Education, Faculty of
Educational and Counselling Psychology, and Special Education (ECPS), Department of
DSpace
UBCV
Maloney, Jacqueline
Doctor of Philosophy - PhD
University of British Columbia
Given the myriad short- and long-term outcomes linked to kindergarteners’ social and emotional competencies, it is important to investigate the factors that may contribute to their promotion. The present study aimed to do so by investigating the contributions of children’s self-regulation and the quality of relationship with their teachers to children’s social and emotional competence in a diverse sample of 139 children in eight urban schools in Western Canada. The specific aims of the present study were twofold: (1) to examine individual differences in social and emotional competencies between kindergarteners identified as having low executive function (EF) proficiency and their classmates with proficient EFs, and (2) to examine the joint contributions of children’s quality of student-teacher relationships and self-regulation to their social and emotional competencies via a series of multiple linear regression models. As hypothesized, we found that children identified as having low EF proficiency scored significantly lower on teacher-ratings of general social and emotional competence (SEC), empathy, peer acceptance, and prosocial behavior compared to their classmates with proficient EFs. Teachers also reported significantly less closeness and more conflict with students with low EFs, signifying lower student-teacher relationship quality with these students than the comparison group. In a subsequent series of linear regression models, the joint contributions of self-regulation and student-teacher relationship quality explained significant amounts of variance in children’s social and emotional competencies. Student-teacher relationship quality explained significantly more variance above and beyond children’s individual self-regulation skills with student-teacher closeness being the most important predictor in most models. Furthermore, significant conditional effects were observed in which student-teacher relationship quality moderated the association between EFs and prosocial behavior, and between behavioral self-regulation and iii empathy. Results were heterogeneous based on the method of measuring self-regulation and the specific social and competence examined. Results suggest that future research into the joint contributions of student-teacher relationship quality and self-regulation on kindergarteners’ social and emotional competence is warranted. Social and emotional learning programs designed to promote student-teacher relationship and self-regulation may be particularly effective at promoting social and emotional competencies, especially among kindergarten children with low EF proficiency.
STUDENT-TEACHER RELATIONSHIPS, SELF-REGULATION, AND SOCIAL AND EMOTIONAL COMPETENCIES IN KINDERGARTENERS by Jacqueline Maloney B.A., Simon Fraser University, 2004 M.A., The University of British Columbia, 2015 A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Human Development, Learning, and Culture) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2022 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Student-Teacher Relationships, Self-Regulation, and Social and Emotional Competencies in Kindergarteners submitted by Jacqueline Maloney in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Human Development, Learning, and Culture Examining Committee: Dr. Kimberly Schonert-Reichl, Professor, Educational and Counselling Psychology, and Special Education, UBC Supervisor Dr. Barbara Weber, Associate Professor, Educational and Counselling Psychology, and Special Education, UBC Supervisory Committee Member Dr. Eva Oberle, Assistant Professor, Health in Populations, UBC Supervisory Committee Member Dr. Kiley Hamlin, Professor, Psychology, UBC University Examiner Dr. Laurie Ford, Associate Professor, Educational and Counselling Psychology, and Special Education, UBC University Examiner iii Abstract Given the myriad short- and long-term outcomes linked to kindergarteners’ social and emotional competencies, it is important to investigate the factors that may contribute to their promotion. The present study aimed to do so by investigating the contributions of children’s self-regulation and the quality of relationship with their teachers to children’s social and emotional competence in a diverse sample of 139 children in eight urban schools in Western Canada. The specific aims of the present study were twofold: (1) to examine individual differences in social and emotional competencies between kindergarteners identified as having low executive function (EF) proficiency and their classmates with proficient EFs, and (2) to examine the joint contributions of children’s quality of student-teacher relationships and self-regulation to their social and emotional competencies via a series of multiple linear regression models. As hypothesized, we found that children identified as having low EF proficiency scored significantly lower on teacher-ratings of general social and emotional competence (SEC), empathy, peer acceptance, and prosocial behavior compared to their classmates with proficient EFs. Teachers also reported significantly less closeness and more conflict with students with low EFs, signifying lower student-teacher relationship quality with these students than the comparison group. In a subsequent series of linear regression models, the joint contributions of self-regulation and student-teacher relationship quality explained significant amounts of variance in children’s social and emotional competencies. Student-teacher relationship quality explained significantly more variance above and beyond children’s individual self-regulation skills with student-teacher closeness being the most important predictor in most