .10. p .001. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 486 SMYTH, FEENEY, EIDSON, AND COLEY plain the school- or dimension-based differences among older chil- dren, it is nevertheless a systematic methodological difference that warrants attention. In addition, whereas Diesendruck and colleagues always con- veyed social category membership via labels (e.g., “this child is a boy”), we used behavioral descriptions for religion and pet cate- gories (e.g., “this child goes to a Catholic church”), and used category labels for gender categories only. As such, one possible explanation for the late emergence of essentialist thinking about religion categories in our study is that membership in religion and pet categories had to be inferred from behavioral descriptions. In other words, conveying category membership via descriptions rather than labels may underestimate the inductive power of these categories for younger children (seeGelman, Collman, & Mac- coby, 1986). Importantly, this possibility is weakened by the observation that gender categories—the only categories whose membership we actually did convey via labels—were consistently the weakest basis for inductive generalizations. Nevertheless, given these possibilities, it is important to assess the generality of our results using a different measure of essentialism. In Study 5 we sought to examine essentialist thinking about social categories in Northern Ireland using an entirely different measure. To do so, we used a modified version of the Essentialism Components Questionnaire, which has previously been used to assess essentialist beliefs in children as young as five (Deeb et al., 2011;Diesendruck & Haber, 2009). Specifically, we used items designed to examine the degree to which children view social categories as distinct from each other (i.e., having strong and well-defined boundaries), and stable (i.e., resistance to change). Both of these measures can be thought of as indices of category naturalness rather than of category coherence (e.g.,Haslam et al., 2000). To the extent that this measure corroborates the results reported above—that older children show more evidence of essen- tialist beliefs about religion categories than younger children, and that such beliefs are most pronounced among those attending segregated schools—it becomes less likely that our inference re- sults are attributable to methodological artifacts. Method Participants.Ninety-four children were recruited from Catholic maintained and integrated primary schools in Northern Ireland. As may be seen inTable 5where we present demographic information about our sample,Ns for each age group in each school type varied between 15 and 16. TheseNs are comparable with those in previous developmental studies involving the Essentialism Components Ques-tionnaire (e.g.,Diesendruck & Haber, 2009). Written parental consent was given for every child who participated. Materials and procedure.Each participant was tested for 10 min in a quiet area of their school/classroom. Participants were asked a series of questions about religion, gender, and pet owner- ship categories. Questions were blocked by dimension, and at the start of each block participants were shown two hand drawn pictures, similar to those used in Studies 2 and 3, and told that each depicted a member of one or other of the social categories assessed by the subsequent questions. For each target dimension, five questions were designed to assess the extent to which participants viewed social categories as distinct and two to assess the extent to which category membership was viewed as stable. All five dis- tinctiveness questions and one stability question were taken from Diesendruck and Haber’s (2009)Essentialism Components Ques- tionnaire. The distinctiveness questions concerned the extent to which members of named social categories (e.g.,Catholicand Protestant) are different in what they like, how they behave, how they look, what they have inside their body and what they think. The stability questions asked about the possibility of changing one’s membership from one category to another and whether one can belong to both categories at once. We counterbalanced the order in which the three social dimen- sions were presented, and within blocks participants answered all of the distinctiveness questions before they answered questions about stability. Distinctiveness questions were asked in one of six different orders and the order of the two stability questions was counterbalanced. Distinctiveness questions were phrased “How much are Catholic children and Protestant children different in…” and malleability questions were phrased “How possible is it for a child who owns a goldfish to swap it for a hamster?” Children answered all questions on a Visual Analogue Scale with four response options. Each response option depicted a stick figure the position of whose arms corresponded to the labels “not at all,” “a little,” “a lot,” or “completely.” For example, in the picture illus- trating the “not at all” response option, the stick figure’s arms rested together on a surface, whereas in the picture illustrating the “completely” response option, the arms were aloft and held as wide apart as possible. Results Exploratory factor analyses.We entered children’s re- sponses into three separate factor analyses— one for each social dimension. All three analyses employed varimax rotation and a principal components extraction method. Factor solutions for re- ligion and pet ownership were identical, producing two factors with eigenvalues above 1. The first factor, distinctiveness, con- sisted of responses to the distinctiveness questions, and the second factor, stability, of responses to the stability questions. For reli- gion, the first factor accounted for 34% of the variance, and the second for 17% of the variance (for rotated factor loadings, see Table 6). For pet ownership, the factors accounted for 33% and 19% of the variance, respectively. The initial factor analysis of gender resulted in three factors with eigenvalues greater than 1. To enable between-dimension comparisons we limited the solution to two factors. The first factor, distinctiveness, accounted for 30% of the variance and the second, stability, for 23% of the variance. Table 5 Demographic Information on Participants in Study 5 School type Age group Religion Catholic maintained 6–7 years old:N 16 Catholic: 91.5% 8–9 years old:N 15 Protestant: 0% 10–11 years old:N 16 Other/Mixed: 6.5% Not religious: 2% Integrated 6–7 years old:N 16 Catholic: 44.5% 8–9 years old:N 15 Protestant: 34% 10–11 years old:N 16 Other/Mixed: 8.5% Not religious: 13% This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 487 ESSENTIALIST THINKING ABOUT RELIGION CATEGORIES Based on the factor analyses, we used the raw scores to calculate each child’s perceived distinctiveness and stability scores by av- eraging their responses for each set of items. Stability scores were derived from reverse-scored stability questions so that higher scores represented more essentialist (i.e., less malleable, or more stable) responses. These scores were analyzed separately via 3 (Age Group) 2 (School) 3 (Dimension) ANOVAs with repeated measures on the last factor. Category distinctiveness.Overall, children believed that gen- der categories (M 2.73) were more distinct than religion (M 2.39) or pet ownership (M 2.44) categories, which did not differ, F(2, 176) 17.99,p .001, partial2 .17, Bonferroni-correctedt testp .001. However, as may be seen inFigure 10, these differences emerged over development (Age Group x Dimension interaction:F(4, 176) 4.45,p .002, partial2 .09). To explore this interaction, we conducted three 2 (School) 3 (Dimension) ANOVAS. These showed increasing differentiation between di- mensions with age: 6-year-olds did not distinguish among the dimensions with respect to distinctiveness,F(2, 60) 0.76,p .472, partial2 .02, whereas for 8-year-olds, gender categories were more distinctive than religion categories (although neither differed from pet ownership categories),F(2, 56) 4.64,p .02, partial2 .14, and for 10-year-olds, gender categories were seen as more distinct than religion or pet ownership categories, which did not differ,F(2, 60) 29.34,p .001, partial2 .49.Category stability.Overall, children believed that gender cat- egories (M 3.16) were more stable than religion categories (M 2.77) which were more stable than pet ownership categories (M 2.36),F(2, 176) 20.86,p .001, partial2 .19, Bonferroni- correctedttestsp .003. However, this was qualified by a significant interaction with Age Group,F(3.6, 158.8) 7.2,p .001, partial2 .14 (seeFigure 11A), and a marginally significant interaction with School,F(1.8, 158.8) 2.76,p .08, partial2 Table 6 Factor Loading of Each Dimension From the Essentialism Components Questionnaire Religion Gender Pet ownership Question Distinctive Stable Distinctive Stable Distinctive Stable 1. What they like .70 .33 .72 .03 .70 .09 2. How they behave .53 .42 .49 .12 .68 .01 3. How they look .65 .01 .77 .21 .64 .11 4. What they have inside their body .66 .009 .44 .008 .74 .11 5. What they think .74 .09 .72 .03 .62 .14 6. Possibility of category change .16 .77 .002 .88 .15 .82 7. Possibility of joint membership .16 .65 .004 .91 .10 .79 1.0 2.0 3.0 4.0 6 yr olds 8 yr olds 10 yr olds s s e n e v i t c n i t s i D n a e M Age Group Religion Pet Ownership Gender Figure 10.Mean distinctiveness score for religion, pet ownership, and gender categories for 6-, 8-, and 10-year-old age groups in Study 5. Error bars represent 95% confidence intervals. 1.0 2.0 3.0 4.0 Catholic Maintained Integrated Mean Stability (B) Stability: School x Dimension, 10-year-olds only Religion Pet Ownership Gender 1.0 2.0 3.0 4.0 6 yr olds 8 yr olds 10 yr olds s s e n e v i t c n i t s i D n a e M Age Group (A) Stability: Age x Dimension Religion Pet Ownership Gender Figure 11.(A) Mean stability score for religion, pet ownership, and gender categories for 6-, 8-, and 10-year-old age groups in Study 5. (B) Mean stability scores by social dimension for 10-year-olds attending Cath- olic Maintained and Integrated Schools. Error bars represent 95% confi- dence intervals. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 488 SMYTH, FEENEY, EIDSON, AND COLEY .03 (seeFigure 11B). To explore these interactions, we conducted three 2 (School) 3 (Dimension) ANOVAS. These again showed increasing differentiation between dimensions with age. Six-year- olds did not distinguish among the dimensions with respect to stability,F(2, 60) 1.81,p .17, partial2 .06, nor did 8-year- olds,F(1.5, 42.2) 2.5,p .11, partial2 .08. In contrast, for 10-year-olds, gender was significantly more stable than religion, which was more stable than pet ownership,F(2, 60) 67.11,p .001, partial2 .69, Bonferroni-correctedttestsp .001. More- over, this difference was qualified by a significant Dimension School interaction,F(2, 60) 8.45,p .001, partial2 .22. Bonferroni-correctedttests on the means involved in the interac- tion revealed that for all 10-year-olds, membership in gender categories was more stable than membership in religion or pet ownership categories (p .008). However, for children attending segregated schools, religion was seen as more stable than pet ownership (p .001), whereas for children attending integrated schools, stability for religion and pet ownership categories did not differ (p .217). Discussion The results of this study are important for two reasons. First, they provide additional support— using an entirely different meth- od—for the claim that essentialist beliefs about religion categories are relatively late-emerging in Northern Irish children, and are more likely to emerge in those attending segregated rather than integrated schools. Whereas 10- to 11-year-olds attending segre- gated schools perceived religion category membership to be sig- nificantly more stable than control category membership, 10- to 11-year-olds attending integrated schools did not distinguish be- tween the stability of religion and control categories. This supports the findings of Studies 1–3 and makes it unlikely that differences in the developmental pattern seen by us in Northern Ireland and by Diesendruck and colleagues in Israel stem from methodological issues. Second, these results address the surprising lack of gender-based inferences in Studies 1– 4. In those studies, children consistently made more inferences based on pet ownership categories— chosen as a control because we did not expect them to be essentialized— than gender categories. We argued above that this finding (see also Diesendruck & HaLevi, 2006;Taylor & Gelman, 1993), coupled with evidence that children perceive gender categories to be highly natural (e.g.,Taylor, 1996;Taylor et al., 2009), is consistent with Haslam et al.’s (2000)analysis of social essentialism into compo- nents ofnaturalnessandcohesiveness.Haslam et al. (2000)have demonstrated that adults’ essentialist beliefs factor into two or- thogonal dimensions: naturalness and cohesiveness (“entitativity;” see alsoRangel & Keller, 2011). The naturalness dimension in- cludes beliefs about the extent to which any social category is ‘real’ rather than conventional, heritable, and stable over time despite environmental influences. The cohesiveness dimension refers to beliefs about the extent to which category members are homogeneous and share an underlying similarity that is predictive of further observable or hidden properties. Results of Study 5 demonstrate that children in Northern Ireland do indeed hold essentialist beliefs about gender categories. Specifically, gender categories were clearly perceived to be more stable and more distinct than religion or pet ownership categories. Taken togetherwith the results of Studies 1– 4, these findings suggest that children may essentialize gender categories with respect to naturalness more so than with respect to cohesiveness. More generally, these results also emphasize the importance of analyzing the develop- ment of essentialist thinking in terms of distinct components (Haslam et al., 2000). Although gender categories were essentialized in terms of be- liefs about distinctiveness and stability, religion categories were essentialized in terms of stability only. We are unsure why this pattern emerged. One interpretative difficulty lies in relating the concept of distinctiveness to Haslam et al.’s two-factor structure. Indeed, previous work using the ECQ links distinctiveness items both to the sharpness of boundaries between categories (Diesend- ruck & Haber, 2009), which is an element of naturalness, and to category uniformity and informativenesss (Deeb et al., 2011), which is an element of coherence. In our view, distinctiveness relates to discrete boundaries between categories rather than to category uniformity. In particular, the distinctiveness questions ask about differences between members of different categories rather than the similarities between members of the same category which might underlie beliefs about informativeness. Another issue with the distinctiveness dimension is that close inspection of factor loadings across the different studies in the literature reveals that individual distinctiveness items have been found to load onto different dimensions. Perhaps the safest interpretation of our find- ings across all five studies is that they suggest that gender cate- gories are essentialized along the naturalness but not the coherence dimension, whereas religion is essentialized along the coherence dimension and along some, but not all, elements of the naturalness dimension. Why the different elements of the naturalness distinc- tion might be dissociated for religion categories will be a question for future research. Meta-Analyses Overall, results consistently suggest that essentialist beliefs about religion develop relatively late among children in Northern Ireland. Results also suggest effects of school context—that es- sentialist thinking about religion categories is predominantly ob- served among children attending segregated schools— but evi- dence from individual studies is less consistent. To examine this potential context effect with more power, we carried out meta- analyses on the results of Studies 1, 2, 3, and 5, using participating schools as the unit of analysis. An advantage of this data analytic strategy is that it also allowed us to examine the effect of com- munity diversity on our measures of essentialist reasoning and beliefs. Effects of School Type on Essentialist Reasoning A total of 20 schools participated in Studies 1, 2, 3, and 5. Six of the participating schools were integrated and 14 segregated. To conduct the meta-analysis, for each participating school we entered the mean difference (and associated standard error) between reli- gion and pet ownership scores on the measure of essentialism administered to participating children (difference between religion inferences and chance responding on the trials placing religion and control category memberships into conflict in Study 1; difference between religion and pet ownership inferences in Studies 2–3 and This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 489 ESSENTIALIST THINKING ABOUT RELIGION CATEGORIES religion and pet ownership essentialism scores in Study 5) into the Comprehensive Meta-analysis software package (Borenstein, Hedges, Higgins, & Rothstein, 2009). Results of the analysis are presented inTable 7. Mixed effect meta-analysis with schools grouped by type, revealed that overall, essentialist reasoning was more evident for religion categories than control categories (std mean difference .27,SE .05, 95% CI [.19, .36], Z(20) 6.02,p .001). Importantly, this category effect was highly significant for segregated schools (std mean difference .30, SE .05, 95% CI [.20, .40], Z(14) 6.00,p .001). In contrast, the effect fell short of significance for integrated schools (std mean difference .15,SE .11, 95% CI [ .07, .37], Z(6) 1.34,p .18), although a test for hetereogeneity between school types was nonsignificant, Q(1) 1.56,p .21. This reinforces the pattern of results across our experimental studies: religion categories were preferentially essentialized among chil- dren attending segregated schools, but not among children attend- ing integrated schools. Effects of Community Diversity on Essentialist Reasoning An alternative explanation for the effect of school type on essentialist reasoning about religion categories is that perhaps integrated schools tend to be in more integrated neighborhoods than segregated schools, and the diversity of the neighborhood, rather than the diversity of the educational setting, is really driving the differences in essentialist thinking. To examine the relationship between community diversity and essentialist thinking about reli- gion categories, we used census data (Northern Ireland Neighbour- hood Information Service, 2012) to estimate the absolute differ-ence between the proportion of Protestants and Catholics in the electoral ward where each of the participating schools was located. Electoral wards in Northern Ireland range in size from approxi- mately 1000 to 9000 inhabitants. Because we did not ask partici- pants for their addresses, we cannot be sure that they lived in the electoral ward where the school was located. However, proximity to the school is a selection criterion for many Northern Irish schools, so primary schoolchildren in Northern Ireland tend to go to a nearby school. Thus, a measure of local community homoge- neity based on school location is likely to be a good measure of the degree to which participating children’s local communities are diverse. In principle, community diversity scores could range from 0 (equal proportions of Catholic and Protestants in the Ward) to 100 (the ward is entirely Catholic or Protestant); in practice, scores ranged from 0.05 to 86.4. The average diversity scores were 29.0 (SD 20.27) for wards in which integrated schools were located, and 43.2 (SD 26.41) for wards in which segregated schools were located. Although this difference was not statistically significant, t(19) 1.17,p .26,d .60, the size and direction of the effect suggests that integrated schools tend to be located in more diverse communities. Accordingly, it is important to assess in a meta- analysis whether local community diversity offers a plausible alternative account of the effects of educational diversity we have observed. If community diversity does explain our results, we would expect the highest degrees of essentialist thinking among children attending schools in the least diverse neighborhoods. To examine this possibility, we carried out a metaregression analysis to test whether community diversity predicted effect size across our Table 7 Meta Analytic Effects of Category (Religion vs. Control) in Each of the Schools, and Community Diversity in Each of the Associated Wards, Included in Studies 1, 2, 3, and 5, Grouped by School Type School typeStudy (Ward)Std difference in meansStandard error95% confidence limitzvaluep Integrated 1 (a) .20 .21 [ .61, .22] .94 .349 1 (b) .34 .17 [.00, .67] 1.96 .050 2 (c) .05 .13 [ .31, .22] .36 .721 3 (d) .57 .16 [.26, .87] 3.64 .001 3 (e) .07 .19 [ .31, .44] .35 .729 5 (f) .11 .15 [ .17, .40] .77 .44 Category effect, integrated sector .15 .11 [ .07, .37] 1.34 .18 Segregated 1 (g) .87 .44 [ .00, 1.74] 1.96 .051 1 (h) .24 .16 [ .08, .55] 1.45 .15 1 (i) .30 .14 [.02, .58] 2.12 .034 1 (j) .72 .27 [.18, 1.25] 2.64 .008 2 (k) .84 .34 [.18, 1.50] 2.50 .012 2 (l) .06 .15 [ .24, .35] .38 .704 2 (m) .29 .18 [ .05, .63] 1.65 .098 2 (n) .29 .23 [ .15, .74] 1.29 .198 3 (o) .19 .16 [ .13, .50] 1.15 .252 3 (p) .40 .15 [.10, .71] 2.59 .009 3 (q) .51 .20 [.12, .89] 2.57 .010 3 (r) .27 .16 [ .05, .59] 1.66 .098 5 (s) .04 .26 [ .47, .55] .15 .88 5 (t) .30 .18 [ .05, .66] 1.67 .09 Category effect, segregated sector .30 .05 [.20, .40] 6.00 .001 Category effect overall .27 .05 [.19, .36] 6.02 .001 This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 490 SMYTH, FEENEY, EIDSON, AND COLEY schools and studies. The results inTable 8suggest that community diversity is unrelated to children’s tendency to essentialize religion categories (regression coefficient 0.002).Figure 12clearly illustrates that the measure of community diversity does not pre- dict the size of the category effect, suggesting that the differences between integrated and segregated schools observed in our studies are not attributable to differential diversity of the communities surrounding the schools. General Discussion Our purpose was to carry out a case study of the development of children’s essentialist thinking about religion categories in North- ern Ireland. Results paint a consistent picture of the development of essentialist thinking among Northern Irish children, and one that differs considerably from our expectations. In Study 1, using a forced choice task, we found that 6-year-olds did not discriminate between the inductive potency of religion and control category membership, but that 8- and 10-year-old children did so. In Study 2 we employed a method which permitted children to base indi- vidual inferences on membership of more than one category, andfound that they did not regard religion category membership as a better basis for social inference than membership in a control category until 10 years of age. The results of Study 3 suggested that children distinguish between religion and control category memberships at eight years. As the willingness to base inferences about individuals on the basis of their category membership de- pends on beliefs about category cohesiveness, these results strongly suggest that children in Northern Ireland come to privi- lege religion categories to guide inferences about novel properties, but that such essentialist reasoning about religion categories in Northern Ireland is relatively late-emerging, and is not observed until (at least) eight years of age. The results of Study 5, in which we directly measured essentialist beliefs about social categories, showed that children do not rate religion categories more stable than control categories until 10 years of age. Obtained using an entirely different method, this finding confirms our conclusions about the timing of the emergence of essentialist reasoning and beliefs about religion categories among Northern Irish children. Our results also revealed differences in the essentialist reasoning of Northern Irish children educated in integrated and segregated schools. In Study 1 we found that children educated in segregated Catholic maintained or State controlled (Protestant) schools per- ceived religion categories to be more inductively potent than control categories by age 8, whereas children educated in inte- grated schools did not differentiate among social dimensions with respect to inductive potential even at age 10. Similar results were obtained in Study 2. Although the results of Study 3 did not replicate this pattern, the tendency to believe membership of religion categories to be more stable then membership of control categories was only observed in 10 year olds attending segregated schools in Study 5. Thus, the overall picture that emerges is of Table 8 Results of Meta-Regression Predicting Essentialist Reasoning About Religion Categories From Community Diversity CovariateRegression coefficientStandard error95% confidence intervalzvaluep Intercept .19 .10 [ .001, .380] 1.95 .051 Community diversity .002 .002 [ .002, .006] .82 .500 Community Diversity -20.0 0.0 20.0 40.0 60.0 80.0 100.0 s n a e m n i f f i d d t S 1.00 0.80 0.60 0.40 0.20 0.00 -0.20 -0.40 -0.60 Figure 12.Scatterplot showing relationship between the diversity of the community in which each participat- ing school was located and the standardized difference between the means for religion and control categories. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 491 ESSENTIALIST THINKING ABOUT RELIGION CATEGORIES essentialist beliefs about religion categories emerging predomi- nantly in children attending religiously segregated schools. The majority of children in our studies who attended integrated schools showed no evidence of more essentialist reasoning about religion categories than about control categories. These conclusions were confirmed by the results of a meta-analysis across the results from all participating schools in Northern Ireland, which also ruled out neighborhood diversity as an alternative explanation for this find- ing. Thus, in Northern Ireland, selective essentialist thinking about religion categories emerges among children attending religiously segregated schools, but not among children attending religiously integrated schools. The results of Study 4 showed, as expected, that children in the United States do not appear to engage in more essentialist reason- ing about religion categories than other social categories. In fact, the pattern we observed among children from the United States in Study 4 was, in many respects, the reverse of the pattern observed in Northern Irish children in Study 1. Northern Irish children showed no evidence of essentialist reasoning until eight years of age, whereas children in the US showed evidence of essentialist reasoning at age six—perhaps because of category novelty— but no evidence of essentialist reasoning at eight or 10 years of age. This is consistent with the idea that the developmental pattern regarding essentialist reasoning about religion categories we ob- served in Northern Ireland may be specific to the particular his- torical, political, and cultural context of Northern Ireland. Comparing Northern Ireland and Israel We sought to generate a Northern Irish case study of the development of essentialist reasoning about religion categories in part to complement the research program of Diesendruck and colleagues on the development of essentialist thinking about eth- nicity categories in Israel (e.g.,Birnbaum et al., 2010;Diesendruck & HaLevi, 2006). It is important to point out that there are multiple important differences between the Northern Irish and Israeli case studies, and as earlier discussion of our methodological choices will have made apparent, our intention was not to replicate the Israeli studies in Northern Ireland. Nevertheless, a qualitative comparison of overall developmental patterns in the two cases is highly informative; it reveals striking parallels as well as important differences in development of essentialist thinking in the two contexts, and raises generative questions for future study. First, like the Israeli data, our studies show that children grow- ing up in a society with a history of conflict between social groups are especially likely to essentialize the categories which are the basis of that conflict. This was evident both within and between cultures. Within cultures, children in Northern Ireland were more essentialist about religion categories than control categories (Stud- ies 1–3 and 5), whereas children in Israel were more essentialist about ethnicity categories than other categories (e.g.,Birnbaum et al., 2010;Diesendruck & HaLevi, 2006). Between cultures, chil- dren in Northern Ireland reasoned differently about religion cate- gories than children in the United States (Study 4), and children in Israel reason differently about ethnicity categories than children in the United States (Diesendruck, Goldfein-Elbaz, et al., 2013). Thus, in both Israel and Northern Ireland, we see differential essentialist thinking about culturally salient social categories.Despite differences between the integrated sectors in Israel and Northern Ireland (Bekerman, Zembylas, & McGlynn, 2009), a second important similarity between Northern Ireland and Israel concerns the different developmental trajectories of essentialist reasoning among children in segregated versus integrated educa- tional contexts. Children attending integrated schools in Northern Ireland show evidence of attenuated essentialist reasoning (Studies 1 and 2) and beliefs (Study 5) about religion categories relative to children attending segregated schools. Likewise, children attend- ing integrated schools in Israel show evidence of attenuated es- sentialist beliefs about ethnicity categories relative to children attending segregated schools (Deeb et al., 2011). Thus, both case studies contain important findings relating to the effects of historical-cultural context and associations with educational diver- sity on how and whether essentialist reasoning about socially relevant categories is manifested. Similarities notwithstanding, our data suggest that in important respects, development of essentialist thinking about social catego- ries differs in Northern Ireland and Israel. First, none of the Northern Irish children included in our studies appeared to develop essentialist beliefs about religion categories until eight years of age, whereas studies consistently show that some Israeli children as young as five years of age show evidence of essentialist rea- soning about ethnicity (Birnbaum et al., 2010;Diesendruck, Goldfein-Elbaz, et al., 2013;Diesendruck & HaLevi, 2006;Segall et al., 2015). Importantly, the pattern that emerged in Northern Irish children’s category-based reasoning (Studies 1–3) was con- firmed in a study using a very different, and perhaps more direct, measure of essentialist beliefs (Study 5), suggesting that this difference is unlikely to be a methodological artifact. There are several reasons why essentialist reasoning about ethnicity catego- ries in Israel may emerge earlier than essentialist reasoning about religion categories in Northern Ireland. First, visual and linguistic cues to ethnic category membership in Israel may make member- ship of such categories much more salient or outwardly obvious than cues to membership in religion categories in Northern Ireland; some theorists hold visual cues to be extremely important to social category essentialism (e.g.,Gil-White, 2001). It is conceivable that because visual cues to religion category membership in Northern Ireland are less readily observable, children become aware of the importance of religion categories later in Northern Ireland than is the case for ethnicity categories in Israel. If so, attendance at a segregated school may be an important component of children’s developing awareness of religion categories in Northern Ireland. Another explanation for later emergence of social essentialist thinking in Northern Ireland involves differences in the timing of relevant input. Specifically, since the signing of the Good Friday Peace Accords in 1998 (and hence for the entire lifetime of the children in these studies), Northern Ireland has been a “post- conflict” society (e.g.,Tam, Hewstone, Kenworthy, & Cairns, 2009). As such, parents in Northern Ireland might be less likely to speak of religion categories in ways that might promote essentialist thinking—such as using generic reference (e.g.,Gelman, Ware, & Kleinberg, 2010). If so, perhaps essentialist reasoning about reli- gion categories in Northern Ireland does not develop until children are taught the societal importance of such categories from some other source, such as attendance at a segregated school. In contrast, the conflict between Arabs and Jews in Israel is, as yet, unresolved, a situation which may result in more parental talk—including This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 492 SMYTH, FEENEY, EIDSON, AND COLEY generic language—about relevant social categories. If so, the ear- lier input in Israel may lead to an earlier emergence of essentialist thinking about culturally relevant social categories (seeSegall et al., 2015). Although clearly beyond the scope of this paper, iden- tifying the causes of the differences in developmental trajectory of essentialist thinking about critical social categories in Northern Ireland and Israel is an important area for further investigation. Although, as mentioned above, differences between children in segregated and integrated schools are evident in both Northern Ireland and Israel, a second important difference between the Northern Irish and the Israeli results is the precise nature of the school differences in the two contexts. To put it simply, in North- ern Ireland, attending segregated schools is associated with an increase in essentialist thinking, whereas in Israel, attending inte- grated schools is associated with a decrease in essentialist thinking. One account that might explain both patterns is that the different effects represent interactions between school context and societal defaults with respect to integration of members of salient social categories. 