models. Furthermore, significant conditional effects were observed in which student-teacher relationship quality moderated the association between EFs and prosocial behavior, and between behavioral self-regulation and iv empathy. Results were heterogeneous based on the method of measuring self-regulation and the specific social and competence examined. Results suggest that future research into the joint contributions of student-teacher relationship quality and self-regulation on kindergarteners’ social and emotional competence is warranted. Social and emotional learning programs designed to promote student-teacher relationship and self-regulation may be particularly effective at promoting social and emotional competencies, especially among kindergarten children with low EF proficiency. v Lay Summary Kindergarteners’ social-emotional skills are important for their well-being in childhood and across their lifetime. Theories of child development pinpoint two important areas that may influence children’s ability to learn social-emotional skills: Relationship quality with teachers, and their ability to willfully stop and change their behavior (self-regulation). This study found that children with low self-regulation also had lower quality of relationships with teachers and poorer social-emotional skills than their classmates. Children’s quality of student-teacher relationship and self-regulation together explained a large amount of the differences in kindergarteners’ social-emotional skills. The strength of the association between self-regulation and social-emotional skills depended on the relationship quality between teachers and children. Programs designed to promote social-emotional skills that also focus on building supportive relationships and self-regulation skills may be particularly effective, leading to short-term and long-term benefits for children. Such programs may be especially important for children who enter kindergarten with low self-regulation. vi Preface My original dissertation study was a randomized controlled trial entitled: Promoting Young Children's Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of The CALM Curriculum. The study was underway in schools when it was halted in March 2020 as a result of school closures due to COVID-19. The present study makes use of the pre-test data collected for the original study in December 2019/January 2020. I was the Co-Investigator of the study, working alongside my research supervisor, Dr. Kimberly Schonert-Reichl who oversaw the study as the Principal Investigator. A small research team made up of members of Dr. Schonert-Reichl’s Social and Emotional Learning Lab also assisted with the study, including Research Coordinator, Dr. Jenna Whitehead-Arruda, and three research assistants who served as second raters for the direct assessment task: Caitlin O’Brien, Amanda Denys, and Vanessa Scoon. The study received approval from the Behavioral Research Ethics Board of the University of British Columbia (approval certificate number: H18-03740) and the Vancouver School Board. The identification and research design, analysis of research data, and manuscript composition are the sole and original work of myself. Dr. Schonert-Reichl provided me with feedback on previous versions of the manuscript, which I incorporated into the final manuscription presented here. I also was responsible for recruitment of study participants, the informed consent process, training research assistants, and the administration of surveys and the direct assessment task to all participants. vii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ........................................................................................................................ vii List of Tables ................................................................................................................................ xi List of Figures ............................................................................................................................. xiii List of Abbreviations ................................................................................................................. xiv Acknowledgements ......................................................................................................................xv Dedication .................................................................................................................................. xvii Chapter 1: Introduction ................................................................................................................1 Chapter 2: Literature Review .......................................................................................................6 2.1 Social and Emotional Development in Early Childhood ................................................ 6 2.2 Defining and Measuring Student-Teacher Relationship Quality .................................. 11 2.3 Defining and Measuring Self-Regulation ..................................................................... 12 2.4 Defining and Measuring Empathy ................................................................................ 16 2.5 Defining and Measuring Prosocial Behavior ................................................................ 19 2.6 Student-Teacher Relationships and Social and Emotional Competencies ................... 20 2.7 Self-Regulation and Social and Emotional Competencies ........................................... 23 2.8 Joint Contributions of Student-Teacher Relationships Quality and Self-Regulation ... 24 2.9 Individual Differences in Self-Regulation in Early Childhood .................................... 28 2.6 Research Questions and Hypotheses ............................................................................ 32 2.6.1 Study Aim 1 Hypotheses ..................................................................................... 