2As we have pointed out previously, Catholics and Protestants in Northern Ireland tend to live in the same commu- nities, and segregation tends to be on the micro level of neighbor- hoods rather than the macro level of towns or sectors (Lloyd & Shuttleworth, 2012). As such, segregated schools—albeit the norm—reflect a departure from the demographic default of a relatively integrated society. Accordingly, we observe the most marked effects on essentialist thinking among children attending segregated schools in Northern Ireland. In contrast, in Israel, Jews and Arabs typically live in different communities and even differ- ent parts of the country, and therefore segregation tends to be on the macro level (for a recent study of the segregation of Arabs in Israel, seeSchnell, Abu Baker Diab, & Benenson, 2015). As such, integrated schools reflect a departure from the demographic de- fault of a relatively divided society. Accordingly, the most marked effects on essentialist thinking reported by Diesendruck and col- leagues is among children in integrated schools. This is a poten- tially important hypothesis which deserves further empirical atten- tion. Importantly, only by presenting a detailed case study of the development of essentialist thinking about social categories in a new and different historical, political, and cultural context— Northern Ireland—to be compared and contrasted with what we already know about development in Israel, was this hypothesis even brought to light. Differences Between Integrated and Segregated Schools in Northern Ireland Why does essentialist reasoning about religion categories emerge much more strongly among children attending segregated schools in Northern Ireland? One possibility, or course, is that spending the majority of one’s time with members of one’s own salient social category helps to reify that category and causes a marked increase in essentialist thinking. Of course, we cannot draw causal conclusions from the present results. Moreover, there are at least two other reasons why attendance at segregated school might be associated with essentialist beliefs about religion catego- ries. First, as the results of our meta-analysis suggests, segregated schools may be located in segregated communities, meaning that community segregation rather than educational diversity may bethe causally important factor. However, we observed almost no statistical relationship between a measure of diversity in the com- munities where participating schools were located, and levels of essentialist thinking about religion categories in those schools. This finding strongly suggests that the different levels of essen- tialist thinking associated with educational environment observed in our studies are not due to community segregation. An alternative account of the associations with educational environment is that they are driven by parental input. As parents choose the primary school attended by their child, the school chosen may be an indicator of the political attitudes to which the child is exposed at home, which may be the critical component in the development of essentialist thinking (seeDegner & Dalege, 2013). Indeed, it has recently been argued that essentialism in Israel is caused more by parental language than by choice of school environment, which turns out to be predicted by parental attitudes (seeSegall et al., 2015). This implies that a segregated school environment per se may play little role in the development of essentialist beliefs about ethnicity categories among Israeli children. Morgan, Dunn, Cairns, and Fraser (1993)found that five major factors contributed to parents in Northern Ireland choosing to send their children to integrated schools. One of these was indeed political ideology, but others included educational quality, dissat- isfaction with their current school, convenience, and mixed mar- riage. This suggests that deciding whether to send a child to an integrated school in Northern Ireland can be a complex and mul- tifaceted decision, and is unlikely to be based solely on political or intergroup attitudes. Clearly, further work will be required to tease apart the relative importance of parental input and school environ- ment in the development of essentialist beliefs about religion categories in Northern Ireland. Future Directions Our findings highlight a number of important avenues for future investigation. As discussed above, identifying the mechanisms responsible for the different developmental trajectories among children in segregated versus integrated schools is one important area for further study. Another important avenue for future re- search hinted at above will be examining the role played by parental linguistic input in the development of Northern Irish children’s beliefs about religion categories. Adult use of generic language (e.g., “Hamster owners are habitually tardy.”) appears to be an important determinant of essentialist thinking in young children (e.g.,Rhodes, Leslie, & Tworek, 2012;Segall et al., 2015). As such it will be important to investigate the frequency with which parents in Northern Ireland use generic language to refer to social categories, and the age at which such use is ob- served. Another important direction for future research will be to ex- plore the underlying structure of social essentialism across a range of categories and cultural contexts. As described above,Haslam et al. (2000)have demonstrated that adults’ essentialist beliefs em- body the components of naturalness and cohesiveness. However, most studies of the development of essentialist thinking utilize a single measure of such thinking. Future studies using multiple 2We thank an anonymous reviewer for suggesting this point. This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. 493 ESSENTIALIST THINKING ABOUT RELIGION CATEGORIES measures of essentialist reasoning such as the category naturalness task (Diesendruck, Goldfein-Elbaz, et al., 2013;Rhodes & Gelman, 2009), the switched at birth task (e.g.,Gelman & Well- man, 1991;Taylor et al., 2009), and the category stability task (Kinzler & Dautel, 2012) may reveal a more complex and nuanced view of the development of essentialist thinking about social categories, because different tasks may tap into different dimen- sions of essentialist beliefs. For example, a switched at birth task may tap into beliefs about naturalness whereas the inference task may tap into the cohesiveness dimension of essentialism. Indeed, as argued above, our results support just such a view of gender categories, which children may perceive as relatively high in naturalness but relative low in cohesiveness. A final important avenue for research will be to map out the continuing trajectory of essentialist beliefs about social categories into adolescence and adulthood in Northern Ireland. Unlike work suggesting a decrease in essentialist thinking in later childhood (e.g.,Deeb et al., 2011;Taylor et al., 2009; but seeEidson & Coley, 2014), our results show little evidence of decreasing essen- tialist thinking. Other work appears to demonstrate an important role for context in determining whether the tendency to hold essentialist beliefs about particular social categories increases or decreases in adolescence (Rhodes & Gelman, 2009). As such, it becomes critical to characterize the entire developmental spec- trum—including adults—to understand the role of context and experience in the development of essentialist thinking about social categories in general and conflict-relevant culturally salient social categories in particular (seeColey, 2000). Conclusions We have shown that children in Northern Ireland come to see religion categories likeCatholicandProtestantas potent guides for inductive inferences in a way that children in the US do not. This tendency emerges by age 8, and is especially evident among children in relatively homogeneous educational settings. When compared with the development of essentialist thinking about ethnicity categories (Arab,Jew) in Israel, these results highlight potentially universal aspects of essentialist thinking about social kinds. They reinforce the unique cognitive status of culturally salient social categories— especially those related to historical and cultural conflict—as well as the potential role of intergroup contact in attenuating essentialist thinking. They also highlight differences in the two cases, and raise questions about the differential devel- opmental trajectories of essentialist thinking among children grow- ing up in different historical, cultural, and political contexts, as well as in the precise mechanism by which context might influence conceptualization of social kinds. Although answering these ques- tions will be a matter for future research, without a detailed look at the development of essentialist thinking about social kinds in a different cultural and historical context, the questions themselves might have remained undiscovered. References Allport, G. W. (1954).The nature of prejudice. London, UK: Addison Wesley. Bastian, B., & Haslam, N. (2006). Psychological essentialism and stereo- type endorsement.Journal of Experimental Social Psychology, 42,228 – 235.http://dx.doi.org/10.1016/j.jesp.2005.03.003Bekerman, Z., Zembylas, M., & McGlynn, C. (2009). 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I have attached the Final assignment since this assignment is building off of it this will be a big deal. I will let you pick the four domains that you are comfortable with and if you want I will help
Developmental Change in Numerical Estimation Emily B. Slusser, Rachel T. Santiago, and Hilary C. Barth Wesleyan University Mental representations of numerical magnitude are commonly thought to undergo discontinuous change over development in the form of a “representational shift.” This idea stems from an apparent categorical shift from logarithmic to linear patterns of numerical estimation on tasks that involve translating between numerical magnitudes and spatial positions (such as number-line estimation). However, the observed patterns of performance are broadly consistent with a fundamentally different view, based on psycho- physical modeling of proportion estimation, that explains the data without appealing to discontinuous change in mental representations of numerical magnitude. The present study assessed these 2 theories’ abilities to account for the development of numerical estimation in 5- through 10-year-olds. The proportional account explained estimation patterns better than the logarithmic-to-linear-shift account for all age groups, at both group and individual levels. These findings contribute to our understanding of the nature and development of the mental representation of number and have more general implications for theories of cognitive developmental change. Keywords:cognitive development, number, numerical cognition, proportion, estimation Contemporary views of cognitive development and learning have been heavily influenced by a large body of work aimed at assessing the development of number representation. This work reveals a de- velopmental sequence that occurs in a similar fashion across multiple age groups, tasks, and timescales (for a review, see Siegler, Thomp- son, & Opfer, 2009). The developmental sequence comprises an apparent discontinuous change in mental representations of numerical magnitude, often described as a representational shift. This view of the nature and development of numerical representa- tions has shaped theoretical approaches to cognition, learning, and development (e.g., Opfer & Siegler, 2007; Siegler et al., 2009). For example, some have suggested that these repeating patterns of change across multiple timescales are consistent with views of cognitive development held by contemporary information-processing and dy- namic systems theorists (Siegler et al., 2009). Microgenetic studies are thought to demonstrate the rapid replacement of one representation with another (Opfer & Siegler, 2007), thereby providing direct sup- port for an overlapping-waves theory of cognitive change (Siegler, 1996). Furthermore, recent studies probing the origins of mathematics and the nature of cultural influences on mathematical cognition havealso drawn on the concept of a representational shift (Dehaene, Izard, Spelke, & Pica, 2008; but see Cantlon, Cordes, Libertus, & Brannon, 2009). This body of work also has clear links to formal education and mathematics learning (e.g., Krasa & Shunkwiler, 2009). Perfor- mance patterns that are thought to indicate the successful achieve- ment of representational change are correlated with performance on standardized math tests and other measures of mathematical ability (Booth & Siegler, 2008; Laski & Siegler, 2007; Ramani & Siegler, 2008; Siegler & Booth, 2004; Siegler & Ramani, 2009; Siegler et al., 2009), and children with mathematical learning disability show a delay in exhibiting these patterns (Geary, Hoard, Byrd-Craven, Nugent, & Numtee, 2007; Geary, Hoard, Nugent, & Byrd-Craven, 2008). The idea of a representational shift has also led to the development of brief, low-cost interventions that can improve math performance in lower income children, purportedly by supporting changes in their number representations (Ramani & Siegler, 2008; Siegler & Ramani, 2009). Evidence for the representational-shift view comes from a fam- ily of tasks that share a common structure: They are typically variations on number-line estimation, involving translations be- tween numerical values and spatial positions on a line. To evaluate children’s performance, researchers examine the relationship be- tween the magnitudes represented by given symbols (most com- monly Arabic numerals, but sometimes visually presented sets of dots or other representations of magnitude) and participants’ esti- mates of those magnitudes (most commonly marked spatial posi- tions on the number line that researchers convert into correspond- ing numerical values). When estimates are plotted asyvalues against given magnitudes on thex-axis, perfectly accurate perfor- mance falls on the liney x. Deviation from this line provides a measure of estimation error. Individuals producing high rates of estimation error tend to overestimate smaller values on the number line, such that their estimates appear better characterized as a loga- rithmic curve than as a straight line (e.g., Berteletti, Lucangeli, Piazza, This article was published Online First May 21, 2012. Emily B. Slusser, Rachel T. Santiago, and Hilary C. Barth, Department of Psychology, Wesleyan University. This work was supported in part by National Science Foundation Grant DRL0950252 to Hilary C. Barth, by a Wesleyan University Psychology Department Postdoctoral Fellowship to Emily B. Slusser, and by the Wesleyan McNair Fellows Program. We thank the participating families, schools, teachers, and administrators who made this work possible. We also thank Elizabeth Chase for her helpful feedback and Anima Acheam- pong, Shipra Kanjlia, Mattie Liskow, and Kyle MacDonald for their assistance with stimulus preparation and data collection. Correspondence concerning this article should be addressed to Hilary C. Barth, Department of Psychology, Wesleyan University, 207 High Street, Middletown, CT 06459-0408. E-mail: [email protected] Journal of Experimental Psychology: General© 2012 American Psychological Association 2013, Vol. 142, No. 1, 193–2080096-3445/13/$12.00 DOI: 10.1037/a0028560 193 Dehaene, & Zorzi, 2010; Booth & Siegler, 2006, 2008; Laski & Siegler, 2007; Opfer & Siegler, 2007; Siegler & Opfer, 2003). Possibly the first study to note this pattern examined second, fourth, and fifth graders’ performance with 0 –100 and 0 –1000 number lines (Siegler & Opfer, 2003). When asked to estimate the positions of numbers on 0 –1000 number lines, sixth graders pro- duced estimates that were linearly related to the presented values, whereas second graders’ estimates were better fit with a logarith- mic curve. Fourth graders’ estimates, on the other hand, showed both patterns: Roughly half were classified as logarithmic and half as linear. Moreover, individual second graders whose estimates were categorized as logarithmic on the 0 –1000 number line pro- duced more linear estimates on a smaller, more familiar number range (0 –100), showing that the same child could produce both estimation patterns depending on the range of numbers presented. A similar developmental pattern arose for kindergarteners and first and second graders tested on a 0 –100 number line (Siegler & Booth, 2004). Kindergarteners’ estimates were better fit by a logarithmic function, second graders’ estimates were better fit by a linear function, and first graders were split between the two (for similar findings and interpretation, see also Booth & Siegler, 2006, 2008; Laski & Siegler, 2007; Opfer & Siegler, 2007; Opfer & Thompson, 2008). These logarithmic and linear estimation pat- terns have also been noted in preschool-aged children (Berteletti et al., 2010; Ramani & Siegler, 2008) as well as across language and culture (see Dehaene et al., 2008; Siegler & Mu, 2008). The representational-shift explanation accounts for these data by supposing that logarithmic or linear estimation patterns provide direct readouts of the participants’ mental representations of number. Thus, children have access to multiple types of coexisting mental number representations, drawing upon linear representations for tasks span- ning more familiar numerical ranges and logarithmic representations for unfamiliar ranges. Over the course of development and experi- ence, children learn to rely primarily on the mature, linear represen- tation of number that supports accurate, linear estimation. Proponents of this view have conducted several studies designed to promote the representational shift by encouraging children’s use of linear, rather than logarithmic, representations. For example, Siegler and Booth (2004) asked children to estimate the positions of multiple numbers on a single number line. This led to a marked improvement on subsequent number-line tasks, with improvement defined as the degree to which children produced linear estimation patterns. Opfer and Siegler (2007) found that feedback for num- bers that should correspond to the greatest discrepancy between logarithmic and linear representations (e.g., 150 on a 0 –1000 number line) is particularly effective in improving performance. Further studies have shown similar effects (characterized as a shift from logarithmic to linear estimation performance) using progres- sive alignment cues (Thompson & Opfer, 2010) and experience with linear numerical board games (Ramani & Siegler, 2008; Siegler & Ramani, 2009). Improvement can be dramatic and sudden, appearing even after only a single feedback trial and occurring broadly across the entire range of numbers tested. This is thought to provide particularly strong evidence for the idea of a representational shift, as children shift from profoundly biased, more logarithmic estimation patterns to much more linear patterns within a single testing session (Opfer & Siegler, 2007; but see Barth, Slusser, Cohen, & Paladino, 2011).Some critics of the representational-shift hypothesis have ar- gued that the choice of a logarithmic model to explain children’s estimation performance is problematic, and that relatively younger children’s estimates may be better explained by a two-segment linear model, with each segment having a different slope. Ratio- nale for one version of this model stems from the notion that estimation errors may differ when the given numbers fall within versus outside a child’s count range (Ebersbach, Luwel, Frick, Onghena, & Verschaffel, 2008). In support of their hypothesis, these researchers argued that kindergarteners’ and first graders’ number-line estimates were better characterized by a segmented linear model than by a logarithmic one, and that the change point for a particular child (the point at which the two linear models were segmented) was significantly correlated with his or her count range.Other researchers also report evidence for a segmented linear model based on first graders’ estimates with 0 –100 number lines (Moeller, Pixner, Kaufmann, & Nuerk, 2009). These authors postulate that the change point in the segmented linear model represents a change from processing single-digit to two-digit numbers, rather than a move from a familiar to an unfamiliar number range. Both versions of the segmented linear hypothesis describe development in terms of the eventual integration of the two-part representation into one holistic linear representation (see also Moeller & Nuerk, 2011; but see De- haene et al., 2008; Young & Opfer, 2011). The use of logarithmic and linear models is nevertheless clearly theoretically motivated in numerical estimation research. In fact, there is a long-standing debate as to whether internal representa- tions of numerical magnitude are organized in a linear or a loga- rithmic fashion. Some maintain that underlying representations of number are logarithmically organized (an idea rooted in the Weber–Fechner law stating that the magnitude of sensation is logarithmically related to objective stimulus intensity; see, e.g., Dehaene, 1997).Others posit that underlying representations of num- ber are linearly spaced and that logarithmic patterns may emerge as a result of scalar variability (variability that increases in proportion to numerical magnitude; see, e.g., Brannon, Wusthoff, Gallistel, & Gib- bon, 2001; Gallistel & Gelman, 1992; cf. Gallistel, 2011). Number-line estimation has been identified as a possible means to reconcile this debate. For example, Siegler and Opfer (2003) argued against the idea of a linear representation with scalar variability after failing to observe scalar variability in number-line estimation tasks. However, typical bounded number-line tasks elicit estimates relative to marked endpoints, prompting partici- pants to make judgments about relative numerical magnitude within a restricted range.Because the task puts an upper bound on participants’ responses, thereby affecting the variability of their esti- mates, the absence of scalar variability in number-line estimates does not imply a lack of scalar variability in mental representations of numerical magnitude (see also Cohen & Blanc-Goldhammer, 2011). This suggests that typical number-line estimation tasks are poorly suited to resolving these long-standing debates over logarithmic ver- sus linear mental representations of number. The question of how (and whether) to draw conclusions about internal scales of magnitude from various types of estimation tasks is complex (e.g., Cantlon et al., 2009; Dehaene, Izard, Spelke, & Pica, 2009; Izard & Dehaene, 2008; Krueger, 1989; Laming, 1997; Poulton, 1989; Teghtsoonian, 1973; see also Vlaev, Chater, Stew- art, & Brown, 2011). Numerical estimation is no exception, and of course we do not solve this problem here. However, there are clear 194 SLUSSER, SANTIAGO, AND BARTH difficulties with the conclusions about mental representations that are commonly drawn from performance on number-line estimation tasks. This article will focus on trying to resolve some of these. One difficulty is that the categorization of estimation data as either logarithmic or linear is questionable, even though most studies only consider these two possibilities (cf. Ebersbach et al., 2008; Moeller et al., 2009; Siegler & Opfer, 2003). A second concern is that by applying logarithmic and linear models to number-line estimation data, researchers effectively treat them as simple tasks that require the estimation of single numerical magnitudes in isolation, failing to acknowledge task constraints with important implications for interpretation. A third potential problem is that typical analyses of these tasks attribute variations in number-line estimation solely to numerical processing and numerical represen- tations, assuming that the spatial components of the task do not introduce their own variations. This assumption is deeply prob- lematic given a wealth of research on the estimation of spatial position in children and adults (e.g., Huttenlocher, Hedges, & Vevea, 2000; Huttenlocher, Newcombe, & Sandberg, 1994). We return to the first two points in more detail below, and to the third in the General Discussion. Theoretical Models Based on Proportional Reasoning The bounded nature of the typical number-line estimation task strongly suggests a need to look beyond the models of unbounded numerical magnitude most often applied to these data. Of course, related ideas about the importance of endpoints and other reference points in this task have been noted before. Ebersbach et al. (2008) recognized the problem of applying inappropriate models to ex- plicitly bounded tasks, suggesting that the assumptions of models tested in many previous studies “might need to be adapted to magnitude estimation tasks that involve anchored response scales” (p. 13).These authors also noted that anchors could be provided explicitly (like the marked endpoints) or even generated by the par- ticipants themselves. Siegler and Opfer (2003) also considered an informal “landmark-based proportionality model,” allowing for the possibility that participants mentally divide the number line in half orin quarters, creating reference points to guide their estimates. Thus, although the existence of reference points in the number-line task has been widely recognized, far less attention has been paid to the im- portant implications of the task’s bounded nature for the interpretation of estimation data (but see Cantlon et al., 2009). Recently, several research groups have approached this problem by applying a psychophysical model of proportion judgment, ap- propriate for bounded estimation tasks, to number-line estimation data. This model was originally developed for tasks involving judgments of perceptual magnitude (see Hollands & Dyre, 2000; Hollands, Tanaka, & Dyre, 2002; Spence, 1990). It does an ex- cellent job of explaining estimation bias in number-line tasks as well, for both 7-year-olds (Barth & Paladino, 2011) and adults (Cohen & Blanc-Goldhammer, 2011; Sullivan, Juhasz, Slattery, & Barth, 2011). Logically, the justification for the use of this model stems from the fact that number-line tasks require the estimation of a smaller magnitude (the value presented) relative to a larger one (the value given at the upper endpoint of the line), thereby eliciting a judgment of a numerical proportion rather than an unbounded numerical magnitude. Thus, a bounded number-line task with Arabic numerals requires participants to retrieve the magnitudes associated with the given values from memory (e.g., by retrieving the magnitudes associated with “43” and “100” on a 0 –100 num- ber line), to estimate the proportion of the two magnitudes, and to produce a corresponding spatial proportion by marking the number line in the appropriate position. The psychophysical model of proportion judgment discussed here is derived from Stevens’ power law, which expresses the relationship between the estimated magnitude of a stimulus and its actual magnitude asy x . The exponent is a free parameter that may be thought of as a quantification of bias associated with estimating a particular type of stimulus magnitude (such as bright- ness, area, or length), and is a scaling parameter. Here “esti- mated magnitude” would be the participant’s estimated position on a number line (which the researcher typically converts to a corre- sponding numerical value) and “actual magnitude” would be the value of the presented numeral (see Figure 1A).Importantly, like 0 25 50 75 100 0 25 50 75 100 β = 0.40, PAE = 16.5% β = 0.45, PAE = 11.6% β = 0.50, PAE = 14.2% A 0 25 50 75 100 B 0 25 50 75 100 C Presented Number Estimated Number β = 0.3, PAE = 15.0% β = 0.6, PAE = 7.2% β = 1.0, PAE = 0.0% β = 0.3, PAE = 7.5% β = 0.6, PAE = 3.6% β = 1.0, PAE = 0.0% Figure 1.Predictions of the proportion-judgment account, as applied to a typical number-line task. A depicts a one-parameter unbounded power function (with the scaling factor, , fixed at 10). B and C depict one- and two-cycle versions of the proportional power model, respectively. The two-cycle version of the model depicts the predicted estimation pattern for observers who use the midpoint of the number line as a reference point. PAE percent absolute error. 195 DEVELOPMENTAL CHANGE the logarithmic and linear functions used to model estimates in many number-line studies, Stevens’ power law has been considered as a model of numerical estimation in various tasks (e.g., Cordes, Gelman, Gallistel, & Whalen, 2001; Izard & Dehaene, 2008; Shepard, Kilpat- ric, & Cunningham, 1975; Siegler & Opfer, 2003; Stevens & Gal- anter, 1957; see also Krueger, 1989, for a review). Spence (1990) suggested that bias in proportion judgments arises from the biases associated with estimating the component part and whole magnitudes. He adapted the power law for propor- tional magnitude judgments, modifying the basic power function to define perceived magnitude (y) in terms of the presented range (such that the scaling parameter included in most formulations of Stevens’ law cancels out, leaving the exponent as the single free parameter). When this model is applied to a 0 –100 number line task, for example, estimates are predicted by the functiony x /(x (100 x) ). Spence’s model predicts that estimates of proportions will take the form ofS-shaped or reverseS-shaped curves, depending on the particular value of in question.Spen- ce’s original formulation cannot account for the patterns of perfor- mance that would arise from an observer using reference points in addition to the two endpoints. However, a generalized form (the cyclical power model; Hollands & Dyre, 2000) predicts a pattern of over- and underestimation, akin to that predicted by Spence’s model, which repeats between every pair of reference points used. Thus, the generalized model is equivalent to the basic Spence model when the number of reference points is fixed at two (the endpoints; see Figure 1B, the “one-cycle” version of the model). But if three refer- ence points are used, as when estimates are made relative to the two endpoints plus a given or inferred midpoint, a “two-cycle” version of the model results (see Figure 1C). The patterns of estimation bias predicted by the psychophysical model described above have been clearly and uncontroversially demonstrated in a variety of perceptual tasks that were either explicitly or implicitly proportional (Hollands & Dyre, 2000; Hol- lands et al., 2002). For example, this pattern was found in a study in which participants estimated the relative quantities of black dots and white dots in a mixed collection (Varey, Mellers, & Birnbaum, 1990; see also Erlick, 1964; Spence, 1990; Spence & Krizel, 1994; Stevens & Galanter, 1957). Yet the idea that these patterns can also be seen in numerical estimation data is less readily accepted (see Opfer, Siegler, & Young, 2011; for a reply, see Barth et al., 2011). To our knowledge, Barth and Paladino (2011) were the first to call attention to this pattern in children’s number-line estimation data, as were Cohen and Blanc-Goldhammer (2011) for adults’ data, even though the same pattern can be seen in estimates gathered in many previous studies (see, e.g., Booth & Siegler, 2006, Figure 2; Ebersbach et al., 2008, Figure 2; Laski & Siegler, 2007, Figures 1 and 2; Moeller et al., 2009, Figure 3; Siegler & Booth, 2004, Figure 3; Siegler & Mu, 2008, Figure 1). Why have these systematic patterns of estimation bias appar- ently gone unnoticed in number-line studies? We can think of two possibilities. First, there is a resounding tendency for researchers to sample heavily from the lower end of the number line and scarcely from the upper end. This is because most studies aim specifically to distinguish between logarithmic and linear fits in the context of the representational-shift hypothesis, rather than to entertain alternative hypotheses (cf. Ebersbach et al., 2008; Moeller et al., 2009). This practice focuses on participants’ pro- pensity to overestimate small numbers, but yields little data toreveal the details of underestimation patterns for larger numbers. Second, contingent on the value of the exponent ( ) and on the participant’s use of reference points, unbounded and cyclical power models may closely resemble logarithmic or linear models (see Figure 1), particularly if numbers near the upper end of the range are sparsely sampled. Developmental Change in the Proportion-Judgment Account If the observed developmental patterns in these estimation data do not indicate a log-to-linear shift, then whatisthe nature of the observed change over development? The proportion-judgment ac- count of number-line estimation can accommodate a notion of gradual change quite different from the categorical change re- quired by the representational-shift account. Developmental change in numerical estimation, here, may be described in terms of (at least) two distinct kinds of changes. The first of these is change in the value of the parameter, which reflects the degree of bias associated with the estimation of individual magnitudes (such as the estimation of magnitudes of different Arabic numerals in typical number-line tasks). The observed parameter may change gradually with age or experience, such that estimates are more accurate for older and more experienced observers (presumably with values of eventually converging on 1, at which point proportion-judgment models are equivalent toy x; see Figure 1). Some evidence in support of this idea has been found in number- line tasks (Barth & Paladino, 2011) and in perceptual tasks (Hol- lands & Dyre, 2000; Spence & Krizel, 1994). Second, learning and development may lead to changes in the use of reference points, including both marked endpoints and, potentially, an inferred midpoint. Our theoretical account predicts that increased accuracy is linked to the number of reference points utilized by a participant and offers a quantitative explanation of this link. For example, a participant with a poor understanding of the task structure or an incomplete knowledge of the numerical range in question may use only the lower endpoint value, treating the task as an open-ended magnitude judgment rather than a proportion judgment. This participant should therefore produce estimates well described by an unbounded power function 1(Ste- vens’ power law; see Figure 1A). Alternatively, a participant appropriately referencing both the given lower and upper endpoint values on the number line would 1It is important to note that this pattern of performance (estimates that are well described by simple power or log functions) could arise in this task from many possible strategies likely to be used by young children with a poor understanding of the task structure and/or little knowledge of the numbers presented. The use of essentially open-ended magnitude judg- ments is just one example; counting up from the left side of the number line by arbitrarily chosen units is another. Some children, moreover, may try to reference the upper endpoint but lack the accurate knowledge of its value that is necessary for a reasonably accurate proportion estimate (i.e., they try to compare the magnitude of “30” to the magnitude of “100,” but they do not yet know what “100” means). These children will also produce similar power- or logarithmic-looking estimates (Barth & Paladino, 2011). For these and other reasons, the applicability of a particular type of function to number-line estimation patterns should not be taken as evidence for a corresponding mental representation of number. 196 SLUSSER, SANTIAGO, AND BARTH produce the pattern of over- and underestimation predicted by the one-cycle version of the proportional model (see Figure 1B). A participant who infers a third reference point at the line’s midpoint would produce the cyclical pattern of over- and underestimation corresponding to the two-cycle version of the model (see Figure 1C).Although each progression—from an unbounded power to a one-cycle proportional to a two-cycle proportional version of the model—results in an increase in overall accuracy, this view requires no representational shift to explain developmental change from more logarithmic-looking to more linear-looking estimation patterns. The Present Study Prior work demonstrated that the proportion estimation model described earlier can account for estimation patterns arising from a single number-line task presented to 5- and 7-year-olds (Barth & Paladino, 2011). That study, however, provided little information about change over development. To address this question, in the present study we investigate how predictions of the proportion- judgment account map onto performance across age and experi- ence through a series of cross-sectional experiments, spanning 5 years. Wealso present children with multiple numerical ranges to evaluate the claim that different estimation patterns for different ranges within children indicate the presence of multiple types of mental number representations (e.g., Siegler & Opfer, 2003). For all experiments, we compare the predictions of the proportional approach to those of the log-to-linear representational-shift account. 2 Broadly, we predict that children’s estimation data will be better explained by the proportion-judgment account than by the representational-shift account. We also predict that estimates will follow the developmental progression described earlier, from the unbounded power function (reflecting effective use of the lower endpoint, but not the upper) to a one-cycle version of the propor- tional model (reflecting the use of both endpoints) to a two-cycle version (reflecting the use of both endpoints plus a midpoint). Finally, we predict that values of the parameter will tend to change with age and experience, such that they will be closer to 1 (corresponding to perfect accuracy) for older children and for children tested on a more familiar number range. Experiment 1 Method Participants.Thirty-three 5- and 6-year-old children (16 boys, 17 girls; mean age 5 years 11 months) completed the task. Most children were recruited through a database of families resid- ing in the central Connecticut area and were tested in a quiet laboratory room. Some children were recruited and tested at local venues such as a nearby children’s museum. No questions were asked about socioeconomic status, race, or ethnicity, but children were presumably representative of the community from which they were drawn. In this community, 84% of adults have a high school diploma and 30% have a bachelor’s degree. Most residents identify as White (80%), Black (12%) or Asian (3%; U.S. Census Bureau, 2000). Stimuli.Children were presented with booklets of pages (27.9 10.8 cm) with a 23-cm line printed in the center of each page. The left end of the line was marked with 0, and the right endof the line was marked with 20 or 100, depending on the condition. The target number for each trial was printed 2 cm above the center of the number line, as in many previous studies of number-line estimation (e.g., Booth & Siegler, 2006; Opfer & Siegler, 2007; Siegler & Opfer, 2003; Thompson & Opfer, 2010). Design.Each child completed two conditions. The “familiar” condition used a smaller numerical range, likely to be more famil- iar to the child, with a number line bounded by 0 and 20. The “unfamiliar” condition used a larger numerical range, likely to be less familiar to this age group, with a number line bounded by 0 and 100. Children always completed the familiar number range first. 3Test trials used a selection of numbers sampled roughly evenly across the given number range (0 –20 or 0 –100 depending on the condition), with no numbers repeated (see Appendix A for a complete list of numbers tested). The order of the trials was randomized for each child. Procedure.The procedure was similar to that reported in Barth and Paladino (2011), which was modeled directly on the procedure of Booth and Siegler (2006). Experimenters first intro- duced the task for the familiar number range: “We’re going to play a game with number lines. I’ll ask you to show me where you think some number should go on the number line. When you decide where the number goes, make a line through the number line.” There was one practice trial at the beginning of each condition; for the initial 0 –20 condition, the experimenter prompted children to mark a new (blank) number line to show where 10 should go. After responding, children were shown a number line marked in the middle. The experimenter asked if they knew why 10 went there and then explained, “Because 10 is half of 20, it goes right in the middle between 0 and 20. So 10 goes right there, but it’s the only number that goes there.” On the first test trial, if children marked the halfway point, the experimenter reminded them that only 10 goes in the middle. Test trials immediately followed the single practice trial. The experimenter read off the Arabic numeral printed above each number line, saying, “Where would you put [X]?” for each trial. After the children responded by marking the line, experimenters concluded the trial by saying, “Thank you.” When switching to the unfamiliar condition, experimenters would say, “Now we’re going to play the game with different numbers. Zero still goes here at this end, but now 100 is here at the other end.” This was followed by the same single practice trial described above, with 50 as the halfway point. Results Data from children producing responses that were uncorrelated with the presented number (Spearman rank correlation,r S,p .05) or were negatively correlated (r S,p .05) on either condition or both conditions were excluded from the following analyses (n 2We do not test the predictions of segmented linear models for two reasons. First, they were explicitly tested by Barth and Paladino (2011), and model selection procedures (Burnham & Anderson, 2002) found them to be unsupported. Second, visual inspection strongly suggests that the data we report here provide little, if any, support for such models. 3As part of another study, children first completed a position-to-number task in which they were given a marked number line and asked which number went with that mark. Data from the position-to-number task are not discussed here. 197 DEVELOPMENTAL CHANGE 8). Data from children who marked over 90% of their responses within a single region comprising 10% of the number line on either condition or both conditions were also excluded (n 5). This resulted in a total of 20 children: five 5-year-olds (mean age 5 years 7 months) and fifteen 6-year-olds (mean age 6 years 6 months). We deliberately chose these exclusion criteria because data from children with extreme response biases or uncorrelated responses are difficult or impossible to interpret. As a measure of general accuracy, each child’s mean percent absolute error (PAE; see Booth & Siegler, 2006, 2008) was com- puted for each task. This was calculated by dividing the absolute difference between the number corresponding to the child’s esti- mate and the presented number by the numerical range, then multiplying the quotient by 100 to express a percentage: PAE Estimated Position – Presented Number Numerical Range 100. Patterns of estimation biases were evaluated by comparing the models described earlier to those comprising the representational- shift account (logarithmic and linear models). Models comprising the proportion-judgment account included an unbounded power function (a single-parameter version of Stevens’ power law, with a fixed scaling factor; see Figure 1A) and the one- and two-cycle versions of the proportional power model (see Figures 1B and 1C; Hollands & Dyre, 2000). Constraints were set such that no model was allowed to project values less than zero. Formal model comparisons determined which model best pre- dicted children’s performance patterns. 4Comparisons were made via AICc (Akaike information criterion, corrected for small sample sizes) scores, as in Barth and Paladino (2011). Differences in AICc scores provide a measure of how well different models can explain data, taking into account both goodness of fit and model complex- ity, where complexity is defined in terms of number of parameters (e.g., Burnham & Anderson, 2002). Because the number of pa- rameters in a model is not the only measure of complexity, we also used a second model selection technique for all our group analyses (leave-one-out cross-validation, or LOOCV, which assesses how a model will generalize to an independent data set; 5Browne, 2000; see Barth et al., 2011, and Opfer et al., 2011, for recent discussion). The findings reported here are based on AICc and LOOCV anal- yses, but we also reportR 2values for each fit because of this measure’s greater familiarity to readers. 6 Familiar range (0 –20).Performance on this task was highly accurate, with a mean PAE of just under 10% (see Figure 2A). There was little evidence of systematic estimation bias in the group median estimates, resulting in rather linear performance (R 2 .980) and a relatively poor fit of the logarithmic model (R2 .776). Further, the linear model was ranked first over the two-cycle (R 2 .935), one-cycle (R 2 .932), and unbounded power func- tions (R 2 .897). With a slope of .891 (intercept of 0), group median performance on this numerical range is very near true accuracy (y x; see Appendix B). This result is consistent with 5- and 6-year-olds’ medians considered separately (see Figures 2B and 2C). An examination of individual children’s estimates reveals, how- ever, that only 30% of the children (n 6) produced estimates that were best explained by a linear model. All other children produced estimates that were best predicted by the proportional reasoningaccount (unbounded power,n 6; one-cycle,n 5; two-cycle, n 3). Unfamiliar range (0 –100).Performance was less accurate on the 0 –100 number range (see Figure 2D), with a mean PAE of 15.7%. When only linear and logarithmic models are considered, the 5- to 6-year-olds’ group median performance on the 0 –100 number line is better characterized by the linear model (R 2 .944) than by the logarithmic model (R 2 .838). However, the un- bounded power function (R 2 .952) is preferred over all others considered here for the group median data, ranking first over the linear model as well as the one-cycle (R 2 .927) and two-cycle (R 2 .766) proportional models (see Appendix B). The majority of individual children (65%;n 13) produced estimation patterns for the 0 –100 task that were best explained by the proportion-judgment account. Most of the remaining children (n 6) produced estimates best characterized by a logarithmic model. Finally, we examined performance patterns of 5-year-olds (the youngest portion of our sample) and 6-year-olds (the majority of the sample) on the 0 –100 task separately (see Figures 2E and 2F). Although the logarithmic model fits 5-year-olds’ median data reasonably well (R 2 .864), the unbounded power function (R 2 .866) offers the best explanation (with comparatively little support for linear, one-cycle, and two-cycle models as explanations of the 5-year-olds’ median data). In contrast, 6-year-olds’ median per- formance is more linear (R 2 .931) than logarithmic (R 2 .864). However, the AICc comparison and LOOCV analyses show that 6-year-olds’ systematic estimation bias (see Figure 2F) is best characterized by the one-cycle proportion-judgment model (R 2 .926). This characterization is also borne out in the individual data (with nine children exhibiting one-cycle patterns, eight children exhibiting two-cycle patterns, and seven simply showing linear estimation patterns). Comparison across tasks.Unsurprisingly, overall accuracy decreased from the 0 –20 number range to the 0 –100 range. The linear model was preferred for group median estimates on the 0 –20 task, whereas the unbounded power function was preferred for group medians on the 0 –100 task. When 5- and 6-year-olds’ performance patterns are considered separately, 5-year-olds’ group median estimates were linear for the more familiar range, but highly biased for the less familiar range, such that the unbounded power function was preferred for the 0 –100 task. Likewise, 6-year-olds’ group median estimates were best fit by a linear model for the familiar range, but by a one-cycle proportional model for the unfamiliar range. 4A Microsoft Excel worksheet for performing simple versions of these analyses (Slusser & Barth, n.d.) is freely available online (http:// hbarth.faculty.wesleyan.edu). 5This analysis first divides each data set into a calibration sample of N 1 and a validation sample of 1. The model of interest is then fit to the calibration sample. This is repeated such that each observation in the sample is used once as the validation sample. An error index (the mean standard error) for each iteration is calculated, with the average mean standard error across all iterations summarizing the model’s fit. 6Comparisons ofR 2values do not take model complexity into account, so they should not be used for comparing the models tested here. 198 SLUSSER, SANTIAGO, AND BARTH Discussion Two important findings emerge from these data. First, for the more familiar 0 –20 numerical range, group median estimates were both quite linear and highly accurate. But at the individual level, even for the familiar range, estimates were better explained by the proportion-judgment account, suggesting that the linear group median estimates do not provide evidence of the use of linear mental representations by individual children. Second, for the less familiar 0 –100 numerical range, estimation biases were apparent at the group level as well as at the individual level, with group medians best described by the unbounded power function. The estimates of the 5-year-olds in the sample (the low end of the age range) were also best described by the unbounded power function. The 6-year-olds’ median estimates, on the other hand, were best explained by the one-cycle proportional model, consistent with the idea that these children were better able to apply appropriate proportional reasoning. This change from an unbounded power function to a one-cycle version of the proportional model may reflect children’s develop- ing understanding of the upper end of the number line. That is, 5-year-old children’s understanding of the numerical magnitudes represented by the upper end of the less familiar number line may be limited (e.g., Barth, Starr, & Sullivan, 2009; Lipton & Spelke, 2005), rendering the reference point marked on the right side of the number line (100) unviable. These children’s estimates may there- fore be made relative to only one reference point (the left endpoint)such that they are effectively open-ended. Only when children become more familiar with the entire number range do they begin to understand how to use both available reference points (0 and 100), yielding a pattern of estimation predicted by the one-cycle proportional model. Overall, these findings provide evidence of the developmental progression predicted by the proportion-judgment account. Al- though our observation of improved accuracy for the more familiar numerical range is consistent with the findings of previous studies, the present findings did not support the idea of a logarithmic-to- linear representational shift. Rather, the observed changes were better explained by the idea that the youngest children were more likely to make open-ended judgments, particularly on the less familiar range, producing estimates consistent with an unbounded power function. The older children were better able to make appropriate proportional estimates, due probably to a greater un- derstanding of the numerical magnitudes involved and perhaps of the task’s proportional structure as well. Do the predictions of the proportion-judgment account outper- form those of the log-to-linear shift account for other age groups and numerical ranges as well? In Experiment 2, we asked older children to perform similar numerical estimation tasks. Experiment 2 Experiment 2 evaluated the predictions of the proportion- judgment account, comparing these to the predictions of the 0 25 50 75 100 0 25 50 75 100 0 5 10 15 20 0 5 10 15 20 0 25 50 75 100 0 25 50 75 100 0 5 10 15 20 0 5 10 15 20 Linear R2= 0.980 Slope = 0.891 Y-Intercept ~ 0 Presented Number Estimated Number A Linear R2= 0.982 Slope = 0.893 Y-Intercept ~ 0 Linear R 2= 0.937 Slope = 0.786 Y-Intercept ~ 0 C B Unbounded Power R 2= 0.866 β = 0.4561-Cycle R 2= 0.926 β = 0.533 Unbounded Power R 2= 0.952 β = 0.448 DE F y l n o s d l O – r a e Y – 6 s d l O – r a e Y – 6 d n a – 5 5-Year-Olds only Estimated Number Familiar Range Unfamiliar Range Figure 2.Median estimates of 5- and 6-year-olds on each task. Estimated number corresponds to the marked position on the number line. The solid line represents the preferred model. The dashed line showsy x. 199 DEVELOPMENTAL CHANGE representational-shift account, with a slightly older age group (7- to 8-year-old children). Children again performed typical number- line estimation tasks on more and less familiar numerical ranges. The specific numerical ranges used in this experiment were 0 –100 and 0 –1000. Method Participants.Twenty-four 7- and 8-year-old children (16 boys, eight girls; mean age 8 years 0 months) completed the tasks of Experiment 2. The sample included eleven 7-year-olds (mean age 7 years 5 months) and thirteen 8-year-olds (mean age 8 years 6 months). They were drawn from the same population as in Experiment 1 and were tested under the same circumstances. Stimuli.Stimuli included booklets identical to those used in Experiment 1, with the exception that each number line was labeled with 0 at the left end and 100 or 1000 at the right end (depending on the condition). Design.As with Experiment 1, each child completed two conditions. For this age group, number lines for the “familiar” range were bounded by 0 and 100 and number lines for the “unfamiliar” range were bounded by 0 and 1000. Each condition presented a series of numbers sampled roughly evenly across theentire range (see Appendix A). The order of trials was randomized for each child. Procedure.The procedure for this experiment was the same as the procedure for Experiment 1, except that Experiment 2 used larger numerical ranges as described above. Results All the children in this age group produced responses correlated with the presented number (r S,p .05), and no child responded only within a small portion ( 10%) of the number line; therefore data from all the children were included. Analyses were conducted as in Experiment 1: An overall measure of accuracy (PAE) was computed, and explanations of children’s estimates were evaluated by comparing AICc scores and LOOCV indices for logarithmic, linear, and proportion-judgment models. Familiar range (0 –100).The two-cycle version of the pro- portional model (consistent with the use of the two explicit end- point values plus a midpoint; Hollands & Dyre, 2000) provided the best fit for the 7- to 8-year-old group’s median data on the 0 –100 task (R 2 .990), ranking it first over linear (R 2 .986), one-cycle (R 2 .984), and logarithmic (R 2 .856) models for group performance (see Figure 3A and Appendix C). Analyses of indi- viduals’ estimates reveal a similar trend, with the majority of the 0 250 500 750 1000 0 25 50 75 100 0 25 50 75 100 0 250 500 750 1000 0 250 500 750 1000 0 25 50 75 100 0 25 50 75 100 0 250 500 750 1000 Estimated Number Familiar Range 2-Cycle R2= 0.990 β = 0.669 Presented Number Estimated Number Unfamiliar Range 2-Cycle R2= 0.993 β = 0.717 2-Cycle R 2= 0.978 β = 0.589 2-Cycle R 2= 0.994 β = 0.4922-Cycle R 2= 0.968 β = 0.3482-Cycle R 2= 0.995 β = 0.560 y l n o s d l O – r a e Y – 8 s d l O – r a e Y – 8 d n a – 7 7-Year-Olds only C AB DF E Figure 3.Median estimates of the 7- and 8-year-olds on each task. Estimated number corresponds to the marked position on the number line. The solid line represents the preferred model. The dashed line showsy x. Note that the 7- and 8-year-olds’ median estimate for the number 52 on the 0 –1000 number line (represented by an open circle) was a statistical outlier and was excluded from the corresponding analyses. Nearly half the children produced estimates that were much too high, tending to place 52 near the position for 500. 200 SLUSSER, SANTIAGO, AND BARTH children (71%) producing one- or two-cycle estimation patterns (n 9 andn 8, respectively). The remaining children’s esti- mates were best fit by a linear model (n 7). Two-cycle proportion-judgment models are also preferred for both the 7-year-olds’ and 8-year-olds’ estimates considered sepa- rately (see Figures 3B and 3C and Appendix C). Interestingly, the value of the exponent ( ) for the two-cycle fit of 7-year-olds’ estimates ( .589) is notably lower than the value for 8-year- olds’ ( .717). Unfamiliar range (0 –1000).The two-cycle version of the proportional model (R 2 .994) ranked first over linear (R 2 .980), one-cycle (R 2 .967), and logarithmic (R 2 .560) models for group performance on the less familiar range (0 –1000; see Figure 3D and Appendix C). Again, analyses of individual chil- dren’s estimates show a similar distribution, with the majority of children (75%) producing estimates best accounted for by one- cycle (n 3) and two-cycle (n 14) versions of the proportional model. The two-cycle model provides the best account of estimation performance in both the 7-year-old and 8-year-old groups (see Figures 3E and 3F). As in the familiar number-line task, values increased across age groups ( .348 for 7-year-olds’ medians and .560 for 8-year-olds’ medians), consistent with more accurate estimation by the older children. Comparison across tasks.Even though performance on both the familiar and unfamiliar tasks shows the same two-cycle pattern of over- and underestimation, mean PAE scores reveal that per- formance improves not only across age but also across tasks (with mean PAE of 6.8% on the 0 –100 range and 10.4% on the 0 –1000 range). Consistent with this finding of increased accuracy, ob- served values also increase across tasks. This is true for median estimates of the entire 7- and 8-year-old group ( .492 for the 0 –1000 condition and .669 for the 0 –100 condition) as well as for 7-year-olds ( .348 for the 0 –1000 condition and .589 for the 0 –100 condition) and 8-year-olds ( .560 for the 0 –1000 condition and .717 for the 0 –100 condition) consid- ered separately. In fact, values for all individuals producing consistent proportion-judgment patterns across tasks were higher (closer to 1) on the familiar range than on the unfamiliar range. Discussion Number-line estimation performance in the 7- and 8-year-old age range was best characterized by the two-cycle version of the proportional model. This pattern of performance is predicted when observers use both the endpoints of the number line and a midpoint as reference points for their estimates. It appears that the 7- and 8-year-olds we tested were able to make use of a central reference point and that estimation accuracy benefited as a result. Children’s estimation patterns provided no support for the log-to-linear shift account. These findings, especially when considered in concert with the findings of Experiment 1 on the 0 –100 task, show quantitatively that one source of increased accuracy in number-line estimation comes from the use of additional reference points. The youngest children in Experiment 1 were apparently unable to make consis- tent use of upper endpoints (reflected by estimates best described by the unbounded power function). The older children in Experi- ment 1 produced estimates that were best explained by the one-cycle proportional model, consistent with the reliable use of both lower and upper explicit endpoint values. The slightly older chil- dren of Experiment 2, however, produced the estimation patterns that are characteristic of the use of three reference points (the two explicit endpoints plus a midpoint). Therefore the findings of Experiments 1 and 2 show the predicted developmental progres- sion of one source of increased accuracy in this task: the appro- priate use of additional reference points (see Figure 1). Experiment 2 further shows that improved estimation accuracy does not arise solely from the use of additional reference points. Children’s estimates also revealed an overall decrease in estima- tion bias with age (reflected by values that were closer to 1 for older children) and for more familiar ranges. The idea that im- proved accuracy is associated with this kind of change, as pre- dicted by the proportion-judgment account, is distinct from the idea that additional reference points confer improved accuracy. In Experiment 3, 8- to 10-year-old children performed similar tasks for even larger numerical ranges. Again, the predictions of the proportion-judgment account were compared to those of the log-to-linear shift account. Experiment 3 Experiment 3 evaluated number-line estimation by 8- to 10- year-old children. Children again performed typical number-line estimation tasks on more and less familiar numerical ranges. The specific numerical ranges used in this experiment were 0 –1000 and 0 –100000. Method Participants.Participants included thirty 8-, 9-, and 10-year- old children (19 boys, 11 girls; mean age 9 years 3 months) drawn from the same population and tested in the same locations as in Experiments 1 and 2. Stimuli.Test booklets were identical to those of Experiments 1 and 2 except that number lines were labeled with 0 at the left end and 1000 or 100000 at the right end (depending on condition). Design.Children completed each of two conditions: The familiar range was bounded by 0 and 1000, and the unfamiliar range was bounded by 0 and 100000. Test trials were sampled roughly evenly from the entire number range (see Appendix A). The order of the trials was randomized for each child. Procedure.Procedures were identical to those of Experi- ments 1 and 2 except for the numbers used. Results One child’s data were excluded from further analyses because responses were not correlated with the presented numbers on one of the two conditions (r S,p .05). Another child was excluded for developmental delays (by parental report). This resulted in a total of 28 children: twelve 8-year-olds (mean age 8 years 4 months), eight 9-year-olds (mean age 9 years 7 months), and eight 10-year-olds (mean age 10 years 5 months). Familiar range (0 –1000).As with the previous two experi- ments, performance on the familiar number range was relatively accurate, with mean PAE of 8.1%. As in Experiment 2, the two-cycle proportional model (R 2 .990) was ranked first over 201 DEVELOPMENTAL CHANGE linear (R 2 .986), one-cycle (R 2 .982), and logarithmic (R 2 .482) models for group performance on the familiar 0 –1000 task (see Figure 4A and Appendix D). The value for the two-cycle fit was .682 (slightly higher than the .492 value for the 7- to 8-year-old group on the same task). An evaluation of individual performance revealed that many of the children who produced estimates best characterized by a pro- portional model showed a one-cycle pattern (n 9). Moreover, estimates from most of the children producing a one-cycle pattern follow a distinct under-then-over pattern, with corresponding values greater than 1 (n 5; mean age 9 years 11 months). This unexpected finding, which contrasts with the over-then-under pat- terns found in the previous experiments (see Figures 2F and 3), is addressed further in later sections. Analyses of the 8- and 9-year-olds’ estimates considered sepa- rately (see Figures 4B and 4C) revealed a pattern similar to that of the 7- and 8-year-olds of Experiment 2, with median estimates in both cases best characterized by the two-cycle proportional model (with a value of .477 for 8-year-olds and .717 for 9-year olds). Ten-year-olds’ performance, on the other hand, was best charac- terized by a one-cycle version (R 2 .979). And consistent with the aforementioned analysis of individual children in which the older children produced under-then-over estimation patterns, 10-year- olds’ median estimates showed the same pattern of bias, resulting in values that exceeded 1 ( 1.243; see Figure 4D). Unfamiliar range (0 –100000).As a group, 8- to 10-year- olds’ estimates (see Figure 4E) are best explained by the two-cycle version of the proportional model (R 2 .989, .540), outper-forming linear (R 2 .970), one-cycle (R 2 .965), and logarithmic (R 2 .309) models (see Appendix D). Analyses of individual performance on this range yield results similar to those from the familiar range. A majority of children (71%) produced estimates best predicted by the proportional model; some children produced estimates best explained by a one-cycle version (n 6), rather than a two-cycle version (n 13). Estimates of all children producing a one-cycle pattern showed an under-then-over pattern, with values greater than 1 (mean age 9 years 11 months). Separating children according to year of age shows that the two-cycle version of the proportional model provide the best account of estimation biases for both 8- and 9-year-olds (R 2 .944 andR 2 .980, respectively), with the values obtained for group medians increasing across age groups ( .349 for 8-year-olds and .547 for 9-year-olds; see Figures 4F and 4G). Ten-year- olds’ performance, on the other hand, was best characterized by a one-cycle version (R 2 .978) with a value over 1 ( 1.398), corresponding to an under-then-over pattern of bias (see Figure 4H). Comparison across tasks.Overall group performance was more accurate for the familiar range (mean PAE 8.1%) than the unfamiliar range (mean PAE 10.7%). The two-cycle version of the proportional model was preferred as an explanation of group performance for both the familiar and unfamiliar ranges, with the degree of bias smaller for the familiar range ( .682) than for the unfamiliar range ( .540). This finding parallels the results of comparisons of 7- and 8-year-olds’ performance on the 0 –100 and 0 –1000 number lines from Experiment 2. 0 250 500 750 1000 0 250 500 750 1000 0 250 500 750 1000 0 25000 50000 75000 100000 0 250 500 750 1000 0 250 500 750 1000 2-Cycle R2= 0.990 β = 0.682 2-Cycle R 2= 0.989 β = 0.5402-Cycle R 2= 0.982 β = 0.4772-Cycle R 2= 0.985 β = 0.7171-Cycle R 2= 0.979 β = 1.243 2-Cycle R 2= 0.944 β = 0.3492-Cycle R 2= 0.980 β = 0.5471-Cycle R 2= 0.978 β = 1.398 Estimated NumberFamiliar Range Presented Number Estimated NumberUnfamiliar Range y l n o s d l O – r a e Y – 9 s d l O – r a e Y – 0 1 o t – 8 8-Year-Olds only 10-Year-Olds only C ADB G EHF 0 25000 50000 75000 100000 0 25000 50000 75000 100000 0 25000 50000 75000 100000 0 25000 50000 75000 100000 Figure 4.Median estimates of 8- to 10-year-olds on each task. The solid line represents the preferred model. The dashed line showsy x. Note that median estimates represented as open circles (corresponding to 5652 and 10870 for 8-year-olds’ performance, 5652 for 10-year-olds’ performance, and 5652 for the 8- to 10-year-old group performance on the 0 –100000 number line) were statistical outliers and excluded from analyses. Again, these outliers result from many children misinterpreting the decimal value (e.g., placing the number 5652 closer to 500000 than 5000). 