33 viii 2.6.2 Study Aim 2: Research Questions ....................................................................... 33 Chapter 3: Method .......................................................................................................................35 3.1 School Recruitment and Participants ............................................................................ 35 3.1.1 Child Participants .................................................................................................. 36 3.1.2 Teacher Participants .............................................................................................. 39 3.2 Procedure ...................................................................................................................... 39 3.2.1 Procedure for Recruiting Teacher Participants ..................................................... 39 3.2.2 Procedure for Recruiting Child Participants ......................................................... 39 3.2.3 Procedure for Administration of Teacher-Report Measures ................................. 42 3.2.4 Procedure for Administration of Child Direct Assessment of Self-Regulation .... 42 3.3 Measures ....................................................................................................................... 43 3.3.1 Direct Assessment of Child Self-Regulation ........................................................ 43 3.3.2 Teacher-Reported Measures of Children .............................................................. 46 3.3.3 Covariates ............................................................................................................. 50 Chapter 4: Results ........................................................................................................................52 4.1 Missing Data ................................................................................................................. 54 4.2 Preliminary Analysis ..................................................................................................... 55 4.3 Aim 1: Between Group Comparisons ........................................................................... 55 4.3.1 Aim 1: Analytic Plan ............................................................................................ 56 4.3.2 Aim 1: Results ...................................................................................................... 57 4.4 Aim 2: Linear Regression Models ................................................................................ 61 4.4.1 Aim 2: Analytic Plan ............................................................................................ 62 Figure 4.1 Moderation Model ............................................................................................... 69 ix 4.4.2 Aim 2: Results ...................................................................................................... 70 4.4.2.1 Checking Assumptions and Diagnostics for Regression Models ..................... 71 4.4.2.2 Correlations among Independent and Dependant Variables ............................. 72 4.4.2.3 SEC ................................................................................................................... 74 4.4.2.4 Empathy ............................................................................................................ 81 4.4.2.5 Prosocial Behavior with Peers .......................................................................... 90 4.5 Results Summary .......................................................................................................... 99 Chapter 5: Discussion ................................................................................................................101 5.1 Similarity of Results to Extant Research .................................................................... 109 5.2 Strengths and Limitations ........................................................................................... 116 5.2.1 Generalizability ................................................................................................... 116 5.2.2 Children’s Research Rights and Informed Consent ............................................ 117 5.2.3 Measurement Strengths and Limitations ............................................................ 118 5.2.4 Strength and Limitations of Study Design .......................................................... 120 5.3 Future Directions ........................................................................................................ 123 5.4 Conclusion .................................................................................................................. 127 References ...................................................................................................................................129 Appendix A: Initial Contact Letter for Principals ..................................................................167 Appendix B: Flyer for Prospective Teacher Participants ......................................................168 Appendix C: Introductory Meeting with Perspective Teacher Participants .......................169 Appendix D: Permission Slip Visit Protocol ............................................................................173 Appendix E: Teacher Consent Form .......................................................................................176 Appendix F: Parent/Guardian Consent Form ........................................................................182 x Appendix G: Cover Letter for Teacher Surveys .....................................................................191 Appendix H: Teacher Demographic Survey ...........................................................................192 Appendix I: Children Demographics .......................................................................................194 