202 SLUSSER, SANTIAGO, AND BARTH Comparisons across the familiar and unfamiliar number-line tasks also showed that the under-then-over pattern emerges with age and does not necessarily change according to familiarity with a given number range. Rather, 10-year-olds’ group median esti- mates follow this pattern on the more familiar 0 –1000 range as well as the less familiar 0 –100000 range. On the individual level, three of the five children who produced this pattern on the 0 –1000 range did so on the 0 –100000 range as well, whereas the other two did not; three more 10-year-olds showed this pattern on the 0 –1000000 but not the 0 –1000 range. These findings provide some evidence that this pattern may be characteristic of children’s number-line estimation strategies at later stages of development but that it is not contingent on their overall familiarity with the number range. Discussion Number-line estimation performance in the 8- to 10-year-old age group was best characterized by the two-cycle proportional model, suggesting that these children were able to make use of central reference points when making their estimates, much like the 7- and 8-year-olds tested on smaller numerical ranges in Experiment 2. Children’s estimation patterns again provided no support for the log-to-linear shift account. We discuss the overall findings from this experiment in combination with those of the other two experiments below. General Discussion The idea that mental representations of numerical magnitude undergo a categorical shift has had a major influence on theoretical approaches to mathematical cognition as well as to cognitive development more broadly. Performance patterns on various nu- merical estimation tasks led to the development of this idea. However, the present work provides evidence for a different in- terpretation, building upon previous research showing that typical patterns of number-line estimation performance are predicted by psychophysical models of proportion estimation (Barth & Pal- adino, 2011; Cohen & Blanc-Goldhammer, 2011; Sullivan et al., 2011). In the present article, we evaluated the relative abilities of the representational-shift and proportion-judgment views to ac- count for children’s estimates and further explored the sources of developmental change underlying these patterns of performance. Children in three age groups (5- to 6-year-olds in Experiment 1, 7- to 8-year-olds in Experiment 2, and 8- to 10-year-olds in Experiment 3) completed typical number-line estimation tasks for both a familiar and less familiar numerical range. We assessed the explanatory power of the quantitative models comprising each theoretical view for median estimates provided by each of the targeted broad age groups (5- to 6-year-olds, 7- to 8-year-olds, and 8- to 10-year-olds). We also evaluated explanations of perfor- mance at more fine-grained subgroups (5-, 6-, 7-, 8-, 9-, and 10-year-olds) and at the individual level. Overall, these data pro- vide overwhelming evidence in favor of the proportion-judgment account: For both group and individual analyses, 7this account provided the best explanation of estimation patterns. We also emphasize that our findings do not rest on the choice of a particular model selection technique: In all cases, AICc and LOOCV anal- yses yielded consistent results.Improvements in estimation performance are well characterized in terms of the sources of change described earlier. First, children’s patterns of performance suggest that accuracy can improve through changes in the use of reference points (see Figure 1). The data suggest that very young children (such as 5-year-olds; see also Barth & Paladino, 2011) do not evaluate the upper endpoint of the number line appropriately. Some may be unable to use this refer- ence point at all, treating the task as an open-ended magnitude judgment and producing highly biased estimates well character- ized by an unbounded power function (see Figure 1A). A child entirely lacking the ability to reason about proportions might also produce this pattern of performance; however, due to substantial evidence for various forms of proportional reasoning in young children (Barth, Baron, Spelke, & Carey, 2009; Boyer & Levine, 2012; Boyer, Levine, & Huttenlocher, 2008; Duffy, Huttenlocher, & Levine, 2005; Jeong, Levine, & Huttenlocher, 2007; McCrink & Spelke, 2010; Sophian & Wood, 1997; Spinillo & Bryant, 1991, 1999) and even infants (McCrink & Wynn, 2007), it seems more likely that this pattern arises from the failure to appropriately apply a proportional strategy to the task, or from a lack of accurate knowledge of the meaning of the upper endpoint numeral (and probably other numerals at the high end of the range), rather than from a total lack of proportional competence. Slightly older children produce estimation patterns that suggest they are able to appropriately consider both endpoints when de- ciding on the location of the given number. This ability, appearing around age 6 in our task, allows children to make more accurate judgments and results in a pattern of bias characterized best by the one-cycle version of the proportional power model (see Figure 1B). This might arise from a more robust ability to apply a proportional strategy to the task, or from a better understanding of the meanings of the larger numerals involved (consistent with previous findings; e.g., Barth, Starr, & Sullivan, 2009; Lipton & Spelke, 2005; see also Matthews & Chesney, 2011, for related findings in adults), or both. Somewhat older children (7- to 10- year-olds in this sample) appear able to use a midpoint value as a reference in addition to the two explicitly labeled endpoints. These children show a biased estimation pattern that repeats itself around the midpoint, producing estimates best characterized by the two- cycle version of the proportional power model (see Figure 1C; Hollands & Dyre, 2000). A second source of improvement inherent to the proportion- judgment account is reflected in the value of the parameter, which gradually increases with age. For example, consider chil- dren’s performance on the 0 –1000 task: Across Experiments 2 and 3, 52 children between 7 and 10 years of age completed this task. Of the 40 children whose individual estimation patterns were best predicted by models of proportion judgment, corresponding values strongly correlate with age in months,r S(40) .652,p .001 (see Figure 5). 7Though the 5- and 6-year-old group’s median performance on the 0 –20 number line was ostensibly linear, individual analyses showed that the majority of these children (14 out of 20) produced estimates that are more consistent with the proportion-judgment account. 203 DEVELOPMENTAL CHANGE What We Can Conclude About Mental Representations of Number It is tempting to conclude from these and other recent findings that once the proportional nature of the number-line estimation task has been taken into account, we may make simple and useful inferences about the nature and development of mental number representations from the data it yields. For example, the underlying power function in the proportion-judgment model could describe a representation of numerical magnitude that is highly compressed in younger children and becomes gradually less compressed with age, as evidenced by smooth change in the parameter from values far below 1 to values near 1 (see also Barth & Paladino, 2011; Cohen & Blanc-Goldhammer, 2011; Sullivan et al., 2011). Although these ideas about compressed numerical magnitude representations may be correct (and broadly consistent with find- ings from other paradigms; e.g., Merten & Nieder, 2009), we urge caution in making such inferences directly from paradigms struc- tured like typical number-line tasks for the following reason. These kinds of tasks involve the production of a spatial proportion— involving lengths or distances—as well as the estimation of a numerical proportion; or in the case of inverse position-to-number tasks (Ashcraft & Moore, 2012; Siegler & Opfer, 2003), the estimation of a spatial proportion and the production of a numer- ical proportion. Attributing performance patterns to numerical processing alone requires assuming that the spatial component of the task does not in itself contribute to variations in performance— that our estimation and production of spatial proportion is veridi- cal. But a substantial set of findings shows that the estimation of spatial position is biased. For example, experimental paradigms structurally similar to number-line estimation have shown that both children and adults exhibit systematic bias when placing a mark on a remembered position within a linear space, or finding ahidden object in a long rectangular sandbox (e.g., Huttenlocher et al., 1994). Thus, because similar patterns of estimation bias are seen in a spatial task with no numbers, we cannot assume that bias in a spatial-numerical mapping task arises from numerical (not spatial) processing. 8 Clearly, however, the values observed in the present data do reflect bias in numerical processing, and not just in spatial pro- cessing. This is demonstrated by the finding that children produced more biased estimates for larger, less familiar numerical ranges than for smaller, more familiar ranges even though each of these tasks had identical spatial components. For instance, 7- and 8-year- olds’ performance on both the more and less familiar number ranges was best characterized by the two-cycle version of the proportion-judgment model, but the value of was closer to 1 on the familiar task than the unfamiliar task ( .669 and .492, respectively; see Figures 3A and 3D). In fact, 21 of the 23 children who produced the same proportion-judgment estimation pattern across tasks yielded values that were closer to 1 on the familiar range (see Teghtsoonian, 1973, for related findings in different tasks). This finding suggests that numerical processing does con- tribute, but that is not a simple index of some stable character- istic of the child’s mental representation of numerical magnitude (this may not be surprising given the considerable debate over the psychological meaning of the parameters of Stevens’ law; e.g., Laming, 1997; Teghtsoonian, 1973). Moreover, given the well- known spatial biases that arise in similarly structured tasks, spatial processing likely also contributes to the values of we observe here, and to the estimates of children and adults in number-line tasks in general. Questions for Future Research An unexpected finding arose from the oldest children’s data. We found that the direction of bias seen in younger children (the typical over-then-under pattern seen, for example, in our 7- and 8-year-olds’ data; see Figure 3) reversed itself with age and expe- rience, with the oldest children (our 10-year-olds) producing in- stead an under-then-over pattern such that their observed values were greater than 1 (see Figures 4D and 4H). This suggests that as children’s estimates gradually become less biased, their estimates do not simply become more and more accurate, constantly ap- proaching perfect performance (with values growing until they approximate 1). Rather, these under-then-over estimation patterns in our oldest children suggest that the values of may eventually overshoot 1. To our knowledge, the emergence of this reversal in the direction of number-line estimation bias over development has 8Very similar patterns of bias arise in a variety of other tasks involving the estimation of magnitudes within a bounded response range (e.g., the width of schematic fish, Duffy, Huttenlocher, & Crawford, 2006; Hutten- locher et al., 2000; and the lightness of a gray square, Huttenlocher et al., 2000). Although these studies are conceptually situated in a larger literature examining category effects on stimulus judgment, it is worth noting that many of these findings appear consistent with the proportion estimation models used here. The relation between these models—the less constrained but perhaps more broadly generalizable category adjustment model (e.g., Huttenlocher et al., 2000) and the more parsimonious but possibly less general cyclical power model of proportion judgment (e.g., Hollands & Dyre, 2000; Hollands et al., 2002)—remains to be determined. 80 90 100 110 120 130 140 0.0 0.5 1.0 1.5 2.0 β-value Age (in months) + Unbounded Version (n = 3) □ One-Cycle Version (n = 12) •Two-Cycle Version (n = 25) Figure 5.Values of the parameter corresponding to the estimates of each child whose performance is best predicted by the proportion-judgment account on the 0 –1000 number-line task (n 40). 204 SLUSSER, SANTIAGO, AND BARTH not yet been reported, so the reason for it is not yet well under- stood. However, this finding appears to be robust, as a slight under-then-over pattern has been observed in adults’ estimation performance (see Cohen & Blanc-Goldhammer, 2011), and a reversal in the direction of bias in older versus younger children has also been observed in a related task (Ashcraft & Moore, 2012; Slusser & Barth, 2012). Two findings in particular may be relevant to future investiga- tions of this reversal. First, values over 1 were associated only with children whose estimates were best explained by the one- cycle version of the proportion-judgment model, suggesting that these children did not make their estimates in relation to unmarked central reference points. Second, the tendency to produce the under-then-over pattern seems to be consistent within children: Those who generated this estimation pattern for a more familiar numerical range were also likely do so for a less familiar range. One possible speculative explanation of the reversal is that older children (and perhaps adults) are, at least implicitly, aware of an erroneous tendency to overestimate values on the lower end of the number line and therefore overcorrect for this bias, resulting in the opposite under-then-over trend. Further studies, however, are needed to explore the reasons for this pattern of performance. Conclusions We believe these data provide strong evidence against two prominent theoretical ideas: that children’s number-line estimates transparently indicate the forms of their mental representations of number and that developmental changes in estimation patterns implicate a discontinuous shift from logarithmic to linear mental representations. These studies show that understanding number- line estimation, and structurally similar tasks, in terms of propor- tion estimation can explicate patterns of bias in children’s perfor- mance. The systematic patterns emerging from estimation performance across this 5-year span also provides evidence that increased task proficiency across development is attributable to a process of developmental change with at least one gradual com- ponent. This work further shows that models of proportion estimation, developed originally for perceptual tasks, can be usefully applied to tasks that involve more abstract assessments of numerical mag- nitude. That is, children’s (and adults’) estimates of numerical magnitude in bounded tasks apparently share many characteristics with estimates of nonnumerical perceptual magnitude in tasks that are both explicitly and implicitly bounded (see Cohen & Blanc- Goldhammer, 2011; Hollands & Dyre, 2000). 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Zeitschrift fu¨ r Psychologie, 219,58 – 63. doi:10.1027/2151-2604/a000047 Appendix A Complete List of Numbers Presented in Test Trials for Each Experiment 0–20 number line (Experiment 1): 2, 3, 4, 6, 8, 12, 14, 16, 17, and 18. 0–100 number line (Experiments 1 & 2): 3, 6, 8, 12, 14, 17, 21, 24, 29, 33, 39, 42, 48, 52, 58, 61, 67, 71, 76, 79, 83, 86, 88, 92, 94, and 97. 0–1000 number line (Experiment 2): 3, 7, 19, 52, 103, 158, 240, 297, 346, 391, 438, 475, 525, 562, 609, 654, 703, 760, 842, 897, 948, 981, 993, and 997. 0–1000 number line (Experiment 3): 8, 15, 25, 56, 109, 154, 237, 290, 338, 388, 430, 467, 517, 560, 599, 650, 696, 761, 839, 889, 939, 980, 989, and 993. 0–100000 number line (Experiment 3): 870, 1522, 2609, 5652, 10870, 15435, 23696, 29022, 33805, 38478, 43043, 46739, 51739, 56087, 60000, 65217, 69783, 76087, 83913, 88913, 93913, 98043, 98913, and 99348. Appendix B Estimates of Relative Support for Each Model, Experiment 1 Model0–20 number line 0–100 number line R 2 AICc AICcR 2 AICc AICc Log-to-linear shift Logarithmic model .776 23.678 24.269 .844 111.982 32.795 Linear model.980 -0.591.944 85.451 6.263 Proportion judgment Unbounded version .897 13.969 14.559.952 79.187 One-cycle version .931 9.851 10.441 .926 90.421 11.234 Two-cycle version .935 9.295 9.885 .765 120.583 41.396 Note. AICc refers to the difference in AICc (Akaike information criterion, corrected for small sample sizes) values compared to the preferred model. As a guide to interpreting these results, we include the benchmarks proposed by Burnham and Anderson (2002, p. 446): “As a rough rule of thumb, models having iwithin 1–2 of the [preferred] model have substantial support and should receive consideration in making inferences. Models having iwithin about 4 –7 of the [preferred] model have considerably less support, while models with i 10 have either essentially no support and might be omitted from further consideration or at least fail to explain some substantial structural variation in the data.” The preferred model (i.e., the model yielding the lowest AICc value and lowest leave-one-out cross-validation error index) is shown in italics. (Appendices continue) 207 DEVELOPMENTAL CHANGE Appendix C Estimates of Relative Support for Each Model, Experiment 2 Model0–100 number line 0–1000 number line R 2 AICc AICcR 2 AICc AICc Log-to-linear shift Logarithmic model .644 150.790 95.797 .566 256.732 89.182 Linear model .986 66.007 11.013 .970 192.574 25.024 Proportion judgment Unbounded version .817 131.563 76.569 .704 245.563 78.013 One-cycle version .984 68.640 13.647 .957 199.459 31.909 Two-cycle version.990 54.994 .989 167.550 Note. AICc refers to the difference in AICc (Akaike information criterion, corrected for small sample sizes) values compared to the preferred model. The preferred model (i.e., the model yielding the lowest AICc value and lowest leave-one-out cross-validation error index) is shown in italics. Appendix D Estimates of Relative Support for Each Model, Experiment 3 Model0–1000 number line 0–100000 number line R 2 AICc AICcR 2 AICc AICc Log-to-linear shift Logarithmic model .368 233.711 84.626 .277 450.321 91.916 Linear model .981 159.843 10.758 .966 383.217 24.812 Proportion judgment Unbounded version .552 224.489 75.404 .417 443.577 85.173 One-cycle version .975 163.903 14.818 .962 383.368 24.963 Two-cycle version.988 149.085 .988 358.405 Note. AICc refers to the difference in AICc (Akaike information criterion, corrected for small sample sizes) values compared to the preferred model. The preferred model (i.e., the model yielding the lowest AICc value and lowest leave-one-out cross-validation error index) is shown in italics. Received November 22, 2011 Revision received March 8, 2012 Accepted April 13, 2012 208 SLUSSER, SANTIAGO, AND BARTH
I have attached the Final assignment since this assignment is building off of it this will be a big deal. I will let you pick the four domains that you are comfortable with and if you want I will help
JOURNAL OF CLINICAL AND EXPERIMENTAL NEUROPSYCHOLOGY 2007, 29 (1), 25–35 © 2006 Psychology Press, an imprint of the Taylor & Francis Group, an informa business http://www.psypress.com/jcen DOI: 10.1080/13803390500276859 NCEN Regression-based developmental models exemplified for Wisconsin Card Sorting Test parameters: Statistics and software for individual predictions Regression-based Developmental Models Christoph Klein, 1 Friedrich Foerster, 2 and Klaus Hartnegg 3 1School of Psychology, University of Wales2Research Group Psychophysiology, University of Freiburg3Brain Research Unit, University of Freiburg The prediction of an individual’s score is relevant in clinical research and requires normative data and a statistical rationale. In the case of developmental research the latter is typically a set of descriptive statistics (e.g., standard scores) for a set of age groups. Here we illustrate a multiple regression approach with a set of 345 Wisconsin Card Sorting Test (WCST) data obtained from subjects aged 6 to 26 years. We modeled linear and curvilinear age effects for each of the 11 WCST variables and, based on this, determined confidence limits for the expected value (mean) and the prediction of individual scores. In these multiple regression models, which accounted for 2% to 26% of the variance, curvilinear age effects clearly dominated linear ones, suggesting the features under scrutiny to be negatively accelerated functions of age. Finally, we developed a statistics program that can be used to apply multiple regression models for individual predictions that are based on normative data with up to 7 predictor var- iables. We discuss the conditions of applicability of the approach, compare it with the conventional standard score approach, discuss its cognitive-developmental implications, and outline the applicability in applied research and practising. INTRODUCTION A “deficit” in neuro-cognitive functions of neuro- logical or psychiatric patients is rarely defined by absolute criteria, but in relation to normative data, which are thus used to make individual predictions about the presence/absence or degree of a deficit in individual patients or groups of patients. “Norma- tive data” in basic research is frequently the aggre- gate statistics of a healthy control group or, if published tests are available, the aggregate statist- ics of a proper normative sample. This holds in principle for investigations both in a develop- mentally rather “static” age range (middle adult- hood) and in developmentally more “dynamic” age ranges (childhood, adolescence). As the latter age ranges are concerned, we suggest and demonstrate here a new approach for making individual predic- tions in clinical trials that are based on normativedata. This approach is based on the following considerations. Neuropsychological research with children, ado- lescents and seniors can use neuropsychological tests to sensitively track normal developmental or ageing-related changes in cognitive functions and, in consequence of this, their alterations in clinical populations. These tests typically provide quanti- tative scores and, most of them, difficulty ranges that allow for discrimination within given age ranges (e.g., all tests that output reaction time, fre- quency of error, or span scores, or grade test items according to difficulty or complexity criteria). With these tests development is implicitly assumed to be a step-wise or continuous, but in any case quantitative process rather than a process that includes developmental stages in the sense of quali- tative changes. The usefulness of such tests as assessment or diagnostic instruments for the prediction Address correspondence to PD Dr. Christoph Klein, School of Psychology, University of Wales, Bangor, The Brigantia Building, Penrallt Road, Bangor, Gwynedd LL57 2AS, Wales, UK [E-mail: [email protected]]. 26 KLEIN, FOERSTER, HARTNEGG of individual scores, however, critically depends on the availability of normative data and an appropri- ate statistical modeling of the developmental effects. Unfortunately, some of the neuropsycho- logical tests developed for children and adolescents lack even proper (i.e., large and representative) normative data bases, and most test authors used normative data, if available, to derive means, standard deviations, confidence intervals etc. for the age ranges under scrutiny. The latter situation holds also for some of the commonly used intelli- gence tests for children and adolescents which refer to a neuropsychological theoretical background (like the K-ABC; Melchers & Preuss, 1992) or have provided some of their subtests for neuropsycho- logical assessment (like the WISC; Lezak, 1995). Although these descriptive statistics obviously allow for correct individual predictions, they are dissatisfying from a theoretical perspective. This is because a chain of age group statistics is not a stat- istical model of (cognitive) development as there is no statistical function that links the different vari- ables across the age groups. Hence, there is a discrepancy between the (implicit) developmental theory underlying these tests conceptualizing development as a continuous quantitative process, and the statistics used for modeling the develop- mental effects and predicting individual scores. Indeed, evidence from the developmental (neuro-) cognitive literature has shown for a number of fea- tures, that development can be conceived of as a continuous process in which the variable under scrutiny is a negatively accelerated function of age (Fischer, Biscaldi, & Gezeck, 1997; Fry & Hale, 2000; Klein, 2001). If development is considered a continuous quan- titative process, age should be modeled statistically as a continuous predictor of the quantitative fea- tures of interest. But this is tantamount to requir- ing the application of regression analysis to model developmental effects. Indeed, (multiple) regression functions allow both for individual predictions — as illustrated in this article — and the derivation of statistical models of continuous developmental processes (Klein, 2001). Regression models have three further advantages. First, in the case of ad hoc sampling one or the other age group may be subject to minor sampling biases. Such biases would obviously afflict both analyses that use standard scores for individual age groups, and analyses that use multiple regression statistics. However, this effect must be considerably dampened for regression functions, because here the estimates at each point of the age continuum are based on the entire sample. As a result, developmental regression functions must result in estimates whichare more stable and precise across samples than group means. Second, the application of regression functions yields one model for an age range, ins- tead of multiple means (but no quantitative model) for various age groups. Given this makes sense the- oretically (see discussion), the regression approach considerably reduces the required sample sizes in normative studies. Finally, the multiple regression model parameters may provide theoretically important insights into the features under scrutiny, which are not obtained by mere comparisons of age group means. This includes direct comparisons of the developmental trajectories of different (sets of) features. In line with this reasoning, Klein (2001) has shown the superposition of (generally strong) curvilinear and (generally weaker) linear developmental effects on different measures of sac- cade control in participants aged 7–28 years. These model parameters differed between measures that are sensitive to prefrontal dysfunctions and mea- sures that are not, thus confirming hypotheses about the protraction of prefrontal cortex develop- ment by way of showing evidence of developmen- tal fractionation. Using the neuropsychological tests as assess- ment instruments in developmental clinical research, however, additionally and necessarily requires the estimation of confidence limits for individual scores. Here it can be shown that if the regression residues show no evidence of hetero- scedasticity the upper and lower confidence limits are symmetrical with respect to the estimated mean (see appendix). In this paper we exemplify the suggested regres- sion analytic approach using data for the Wisconsin Card Sorting Test (WCST; Grant & Berg, 1948). This test has been used both for basic research and for the assessment of cognitive functions in healthy subjects and patients. The WCST has become a popular neuropsychological test in studies with adult psychiatric (Green, Satz, Ganzell, & Vaclav, 1992) or neurological (e.g., Eslinger & Grattan, 1993) patients. A number of cognitive functions such as deductive reasoning, cognitive set shifting, and working memory has been associated with the WCST (Heaton, Grant, & Mathews, 1993). As most of these component functions have been linked with the neuropsychological construct of “executive functions” (EF), the WCST is now widely held as a test of executive functions (Denckla, 1996). These functions, in turn, have been linked to the prefrontal cortex (PFC; Denckla, 1996; Mentzel et al., 1998). Prefrontal regions are considered as higher-order (motor) association areas (Fuster, 1989) and thus operate as the “orchestrating” components in functional REGRESSION-BASED DEVELOPMENTAL MODELS 27 systems that also include more posterior cortical and subcortical brain structures (Alexander, DeLong, & Strick, 1986). Accordingly, functional imaging research has demonstrated metabolic increases in prefrontal and further cortical and subcortical areas during the execution of the WCST (Monchi, Petrides, Petre, Worsley, & Dagher, 2001). The WCST as a measure of executive functions is potentially useful for developmental cognitive research and assessment. First, both executive functions (e.g., Klein, 2001) and prefrontal cortex (e.g., Jernigan, Trauner, Hesselink, & Tallal, 1991) seem to exhibit protracted development during childhood and adolescence. Second, as WCST and intelligence scores may load on different factors (Ardila, Galeano, & Rosselli, 1998), reflecting their low to moderate correlation (Ardila, Pineda, & Rosselli, 2000), WCST performance may in prin- ciple complement the assessment of cognitive capa- bilities provided by common intelligence tests. Third, the WCST has a rather play-like nature and is thus suited for also testing younger children. To our knowledge, three studies have examined WCST performance in moderate to large samples of 5–12-year-old children of different cultures (Chelune & Baer, 1986: North-American, N = 105; Rosselli & Ardila, 1993: South-American, N = 233; Shu, Tien, Lung, & Chang, 2000: Asian, N = 219). Although all studies reported substantial perform- ance improvements for the WCST parameters under scrutiny, age group means (including the age at which an adult level of performance was reached) or correlations between WCST scores and age varied between studies (Rosselli & Ardila, 1993; Shu et al., 2000). In some of these studies, WCST scores did not substantially correlate with teacher ratings of academic achievement (Rosselli & Ardila, 1993), only weakly with the father’s years of education (Shu et al., 2000), the family’s socioeconomic status (Rosselli & Ardila, 1993), and gender (Rosselli & Ardila, 1993; Shu et al., 2000). Based on the outlined methodological consider- ations, this study aims at demonstrating the useful- ness and limitations of multiple regression models in cognitive (neuro-) developmental research. Based on a non-representative sample of 345 sub- jects who accomplished a computerized version of the WCST we exemplify the statistical modeling. This paper, hence, does not provide normative data that could be used in clinical trials for individ- ual predictions. In addition, we offer on our web- site software that allows for the prediction of an individual’s mean and confidence limits. Norma- tive data given, this software can be used byresearchers and practitioners that are interested in making individual predictions in developing or ageing populations. METHODS Subjects Data from 345 participants were available for stat- istical analyses. Subjects were recruited via news- paper advertisements. Upon the initial phone contact we asked the adult participants or the par- ents of the younger participants about past or cur- rent (a) neurological or (b) psychiatric diseases or (c) viewing problems that could no be corrected. If any of these exclusion criteria was met, a partici- pant candidate was not invited to the lab session. The participants’ ages ranged from 6 to 26 years (72–312 months), with a mean age of 12.9 ± 3.9 years (159 ± 45 months). 36% of the participants were male, all were German. Gender and age were unrelated, as were IQ and age. The mean T-score in Raven’s Standard Progressive Matrices (SPM; Heller, Kratzmeier, & Lengfelder, 1998) was 51.8 ± 10.9. WCST testing began at 3:15 p.m. on average, and this time was not correlated with the partici- pants’ ages (r = −.07). Procedures All participants were tested individually with a com- puter-based version of the Wisconsin Card Sorting Test that was tailored following the instructions pro- vided by Grant and Berg (1948; Heaton, Chelune, Talley, Kay, & Curtiss, 1993). Our computerized WCST comprises four stimulus cards presented in the upper part of the screen, and 128 response cards in the lower part. The response cards show figures composed of crosses, circles, triangles, or stars, that differ in the number of elements (one, two, three, and four) and their color (blue, yellow, green, or red). Response cards are presented one after the other to the participant who is instructed to match it to one of the stimulus cards. No explanation of the sorting principle is given, and the subject is only instructed that s/he will be given feedback (correct or incorrect) after each sort. Matching is initially according to color. After 10 consecutive correct matches the sort- ing principle is changed covertly. Form and number are the subsequent sorting dimensions. This series of sorting dimensions is repeated when the third cate- gory is achieved. Neuropsychological testing took about 10–15 minutes. The WCST was always pre- sented after the SPM. All participants were tested separately, and siblings were tested on the same day 28 KLEIN, FOERSTER, HARTNEGG immediately one after another. At the beginning, the laboratory was shown to the participants (and, in the case of younger children, the accompanying parent). If a subject agreed to participate, adults or parents (for their children) gave their written consent and testing could begin. Parents could remain in the lab- oratory at the child’s request. Data analysis The following 11 parameters were defined accord- ing to Grant and Berg (1948) and determined off line by a computer program: (a) number of trials administered (NTA), (b) total number correct (TNC); (c) total number of errors (absolute, TNE); (d) perseverative responses (absolute, PR); (e) per- severative errors (absolute, PE); (f) non-perseverative errors (absolute, NPE); (g) conceptual level responses (absolute, CL); (h) number of categories completed (NCC); (i) trials to complete first category (TCFC); (j) failures to maintain set (FMS). In addition, the “efficiency ratio” was defined as the ratio of NCC and NTA according to Voeller, Edge, Morris, Rao, and Heilman (1993, cf. Riccio et al., 1994). Following the rationale and procedure described in greater detail in Klein (2001), linear and curvi- linear effects of age on each of these criteria were determined by using age (in months) and its inverse (age −1) as predictors in multiple regression proce- dures. These predictors were found in the follow- ing manner. First, bivariate correlations between the dependent variables on the one hand, and transformations of the age variable were accom- plished. These transformations ranged from age −3 to age −1 in steps of .01. In many cases these corre- lations were greatest for age −1. In most other cases, the correlation between the dependent variable and age −1 was very close (within .02) to the maximum correlation obtained for the set of transformed var- iables. Second, the residues of the dependent varia- ble after partialling out age −1 were examined in order to check for remaining (residual) age effects in the dependent variables’ distributions. As in some cases a linear trend was still discernible, the variables “age −1” and “age” were partialled out, and the residues of the dependent variables were re-examined in order to verify the absence of any systematic relation with chronological age. The corresponding multiple regressions using least-square estimates of the criteria have the gen- eral form: criterion = a + b 1*age + b 2*age −1 + error, and provide a prediction of the variable under consideration by the two age variables. Pos- sible gender effects on the WCST parameters were assessed with a multivariate analysis of variance(MANOVA). The main effect of factor GENDER as well as its interaction with the WCST scores turned out to be non-significant (Fs ≤ 2). Accord- ingly, male and female participants scored compa- rably in all WCST measures. Hence, our results will be presented for the pooled male and female sub-samples. Finally, we present software (avail- able on our homepage) for the prediction of indi- vidual raw and standardized scores in WCST parameters (described in detail in the appendix). RESULTS The results of our study are shown in Figures 1–3 and Table 1. Table 1 documents the nonstandard- ized multiple regression parameters (columns “regression equations”), the F-values for the linear (“age”) and curvi-linear (“age −1”) effects of age, and summary statistics like the proportion of vari- ance explained (R 2) and the F-values for the entire model for each of the WCST parameters. The non- standardized regressions weights (b 1, b 2) together with the intercept (a) allow the prediction of individual scores according to equation 1 (see appendix), using age in months and its inverse as predictors. The corresponding regression functions are graphically shown in Figures 1–3 as dashed lines. A common feature of these functions is that the WCST scores are, in different degrees, negatively accelerated functions of age. The predominance of curvi-linear over linear age effects is statistically reflected and quantified by the F-values shown in Table 1, which are considerably larger for age −1 than age (except for FMS, which is unrelated to age). The proportions of variance accounted for by the two age variables range between 3% (TNC) and 25–26% (TNE, NCC, E-R). Moderate age effects were found for NTA (17%), PR (18%), PE (20%), and NPE (21%). The regression residues (after partialling out the two age variables) were negligibly correlated with chronological age for most of the WCST variables. In Figures 1 to 3, the dotted lines close to the estimated mean reflect the boundaries of the 95% confidence limits for the expected value (i.e., the mean), the thin “outer” lines those for the pre- dicted individual scores. As only the latter interval is based on an error variance estimate that includes the mean squared error (see appendix), these boundaries must be considerably broader than those for the expected value. The confidence limits for the predictions of individual scores can be computed for new individual’s scores with the pro- gram CONFIREG (see Appendix). If truly normative REGRESSION-BASED DEVELOPMENTAL MODELS 29 data were available, CONFIREG could be used to assess whether an individual’s score is atypical for the normal population. The difference between developmental trajecto- ries that are based on regression functions (e.g., Klein, 2001) versus age group means (e.g., Fischer et al., 1997) is illustrated in Figure 3 in comparisonwith Figures 1–2. Figure 3 reveals that at the transition between certain ages the developmental trajectories of some WCST parameters reverse their direction (e.g., from 9 to 10, 13 to 14, and 15 to 16 years). This likely effect of a sampling error is obviously dampened and smoothed in the regres- sion-based trajectories. Figure 1.Multiple regression functions for criterion variabels TNE, PR, PE, and NPE as predicted by age in months and its inverse. The dashed line represents the predicted mean, the dotted lines its 95% confidence intervals. The outer solid lines represent the 95% confidence interval for individual scores. 30 KLEIN, FOERSTER, HARTNEGG DISCUSSION In this article we portrayed a multiple regression approach to the modelling of developmental effects using the different parameters of the WCST. The sub- sequent discussion will focus on the following points: (1) conditions of applicability of the model; (2) cogni- tive-developmental implications; (3) comparison withconventional standard score approaches; (4) applica- bility in applied research and practising. Ad (1) Statistical models are generally only applicable if their assumptions are met. As the statistical Figure 2.Multiple regression functions for criterion variabels NCC, EFFRATIO, and PCA factors 1 and 2, as predicted by age in months and its inverse. The dashed line represents the predicted mean, the dotted lines its 95% confidence intervals. The outer solid lines represent the 95% confidence interval for individual scores. REGRESSION-BASED DEVELOPMENTAL MODELS 31 assumptions are concerned, a (multiple) regression approach to the modeling of cross-sectional devel- opmental effects makes sense only if both age as the predictor and the criterion variable can be con- sidered as continuous quantitative variables. In this situation, multiple regression models using chronological age and its inverse can model and, hence, quantify superimposed linear and curvilin- ear cross-sectional developmental effects on diff- erent (and, possibly, to-be-compared) criterion variables. From a statistical perspective, these models are appropriate as cross-sectional develop- mental models to the extent that the regression residues (statistical errors) are unrelated to age and the predicted scores (see Klein, 2001). In this situation, the observed response comprises of the predicted response plus error. These assumptions must be verified for each individual data set andvariable, and may obviously not hold (and hence yield awkward functions) for variables with a coarse grading and/or ceiling effects. Concerning the WCST, all number and percentage measures that are based on the entire set of trials are ‘fine- grained’ enough to be treated like continuous vari- ables. Conversely, measures like NCC do not allow for this fine-grained differentiation, and multiple regression models provide at best a rough approxi- mation (see Figure 2). Another, theoretical, assumption is relevant here as well. This assumption is indirectly related to the application of regression models, but directly related to test construction. This is the assumption of whether the developmental process under scru- tiny is a quantitative or qualitative one. Most cog- nitive, neuropsychological and intelligence tests allow only for the quantitative differentiation Figure 3.Group means in different WCST parameters for the age groups 6–18 years. TABLE 1 Model equations for the WCST task parameters Regression analyses ab 1 b2 Fa pF a pR 2 R2 adj Fp NTA80.80−.0004 3837 <1 n.s. 9.04 .003 .18 .17 37.16 .0001 TNE−38.25 .1330 6954 5.69 .02 35.06 .0001 .25 .25 58.48 .0001 PR−19.18 .0661 3750 2.98 n.s. 21.68 .0001 .19 .18 39.25 .0001 PE−16.16 .0578 3267 3.37 n.s. 24.27 .0001 .20 .20 43.77 .0001 NPE−22.09 .0752 3686 5.39 .02 29.21 .0001 .21 .20 45.39 .0001 NCC10.85−.0119−549 8.71 .003 42.17 .0001 .26 .26 61.27 .0001 E-R.1074−.0008−6.239 1.90 n.s. 26.00 .0001 .26 .26 60.20 .0001 TCFC−17.76 .0824 2744 7.27 .007 18.21 .0001 .09 .08 16.04 .0001 CLR132.9−.1755−5284 13.34 .001 27.27 .0001 .10 .10 19.94 .0001 TNC119.1−.1335−3117 10.26 .002 12.62 .0004 .04 .03 6.38 .002 FMS2.83−.0084−21.43 3.23 n.s. 0.05 n.s. .06 .05 10.42 .0001 Note. CLR = conceputal level responses; E-R = efficiency ratio (NCC/NTA); FMS = failures to maintain set; NPE = non-perseverative errors; NCC = number of categories completed; NTA = number of trials administered; PE = perseverative errors; PR = perseverative responses; TNE = total number of errors; a = F-values based on Type III sum of squares; 32 KLEIN, FOERSTER, HARTNEGG between individuals and would thus be unable to unveil existing qualitative differences. Conversely, a typical Piaget task is designed to test for qualita- tive differences in problem solving between differ- ent stages of cognitive development (and thus “constructs” these developmental stages). How- ever, Pascual-Leone (1970) has nicely shown with his concept of the M space, that the qualitatively different “stages” of cognitive development as sug- gested by Piaget can be theoretically reduced to the quantitative development of M space capacity. Similarly, intelligence researchers have begun to consider that individual differences in the ability to solve qualitatively different intelligence tasks (which also varies as a function of age) can be a consequence of individual differences in working memory capacity (Kyllonen & Christal, 1990; Schweizer, 1995). It may be possible, hence, to reduce qualitative to quantitative developmental differences in one or more underlying cognitive processes. Conversely, however, quantitative dif- ferences may be the result of using qualitatively different “processing” strategies. Given the quali- tative uniformity of the trials and the purely quan- titative scoring of the WCST this means, that the cognitive developmental processes underlying test performance (such as working memory and cogni- tive set shifting) are considered to be quantitative rather than qualitative in nature. A limitation of the interpretability of all statist- ical developmental models refers to the fact that age is a global organism variable that may be con- founded with other developmentally powerful fac- tors such as cohort effects. This is probably less of an issue in research with children and adolescents. Life span developmental research, however, may require the integration of additional information such as cohort effects or other confounds into the model. Unless the developmental trajectories for the confounds are identical (or, perfectly corre- lated) with those of the criteria, the different source of developmental differences can be disentangled. Ad (2) That the relation between age and most WCST variables was curvilinear reveals that WCST profi- ciency increases as a negatively accelerated func- tion of age. This observation fits into what is known for other features in this age range. For instance, Fischer et al. (1997) described and Klein (2001) quantified the developmental functions for various parameters of saccade control. Similar analyses were accomplished by Fry and Hale (2000) for different cognitive measures such as IQ, work-ing memory, and processing speed, and Klein (2001) for the raw score of Raven’s Standard Pro- gressive Matrices. The diversity of the cognitive functions (WCST, pro- and anti-saccade measures, processing speed, IQ) that seem to follow this pat- tern suggests that a conceptualization of develop- ment as a quantitative-continuous process may be applicable to a broad range of tests of cognitive functions. Ad (3) An advantage of multiple regression estimates of developmental effects, when compared to estimates based on standardized scores, was illustrated in Figure 3 on the one side and Figures 1–2 on the other. Tracing development via group means results in trajectories that may contain implausible developmental effects. It is, for instance, unlikely that the developmental trajectories of some WCST variables reverse their direction (see Figure 3). Similar results had been presented by Chelune et al. (1986; failures to maintain set, from 6 to 7 and 10 to 11 years of age), Rosselli and Ardila (1993; e.g., correct responses from 9–10 to 11–12 years of age), and Shu et al. (2000; e.g. perseverative responses and nonperseverative errors from 10 to 11 years of age) for WCST scores, and Fischer et al. (1997) for saccade parameters. Such odd tra- jectories probably do not reflect developmental dif- ferences between the age groups but sampling biases due to non-representative (stratified or ran- dom) sampling. Massive sampling bias at one or the other age can obviously distort the entire regression function to some extent. In this situ- ation, re-sampling or discarding the biased age bin within the traditional approach based on age group means, would obviously be preferable over relying on a seriously distorted regression model. This should, however, occur in a considerably dampened fashion, because the estimate at each point along the age continuum is based on the entire sample. Nevertheless, both a representative sampling strategy and appropriate statistical tech- niques are required to obtain truly normative data. Ad (4) With respect to the applicability of the multiple regression model to applied research and practis- ing, it is important to realise that we studied here developmental differences rather than develop- mental changes. Accordingly, the model can be used for status diagnostic / assessment, but not process diagnostic / assessment (Pawlik, 1982). REGRESSION-BASED DEVELOPMENTAL MODELS 33 Status diagnostic, however, is important in many research and practical applications where the pre- diction of individual scores on the basis of norma- tive data is required. Our program CONFIREG which is described in detail in the appendix can, in principle, exploit the information of up to 7 varia- bles to predict an individual’s score in dependent measures such as the WCST scores. Although, for the present purpose, we used only the two age vari- ables (age and age −1) that were necessary to model developmental effects, additional information such as the IQ or other neuropsychological test results that may routinely be available in research studies or clinical trials as well as information relevant to possible cohort effects may provide incremental validity to the prediction and thus enhance its pre- cision. Applied to the data of a truly representative normative sample, this procedure can be used to determine whether an individual’s score lies out- side the confidence intervals of the distribution of normative scores. This may, for instance, be useful in basic research or practical diagnostics of patients with attention-deficit hyperactivity disor- dered (ADHD). Here, it has become clear that only a few cognitive tests or measures can separate patients from controls in group statistics (Klein & von Stralendorff, 2002), and that this is presuma- bly the case because only a portion of ADHD patients show deficient performance at all (Nigg, 2004). The application of our regression-based software CONFIREG could thus help identifying the individual ADHD patients who show the defi- cit and thus determining their proportion in a given sample. CONCLUSIONS This study aimed at demonstrating the advantages of multiple regression approaches to the modeling of developmental effects and the prediction of indi- vidual scores in studies with normal subjects or patients. However, normative data from large and representative samples of children and adolescents are currently still missing for a number of neu- ropsychological tests although they are critically needed, for instance, to make individual predic- tions in clinical trials. Such normative data are cur- rently available primarily for established intelligence tests such as the WISC, K-ABC, or Raven’s matri- ces. Although many IQ subtests (e.g., the WISC labyrinth test, Wechsler’s digit span forward/back- ward tests, or Thurstone’s fluency tests) have been subsumed under neuropsychological constructs (Lezak, 1995), the scope of neuropsychological test contents is broader. Applied psychologicalresearch should hence foster the establishment of normative data for neuropsychological tests such as the WCST, and others. Original manuscript received 3 October 2004 Revised manuscript accepted 27 July 2005 First published online 27 October 2006 REFERENCES Alexander, G.E., DeLong, M.R., & Strick, P.L. (1986). Parallel organization of functionally segregated cir- cuits linking basal ganglia and cortex. Annual Review of Neuroscience, 9, 357–381. Ardila, A., Galeano, L.M., & Rosselli, M. (1998). Toward a model of neuropsychological activity. Neu- ropsychology Review, 8, 171–190. Ardila, A., Pineda, D., & Rosselli, M. (2000). Correla- tion between intellingence test scores and executive function measures. Archives of Clinical Neuropsychol- ogy, 15, 31–36. Denckla, M.B. (1996). A theory and model of executive function: A neuropsychological perspective. In G.R. Lyon & N.A. Krasnegor (Eds.). Attention, memory, and executive function (pp. 263–278). Baltimore: Paul H. Brookes Publ. Co. Eslinger, P.J., & Gratton, L.M. (1993). Frontal lobe and frontal-striatal substrates for different forms of human cognitive flexibility. Neuropsychologia, 31, 17–28. Fischer, B., Biscaldi, M., & Gezeck, S. (1997). On the development of voluntary and reflexive components in human saccade generation. Brain Research, 754, 285–297. Fry, A.F., & Hale, S. (2000). Relationships among pro- cessing speed, working memory, and fluid intelligence in children. Biological Psychology, 54, 1–34. Fuster, J.M. (1989). The prefrontal cortex: Anatomy, physiology and neuropsychology of the frontal lobe (2nd ed.). New York: Raven Press. Grant, D.A. & Berg, E.A. (1948). A behavioral ana- lysis of the degree of reinforcement and ease of shifting to new responses in a Weigl-type card sort- ing problem. Journal of Experimental Psychology, 38, 404–411. Green, M.F., Satz, P., Ganzell, S., & Vaclav, J.F. (1992). Wisconsin Card Sorting Test performance in schizo- phrenia: Remediation of a stubborn deficit. American Journal of Psychiatry, 149 (1), 62–67. Heaton, R.K., Chelune, G.J., Talley, J.L., Kay, G.G., & Curtiss, G. (1993). Wisconsin Card Sorting Test man- ual – revised and expanded. Lutz, FL: Psychological Assessment Resources, Inc. Heller, K.A., Kratzmeier, H., & Lengfelder, A. (1998). Standard progressive matrices / Matrizen-test-manual (Band 1). Weinheim: Beltz-Verlag. Jernigan, T.L., Trauner, D.A., Hesselink, J.R., & Tallal, P.A. (1991). Maturation of the human cerebrum dur- ing adolescence. Brain, 114, 2037–2049. Klein, C. (2001). Developmental functions for param- eters derived from pro- and anti-saccade tasks in 199 participants aged 6–28 years. Experimental Brain Research, 139, 1–17. Klein, C. & von Stralendorff, I. (2002). Neuropsycholo- gische defizite bei Aufmerksamkeitsdefizit-Störung (ADS): Theorien und phänomene. In M. Myrtek 34 KLEIN, FOERSTER, HARTNEGG (Ed.). Die Person im biologischen und sozialen Kon- text. Goettingen: Hogrefe-Verlag. Kyllonen, P.C. & Christal, R.E. (1990). Reasoning abil- ity is (little more than) working memory capacity?! Intelligence, 14, 389–433. Lezak, M.D. (1995). Neuropsychological assessment. New York: Oxford University Press. Melchers, P., & Preuss, U. (1992). Bearbeitung der Kaufman Assessment Battery for Children für den deutschsprachigen Raum. Teil 1: Vorstellung des Verfahrens. [Adaptation of the Kaufman Assessment Battery for Children (K-ABC) for German-speaking children: I. Description of the battery]. Zeitschrift fuer Kinder- und Jugendpsychiatrie, 20, 85–93. Mentzel, H.J., Gaser, C., Volz, H.-P., Rzanny, R., Haeger, F., Sauer, H., & Kaiser, W.A. (1998). Cogni- tive stimulation with the Wisconsin Card Sorting Test: Functional MR Imaging at 1.5 T. Radiology, 207, 399–404. Monchi, O., Petrides, M., Petre, V., Worsley, K., & Dagher, A. (2001). Wisconsin Card Sorting revisited: Distinct neural circuits participating in different stages of the task identified by event-related func- tional Magnetic Resonance Imaging. The Journal of Neuroscience, 21, 773–774. Pascual-Leone, A. (1970). A mathematical model for the transition rule in Piaget’s Developmental Stages. Acta Psychologica, 32, 301–345. Pawlik, K. (1982). Modell- und praxisdimensionen psy- chologischer diagnostik. In K. Pawlik (Ed.), Diagnose der diagnostik (pp. 13–44). Stuttgart: Klett-Cotta. Riccio, C.A., Hall, J., Morgan, A., Hynd, G.W., Gonzalez, J.J., & Marshall, R.M. (1994). Executive function and the Wisconsin Card Sorting Test: Rela- tionship with behavioral ratings and cognitive ability. Developmental Neuropsychology, 10 (3), 215–229. Rosselli, M. & Ardila, A. (1993). Developmental norms for the Wisconsin Card Sorting Test in 5- to 12-year-old children. The Clinical Neuropsychologist, 7(2), 145–154. Schweizer, K. (1995). Hypothesen zu den biologischen und kognitiven Grundlagen der allgemeinen Intelli- genz. Zeitschrift fuer Differentielle und Diagnostische Psychologie, 16, 67–81. Shu, B.-C., Tien, A.Y., Lung, F.W., & Chang, Y.Y. (2000). Norms for the Wisconsin Card Sorting Test in 6- to 11-year old children in Taiwan. The Clinical Neuropsychologist, 14(3), 275–286. Voeller, K.K.S., Edge, P., Morris, M.K., Rao, P.V., & Heilman, K.M. (1993). The Wisconsin Card Sorting Test as a measure of response to methylphenidate in children with attention deficit hyperactivity disorder. Paper pre- sented at the annual conference of the International Neuropsychological Society, Galvestone, TX, USA. APPENDIX THE PROGRAM “CONFIREG” The program CONFIREG uses statistical informa- tion derived from the data of a normative sample in order to estimate the mean as well as the upper and lower bounds of a specified confidence limit for a single subject. This information stems from the SAS procedure “REG”. Applying the General Linear Model (GLM) yields estimates of regression weights and standard errors. The regression weights (intercept b 0 and weights b 1 to b k; k = number of predictors) are used to compute the individual’s predicted value = b 0 + b 1x1i + … + b kxki (predictor values equation 1). Confidence intervals can be computed for the estimated score and for the single new case y i under considera- tion. The two confidence intervals differ in the esti- mation of the error variance. Both error variance estimations are derived from the generalized covar- iance matrix. The inverse covariance matrix of the estimates is computed as COVB=(X’X) −1MSE, where X is the N x (k+1)-matrix, with k+1 being the intercept and the number of predictors and N the number of subjects. MSE is the mean squared error and is documented in the SAS ANOVA table. The matrix COVB can be put out with the option COVB in the REG model statement. Different error variances can be computed with COVB: (a) StErr(predicted value) = √(x iCOVBx i’) and (b) StErr(individual value) = √(MSE+ x iCOVBx i’). The confidence interval with a level of significance α and the t-statistic t α/2,N-k-1 is symmetric with respect to the predicted value: (b 0 + b 1x1i + … + b kxki − t α/2,N-k-1 StErr i, b 0 + b 1x1i + … + b kxki + t α/2,N-k-1 StErr i). Note that the width of a confid- ence interval also depends on the sample size (as reflected by t α/2,N-k-1 StErr i). CONFIREG and an SAS Macro for statistical analyses is available at our home page at: http:// staff.psychology.bangor.ac.uk/Members/psse0b/ confireg.zip/. yi xx xi1iki’ ,…, ;= () yi REGRESSION-BASED DEVELOPMENTAL MODELS 35 APPLICATION OF “CONFIREG” 1. Start the program under Windows. (When starting the first time no regression information file is available). 2. Type into the empty sheet the global informa- tion (sample size, the α-level of the confidence interval, mean squared error) and the informa- tion that is specific to the predictors (name, regression weights, generalized inverse covari- ance matrix (lower triangular only)). 3. Type in the predictor values and (for document- ing only) name and value of the dependent variable of the single case for whom you wish to estimate the confidence interval. 4. Click on button APPLY in order to estimate and display the confidence interval and the decision whether the individual’s values lie whithin it. Also, z-, T-, and stanine scores for the individual are displayed. 5. Chose among the following options: (a) CLEAR: clear the sheet/formular and restart with 2; (b) STORE: store the information provided in the sheet/formular into a file named *.prf, which can be used for later applications (program termi- nates); (c) enter new predictor scores or alter the α-level, then click APPLY; (d) CANCEL: program terminates without storing in *.prf.
I have attached the Final assignment since this assignment is building off of it this will be a big deal. I will let you pick the four domains that you are comfortable with and if you want I will help
AdvAnces in cognitive Psychology reseArch Article http://www. ac-psych .or g 2016 • volume 12(1) • 10-19 10 Counterfactual Evaluation of Outcomes in Social Risk Decision-Making Situations: The Cognitive Developmental Paradox Revisited Iván Padrón 1, María Jose Rodrigo 1 and Manuel de Vega 2 1 d evelopmental Psychology, University of la laguna, la laguna, spain 2 cognitive Psychology, University of la laguna, la laguna, spain risk decision making, counterfactual evaluation of outcomes, social feedback, adolescence We report a study that examined the existence of a cognitive developmental paradox in the counterfactual evaluation of decision-making outcomes. According to this paradox adolescents and young adults could be able to apply counterfactual reasoning and, yet, their counterfactual evaluation of outcomes could be biased in a salient socio-emotional context. to this aim, we ana – lyzed the impact of health and social feedback on the counterfactual evaluation of outcomes in a laboratory decision-making task involving short narratives with the presence of peers. Forty risky (e.g., taking or refusing a drug), forty neutral decisions (e.g., eating a hamburger or a hotdog), and emotions felt following positive or negative outcomes were examined in 256 early, mid- and late adolescents, and young adults, evenly distributed. results showed that emotional ratings to nega – tive outcomes (regret and disappointment) but not to positive outcomes (relief and elation) were attenuated when feedback was provided. evidence of development of cognitive decision-making capacities did also exist, as the capacity to perform faster emotional ratings and to differentially allocate more resources to the elaboration of emotional ratings when no feedback information was available increased with age. overall, we interpret these findings as challenging the traditional cognitive developmental assumption that development necessarily proceeds from lesser to great – er capacities, reflecting the impact of socio-emotional processes that could bias the counterfactual evaluation of social decision-making outcomes. corresponding author: iván Padrón gonzález, developmental Psychology, University of la laguna, c ampus guajara sn, la laguna, 38200, spain. email: [email protected] AbstrAct Keywords doi • 10.5709/acp-0183-2 Introduct Ion There is now a broad acknowledgement that counterfactual evaluation of outcomes plays a role in everyday decision making. Upon making the decision and observing the outcomes, people are able to proc – ess not only what actually occurred but also an alternative course of events that might have occurred if a different option had been chosen. This complex evaluation requires the cognitive capacity to engage in counterfactual thinking, which is usually accompanied by emotions (Byrne, 200 5; Epstude & Roese, 200 8; Roese, 200 5). Some studies have analyzed counterfactual emotions, such as regret or disappointment, by manipulating the feedback participants saw after making a deci – sion to play certain gambles: full-feedback (regret: participant sees the outcomes from both the chosen and unchosen gamble) versus partial- feedback (disappointment: participant only sees the outcome from the chosen gamble) ( Camille et al., 200 4). Other studies have also characterized regret and disappointment by differential agency attribution: personal/controlled agency for re – gret and relief, external/uncontrolled agency for disappointment and elation ( Girotto, Legrenzi, & Rizzo, 199 1; Wilkinson, Ball, & Alford, 201 5; Wilkinson, Ball, & Cooper, 201 0). According to this approach, the emotions of regret and relief typically arise in risk situations (e.g., AdvAnces in cognitive Psychology reseArch Article http://www. ac-psych .or g 2016 • volume 12(1) • 10-19 11 taking or refusing a drug), where one is, or feels, responsible for the occurrence of a negative or positive outcome that is under one’s control (Connolly & Zeelenberg, 200 2; Coricelli & Rustichini, 201 0; Ferrell, Guttentag, & Gredlein, 200 9; van Dijk & Zeelenberg, 200 2; Zeelenberg & Pieters, 200 7). By contrast, the emotions of disappointment and ela – tion typically arise in neutral situations (e.g., eating a hamburger or a hotdog), where one is relatively free of self-blame, because the negative or the positive outcome of the decision is appraised as beyond one’s control, such as an accident ( Zeelenberg & Pieters, 200 7; Zeelenberg, van Dijk, Manstead, & van der Pligt, 200 0). The present study takes this second approach to the study of coun – terfactual emotions in risk decision-making situations. We examined the adolescents’ and young adults’ decisions involving controlled and uncontrolled events and their counterfactual evaluation of their negative and positive outcomes to induce the respective emotions of regret, relief, disappointment, and elation. Adolescence is a period of increasing risk-taking behavior, including practicing dangerous sports, drinking alcohol, engaging in unsafe experimentation with addictive substances, among others (Vermont Department of Health, 201 3). However, the topic of the counterfactual evaluation of outcomes has been largely neglected in the decision-making literature. And yet, counterfactual feelings, such as regret, may help adolescents to prevent risky consequences by making adaptive changes in their behavior for future occasions ( Epstude & Roese, 201 1; Smallman & Roese, 200 9; Wong, Haselhuhn, & Kray, 201 2). Moreover, little is known about adolescents’ and young adults’ sensitivity to counterfactually mediated emotions in social situations involving the presence of peers. In these cases, heightened sensitivity to the peer presence has been linked to the adolescent increases in risky decisions, in spite of their acknowledg – ment of the potential consequences on health ( Blakemore & Robbins, 201 2). Therefore, it could be the case that the counterfactual evaluation of outcomes is biased in social situations with peer presence, leading to a poor weighing of the consequences. To this aim, the study presents short narratives involving situations in which the presence of peers was made salient in all cases. To better challenge the process of evaluation of outcomes, we also manipulated the presence or absence of health and peer-relevant feedback to examine its impact on the counterfactual evaluation of negative and positive outcomes. The Cognitive Developmental Paradox Revisited The findings of this study may help to demonstrate the possible exist – ence of a cognitive developmental paradox not only in the decision- making process but also in the realm of the counterfactual evaluation of outcomes. Traditional developmental theory presupposes that with age cognitive development proceeds from lesser to greater sophistica – tion, and that increased cognitive skill should decrease the likelihood of participation in risks ( Arnett, 199 5; Elkind, 198 5; Halpern-Felsher & Cauffman, 200 1; Vartanian, 200 0). The cognitive paradox is that ado – lescents take more risks than children or preadolescents, even when they have more cognitive decision-making skills ( Boyer, 200 6). It is similarly perplexing that adolescents do take more risks than adults, but have relatively similar cognitive decision-making capacities, at least in terms of their capacity to analyze risk-taking situations and to estimate the probability of the outcomes ( Boyer, 200 6). Crucially, adolescents are even able to perceive the negative outcomes associated with a risky decision similarly to adults (e.g., Burnett, Bault, Coricelli, & Blakemore, 201 0; Reyna & Farley, 200 6). What happens with regard to the counterfactual evaluation of out – comes in risk decisions? Is there a cognitive developmental paradox, too? The studies on the developmental progression of counterfactual reasoning from childhood to adulthood have shown that although five- to seven-year-old children are able to experience regret and relief ( Guttentag & Ferrell, 200 8; Weisberg & Beck, 201 0, 201 2), the ability to experience these emotions continues to develop throughout late childhood and adolescence, suggesting that children’s ability to reason counterfactually is not fully developed in all children before 12 years of age ( Habib et al., 201 2; Rafetseder & Perner, 201 