Appendix J: Teacher-Ratings of Children’s Social and Emotional Competencies .............196 Appendix K: Instructions for Behavior Rating Inventory of Executive Function – Preschool......................................................................................................................................................199 Appendix L: Head, Toes, Knees, Shoulders – Extended Task Assent Script .......................200 Appendix M: Graphs of Conditional Effects of STR Quality ...............................................201 Appendix N: J-N Tests for Regions of Significant for Conditional Effects ..........................210 Appendix O: Effect Sizes for Moderation Models ..................................................................213 Appendix P: Descriptive Statistics by Gender ........................................................................214 Appendix Q: Descriptive Statistics by EF Group ...................................................................215 Appendix R: Correlations with BRIEF-P Subscales ..............................................................216 xi List of Tables Table 2.1 Social and Emotional Competencies in Early Childhood ............................................... 8 Table 3.1 Child Participants’ First Languages .............................................................................. 38 Table 4.1 Descriptive Statistics and Reliability for Variables of Interest ..................................... 58 Table 4.2 Independent Samples t-Test Statistics for Equality of Means ...................................... 60 Table 4.3 Effect Sizes for Between-Group Mean Differences ..................................................... 61 Table. 4.4 Hierarchical Linear Regression Models ...................................................................... 65 Table 4.5 Correlations Among Variables ..................................................................................... 74 Table 4.6 Regressing BRIEF-P and STR Quality on SEC ........................................................... 76 Table 4.7 Model Fit and Effect Size: BRIEF-P + STR Quality on SEC ...................................... 77 Table 4.8 Predictor Importance: BRIEF-P + STR Quality on SEC .............................................. 77 Table 4.9 Regressing HTKS-E and STR Quality on SEC ............................................................ 79 Table 4.10 Model Fit and Effect Size: HTKS-E + STR Quality on SEC ..................................... 80 Table 4.11 Predictor Importance: HTKS-E + STR Quality on SEC ............................................ 80 Table 4.12 Regressing BRIEF-P + STR Quality on Empathy ...................................................... 83 Table 4.13 Model Fit and Effect Sizes: BRIEF-P + STR Quality on Empathy ........................... 84 Table 4.14 Predictor Importance: BRIEF-P + STR Quality on Empathy .................................... 84 Table 4.15 Regressing HTKS-E and STR Quality on Empathy ................................................... 86 Table 4.16 Model Fit and Effect Size: HTKS-E + STR Quality on Empathy .............................. 87 Table 4.17 Predictor Importance: HTKS-E + STR Quality on Empathy ..................................... 87 Table 4.18 Regressing BRIEF-P and STR Quality on Prosocial Behavior .................................. 91 Table 4.19 Model Fit and Effect Size: BRIEF-P + STR Quality on Prosocial Behavior ............. 92 xii Table 4.20 Predictor Importance: BRIEF-P + STR Quality on Prosocial Behavior .................... 92 Table 4.21 Regressing HTKS-E and STR Quality on Prosocial Behavior ................................... 97 Table 4.22 Model Fit and Effect Size: HTKS-E + STR Quality on Prosocial Behavior .............. 98 Table 4.23 Predictor Importance: HTKS-E+ STR Quality on Prosocial Behavior ...................... 98 Table N.1 Conditional Effects of Conflict on Correlation Between Behavioral Self-Regulation and Empathy ............................................................................................................................... 210 Table N.2 Conditional Effects of Closeness on Correlation Between EFs and Prosocial Behavior with Peers .................................................................................................................................... 211 Table N.3 Conditional Effects of Conflict on Correlation Between EFs and Prosocial Behavior with Peers .................................................................................................................................... 212 Table O.1 Effect Sizes for Moderation Models .......................................................................... 213 Table P.1 Variable Means by Gender ......................................................................................... 214 Table Q.1 Variable Means by EF Group .................................................................................... 215 Table R.1 Correlations with BRIEF-P Subscales ....................................................................... 216 xiii List of Figures Figure 4.1 Moderation Model ....................................................................................................... 69 Figure 4.2 Conditional Effects of Conflict on Correlation of HTKS-E and Empathy ................. 89 Figure 4.3 Conditional Effect of Closeness on Correlation of EFs and Prosociality ................... 94 Figure 4.4 Conditional Effect of Closeness on Correlation of EFs and Prosociality ................... 95 Figure M.1 Conditional Effects of Closeness on Correlation of EFs and Empathy ................... 201 Figure M.2 Conditional Effects of Conflict on Correlation of EFs and Empathy ...................... 202 Figure M.3 Conditional Effects of Closeness on Correlation of EFs and SEC .......................... 