2; Rafetseder, Schwitalla, & Perner, 201 3). Therefore, a pure cognitive account would expect that the increase in cognitive sophistication in counterfactual reasoning that is shown to come with the transition from childhood to adolescence, especially from 12 years of age on (e.g., Habib et al., 201 2), should lead to a better evaluation of the outcomes. Counterfactual emotions, such as regret, are highly adaptive and can have a signifi – cant impact on the reduction of risky decisions in the future ( Conner, Sandberg, McMillan, & Higgins, 200 6; Richard, van der Pligt, & De Vries, 199 6). There are reasons to suspect, however, that a cognitive developmen – tal paradox could also exist in the counterfactual evaluation of out – comes. According to the dual-processes account ( Boyer, 200 6; Crone & Dahl, 201 2; Somerville, Jones, & Casey, 201 0; Steinberg, 201 0), adolescents’ decisions appear to be highly sensitive to the presence of socio-emotional cues (e.g., peers) as demonstrated by their increased risk-taking behavior as compared to youth and adults in presence of peers ( Gardner & Steinberg, 200 5). Similarly, the counterfactual evalu – ation of outcomes after making a choice could be biased in a salient socio-emotional context ( Amsel, Bowden, Cottrell, & Sullivan, 200 5). Thus, though there may be some cognitive development in the coun – terfactual reasoning in adolescent years, the outcome evaluation could be biased since adolescents are confronted not only to negative health consequences but also to potential benefits that are emotionally or socially valuable, such as increasing popularity among peers ( Boyer, 200 6; Crone & Dahl, 201 2; Somerville et al., 201 0). To test this possibil – ity, in this study we manipulated the presence or absence of feedback on health and peer popularity. The existence of a cognitive developmental paradox and its pos – sible explanation according to the dual-process proposal has not been tested in the realm of counterfactual evaluations of decision-making outcomes in social situations. The exception is one recent study ex – amining the ability to experience regret and relief in children, adoles – cents, and young adults who performed a gambling task in a socio- emotional context of competition, in which they were informed that their outcome would be compared with that of a competitor ( Habib et al., 201 5). Results showed that in the maximal regret condition (a AdvAnces in cognitive Psychology reseArch Article http://www. ac-psych .or g 2016 • volume 12(1) • 10-19 12 low loss combined with a high win for the competitor) adolescents did not experience regret, whereas children and young adults did. Under outcome conditions designed to induce relief (in which the competi – tor obtained a lower outcome than the participant), adolescents and young adults experienced relief, whereas children did not. However, these findings are not conclusive since the gambling task did not depict risk decision-making situations under uncertainty. Only controllable events were included, and all the situations were competitive without a contrasting condition. The Present Study The present study uses analogues to real-life social decision-making by means of the social context decision-making task (SCDT, Rodrigo, Padrón, de Vega, & Ferstl, 201 4). This task involves verbal narratives describing situations in which the participants were asked to imag – ine themselves, accompanied by a peer, either involved in risky/safe choices (e.g., drinking a lot or staying sober) in risk situations, or neutral choices (e.g., eating a hamburger or a hotdog) in neutral situa – tions, and they were told the positive and negative outcomes. Receiving consequences in risk situations involves controllable events since par – ticipants may have clear expectations about the possible outcomes of each choice. This is not the case when receiving consequences in the neutral situations where expectations about the outcomes are not clear since they involve uncontrollable events (e.g., accidents). In this way, by manipulating the type of decisions to be made either in risky or in neutral situations as well as the negative or positive outcomes re – ceived, we can create the counterfactual conditions to experience the four emotions (regret, relief, disappointment, and elation) in the same study. The study also manipulates the conditions that make the task more or less socio-emotionally salient to examine their impact on the counterfactual evaluation of outcomes. Thus, we manipulated the pres – ence or not of feedback, given after participants were told the outcome of their decision in the task. The feedback includes information on the impact of the consequences on health status and peer popularity on each trial, but also information about the accumulative gains and losses every 10 trials. Both the risky and the neutral trials involved the same sequence of events presented on the screen as illustrated in Figure 1: 1) A second-person scenario describing “you” as accompanied by a close friend; 2) the two alternative options for the decision-making task in that scenario; 3) the outcome of the choice selected, either positive or negative; 4) the emotional rating scale, where participants had to indicate “how do you feel about what just happened?” using a linear scale from -5 ( extremely bad ) to +5 ( extremely good ), placed at the bottom of the screen; and 5) the feedback information (half of the trials), to inform partici – pants about the gains and losses in health and peer popularity depend – ing on the choice made and the negative or positive consequence received. The outcomes presented were pre-set by the experimenter follow – ing a table of contingencies (Table 1). First, there were gains and losses in health and peer popularity in risk situations, whereas in neutral situations there were gains and losses in health but no gains or losses in peer popularity. The reason is that in real-life situations there are no clear expectations concerning the impact on peer popularity of eating a hamburger or a hotdog. Second, after making a safe choice, participants received a positive outcome in health but not in popularity, since avoid – ing risks does not help to increase popularity among peers. However, the experimental trials followed by a safe decision were not entered into the analyses since the comparison was made among regret, relief, disappointment, and elation, which are the conditions that are factori – ally crossed. Another reason is that if we had included in “safe trials” a negative health outcome, then this outcome would have necessarily resulted from uncontrolled events, producing a sort of confounding with the disappointment condition. Finally, another feature of the task is that participants made actual decisions. Thus, in the risk situations participants can be conservative (i.e., choose the safe option over the Figure 1. trial sequences (grey boxes) and measurements recorded (white boxes). notice that the cumulative feedback (dashed box) is only available in the feedback condition. Election Outcome Emotion Health Popularity Risk 75% Negative Regret -30 +10 Risk 25% Positive Relief +10 +30 Safe* 100% Positive Happiness +30 -30 Neutral 35% Negative Disappointment -30 0 Neutral 65% Positive Elation +10 0 tA ble 1. table of Pre-s et contingencies, emotions and Feedback on gains and l osses in health and Peer Popularity Note . * Not used in the analyses. AdvAnces in cognitive Psychology reseArch Article http://www. ac-psych .or g 2016 • volume 12(1) • 10-19 13 risky option), which may change the percentage of negative and posi – tive outcomes actually received. By contrast, in the neutral situations the amount of negative outcomes that the participants received after their decisions corresponds to the nominal probability set up by the experimenter because the two choices (A or B) are equivalent in terms of possible outcomes. Our main goal was to investigate whether providing feedback on health status and peer popularity modulates participants’ performance on the counterfactual evaluation of the outcomes (emotional ratings, rating times, and feedback observation time). We expected lower emotional ratings when this feedback is provided, compared to the no feedback condition. When presenting feedback, the negative peers’ reactions (decrease in popularity) were highlighted, which made more salient the socio-emotional context leading to bias in the evaluation of outcomes. Specifically, the feeling of regret resulting from risky choices and negative outcomes would be lessened in the feedback condition. The reason is that in our task risky choices with negative outcomes, though involving health dangers, were associated to gains in peer pop – ularity. This would not be the case for the feeling of relief resulting from risky choices with positive outcomes both in health and popularity. To support our expectation, the feeling of regret was also attenuated in a gambling task by providing a socio-emotional context of competition with peers ( Habib et al., 201 5). We also predicted that the emotional ef – fect would be more visible in mid-late adolescents, who are reported to be more sensitive to peer effects ( Albert, Chein, & Steinberg, 201 3). In turn, we expected that the feeling of disappointment would be stronger than that of elation, but it would not be so affected by feedback condi – tions, age, or sex, since it is related to serious negative outcomes but derived from uncontrollable events and with no consequences on peer popularity. Previous studies on gender effects reported that adolescent women are more prone than men to perceive situations as risky (Bohlin & Erlandsson, 200 7). In fact, boys and men are less risk averse than wom – en ( Borghans, Golsteyn, Heckman, & Meijers, 200 9; Van Leijenhorst, Westenberg, & Crone, 200 8). In absence of previous evidence, we would expect that women, who are usually more risk averse and presumably more prone to feeling regret, would be more affected than men by the feedback condition by lessening the emotional impact of consequences in risk situations, especially in regret conditions. Altogether, the results of the present study could help to demon – strate the existence of a cognitive developmental paradox in the coun – terfactual evaluation of decision-making outcomes to the extent that the presence of feedback with health and socially relevant information could affect this evaluation process, as well as the possible impact of age, and gender effects. Method Participants A total of 256 volunteers participated in the study, belonging to four age groups: 64 early adolescents (EA), aged 13-14, 32 female and 32 male, MAge = 13.5 years, SD = 0.5; 64 mid-adolescents (MA), aged 15-16, 32 female and 32 male, MAge = 15.6 years, SD = 0.5; 64 late adolescents (LA), aged 17-18 years, 32 female and 32 male, MAge = 17.50 years, SD = .50, from one public high school and 64 young adults (YA), aged 19-20, 32 female and 32 male, MAge = 19.5 years, SD = 0.5, from a public university and one public technical school. After explaining the aim of the study to the teaching staff of each academic center and receiving the permission from the officials, students volunteered to participate. Written parental consent was obtained for children and adolescents prior to the assessment session. Written consent was also obtained for adult participants, who also volunteered after receiving information about the research. The procedure was approved by the Committee for Research Ethics and Animal Welfare at the University of La Laguna. Task and Procedure The study used a social context decision-making task (SCDT) involv – ing two types of verbal materials: forty risk situations and 40 neutral situations ( Rodrigo et al., 201 4). Pilot studies were performed for the elaboration of the verbal materials to select the situations, their choices, and outcomes, using different participants. Sixty-three risk scenarios were written, based on situations selected from the Youth Risk Behavior Survey ( Vermont Department of Health, 201 3). They belonged to four domains: Behaviors that contribute to unintentional injuries (e.g., jumping into the sea from a high rock), risky sporting practices (e.g., climbing without appropriate equipment), unhealthy behaviors (e.g., competing to demonstrate who can eat more burg – ers), and alcohol and other drug use (e.g., consuming cocaine). Sixty participants (half adolescents and half young adults of both genders) were asked to report whether they had been involved in or personally witnessed a similar situation or not. Then, they were given examples of risky and safe options for each situation, and asked to rate on a scale of 1 to 5 how dangerous these actions would be for the protagonist. For the neutral situations, 60 neutral options were also created and par – ticipants had to choose between the two neutral options. We selected only those situations where each option had a 50% of probability of being selected, with no significant age and gender differences (40 situ – ations). To select the positive and negative outcomes, 120 participants (half of them adolescents and half young adults of both genders) were presented with a list of 128 negative events (e.g., risk situations: “while smoking marijuana you feel dizzy and have to go to the doctor”; neu – tral situations: “while preparing a snack you cut your finger and bleed profusely”), and 128 positive events (e.g., risk situations: “you enjoy swimming at the beach”; neutral situations: “you enjoy the meal at the restaurant”). The participants rated them on a bipolar scale from -5 (very negative ) to +5 ( very positive ). The length of the sentences in the scenarios was matched in the number of words and unfamiliar words were avoided in all the scenarios. Example of a risk situation: “You are in a disco with your close friend. In the toilet you and your friend meet a guy who offers you cocaine”. Decision: 1) “You buy it” (risky choice), 2) “You tell him that you are not interested” (safe choice). AdvAnces in cognitive Psychology reseArch Article http://www. ac-psych .or g 2016 • volume 12(1) • 10-19 14 Outcomes (risky choice): 1) Negative: “You got very sick and had to go to the hospital”, or 2) Positive: “You had a big ’high’ and felt great” Outcomes (safe choice): Positive: “You enjoyed dancing with your friends”. Example of a neutral situation: “You are in a restaurant with your friend checking the menu for lunch”. Decision: 1) “You decided to get a hamburger”, 2) “You decided to get a hotdog”. Outcomes: 1) Negative: “The mayonnaise was spoiled and you got sick and had to go to the hospital”; 2) Positive: “You enjoyed the meal as it was very good”. Participants received the scenarios of the risk and neutral situa – tions auditorily and the choices and outcomes in written format. The presentation of each piece of information was self-paced, allowing for the recording of chronometric data in addition to the behavioral data. The 80 trials (40 risk and 40 neutral situations) were separated by an inter-trial interval of 5 s, and preceded by a 5-trial practice phase. The stimulus presentation was controlled by means of Cogent 2000, a MATLAB Toolbox for presenting stimuli and recording responses with precise timing. The task was administered individually to the participants in a quiet room at their Secondary School. They were asked to imagine themselves (“imaging you”) as vividly as possible in each situation ac – companied with a close friend and choose between the two alternative actions. They were informed that their decisions would have positive or negative outcomes with more or less impact on their health status and their popularity among friends. Half of the participants, randomly se – lected from the total sample, were submitted to the feedback condition being informed at the end of every trial (by means of bars diagrams) of the specific gains and losses obtained in peer popularity and health (see Table 1). Every 10 trials they were also informed of the cumulative gains and losses in peer popularity and health, having started the task with 300 points in popularity and 300 points in health status. Finally, all participants were informed that as a bonus for their participation one of them would win a laptop computer in a random draw to be made at the end of the data collection. The duration of the task varied between 20 and 25 min, depending on participants’ response times. With respect to the procedure, once participants entered a quiet room at the school half of them completed the battery of self-report assessment measures first (the self-report questionnaires were not included in analysis as they contained information that is irrelevant to this study) and then, individually, the SCDT in another room; the other half followed a reversed order (first SCDT and then question – naires). Design and Plan of Analyses A mixed factorial design was used with age (four groups) or gender (two groups) and feedback (present/absent) as between-participant factors, and type of choices (risky/neutral) and outcome valence (nega – tive and positive) as within-participant factors. The dependent vari – ables were the emotional rating, rating time, and observation time of feedback (just in the feedback condition). Rating time is an index of the cognitive cost allocated to the performing of the emotional rating. Observation time is the time spent watching the feedback informa – tion, being an indication of the cognitive effort required to process this information. Four emotional conditions were analyzed resulting from the combination of type of choices and valence of outcomes: (a) risky choice and negative outcomes (regret); (b) risky choice and positive outcomes (relief ); (c) neutral choice and negative outcomes (disap – pointment); (d) neutral choice and positive outcomes (elation). The emotional condition resulting from choosing the safe option was not included in the analyses as it always involved positive consequences and could not be crossed factorially with the other emotional condi – tions. In all the cases analyses of variance (ANOVAs) were used and effect sizes (eta partial square, η p2 ) were calculated ( small : > .01; me- dium : > .06 and large : > .14). T-test and post hoc Bonferroni corrected comparisons were used when necessary. Data points lying > 3 SD from the grand mean of the dependent variables involving time measures in each analysis were considered outliers and were excluded from that analysis (2% of the data as average). results Emotional Ratings Following Outcomes Means and standard deviations of emotional ratings after reading the consequences are shown in Table 2. As expected, means are negative for negative emotions and positive for positive emotions and all sig – nificantly differed from zero ( p = .001), which would suggest that par – ticipants experienced regret and disappointment for negative emotion scores and relief or elation for positive emotion scores. Risk situations Neutral situations Regret M (SD) Relief M (SD) Disappoint- mentM (SD) ElationM (SD) Feedback Emotion ratings (-5,+5) -1.38 (1.56) 1.80 (1.54) -1.83 (1.38) 3.06 (1.20) Rating times (ms) 2616 (711) 2613 (754) 2782 (650) 2567 (548) Observation times (ms.) 2264 (920) 1960 (699) 1641 (516) 1699 (546) No Feedback Emotion ratings (-5,+5) -3.13 (1.4) 1.46 (1.98) -3.31 (1.13) 3.52 (1.04) Rating times (ms) 2991 (778) 2804 (895) 2951 (638) 2718 (508) tA ble 2. Means and standard deviations of outcome Measures Under Feedback and no Feedback c onditions AdvAnces in cognitive Psychology reseArch Article http://www. ac-psych .or g 2016 • volume 12(1) • 10-19 15 Age and gender differences were observed in rating times ac – cording to feedback conditions. Overall, rating times significantly decreased with age, F(3, 204) = 3.52, p = .016, η p2 = .087 , with only the difference between early adolescents and young adults being reliable, p < .05, all other comparisons p > .10 (EA: M = 2,888; SD = 481; MA: M = 2,745; SD = 606 ; LA: M = 2,821; SD = 569 ; YA: M = 2,591; SD = 484). However, sensitivity of rating times to feedback conditions also changed with age, F(3, 204) = 3.27, p = .032, η p2 = .097, (Figure 3). Overall, emotional rating times were shorter for feedback conditions than for no feedback conditions only in late adolescents ( p < .001) and young adults ( p < .05). There was an interaction of gender by feedback and type of choice, F(1, 204) = 4.37, p = .038, η p2 = .021. Simple effects showed that wom – en’s rating times in risky choices (regret and relief ) were significantly shorter in the feedback condition than in the no feedback conditions (p < .01). Men’s rating times in neutral choices (disappointment and elation) were significantly shorter in the feedback condition than in the no feedback condition ( p < .05). Observation Times The last set of analyses was performed in the feedback condition only, since the dependent variable was the observation time of feedback information (see Table 2). Participants spent more time inspecting the feedback information in risky choices (2,112 ms) than in neutral choices (1,670 ms), F(1, 115) = 81.67, p = .001, η p2 = .415. and after receiving negative outcomes (1,952 ms) as compared to positive out – comes (1,829 ms), F(1, 115) = 4.97, p = .029, η p2 = .028. Both effects were qualified by a type of choice × outcome valance interaction, F(1, 111) = 13.24, p =.001, η p2 = .103, showing that the above difference was significant in the risky choices (regret > relief, p = .001) but not in the neutral choices (disappointment = elation, p > .10). Overall, the observation times decreased with age, F(3,115) = 3.09, p = .030, η p2 = .075, with the difference being reliable between early adolescence and mid-adolescence ( p = .024), late adolescence ( p = .007) and young adults ( p = .024), (2,167 ms, 1,833 ms, 1,771 ms, 1,831 ms, respectively). Overall, emotional ratings were lower in the feedback condition than in the no feedback condition, F(1, 206) = 40.4, p = .001, η p2 = .164 (on average 2.0 and 2.9 respectively). There was a main effect of type of choice, F(1, 204) = 69.85, p = .001, η p2 = .255, showing that the emotional ratings were higher in neutral choices than in risky choices. There was also a main effect of outcome valence on emotional rat – ings, F(1, 204) = 1191, p = .001, η p2 = .854), showing higher emotional ratings for negative outcomes (regret and disappointment) than for positive outcomes (relief and elation). However, there was a significant interaction of feedback by outcome valence, F(1, 200) = 45.88, p = .001, ηp2 =.187 (Figure 2). Thus, emotional ratings for positive outcomes (relief and elation) did not differ between feedback ( M = 2.43, SD = 1.3) and no feedback conditions ( M = 2.49, SD = 1.5). By contrast, emotional ratings for negative outcomes (regret and disappointment) were significantly lower under feedback conditions ( M =1.60, SD = 1.4) than under no feedback conditions ( M = 3.22, SD = 1.2). Significant age effects were not observed. There was a significant gender effect according to the outcome valence on emotional ratings, F(1, 206) = 5.26, p = .023, η p2 = .025. Women reported higher emotional ratings than men when they were told the negative outcome of their decision (regret and disappoint – ment), whereas gender differences were not significant for positive outcomes (relief and elation). Emotional Rating Times Means and standard deviations of emotional rating times after reading the consequences are shown in Table 2. Participants spent more time on the emotional ratings in the no feedback version (2,860 ms) than in the feedback version (2,646 ms), F(1, 200) = 7.49, p = .050, η p2 = .020. There was a main effect of outcome valence, F(1, 200) = 19.1, p = .001, ηp2 = .087, indicating that emotional ratings for negative outcomes took more time than those for positive outcomes. No interaction effects with feedback were observed. Figure 2. interaction effects of feedback by outcome valence on the emotional ratings. Figure 3. Age differences in emotional rating times by feedback condition. AdvAnces in cognitive Psychology reseArch Article http://www. ac-psych .or g 2016 • volume 12(1) • 10-19 16 dI scuss Ion This study examined the existence of a cognitive paradox in the coun – terfactual evaluation of risk decision making by means of exploring the impact of gains and losses in health status and peer popularity, as well as age and gender effects. As expected, the presence of feedback in risk situations determines an attenuation of the participants’ emotional experience derived from outcomes as compared to the no feedback conditions, as shown by the lower emotional ratings, and shorter rating times in the former condition. No effect was obtained from the manipulation of feedback in the neutral situations, as expected. Moreover, what seems to be specifically affected in risk situations are the emotions of regret and disappointment which were attenuated in the feedback condition as compared to the no feedback condition, whereas emotions linked to positive outcomes (relief and elation) were not affected by the presence or absence of feedback. This is remarkable, since overall the processing of negative outcomes demands more effort and provokes higher emotional arousal than the processing of positive outcomes, as suggested by higher emotion ratings, and longer rating times. The impact of feedback on risky choices is not likely to be due to the instructions received at the beginning of the task, since in both the feedback and no feedback versions participants were informed that their decisions would have positive or negative consequences with more or less impact on their health status and their popularity among friends. Also it is not likely to be due to a game-like effect according to which participants tend to disregard the task information waiting for the final feedback, since the emotional attenuation is confined to the negative consequences but not to the positive ones. As expected, participants evaluating the outcomes in the feedback condition were less sensitive to regret feelings as compared to relief feelings ( Habib et al., 201 5), both derived from risky choices, suggest – ing that they decreased their avoidance of harm, probably due to the positive impact of negative consequences in peer popularity. However, the counterfactual evaluation associated to the feeling of regret involves more attention demands than that of the feeling of relief, since observa – tion times of feedback information were larger for regret as compared to relief conditions. Probably, participants had to pay comparatively more attention to the conflicting information presented involving health losses and popularity gains in regret conditions, whereas in relief conditions both aspects involve gains. Unexpectedly, participants were also less sensitive to disappoint – ment feelings under feedback conditions, as compared to elation, which suggests that the surprise effect provoked by non-controlled negative circumstances ( Zeelenberg & Pieters, 200 7) is also attenuated in this condition. In other words, participants seem to decrease their aversion to ambiguity (e.g., Weber & Tan, 201 2), even when feedback involved only health risks. However, this is a “short life” attenuation effect since by the time participants are facing the feedback informa – tion, observation times did not differ for disappointment and elation conditions. Probably, there are not many lessons to be learnt from hav – ing experienced outcomes under uncontrolled circumstances, as there is no chance to undo what has happened. In favor of this interpreta – tion, previous studies have shown that disappointment, as compared to regret, is relatively free of self-blame and does not lead to behavior change ( Zeelenberg et al., 200 0; Zeelenberg & Pieters, 200 7). Emotional ratings to outcome information did not vary across age groups, in line with previous results indicating that the children’s abil – ity to reason counterfactually is already in place after 12 years of age (Rafetseder et al., 201 3; Rafetseder & Perner, 201 2). In fact, previous decision-making studies have found age differences in adolescents’ counterfactual emotions but confined to the comparison to child or adult groups, which respectively were younger and older than our participants’ age groups ( Burnett et al., 201 0; Habib et al., 201 2). Also their results are hardly comparable to ours as they followed a different procedure to elicit counterfactual and non-counterfactual emotions in gambling situations. In our study, rating times and observation times of feedback information were sensitive to developmental effects, since overall there were shorter times with age, probably due to improve – ments in executive functioning ( Crone, 200 9; Schiebener, García-Arias, García-Villamisar, Cabanyes-Truffino, & Brand, 201 4). However, sen – sitivity of rating times to feedback conditions changed with age, since emotional rating times were shorter for feedback than for no feedback conditions only in late adolescents and young adults. This age-related effect qualified a general trend observed, showing that counterfactual evaluations made in absence of feedback were more costly than in pres – ence of feedback, suggesting that in absence of explicit task informa – tion participants have to rely upon their own cognitive resources to evaluate the outcomes. It seems that late adolescents and young adults were more able to cope with this extra cognitive demand than early and mid-adolescents. Gender effects on emotional ratings showed that women expe – rienced more emotional intensity than men when confronted with negative outcomes (regret and disappointment) but not when facing positive outcomes, with no feedback effects. That means that overall women become more emotionally activated than men not only when faced with the prospect of receiving negative results but also when actu – ally experiencing harmful consequences ( Bohlin & Erlandsson, 200 7; Clark et al., 200 8). However, the interaction of gender by feedback and type of choice on emotional rating times showed that the awareness of health losses and peer benefits led women to spend shorter times in the risk decisions (i.e., to become less “risk averse”), whereas they led men to spend shorter times in the neutral decisions (i.e., to become less “ambiguity averse”). However, all gender results were weak so they deserve further exploration. In keeping with the ecological validity of the task we are aware of two possible limitations of the study. First, feedback information dif – fers under risk (health and peer popularity information) and neutral (only health information) situations. Introduction of an arbitrary weight towards gains and losses in peer popularity depending on the neutral choices, instead of a “zero” score, could have affected results in unknown ways. However, we managed to perform the analyses and to draw the main conclusions from the comparisons performed within each type of choice (risk or neutral). Second, it would be interesting to have included a measure of executive functioning to support our AdvAnces in cognitive Psychology reseArch Article http://www. ac-psych .or g 2016 • volume 12(1) • 10-19 17 interpretation of decreasing times with age in the counterfactual evaluation of outcomes. Third, arguably using real-life scenarios would have entailed some misunderstandings in the interpretation of risk and neutral situations. To keep this possibility at minimum, we have performed pilot studies to elaborate verbal material that could be com – parable across ages and genders. We think that simulation of real-life situations is worthwhile to increase the participants’ chances of visual – izing the course of actions and foreseeing their consequences, and to facilitate the participants’ actual engagement in counterfactual-related emotional states. In conclusion, this study demonstrated that the cognitive devel – opmental paradox also existed when considering the counterfactual evaluation of outcomes in a salient socio-emotional context. Evidence of development of cognitive decision-making capacities does exist, as young adults were more capable of performing faster emotional ratings than early adolescents. Moreover, late adolescents and young adults were able to differentially allocate more cognitive resources to the counterfactual evaluation than younger participants in situations when no feedback information is available. However, the paradox ex – ists since across the age groups enhancing the health and the socially relevant consequences of the choices by means of feedback negatively affected the counterfactual evaluation in risk situations by attenuating the emotional sensitivity to the outcomes of the choices, especially the negative ones. This could be potentially damaging since there would be less chances to anticipate regret or to avoid the previously chosen option in the future, two cognitive capacities that are already present in older children ( Guttentag & Ferrell, 200 8; O’Connor, McCormack, & Feeney, 201 4). Altogether, the present findings challenge the tradition – al cognitive developmental assumption that development necessarily proceeds from lesser to greater capacities and revealed the importance of socio-emotional processes in the counterfactual evaluation of social decision-making outcomes. Acknowledgement This work was supported by the Spanish Ministry of Economy and Competitivity under the Grant PSI 2012-32879 to María José Rodrigo, and by the NEUROCOG project supported by the Canarian Agency for Research, Innovation and the Information Society and the European Regional Development Funds to Manuel de Vega. RefeRences Albert, d., chein, J., & steinberg, l. (2013 ). the teenage brain peer influences on adolescent decision making. Current Directions in Psychological Science, 22 , 114–120. doi: 10.1177/0963721412471347 Amsel, e., Bowden, t., cottrell, J., & sullivan, J. (2005 ). Anticipating and avoiding regret as a model of adolescent decision mak – ing. in J. e. Jacobs & P. A. Klaczynski (e ds.), The development of judgment and decision making in children and adolescents (pp. 119–154). Mahwah, UsA: erlbaum. Arnett, J. J. (1995 ). t he young and the reckless: Adolescent reck – less behavior. 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I have attached the Final assignment since this assignment is building off of it this will be a big deal. I will let you pick the four domains that you are comfortable with and if you want I will help
Relationships among Negative Emotionality, Responsive Parenting and Early Socio-cognitive Development in Korean Children Kijoo Cha* Early Childhood Education, Gachon University, Seongnam-si, Gyeonggi-do Korea The present study examined the interplay among negative emotionality, responsive parenting and socio-cognitive developmental outcomes (i.e., communication, personal-social and problem-solving outcomes) in about 1620 Korean children using three waves of longitudinal data spanning thefirst 2 years of their life. Results from the Structural Equation Modeling (SEM) demonstrated that there were moderate to low degrees of stability in negative emotionality, responsive parenting and socio-cognitive developmental outcomes from infancy to toddlerhood. Evidence for reciprocity in the parent–child relationship was found; responsive parenting predicted higher levels of subsequent child communication (in infancy and toddlerhood), and infants’higher problem- solving ability predicted higher responsive parenting in toddlerhood. Overall, the cross-age associations among the variables were similar between boys and girls, but some different patterns were observed: when controlling for family contextual factors and the within-time correlations, negative emotionality at an earlier point significantly predicted lower responsive parenting at a later point and vice versa only in girls during infancy, but neither in boys nor in toddlerhood. The implications of thesefindings are discussed. Copyright © 2016 John Wiley & Sons, Ltd. Key words:negative emotionality; stability of temperament; reciprocity; responsive parenting; child gender The relationship between young children and their parents is highly likely to be bidirectional; that is, children’s temperament or development is likely to elicit *Correspondence to: Kijoo Cha, Gachon University, Early Childhood Education, Seongnamdae-ro 1342, Sujeong-gu, Seongnam-si, Gyeonggi-do, Korea. E-mail: [email protected] Infant and Child Development Inf. Child. Dev.26: e1990 (2017) Published online 10 June 2016 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/icd.1990 Copyright © 2016 John Wiley & Sons, Ltd. 1 of 29 certain behavioural patterns from their parents over time, which in turn may affect the children’s temperament or development (Barnett, Gustafsson, Deng, Mills-Koonce, & Cox, 2012; Bornstein, Hendricks, Haynes, & Painter, 2007). In the past few decades, human and animal research has shown that the early years of life, particularly infancy and toddlerhood, are crucial in the individual’s overall life outcomes because of high brain plasticity during these developmental periods and the impact of early mother–child interactions on emotional and cognitive development in adulthood (Cameron et al., 2005; Colantuoni et al., 2011; Kang et al., 2011; Naumova, Lee, Rychkov, Vlasova, & Grigorenko, 2013). Despite the significance of infancy and toddlerhood in human developmental trajectories, relatively fewer studies have examined the comprehensive interplay among child temperament, parenting and early socio-cognitive development in infancy and toddlerhood. Furthermore, even fewer studies have examined the possible differences in the interplay of these variables in boys and girls, particularly with non-Western samples. To address these gaps in the literature, the present study examined the transactional associations among temperament, parenting behaviours and child developmental outcomes longitudinally, with data spanning thefirst 2 years of life among a nationally representative sample of Korean children and their mothers. Negative Emotionality and Parenting Negative emotionality is defined as a child’s temperamental tendency to react to stressors with high degrees of negative effect, such as negative mood, unsoothability and irritability. (Rothbart & Bates, 2006), often used interchangeably with the term‘difficult temperament’in the literature. As suggested from the definition, negative emotionality is inversely related to emotional self-regulation (Bridgett et al., 2009; Lee, Zhou, Eisenberg, & Wang, 2012). Many prior studies that examined the continuity of negative emotionality during infancy, toddlerhood and early childhood revealed low to moderate degrees of stability (0.2–0.5) (Casalin, Luyten, Vliegen, & Meurs, 2012; Komsi et al., 2006; Putnam, Rothbart, & Gartstein, 2008), which suggests that negative emotionality is subject to considerable changes over time. One of the most-studied proximal factors found to be associated with negative emotionality is parenting practices. Studies investigating the links between difficult temperament and supportive parenting (embracing warmth, sensitivity, responsiveness and acceptance) have revealed mixedfindings, mostly based on simple concurrent associations, with a greater number of studies reporting negative associations and fewer studies reporting positive associations (for a review, see Belsky & Jaffee, 2006; Paulussen-Hoogeboom, Stams, Hermanns, & Peetsma, 2007). Despite the strong theoretical support for transactionality in parent–child relationships, relatively fewer studies have reported the contribution of children’s negative emotionality to parenting behaviours, especially ininfancyandtoddlerhood(e.g. Boivin et al., 2005; Bridgett et al., 2009; Forget-Dubois et al., 2007; Katainen, Räikkönen, & Keltikangas-Järvinen, 1997; Lipscomb et al., 2011). Additionally, empirical studies revealing reciprocity in parent–child relationships mostly come from studies with older children, preschool- or elementary school-aged children (e.g. Combs-Ronto, Olson, Lunkenheimer, & Sameroff, 2009; Larsson, Viding, Rijsdik, & Plomin, 2007; Lengua, 2006; Lengua & Kovacs, 2005). Thus, the present study addressed these gaps in the literature. 2of29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd Negative Emotionality, Parenting and Early Socio-cognitive Development Negative emotionality characteristics are likely to have a negative impact on early social and cognitive outcomes. Children low in negative emotionality, that is, those who were temperamentally better regulated and less reactive tended to have more positive peer relations and were more likely to be nominated as friends by peers (e.g. Gleason, Gower, Hohmann, & Gleason, 2005). Similarly, preschoolers who scored lower on negative emotionality tended to score higher on measures of early literacy, counting and numeracy skills, even when controlling for parental education, child gender and vocabulary (Coplan, Barber, & Lagace-Seguin, 1999). Regarding language development, higher degrees of negative emotionality were associated with lower levels of vocabulary among 21-month-old children (Salley & Dixon, 2007), and with lower levels of vocabulary and narrative ability among 2- to 4-year-old children (Noel, Peterson, & Jesso, 2008). As the possible underlying mechanism of the observed links between temperament and language development, researchers postulated that high reactivity places a relatively greater load on self-regulatory systems, thereby leaving less amount of cognitive resources for the child to attend to and process given information, which would ultimately result in a slower rate of language acquisition (Reiser-Danner, 2003; Rothbart & Bates, 2006). As an alternative but not mutually exclusive hypothesis, it has also been posited that negative emotionality can deteriorate the quality of interpersonal relationships and linguistic inputs, leading to lower levels of language ability (Reiser-Danner, 2003). The same rationale can be employed to explain negative associations between difficult temperament and cognitive development. For example, Molfese et al. (2010) found that mothers having children with higher negative emotionality tended to display higher levels of stress, which in turn was associated with children’s lower cognitive development. A number of relevant studies have reported significant associations between parenting behaviours and the language and pro-social skills of children (Barnett et al., 2012; Bornstein et al., 2007; Deater-Deckard et al., 2001; Deiner & Kim, 2004; Landry, Smith, & Swank, 2006). Barnett et al. (2012) reported significant longitudinal paths from sensitive parenting behaviours to later child social competence (pro-social behaviours) and language development (expressive and receptive vocabulary) across 12 months to 36 months of age. It is notable that the authors found evidence of the influence of child development on parenting behaviours as well: higher levels of child social competence (among girls) and receptive vocabulary (among boys) predicted higher levels of subsequent sensitive parenting, which reveals another aspect of the transactional relationship of parent–child interactions. Culture and Negative Emotionality, Parenting and Early Development Mainstream social values underlie how parents socialize their children. Parents respond differently to children’s behaviours depending on social desirability or acceptability of their behaviours (Goodnow & Collins, 1990; Markus & Kitayama, 1991). Some studies suggest that Korean mothers’responses to children’s negative emotionality might vary from what has been found among Western mothers (Lee, Norr, & Oh, 2005; Park, Trommsdorff, & Lee, 2012), which might have originated from differences in socio-cultural norms regarding parenting (Goodnow & Collins, 1990; Markus & Kitayama, 1991). Although Korean parenting has gone through substantial changes in the past few decades owing to industrialization and Westernization, Korea has been found Negative Emotionality, Parenting and Socio-cognitive Development3of29 Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd to still maintain a traditional interdependent culture characterized by human-relatedness, which is well revealed by family interdependence (Markus & Kitayama, 1991), especially a strong psychological bond between mothers and their children (Park & Cheah, 2005). Korean mothers tend to regard their children as extensions of themselves, rather than separate beings, which may well make them feel a strong sense of responsibility for their children’s well-being and development (Park & Kim, 2006). For example, Korean mothers were found to respond with self-blame or guilt to their children’s negative developmental outcomes rather than with anger, as observed in Western mothers (Lee et al., 2005). Moreover, in a recent study regarding Korean mothers’reactive (responding to children’s direct cues) versus proactive (anticipating children’s needs) sensitive behaviours in parenting (Park et al., 2012), Korean mothers tended to prefer proactive sensitive behaviours to a greater extent than did German mothers from an individualistic culture, pointing out the child’s immaturity in dealing with emotional distress as the reasons for the preference (Ziehm, Trommsdorff, Heikamp, & Park, 2013). In sum, considering that emotional distress is related to the manifestation of negative emotionality and low emotional regulation, Korean mothers’strong psychological bond with children, perception of children as immature in emotional regulation, and strong sense of responsibility for children’s development may lead them to be less disturbed by infants’and toddlers’negative emotionality, compared to Western mothers. Thus, these characteristics of Korean mothers might result in the absence of a path from negative emotionality to responsive parenting, which is different from what has been observed in Western mother–child relationships. Regarding associations between parenting behaviours and child language or cognitive development, extant studies with samples from various countries tend to converge on thefinding that sensitive and responsive parenting behaviours positively affect child language or cognitive development (Walker et al., 2007), although parental beliefs about their roles in or approaches to child development vary across cultures (Bradley et al., 1989; Parmar, Harkness, & Super, 2004). Gender and Negative Emotionality and Parenting Parents’response to their children, including children’s difficult temperamental attributes, is influenced by their beliefs and expectations about gender-appropriate behaviours and characteristics (Brown, Craig, & Halberstadt, 2015). Prior studies investigating the differences in parents’socialization behaviours between boys and girls have been based on the assumption that differential parenting behaviours from early years might be the foundation for later-appearing gender-related variations in children’s behaviours (Fausto-Sterling, García-Coll, & Lamarre, 2012a, 2012b; Martin & Ruble, 2010). Among these studies, research concerning infancy and toddlerhood has focused on the aspects of maternal daily caretaking behaviours (e.g. touching, lifting, moving and supporting new activities) (e.g. Fausto-Sterling et al., 2015), communication/language interactions (e.g. Clearfield & Nelson, 2006) or interactions during disciplining (e.g., Ahl, Fausto-Sterling, García-Coll, & Seifer, 2013), disclosing gender-related differences in maternal behaviours even as early as thefirst year of life. Ahl et al. (2013) found that, overall, mothers of infant boys tended to spend a longer time on disciplining and used disciplinary words more frequently as compared to mothers of girls. However, interestingly, as compared to mothers of infant girls, mothers of infant 4of29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd boys were also inclined to utter more affectionate terms and employ milder discipline strategies with their male infants, who manifested a greater number of negative effects during discipline interactions than did female infants. Indeed, some studies have demonstrated that the child’s gender moderates the relationship between the child’s negative emotionality and parenting behaviours (Chaplin, Cole, & Zahn-Waxler, 2005; Garside & Klimes-Dougan, 2002; Gordon, 1983; Klein, 1984; Putnam, Sanson, & Rothbart, 2002). Specifically, parents, in keeping with traditional gender-stereotyped expectations, tended to approve the expressions of negative-dominant emotions (e.g. anger and contempt) to a greater extent among boys than among girls, while the opposite pattern was observed in terms of negative-submissive emotions (e.g. shyness and fear). Even though there has been no empirical study directly addressing child-gender-related disparity in Korean parenting during the early years of life, some remotely related studies allow us to hypothesize how differently Korean mothers might respond to children’s negative emotionality as a function of the child’s gender. For instance, in a study examining the socialization beliefs of Korean mothers of preschoolers, Park and Cheah (2005) reported that mothers of boys were more likely to point out the child’s developmental readiness (e.g. ‘Because at this age, the child is capable of understanding sharing’) as reasons for the importance of controlling negative emotions, whereas mothers of girls were more likely to resort to moral reasons (e.g.‘The skill is important because it shows that the child is kind, thoughtful, and considerate’), suggesting the continuous presence of traditional gender-stereotyped expectations even among younger generations of Korean mothers. In this respect, Korean mothers’socialization behaviours correspond to the patterns found among Western parents discussed above. Probably, this tendency is likely stronger among Korean mothers, considering that Confucianism, characterized by patriarchy-based strict division of gender roles, dominated the political ideology and way of life in the Korean society since long (Finch & Kim, 2003). Thus, the reviewed studies among both Western and Korean samples lead to the hypothesis that Korean mothers’ responsive parenting behaviours are less likely to be affected by the negative emotionality of boys than of girls. Taken altogether, the reviewed literature has revealed the following: (i) the reciprocal nature between temperamentalattributes and parenting behaviours with less evidence for infants and toddlers and (ii) overall positive and negative associations that sensitive and responsive parenting, and negative emotionality, respectively, have with the socio-cognitive development of children across cultures. However, some important gaps remain in this research area. Relatively fewer studies have examined the cross-lagged reciprocal relationships among temperament, parenting and child development and simultaneously probing the possible discrepancies between boys and girls during infancy and toddlerhood. Furthermore, even fewer studies have been conducted on subjects from non-Western cultures. Thus, the present study aimed to expand the literature by addressing the following research questions with a nationally representativelongitudinal dataset of Korean children and mothers concerning thefirsttwoyearsoflife. Research Questions (RQs) and Hypotheses 1 How stable are negative emotionality, responsive parenting behaviours and developmental outcomes (communication, personal-social and problem-solving outcomes) over time (RQ 1 in Figure 1)? Negative Emotionality, Parenting and Socio-cognitive Development5of29 Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd In general, the reviewed studies revealed low to moderate degrees of stability in negative emotionality, responsive parenting and socio-cognitive development during the early years. Thus, similar results were expected in this study. 2 Are there any transactional effects between the child’s negative emotionality and parenting behaviours over time (RQ 2 in Figure 1)? Considering Korean mothers’strong psychological ties with and view on their children as beings that are immature in emotional regulation, the path from negative emotionality to subsequent responsive parenting was not expected (possible differences between boys and girls are discussed in RQ 5), while the positive impact of responsive parenting on subsequent negative emotionality was. 3 Are there any transactional effects between parenting behaviours and each developmental outcome over time (RQ 3 in Figure 1)? Based on previous studies that reported the positive impact of children’s higher language and cognitive outcomes on later parenting as well as the impact of responsive parenting on child development, reciprocity was hypothesized in the associations between parenting and socio-cognitive development. No cross-national differences were expected in this respect since responsive parenting has been found to foster children’s development regardless of cultural background, as discussed earlier. 4Does the child’s negative emotionality predictsubsequent socio-cognitive developmental outcomes (communication, personal-social and problem- solving outcomes) (RQ 4 in Figure 1)? A few previous studies examining the associations between negative emotionality and socio-cognitive development have shown that negative emotionality exerts negative effects on language, social and cognitive development. Thus, significant Figure 1. A Conceptual Model. 6of29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd paths from negative emotionality to subsequent socio-cognitive development were hypothesized to appear. 5 Do the associations among the variables (RQs 1–4) differ as a function of the child’s gender? That is, does the child’s gender moderate the associations among the variables? The aspect of negative emotionality examined in the present study bears on the intensity of expressing negative reactions in response to external stimuli, which can be considered as dominant rather than submissive emotions. Thus, it is possible that the sample mothers might have been less annoyed by their sons’ negative emotionality due to a traditional bias against gender-related characteristics, while being relatively more irritated by their daughters’negative emotionality. Therefore, a significant path from negative emotionality to less subsequent responsive parenting was expected only among girls. In terms of other relationships such as‘negative emotionality and socio-cognitive development’and ‘responsive parenting and socio-cognitive development’, no gender-related differences were anticipated since these associations were assumed to concern common or natural physiological mechanisms underlying human adaptation and development. In addressing these research questions, relevant variables (i.e., marital satisfaction, maternal distress and stressful life events) were controlled as covariates, based on previous studies that suggested that socio-demographic factors (family SES) and stressful family experiences (maternal depression and marital conflict) affected both temperament and parenting behaviours (Bradley & Corwyn, 2002; Pauli-Pott, Mertesacker, & Beckmann, 2004; Sturge-Apple, Davies, & Cummings, 2006). METHODS Participants The sample of the present study came from the large-scale national Panel Study on Korean Children (PSKC) conducted by the Korea Institute of Child Care and Education (KICCE). The PSKC identified a nationally representative sample of approximately 2000 children and their families in Korea, since 2008, through yearly data collection. The present study used data from thefirst three measurement waves that spanned across the children’sfirst 2 years of life. The data set at thefirst wave (W 1, 2008), on child development and family socio-demographics, was collected through a standardized child assessment tool (the Korean Age and Stages Questionnaire (K-ASQ), infants’age: 4 and 5 months) and parent questionnaires (N= 2078, boys: 50.8%, girls: 49.2%). At the second measurement wave (W 2, 2009), with the attrition of 226 families and the recruitment of 52 families, a total of 1904 children (boys: 50.5%, girls: 49.5%) and mothers participated in the data collection (infants’age: 13 to 15 months). At the third measurement wave (W 3, 2010), the sample children (N= 1802) were about 25 to 27 months old (boys: 50.9%, girls: 49.1%). In the current analysis, only the children and mothers who took part in the data collection at all three time points were included (N= 1620).T-tests were conducted to check whether there were differences between the groups of participants who were included and excluded in the analysis across all three waves, in terms of the main variables [i.e. child’s negative emotionality, responsive parenting, child’s developmental outcomes Negative Emotionality, Parenting and Socio-cognitive Development7of29 Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd and domestic factors (family SES, marital satisfaction, maternal distress and stressful life events)]. Significant differences were found only sporadically across a few variables: child’s communication (higher in the participants included; t= 2.92,p<.01) and personal-social outcomes at W 1(higher in the participants included;t= 4.08,p<.01), responsive parenting at W 2(higher in the participants excluded;t= 2.02,p<.05) and maternal distress at W 3(higher in the participants excluded;t= 2.45,p<.05). Throughout the three waves of data, the parents (99.6% of the sample) were married, and less than 1% of the sample families were from ethnic minority groups. Additionally, majority of the sample parents [about 70% in both mothers (M = 31.1 years) and fathers (M = 33.6 years)] had two or more years of college, compared to approximately 30% of parents having completed high school. Parents with less than high school education accounted for less than 1% of the total sample. The educational attainment of the sample parents was only somewhat higher than the average of the Korean population of similar age (two or more years of higher education: 64% in 25- to 34-year-old) (OECD, 2013). Measures Negative emotionality Information on negative emotionality was collected through a parent questionnaire. The questions were taken from the emotionality scale of Buss and Plomin’s (1984) Emotionality, Activity and Sociability (EAS) -Temperament Survey for Children-Parental Ratings. Among the three scales, the emotionality items address infants’negative mood, irritability and intensity of negative reactions, that is, negative emotionality (e.g.‘my baby cries easily’;‘my baby tends to be somewhat emotional’;‘my baby often fusses and cries’;‘my baby gets upset easily’; and‘my baby reacts intensely when upset’). Thefive items were rated on a 5-point scale, from not typical of my child (1 point) to very typical of my child (5 points). The Korean version of the EAS showed good internal consistency (0.74 in the 2008 wave, 0.98 in the 2009 wave and 0.86 in the 2010 wave), as did the original EAS (internal consistency M = 0.83) among children aged 1 to 9 years (Buss & Plomin, 1984). The ratings for each item were totaled, and higher scores on emotionality indicated the infant’s higher level of negative emotionality. Parenting behaviours Information on parenting behaviours was also collected through items taken from the Parental Style Questionnaire (PSQ; Bornstein, 1989). The social interaction scale of the PSQ, which was used in the present study, consists of two facets of positive parenting behaviours: parental warmth (e.g.‘I provide my child with positive affectionate displays of warmth and attention’;‘I spend time talking to or conversing with my child’) and responsiveness (e.g.‘I promptly and appropriately respond to my child’s expressed distress or discomfort’;‘I provide my child with quick and positive feedback to his/her bids for attention’;‘Iam aware of what my child wants and/or is feeling’). The items were rated on a 5-point scale from hardly at all (1 point) to all the time (5 points). These ratings were then totaled for analyses, with higher scores indicative of warmer and more responsive parenting (henceforth, responsive parenting). The social interaction scale in this study showed an alpha reliability of 0.70, 0.92, and 0.98 in the 2008, 2009, and 2010 waves, respectively. 8of29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd Socio-cognitive developmental outcomes Child developmental outcomes were measured by the Korean Age and Stages Questionnaire (K-ASQ), which is the Korean version of the ASQ validated by Huh, Squires, Lee, and Lee (2006) in the Korean context. The ASQ is a tool to assess the developmental status of young children using six questions infive developmental areas: communication, gross motor skills,fine motor skills, problem-solving and personal-social skills. Among these areas, three regarding socio-cognitive development were included in the current analyses: communication, personal-social skills and problem-solving. The communication scale addresses children’searly expressive and receptive language development and orientation towards communi- cation (e.g.‘When your baby wants something, does he tell you by pointing to it?’;‘If you point to a picture of a ball (kitty, cup, hat etc.) and ask your child,‘What is this?’ ‘Does your child correctly name at least one picture?’). The personal-social scale addresses children’s self-help skills (autonomy, personal) and interactions with other people or objects (social) (e.g.‘When you dress your baby, does she push her arm through a sleeve once her arm is started in the hole of the sleeve?’;‘When playing with either a stuffed animal or a doll, does your child pretend to rock it, feed it, change its diapers, put it to bed and so forth?’;‘Does your baby act differently towards strangers than he does with you and other familiar people?’). The problem-solving scale assesses children’s cognitive functioning (e.g. memory, attention and information-processing) and adaptive goal-directed behaviours to solve problems (e.g.‘After watching you hide a small toy under a piece of paper or cloth, does your babyfind it?’;‘If your child wants something she cannot reach, does shefind a chair or box to stand on to reach it (for example, to get a toy on a counter or to“help”you in the kitchen)?’). Questions are answered with‘Yes’(10 points), ‘Sometimes’(5 points) or‘Not yet’(0 points). Scores for each item were totaled within each developmental area, with a maximum of 60 points. A comparison of the parental responses to the K-ASQ with the results from other validated assessment tools proved the validity of the K-ASQ: the percentage agreement of the results between the K-ASQ and the Korean version of the Denver II was 97% for 27-month-old (Lee et al., 2011). The alpha reliability of the K-ASQ was 0.74, 0.73 and 0.70 in the 2008, 2009 and 2010 waves, respectively. Maternal distress The degree of maternal depression was assessed by the Kessler Psychological Distress Scale (K6) (Kessler et al., 2002), a simple measure of psychological distress involving six questions on one’s emotional state (e.g. During the past 4 weeks, how much of the time did you feel: so sad that nothing could cheer you up?; nervous?; restless orfidgety?; hopeless?; that everything was an effort?; and worthless?). The alpha reliability of the K6 was 0.99, 0.99 and 0.97 in the 2008, 2009 and 2010 waves, respectively. The K6 was validated on the Korean population (Paik, 2010). Each of the six questions was rated on a 5-point Likert scale, from 1 (none of the time) to 5 (all of the time). The ratings of all six questions were totaled, yielding a minimum score of 6 and a maximum score of 30. Scores at the lower end of the scale indicate a low level of psychological distress, while higher scores indicate a high level of psychological distress. Stressful life events Twenty-seven items regarding stress-causing family life events within the past one year were rated either‘0’or‘ 1’depending on whether the event was experienced (=1) or not (=0) (e.g.‘Took out a loan or refinanced a loan to cover Negative Emotionality, Parenting and Socio-cognitive Development9of29 Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd increased expenses’;‘A parent/spouse died’;‘Parent/spouse became seriously ill or injured’;‘A member lost or quit a job’;‘Spouse/parent was separated or divorced’). These items were taken from the Family Inventory of Life Events and Changes (FILE) (McCubbin, Patterson, & Wilson, 1982), the translated version of which was validated among Korean adults (Choi & Ok, 1997). Scores were totaled, higher scores indicating a higher frequency of stressful family experiences during the past one year and a higher degree of tension and negative emotions within the family commensurate with the stressful events. The reliability coefficient of the FILE was 0.67, 0.62 and 0.64 in the 2008, 2009 and 2010 waves, respectively. Marital satisfaction Mother’s overall marital satisfaction was assessed by the Revised-Kansas Marital Satisfaction Scale (RKMSS), which was adapted from the Kansas Marital Satisfaction Scale (KMSS) to the Korean cultural context and validated (Chung, 2004). Four items were rated on a 5-point Likert Scale (1 = very dissatisfied to 5 = very satisfied) and totaled for the analyses (Min: 4 points, Max: 20 points) (alpha = 0.98, 0.94 and 0.96 in 2008, 2009 and 2010, respectively). Higher scores indicate higher levels of marital satisfaction in mothers. Analysis Structural equation modeling (SEM) was used to test cross-lagged models consisting of autoregressive and cross-time transactional paths between emotionality, parenting and the respective domain of three development outcomes (i.e. communication, personal-social and problem-solving) across the three waves of data (see Figure 1). The model also included within-time correlations among negative emotionality, parenting and each developmental outcome; for readability and simplicity, these within-time correlations have not been presented in thefinal model (Figures 2–6). The model was estimated using the robust maximum likelihood estimator in the M PLUS 7.11 (Muthén & Muthén, 2013). Based on the zero-order within-time correlations (Tables 2–4), the effects of maternal distress, marital satisfaction and stressful life events on both negative emotionality and Figure 2. Cross-lagged models among negative emotionality, responsive parenting and communication outcomes. 10 of 29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd parenting were controlled in the model to prevent spurious associations from appearing. Family SES (a composite of parental education and family income) and maternal age were deleted as confounders in thefinal model (Figures 2–4) because when their effects on the main variables were controlled, the modelfit indices [e.g. comparativefit index (CFI), Tucker-Lewis index (TLI) and root mean square error of approximation (RMSEA)] dropped as compared to when they were not, and they had no or very weak significant correlations with the main constructs across the three waves. To test the moderating effects of child gender in the associations among the main constructs, a multiple group SEM was conducted in the following steps (Bollen, 1989). First, the hypothesized paths among the variables were constrained to be equal in the models for boys and girls, respectively. Next, the difference in the Figure 3. Cross-lagged models among negative emotionality, responsive parenting and personal-social outcomes. Figure 4. Cross-lagged models among negative emotionality, responsive parenting and problem-solving outcomes. Negative Emotionality, Parenting and Socio-cognitive Development11 of 29 Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd chi-squared statistics between the unconstrained and constrained models was calculated. Then, this chi-squared difference statistic was compared to the chi-squared distribution to see whether the constrained and unconstrained models were significantly different from each other. RESULTS Descriptive Statistics The descriptive statistics of negative emotionality, parenting and developmental outcomes at three measurement points have been presented in Table 1. Negative emotionality for girls was slightly higher than that for boys across all three points, but significant difference between the two groups was found only at W 3(t= 2.23, p<.05). Responsive parenting for girls was also slightly higher only at W 3than that for boys (t= 1.94,p<.05). Finally, all socio-cognitive outcomes of girls were Figure 5. Cross-lagged models among negative emotionality, responsive parenting and communication outcomes for boys (n= 828). Figure 6. Cross-lagged models among negative emotionality, responsive parenting and communication outcomes for girls (n= 792). 