203 Figure M.4 Conditional Effects of Conflict on Correlation of EFs and SEC ............................. 204 Figure M.5 Conditional Effects of Closeness on Correlation of HTKS-E and SEC .................. 205 Figure M.6 Conditional Effects of Conflict on the Correlation of HTKS-E and SEC ............... 206 Figure M.7 Conditional Effects of Closeness on Correlation of HTKS-E and Prosociality ...... 207 Figure M.8 Conditional Effects of Conflict on Correlation of HTKS-E and Prosociality ......... 208 xiv List of Abbreviations BRIEF-P = Behavior Rating Inventory of Executive Functions – Preschool Version EFs = executive functions HTKS-E = Head, Toes, Knees, Shoulder – Extended task of self-regulation SEC = composite variable representing general social and emotional competence SEL = social and emotional learning STR = student-teacher relationships xv Acknowledgements I honour and thank the peoples of the xʷməθkʷəy̓əm (Musqueam), skwxwú7mesh (Squamish), and səlilwətaɬ (Tsleil-Waututh) Nations on whose traditional lands this research was conducted. They and their ancestors have sustained these lands for millennia, since time immemorial. Generations of Indigenous families have been grievously impacted by the legacy of Indian Residential and Day Schools run by the Canadian government and churches. It is my hope that this research, and research like it, will contribute to truth and reconciliation by raising awareness of the important influence of school experiences on children’s lifelong well-being and, potentially, for the generations that follow. I offer my gratitude to my research committee, Dr. Kimberly Schonert-Reichl, Dr. Barbara Weber, and Dr. Eva Oberle. Not only have I benefited from their expertise on respectfully conducting research with children, but I have also been inspired by their example that it is possible to be a Researcher and a dedicated parent. I could have not wished for a more exceptional committee. I owe my particular thanks to my Research Supervisor, Dr. Kimberly Schonert-Reichl, who has inspired me throughout every step of this journey. I offer my sincere appreciation for her guidance, feedback, and encouragement while reworking my dissertation after my original study was halted due to COVID-19 school closures. The challenge felt insurmountable at times, yet Dr. Schonert-Reichl’s support and compassionate tenacity helped see me through. xvi I thank the members of Dr. Schonert-Reichl’s Social and Emotional Learning Lab who have been my family during my studies at UBC. I have learned so much from each of you. I offer my special thanks to Dr. Jenna Whitehead-Arruda, who served as Research Coordinator for the original study, and to Caitlin O’Brien, Amanda Denys, and Vanessa Scoon, who volunteered as Research Assistants for school visits. Finally, I thank my amazing family who have been patient and reassuring throughout this process. In particular, I thank my husband, Brice, whose support has been integral to completing my degree. It was not easy, but we did it! xvii Dedication To my son, Theo, and my nephews. You are the inspiration for this work. To all children: You have the right to a positive school experience that supports your well-being and provides the foundation for a rewarding life throughout childhood and beyond. To the caring teachers dedicated to supporting children, even in the face of great challenges. And, to my Mom, who got me off to a great start. 1 Chapter 1: Introduction Social and emotional development in the early years provides a critical foundation for children’s well-being, learning, and day-to-day interactions, not only for early childhood, but also for years to come. Many children experience a rapid development in social and emotional competencies during early childhood, often described as ages three to six (Bierman et al., 2018). This developmental growth in social and emotional competencies is highly influenced by children’s environmental input (Greenberg et al., 2017), and especially their relationships with caregivers (e.g., parents, guardians, teachers; Ferreira et al., 2016; Mahoney et al., 2020). In the short-term, social and emotional competencies in early childhood are linked to school readiness, enjoyment of school, quality of relationships with peers and teachers, and learning (Blewitt et al., 2018; Harrington et al., 2020; Hunter et al., 2018; Valiente et al., 2020; Wenz-Gross et al., 2018). In the long term, social and emotional competencies predict myriad important life outcomes affecting physical, social, and mental health and well-being (Jones et al., 2015; Sege & Harper Browne, 2017). Social and emotional competencies play an especially important role as children transition to formal schooling. Children’s experience in kindergarten is of particular importance because it sets the stage for later school experiences. Children who fare well in kindergarten tend to have better school experiences and better academic performance in later school years than children who do not (McClelland et al., 2006; Pelletier & Corter, 2019; West, 2017). Transitional periods, such as starting kindergarten, can be especially challenging for children because they are required to draw on previously learned skills and apply them to novel situations and tasks (Denham & Weissberg, 2004). Children encounter myriad new challenges and expectations for their learning and behavior as they transition to kindergarten. Children must feel secure enough 2 to separate from primary caregivers to make a smooth transition into the school day and have the social skills to connect with new people (Denham et al., 2009). They also have to navigate behavior, interpret emotions, and regulate emotional arousal within the context of social interactions (Denham, Bassett, Way, et al., 2012). Once entering formal schooling, children are often expected to be able to stop, think, and choose prosocial actions (McClelland & Cameron, 2019). Success in kindergarten requires that children be able to focus, maintain concentration, and shift their attention to salient information as required (Blair & Raver, 2015). Not all children arrive to kindergarten with the social and emotional competencies necessary to meet these everyday demands. Indeed, over the past 15 years in the Province of British Columbia, there has been a steady rise in children entering kindergarten without the necessary social and emotional competencies to thrive (Human Early Learning Partnership, 2019). Children with proficient social and emotional competencies have an advantage in academic contexts, however. They have greater acceptance from teachers and peers, receive more positive feedback and instruction from teachers, and participate more in the classroom (Denham & Brown, 2010). In sum, children who enter kindergarten with more proficient social and emotional competencies appear to have a head start compared to other children. Thus, it is important to have a clearer picture of factors that are related to social and emotional competencies in early childhood to better understand how to promote healthy social and emotional development and a positive school experience for all kindergarteners. Doing so may contribute to a cascade of positive outcomes throughout children’s school years into adolescence and adulthood, even more so than academic achievement (Sorensen et al., 2016). Early childhood researchers have identified two factors that are strongly related to kindergarteners’ social and emotional competencies: quality of student-teacher relationships 3 (Longobardi et al., 2021) and self-regulation skills (Rademacher & Koglin, 2019). Supportive and caring student-teacher relationships and self-regulation are foundational for healthy social and emotional development, school engagement, and academic performance (Konishi & Wong, 2018; Robson et al., 2020). Of particular importance is that quality of relationships and self-regulation skills are malleable. Interventions studies have demonstrated that it is possible to improve the quality of student-teacher relationships by training teachers (Kincade et al., 2020). Similarly, self-regulation skills can be improved with the right environmental supports and opportunities for practice (Blair et al., 2018; Takacs & Kassai, 2019). Gaps and Limitations in the Field There exists an abundance of research that indicates that young children with low self-regulation proficiency are at risk for developing emotional and behavioral disorders in the classroom (e.g., Brocki et al., 2019; Nucifora & Walker, 2021). There is a paucity of research, however, that specifically examines individual differences in social and emotional competence between young children with low self-regulation proficiency and their peers with proficient self-regulation skills. Given the importance of social and emotional skills in early childhood for prevention and early intervention of emotional and behavioral disorders (Bierman & Sanders, 2021), it is advantageous to understand how social and emotional competencies may differ in kindergarten children with low self-regulation proficiencies compared to their more proficient peers. Doing so, may help identify children who would benefit from targeted support in kindergarten. Thus, the first aim of the present study was to compare social and emotional competencies between children who met a clinical cut off for executive function deficits and their classmates with proficient executive functions, a foundational component of self-regulation, in a public-school sample of kindergarteners. 4 A second limitation in the field is the absence of studies that have examined the joint contributions of self-regulation and student-teacher relationship quality on young children’s social and emotional competence. Research has primarily focused on examining self-regulation or student-teacher relationship quality as individual predictors of social and emotional competence (for reviews see Rademacher & Koglin, 2019; Wang et al., 2020). Theories of social and emotional development in early childhood posit, however, that children’s self-regulation skills and their relationship quality with teachers work together to form a foundation for early social and emotional development (Denham & Brown, 2010; Lopez et al., 2021; Valiente et al., 2020). Indeed, researchers have observed that relation of self-regulation skills to academic performance and to school engagement is conditional upon the quality of student-teacher relationship in kindergarteners, with positive student-teacher relationships serving as a protective factor for students with low proficiency in self-regulation skills (Graziano et al., 2015; Liew et al., 2010). It remains to be seen, however, whether this same pattern is evident in relation to kindergarteners’ social and emotional competencies. Hence, the second aim of the present study was to investigate the joint contribution of quality of student-teacher relationships and self-regulation in relation to kindergarteners’ social and emotional competencies via a series of linear regression models. Addressing these two limitations provides additional insights to the field on how children with low self-regulation proficiency may be at a disadvantage in the kindergarten classroom compared to their peers with better self-regulation proficiency in social and emotional competencies, which play an important role in positive and successful kindergarten experiences (Harrington, 2020; Welsh et al., 2020). Moreover, the findings shed led on how the quality of relationships with teachers may contribute additional influence over and above self-regulation 5 proficiency to promote or hinder social and emotional competence. Together these observations can be applied to inform teaching practices and interventions designed to promote social and emotional learning (SEL) in early childhood. 