12 of 29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd Table 1. Descriptive statistics on temperament, parenting, and social developmental outcomes Boys Girls Total Mean (SD) Min/max Mean (SD) Min/max Mean (SD) Negative emotionality NE at W 1 13.60 (2.97) (n= 811) 5/25 13.63 (3.11) (n= 779) 6/25 13.62 (3.04) (n= 1590) NE at W 2 13.41 (3.06) (n= 825) 5/25 13.61 (3.24) (n= 787) 5/25 13.51 (3.15) (n= 1612) NE at W 3 16.06 (2.05) (n= 811) 9/23 16.28 (2.00) (n= 770) 7/22 16.17 (2.03) (n= 1581) Responsive Parenting Parenting at W 1 24.20 (2.94) (n= 758) 14/30 23.24 (3.03) (n= 725) 6/30 24.22 (2.98) (n= 1483) Parenting at W 2 23.43 (2.89) (n= 824) 14/30 23.47 (2.98) (n= 789) 14/30 23.44 (2.93) (n= 1613) Parenting at W 3 22.87 (3.28) (n= 814) 6/30 23.17 (2.94) (n= 774) 12/30 23.02 (3.11) (n= 1588) Communication Communication at W 1 53.89 (8.83) (n= 828) 15/60 53.76 (8.72) (n= 792) 10/60 53.83 (8.78) (n= 1620) Communication at W 2 47.75 (11.57) (n= 828) 5/60 51.04 (10.29) (n= 792) 10/60 49.54 (11.09) (n= 1620) Communication at W 3 50.61 (12.42) (n= 828) 0/60 55.02 (9.09) (n= 792) 10/60 52.76 (11.14) (n= 1620) Personal-social Personal-social at W 1 55.03 (7.79) (n= 828) 10/60 54.44 (8.32) (n= 792) 15/60 54.74 (8.05) (n= 1620) Personal-social at W 2 51.53 (11.41) (n= 828) 5/60 53.24 (10.32) (n= 792) 5/60 52.37 (10.92) (n= 1620) Personal-social at W 3 54.11 (9.32) (n= 828) 0/60 55.767.83 (n= 792) 20/60 54.92 (8.68) (n= 1620) Problem-solving Problem-solving at W 1 56.17 (7.43) (n= 828) 0/60 56.00 (7.26) (n= 792) 20/60 56.08 (7.35) (n= 1620) Problem-solving at W 2 48.59 (12.67) (n= 828) 0/60 50.20 (11.23) (n= 792) 0/60 49.38 (12.01) (n= 1620) Problem-solving at W 3 53.19 (8.53) (n= 828) 0/60 55.00 (6.94) (n= 792) 20/60 54.07 (7.85) (n= 1620) W1,first measurement wave (2008); W 2, second measurement wave (2009); W 3, third measurement wave (2010) Negative Emotionality, Parenting and Socio-cognitive Development13 of 29 Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd significantly higher than those of boys at W 2and W 3(communication:t= 6.04, p<.001 at W 2;t= 8.12,p<.001 at W 3; personal-social outcome_t= 3.15,p<.001 at W 2;t= 3.84,p<.001 at W 3; problem-solving:t= 2.71,p<.01 at W 2;t= 4.67, p<.001 at W 3) while there was no significant difference at the initial point (W 1) between the two groups. Correlations among All Study Variables The within-time correlations among all study variables have been presented in Tables 2–4 and the cross-time correlations of the main constructs in Table 5. Nega- tive emotionality was concurrently associated with lower levels of responsive parenting at W 1(r= 0.117,p<.001) and W 2(r= 0.216,p<.001), but not at W 3 (Tables 2–4). Responsive parenting tended to be associated with slightly higher levels of developmental outcomes (communication, personal-social and problem-solving outcomes) concurrently and prospectively across all three waves, whereas negative emotionality was concurrently associated with lower levels of personal-social (r= 0.081,p<.001) and problem-solving (r= 0.058,p<.05) outcomes only at W 2. The within-time correlations between the three developmen- tal outcomes were moderately strong (r= 0.5,p<.001) at W 1and were slightly weaker at W 2and W 3(r= 0.3–0.4,p<.001) (Tables 2–4). The over-time correlations within the respective domain of socio-cognitive developmental outcomes across three measurement points were rather weak (r= 0.1–0.2,p<.001) (Table 5). Correlations between the negative emotionality estimates of adjacent years tended to become weaker from W 1to W 3(Table 5). Finally, overall, the family contextual factors (i.e. maternal distress, stressful life events and marital satisfaction) were consistently associated with negative emotionality and responsive parenting throughout all the three measurement points (Tables 2–4). Testing the Cross-lagged Model The structural models for each of the developmental outcomes and each gender (Figures 2–6)fit the data well. The modelfit indices (see Figures 2–6) satisfied the criteria (CFI≥.95, RMSEA≤.06, and SRMR≤.08) recommended by Hu and Bentler (1999) for a relatively goodfit between the data and a hypothesized model. Concurrent paths among negative emotionality, parenting and each developmen- tal outcome have not been presented in Figures 2–6 for readability. The rest of this section addresses the research questions presented earlier. 1 How stable are negative emotionality, responsive parenting behaviours and developmental outcomes over time? All the autoregressive paths were statistically significant and in positive directions, suggesting a cross-time stability in negative emotionality, responsive parenting behaviours and developmental outcomes, except autoregressive paths of socio-cognitive development between W 1and W 3(Figures 2–4). Socio-cognitive development tended to show only a very weak degree of consistency over time (0.13–0.25). Negative emotionality (0.20–0.44) and responsive parenting (0.39–0.46) showed low to moderate degrees of stability. Finally, the stability of negative emotionality and responsive parenting decreased over time from infancy to toddlerhood, while that of communication and problem-solving abilities increased. 14 of 29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd Table 2. Zero-order correlations among variables related to temperament, parenting, social developmental outcomes, socio-demographics and domestic experiences at Wave 1 No. 12345678910 1 Family SES–––––––––– 2 Child sex 1 0.037 (n= 1535)––––––––– 3 Maternal age0.178*** (n= 1498)0.043 (n= 1407)–––––––– 4 Maternal distress 0.078*** (n= 1396) 0.034 (n= 1475) 0.053* (n= 1471)––––––– 5 Stressful live events 0.133*** (n= 1405) 0.043 + (n= 1486)0.049* (n= 1492)0.264*** (n= 1475)–––––– 6 Marital satisfaction0.113*** (n= 1403) 0.010 (n= 1481) 0.071* (n= 1428) 0.382*** (n= 1472) 0.205*** (n= 1481)––––– 7 Negative emotionality 0.042 (n= 1508)0.004 (n= 1590) 0.118*** (n= 1520)0.215*** (n= 1450)0.049 + (n= 1459) 0.109*** (n= 1454)–––– 8 Parenting 0.057* (n= 1402)0.006 (n= 1483)0.014 (n= 1468) 0.268*** (n= 1472) 0.062* (n= 1483)0.206*** (n= 1478) 0.117*** (n= 1456)–– – 9 Communication 0.004 (n= 1535) 0.007 (n= 1620) 0.015 (n= 1580) 0.057* (n= 1475) 0.039 (n= 1486)0.036 (n= 1481) 0.017 (n= 1590)0.285** (n= 1483)–– 10 Personal-social 0.011 (n= 1535) 0.037 (n= 1620) 0.022 (n= 1580) 0.082** (n= 1475) 0.074* (n= 1486)0.025 (n= 1481)0.026 (n= 1590)0.100*** (n= 1483)0.488*** (n= 1620)– 11 Problem-solving 0.036 (n= 1535) 0.011 (n= 1620) 0.013 (n= 1580) 0.080* (n= 1475) 0.057* (n= 1486)0.034 (n= 1481)0.021 (n= 1590)0.100*** (n= 1483)0.441*** (n= 1620)0.526*** (n= 1620) 1Boys were coded as 1 and girls as 2.+p<.10. *p<.05. **p<.01. ***p<.001. Negative Emotionality, Parenting and Socio-cognitive Development15 of 29 Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd Table 3. Zero-order correlations among variables related to temperament, parenting, social developmental outcomes, socio-demographics and domestic experiences at wave 2 No. 12345678910 1 Family SES–––––––––– 2 Child sex 1 0.037 (n= 1535)– 3 Maternal age 0.178*** (n= 1498)0.043 (n= 1407) 4 Maternal distress 0.141*** (n= 1524) 0.011 (n= 1609) 0.043 (n= 1614) 5 Stressful live events 0.189*** (n= 1535)0.026 (n= 1620)0.015 (n= 1570)0.308*** (n= 1609) 6 Marital satisfaction0.130*** (n= 1515)0.006 (n= 1598) 0.027 (n= 1519) 0.337*** (n= 1587) 0.218*** (n= 1598) 7 Negative emotionality 0.069** (n= 1527)0.030 (n= 1612) 0.077*** (n= 1573)0.247*** (n= 1606)0.112*** (n= 1612) 0.123*** ( n= 1590) 8 Parenting 0.117*** (n= 1528)0.007 (n= 1613)0.067 (n= 1564) 0.324*** (n= 1604) 0.071** (n= 1613)0.203*** (n= 1591) 0.216*** (n= 1607) 9 Communication 0.020 (n= 1535)0.149*** (n= 1620) 0.013 (n= 1544) 0.019 (n= 1609)0.017 (n= 1620)0.006 (n= 1598) 0.039 (n= 1612)0.088*** (n= 1613) 10 Personal-social 0.000 (n= 1535)0.078*** (n= 1620) 0.015 (n= 1544) 0.056* (n= 1609)0.028 (n= 1620)0.026 (n= 1598) 0.081** (n= 1612) 0.086*** (n= 1613)0.400*** (n= 1620) 11 Problem-solving 0.025 (n= 1535)0.067** (n= 1620)0.001 (n= 1544) 0.033 (n= 1609)0.021 (n= 1620)0.033 (n= 1598) 0.058* (n= 1612)0.070** (n= 1613)0.398*** (n= 1620)0.424*** (n= 1620) 1Boys were coded as 1 and girls as 2.+p<.10. *p<.05. **p<.01. ***p<.001. 16 of 29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd Table 4. Zero-order correlations among variables related to temperament, parenting, social developmental outcomes, socio-demographics and domestic experiences at wave 3 No. 12345678910 1 Family SES–––––––––– 2 Child sex 1 0.037 (n= 1535)– 3 Maternal age 0.178*** (n= 1498)0.043 (n= 1407) 4 Maternal distress 0.068** (n= 1503) 0.054* (n= 1586)0.033 (n= 1479) 5 Stressful live events 0.202*** (n= 1512) 0.023 (n= 1596)0.005 (n= 1488)0.303*** (n= 1586) 6 Marital satisfaction 0.102*** (n= 1498)0.038 (n= 1579)0.001 (n= 1501) 0.313*** (n= 1570) 0.191*** (n= 1579) 7 Negative emotionality 0.038 (n= 1498)0.056* (n= 1581) 0.026 (n= 1539)0.187*** (n= 1573)0.115*** (n= 1581) 0.024 (n= 1566) 8 Parenting 0.106*** (n= 1504) 0.055* (n= 1588) 0.000 (n= 1511) 0.318*** (n= 1579) 0.131*** (n= 1588)0.228*** (n= 1572) 0.006 (n= 1574) 9 Communication 0.091*** (n= 1535)0.198*** (n= 1620) 0.031 (n= 1591) 0.106*** (n= 1586) 0.038 (n= 1596)0.065* (n= 1579) 0.006 (n= 1581)0.176*** (n= 1588) 10 Personal-social 0.015 (n= 1535)0.095*** (n= 1620)0.001 (n= 1591) 0.030 (n= 1586) 0.033 (n= 1596)0.081** (n= 1579) 0.015 (n= 1581)0.071** (n= 1588) 0.281*** (n= 1620) 11 Problem-solving 0.048 + (n= 1535)0.116*** (n= 1620) 0.003 (n= 1591) 0.038 (n= 1586) 0.025 (n= 1596)0.045 + (n= 1579) 0.047 + (n= 1581)0.088*** (n= 1588)0.379*** (n= 1620)0.371*** (n= 1620) 1Boys were coded as 1 and girls as 2.+p<.10. *p<.05. **p<.01. ***p<.001. Negative Emotionality, Parenting and Socio-cognitive Development17 of 29 Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd Table 5. Zero-order correlations among temperament, parenting, social developmental outcomes at waves 1, 2 and 3 No. 1 2 34567891011121314 1NE(W 1)– – – ––––––––––– 2NE(W 2) .466***– – ––––––––––– 3NE(W 3) .217*** .277***– ––––––––––– 4P(W 1) .117*** .156*** .028––––––––––– 5P(W 2) .099*** .216*** .052* .509***–––––––––– 6P(W 3) .089*** .166*** .006 .445*** .554***––––––––– 7 Com (W 1) .017 .020 .031 .085* .069** .058*–––––––– 8 Com (W 2) .006 .039 .014 .098** .088*** .086*** .162***––––––– 9 Com (W 3) .011 .023 .001 .127*** .114*** .176*** .078** .263***–––––– 10 PS (W 1) .026 .035 .007 .100*** .085** .063* .488*** .169*** .093***––––– 11 PS (W 2) .049 + .081** .001 .089** .086** .089*** .158*** .400*** .136*** .190***–––– 12 PS (W 3) .027 .038 .015 .046 + .044 + .071** .069** .241*** .281*** .061* .152***––– 13 PrS (W 1) .021 .019 .008 .100** .105*** .075** .441*** .154*** .076** .526*** .187*** .086***–– 14 PrS (W 2) .020 .058* .041 .053* .070** .061* .160*** .398*** .179*** .138*** .424*** .163*** .136***– 15 PrS (W 3) .019 .021 .047 + .085** .049* .088** .103*** .247*** .379*** .096*** .158*** .371*** .092*** .230*** NE, negative emotionality; P, parenting; Com, communication; PS, personal-social; PrS, problem-solving; W 1,first measurement wave (2008); W 2, second measurement wave (2009); W 3, third measurement wave (2010). +p<.10. *p<.05. **p<.01. ***p<.001. 18 of 29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd 2 Are there any transactional effects between negative emotionality and responsive parenting behaviours over time? When accounting for domestic experiences that were associated with both negative emotionality and parenting, and concurrent associations among negative emotionality, parenting and a developmental outcome at each measurement point, only responsive parenting at W 1longitudinally predicted lower levels of negative emotionality at W 2( .067,p<.01), but not vice versa, nor at different waves (Figures 2–4). 3 Are there any transactional effects between parenting behaviours and each developmental outcome over time? Although no transactional cross-lagged paths were found between responsive parenting and developmental outcomes during the same period, the positive impact on each other was observed across different developmental periods (Figures 2–4). The positive impact of responsive parenting on subsequent development was found in infancy and toddlerhood (i.e. communication), when concurrent correlations at each measurement point were taken into account. The impact of the child’s development on responsive parenting was found in infancy: children’s higher problem-solving predicted higher levels of subsequent responsive parenting. Not reaching significance level (.05), children’s personal-social outcomes marginally predicted higher levels of subsequent responsive parenting in toddlerhood (0.039,p= .069). 4Does the child’s negative emotionality impact subsequent developmental outcomes? When the concurrent covariance was controlled, the statistically significant impact of negative emotionality on child development was not found: negative emotionality at W 1only marginally predicted lower levels of personal-social outcomes at W 2( 0.043,p= 0.079) (Figures 2–4). 5 Do these over-time relations among the variables (RQs 1–4) differ as a function of the child’s gender? That is, does the child’s gender moderate these associations among the variables? The constrained model, in which all the paths are set to be equal between boys’ and girls’models, did not produce statistically significant differences in modelfit in comparison with the unconstrained model across all developmental outcomes, thereby failing to reject the null hypothesis that the pattern of associations does not vary between boys and girls (communication:Δχ 2(127) = 115.09,p= 0.76; personal-social outcomes:Δχ 2(127) = 117.47,p= 0.71; and problem-solving:Δχ 2 (127) = 131.83,p= 0.37). Although significant moderation effects of the child’s gender were not found in this study because the significant paths in the models for boys and girls did not differ greatly from each other, a few significantly different paths were observed between boys and girls. The most prominent difference was the cross-lagged reciprocity observed between responsive parenting and negative emotionality in infancy only among girls (Figures 5 and 6; the rest offinal models, for boys and girls separately, are available from the author on request). The coefficient for a path from negative emotionality at W 1 to responsive parenting at W 2was .064– .065, (p<.05) and that for a path from responsive parenting at W 1to negative emotionality at W 2was .074– .078 (p<.05) depending on the developmental outcome included in the model (i.e. communication, personal-social and problem-solving outcomes). Another gender Negative Emotionality, Parenting and Socio-cognitive Development19 of 29 Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd difference was that responsive parenting at W 2 predicted higher levels of communication ability at W 3only among boys (.091,p<.05): the significant path between the two variables found in the entire sample disappeared in the girls-only model. DISCUSSION The present study attempted to address the gaps in the literature by capturing the differences in longitudinal interplay among negative emotionality, parenting and the respective domain of early socio-cognitive development (communication, personal-social skills and problem-solving abilities) between boys and girls during thefirst 2 years of life, with a non-clinical sample from a non-Western culture. Overall, thefindings of this study demonstrated that negative emotionality, parenting behaviours, and children’s socio-cognitive development during the initial years are stable with low to moderate degrees of associations, which are partially transactional and different between boys and girls, while exhibiting a general cross-cultural similarity. Stability of Negative Emotionality and Socio-cognitive Development As found in the current study, many of the previous studies that examined relative or structural stability of temperamental characteristics during infancy to early childhood by investigating cross-age correlations or structural coefficients revealed low to moderate degrees of consistency (0.2–0.5) in negative emotionality (Bornstein et al., 2015; Casalin et al., 2012; Komsi et al., 2006; Putnam et al., 2008; Putnam et al., 2002). Focusing on over-time changes in the consistency of negative emotionality, extant studies have reported mixedfindings regarding developmen- tal trajectories during the early years of life. In line with the observed reduction in the consistency of negative emotionality from infancy to toddlerhood in the present study, Bornstein et al. (2015) uncovered that during thefirst year of life, stability of temperamental distress to limitations, related to reactivity measured in this study, became weaker over time. In contrast, Putnam et al. (2008) found that cross-age correlations of negative emotionality traits increased in magnitude between toddlerhood and early childhood than between infancy and toddlerhood. However, unlike some of the prior studies that solely counted on the comparison of correlations without controlling for probable covariates, the present study examined cross-age relations by holding constant the concurrent family factors found to affect the consistency of negative emotionality, such as maternal distress, marital satisfaction and stressful life events, while also taking into account concurrent correlations among the variables. Thus, the present study’s estimates of relative stability, extracted from more rigorous analyses, reinforced the conclusion that negative emotionality tends to be only moderately stable during infancy and toddlerhood in a Korean sample. Absolute temperamental stability, that is, over-time mean level changes in temperament, particularly in the dimensions related to negative emotionality, has also been found to vary depending on the developmental periods (Bridgett et al., 2009; Lipscomb et al., 2011; Partridge & Lerner, 2007). For example, Bridgett et al. (2009) and Lipscomb et al. (2011) have found a continuous increase in negative emotionality during infancy and early toddlerhood, while Partridge and Lerner (2007), based on more frequent and longer observation, have reported 20 of 29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd an increase in negative emotions until toddlerhood and a decrease thereafter until early childhood. Reduction in the relative or absolute stability of negative emotionality, especially the former, which was found to occur in toddlerhood in the present study, could be at least partially explained by the biological maturation of the self-regulatory system in toddlerhood (Posner, Rothbart, Sheese, & Voelker, 2012; Rothbart & Bates, 2006). For example, the development of the executive attention system, which controls inhibition and attention shifting,first appears towards the end of thefirst year of life and continues to develop during childhood (Calkins, 2004; Posner et al., 2012). Attention control, such as avoidance of negative stimuli, is an important strategy for infants to modulate negative emotions aroused by external factors (Calkins, 2004). Thus, maturation of the physiological foundation for emotional self-regulation could explain the decrease in negative emotionality stability after infancy. However, the observed decrease in the stability of negative emotionality over time might have resulted from a measurement error or simply from the differences in the interval between W 1and W 2, and W 2and W 3 (W 1–W 2: about 8 months, W 2–W 3: about 12 months) (Bornstein et al., 2015; Parade, Dickstein, Schiller, Hayden, & Seifer, 2014). Indeed, greater stability is expected over brief periods, in comparison to longer time spans. Socio-cognitive developmental outcomes showed only a very weak strength of consistency. However, the lack of longitudinal studies examining the stability of early socio-cognitive development during infancy and toddlerhood makes it difficult to judge whether the low consistency in the developmental outcomes is mainly due to measurement error or indeed demonstrates that the characteristics of early socio-cognitive development are considerably malleable to environmental influence (Houck, 1999). Thus, the degree of stability in each of the developmental areas would gradually become evident with more future studies. Reciprocity in the Mother–Child Relationship between Boys and Girls: Infancy vs. Toddlerhood The impact of negative emotionality on subsequent responsive parenting was not observed in the present study, which might be attributed to the characteristics of Korean mothers. Many studies using Western samples have shown that mothers having temperamentally difficult children are inclined to display less responsive or more rejecting parenting over time (Larsson et al., 2007; Lengua, 2006; Lengua & Kovacs, 2005). However, given Korean mothers’tendency to respond with self-blame or guilt to their children’s negative developmental outcomes (Lee et al., 2005) and perception of children as immature in emotional self-regulation (Ziehm et al., 2013), Korean mothers might have been less bothered by infants’ and toddlers’negative emotionality, which led to no observed negative impact of negative emotionality on subsequent responsive parenting overall. Thus, future studies with successive panel data would be able to disclose variations in the relations between responsive parenting and negative emotionality across longer developmental periods, along with changes in mothers’expectations and parenting emphases towards their growing children (McNally, Eisenberg, & Harris, 1991; Roberts, Jeanne, & Block, 1984). The absence of significant paths from responsive parenting to subsequent negative emotionality during toddlerhood might have resulted from the relatively lower malleability of the brain during toddlerhood than during infancy (Colantuoni et al., 2011; Kang et al., 2011; Naumova et al., 2013), when taking into Negative Emotionality, Parenting and Socio-cognitive Development21 of 29 Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd account the concurrent associations between them. Considering that the formation of synaptic connections in the prefrontal cortex, involved in emotional regulation (Etkin, Egner, & Kalisch, 2011), is relatively more active in infancy than in other developmental periods, children’s negative emotionality in toddlerhood might have been less susceptible to mothers’parenting, as compared to that in infancy. This possibility also aligns with thefinding that fewer significant cross-time associations were found between responsive parenting and socio-cognitive developmental outcomes during toddlerhood than during infancy. Although the transactionality between responsive parenting and negative emotionality was not found in the overall analysis (using the whole sample) across infancy and toddlerhood, it was observed among the girls in infancy. When accounting for covariates (i.e. maternal distress, marital satisfaction and stressful life events) and within-time correlations, each of the observed strengths of the cross-lagged paths between responsive parenting and negative emotionality was similar, being also comparable to the average effect size (R= .06,p<.05) revealed in the Paulussen-Hoogeboom et al. (2007) meta-analysis of relevant studies. Additionally, these bidirectional relations between responsive parenting and negative emotionality aligned with prior studies showing reciprocity between parenting and negative emotionality in older children (Combs-Ronto et al., 2009; Larsson et al., 2007; Lee et al., 2012; Lengua, 2006; Lengua & Kovacs, 2005) and the significant impact of the child’s difficult temperament on parenting behaviours (e.g. Bridgett et al., 2009; Lipscomb et al., 2011). As hypothesized, a significant path from negative emotionality to responsive parenting was not found in boys. This result might have been partially derived from parents’tendency to approve boys’expressions of negative-dominant emotions (e.g. anger and contempt) to a greater extent than of girls, while the opposite pattern was observed with respect to negative-submissive emotions (e.g. shyness and fear), which was in line with traditional gender-stereotyped expectations (Chaplin et al., 2005; Garside & Klimes-Dougan, 2002; Gordon, 1983; Klein, 1984; Putnam et al., 2002). Regarding thefinding that the positive impact of responsive parenting on subsequent negative emotionality during infancy was found only among girls, possible developmental differences in gene expression between the male and female brain (Kang et al., 2011; Weickert et al., 2009), which are mostly pronounced during the prenatal and neonatal periods, might have contributed to engendering the result by giving rise to gender-related variations in susceptibility to environmental influences, in concert with parents’ gender-related socializing practices (Fausto-Sterling et al., 2012a, 2012b). Next, regarding the associations between parenting and child development, responsive parenting overall predicted higher levels of communication in infancy and toddlerhood as had been expected. These results are compatible with the well-establishedfindings of the positive impact of warm and responsive parenting on children’s subsequent language and social development among Western samples (e.g. Barnett et al., 2012; Bornstein et al., 2007; Deater-Deckard et al., 2001; Deiner & Kim, 2004; Landry et al., 2006; Tamis-LeMonda, Bornstein, & Bauwell, 2001), suggesting that physiological responses towards a nurturing environment featured by warmth and responsiveness tap a universal biological mechanism conducive to human adaptation and development. Turning to gender differences in the cross-lagged relations between responsive parenting and communication outcomes, it seems that boys are more sensitive to responsive parenting at least in terms of early language development, although their average scores on communication were consistently lower than those of girls: between W 2and W 3, responsive parenting predicted higher levels of subsequent 22 of 29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd communication ability only in boys, and not in girls. Thesefindings are inconsistent with the Barnett et al. (2012)finding that sensitive parenting at 12 months predicted receptive communication at 24 months among both boys and girls, with path coefficients being greater among girls than among boys. Prior studies have shown that children’s language ability is positively associated with the amount of parental speech directed to them (Hart & Risely, 1995; Weizman & Snow, 2001), and parents tend to provide more verbal stimulations to or engage in conversation with daughters than with sons (Clearfield & Nelson, 2006; Leaper, 2002; Leaper, Anderson, & Sanders, 1998). However, due to the absence of information regarding the amount and quality of linguistic input offered to the sample of boys and girls in the present study, along with chance of measurement error, thisfinding remains incomprehensible at this point. Thus, more research is needed to examine the interplay among sensitive parenting, linguistic input and the child’s language outcomes and the role of the child’s gender in the interplay during infancy and toddlerhood. Finally, it should be noted that the unidirectional path from parenting to negative emotionality found in this study does not indicate that the socialization process in the early years is solely determined by parents, with no contribution from the children. Although the temperamental emotional negativity did not predict the changes in parenting behaviours longitudinally (in the analysis of the entire sample), children’s early problem-solving ability (and personal-social outcome marginally) predicted higher levels of subsequent responsive parenting. The evidence showing children’s early socio-cognitive development contributes to higher responsive parenting corroborates reciprocity in parent–child relations, alongside a line of research unveiling bidirectional associations between the child’s temperament and parenting. In sum, the present studyfindings are in accordance with those of previous studies on European–American samples in three aspects: (i) the observed moderate stabilities in negative emotionality (~.2–.4) and responsive parenting (~.3–.45); (ii) the positive impact of responsive parenting on children’s subsequent socio-cognitive development; and (iii) the impact of children’s development on subsequent parenting behaviours. In contrast, afinding that deviated from the mainstreamfindings from Western samples was that children’s negative emotionality did not predict subsequent parenting in the overall sample. Hypothetically, the observed dominance of unidirectional paths from responsive parenting to negative emotionality may be because mothers’responses to the child are influenced by cultural child-caring beliefs, while children’s physiological responses to favourable environmental influences (responsive parenting) during the initial years of life concern universal or cross-culturally similar aspects of human adaptive behaviours. Additionally, the reciprocity between responsive parenting and negative emotionality observed only among girls, only in infancy, suggests that different patterns in parent–child interactions might appear as mothers’expectations towards children’s behaviours change depending on the children’s age and gender (as partially observed in the current study). Limitations Important limitations should be noted. First, the data used in the current analyses were gathered through parental report and, thus, were exposed to parents’ subjective evaluations and judgments. Additionally, since parents were a common source of both child temperament and their own parenting behaviours, these two Negative Emotionality, Parenting and Socio-cognitive Development23 of 29 Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. Dev.26: e1990 (2017) DOI: 10.1002/icd lines of information might not be potentially independent (Putnam et al., 2002). However, some studies revealed a strong objective component in parental ratings (Bates & McFayden-Ketchum, 2000) and convergence between parental ratings and observational assessments (Kochanska, Murray, & Coy, 1997). Indeed, parents’report of children’s developmental outcomes used in the current study showed extremely high accordance (97%) with the objective assessment by examiners. Next, this study could not take into account mothers’levels of self-regulation in the relationship between the child’s negative emotionality and parenting behaviours despite the recent evidence that parental self-regulation can be a moderating factor in temperament-parenting associations (Bridgett, Burt, Edwards, & Deater-Deckard, 2015). Additionally, this study heavily focused on attributes such as irritability, reactivity and unsoothability among many other temperamental traits under the overarching construct of negative emotionality. Considering cross-cultural studies revealing discrepancies in parental responses towards different negative emotionality traits, especially in terms of negative-submissive emotions (e.g. inhibition and shyness) (Chen et al., 1998; Chen, Yang, & Fu, 2012), further studies are needed to examine the associations among other negative emotionality characteristics, parenting and child development with samples from different cultures. Finally, in relation to the previous point, negative emotionality in the current study was a rather broad construct consisting of a few reactivity-related general traits, not measuring one specific dimension of difficult temperament (e.g. fear, anger and frustration), which might have obscured the reciprocity in the associations between negative emotionality and responsive parenting. CONCLUSION The main implication of thesefindings for parents, teachers and policy-makers is the importance of warm and responsive childcare during the initial years of life, especially during thefirst year. The observed positive impact of responsive parenting reinforces the significance of persistent provision of warm and responsive child caring, no matter how difficult children are, and the importance of establishing systematic channels to provide new parents and infant day care workers with relevant information and training. In particular, the observed greater impact of responsive parenting during infancy points to the need to provide pre-parent education for expectant parents to reduce unintentional harm that can occur due to parents’ignorance and inexperience during thefirst year. Additionally, the negative associations between stress-generating family factors and responsive parenting found in this study support the need for social policies and interventions that include comprehensive social services and parent education (e.g. the Comprehensive Conditional Cash Transfer; Fiszbein & Schady, 2009), in order to directly tackle stress-generating factors in at-risk families and make home environment developmentally conducive and nurturing. REFERENCES Ahl, R. E., Fausto-Sterling, A., García-Coll, C. & Seifer, R. (2013). Gender and discipline in 5-12-month-old infants: A longitudinal study.Infant Behavior and Development,36, 199–209. 24 of 29K. Cha Copyright © 2016 John Wiley & Sons, Ltd.Inf. Child. 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