6 Chapter 2: Literature Review This chapter reviews literature from several areas relevant to the present study. It begins with a general overview of social and emotional development in early childhood. Next, definitions for each of the variables of interest are put forth and approaches to their measurement discussed. Subsequently, the literature examining the associations between student-teacher relationship quality and social and emotional competencies in early childhood is summarized. This includes an examination of research documenting the links between student-teacher relationships and children’s self-regulation, and specifically, children’s executive functions, (EFs), which are posited to be a foundational component of self-regulation (McClelland et al., 2014). Subsequently, studies on the relations between self-regulation and other social and emotional competencies are reviewed. Finally, research examining individual differences in the development of self-regulation throughout early childhood is summarized. The chapter ends with an overview of the research questions guiding the present study. 2.1 Social and Emotional Development in Early Childhood Individuals’ social and emotional development is linked to health and social outcomes beginning in infancy and extending across the lifespan (Bierman et al. 2018). Social and emotional development relies on complex interactions among individual skills and traits and environmental experience (Lopez et al., 2021). During early childhood, the foundations of lifelong social and emotional development are set through forming supportive and secure relationships with caregivers, experiencing and expressing a full range of emotions, and developing self-regulation skills to purposefully regulate one’s attention, emotions, and behavior (Immordino-Yang et al., 2019). Social and emotional competencies play an especially important role in school readiness (Harrington et al., 2020; Welsh et al., 2020). 7 Denham and Brown (2010) outlined key developmental tasks in the early years that are essential for children’s social and emotional development in their prism model of social and emotional development, which adapted the Collaborative for Social, Emotional, and Academic Learning (CASEL) framework of SEL for early childhood (see Mahoney et al., 2020 for a description of the CASEL framework). Foundational to the development of social and emotional competencies is children’s ability to self-regulate emotional arousal in social interactions (Denham et al., 2014). Self-regulation skills are put to test in preschool and kindergarten contexts in which children are learning how to navigate new relationships with teachers and peers successfully (Blair & Diamond, 2008). In the prism model, social and emotional development depends on supportive caregiving to facilitate children’s self-regulation (Denham & Brown, 2010). When children experience supportive relationships with their parents, teachers, and peers, they are able to enlist self-regulation skills to facilitate their learning of other social and emotional skills (Denham & Brown, 2010). As a result, their social and emotional competencies are theorized to improve. Better social and emotional competencies are thought to lead to more positive social interactions and acceptance by peers (Denham et al., 2014; Denham & Brown, 2010). Table 2.1 describes core social and emotional competencies and related skills that develop during early childhood as outlined in Denham and Brown’s (2010) prism model of SEL. 8 Table 2.1 Social and Emotional Competencies in Early Childhood Core Competencies Skills Development for Early Childhood Self-Awareness Recognizing and naming emotions Recognizing interests, values, and strengths Self-Regulation Monitoring and regulating emotions by employing self-soothing techniques or seeking out help to regulate (e.g., engaging in a calming strategy, asking for a hug) Expressing emotions in adaptive ways that do not harm others Executive functions Delayed gratification Self control Social Awareness Joint attention Perspective-taking Empathy Interpreting the actions and emotions of others Appreciating others’ similarities and differences Relationship Skills Initiating and maintaining social interactions Prosocial action Listening Cooperating Taking turns Asking for help Conflict resolution 9 Responsible Decision Making Analyzing and interpreting social situations Understanding consequences Problem-solving skills Following agreements and rules Note. Table 2.1 depicts core social and emotional competencies required to successfully navigate social situations in early childhood, such as at home, school, or the playground. Although listed separately, the core competencies are interrelated with some skills providing a necessary foundation for others. For example, self-regulation is posited to be foundational for learning new social and emotional skills (Denham & Brown, 2010). Similarly, empathy is a motivator for prosocial action (Decety et al., 2017; Spinrad & Eisenberg, 2017). These competencies develop across the lifespan (Mahoney et al, 2020). 10 Children with more proficient social and emotional competencies tend to have a smoother transition to kindergarten, more rewarding social relationships at school, better academic performance, and more enjoyment at school (Jones et al., 2015). Research suggests that proficient social and emotional competencies may also serve as protective factors against serious issues throughout the trajectory of one’s life, such as mental illness (Weare & Nind, 2011), bullying and victimization (Divecha & Brackett, 2019), high school graduation (Jones et al., 2015), and criminality (Sorensen et al., 2016). For example, children with proficient social and emotional competencies as rated by teachers in kindergarten reported having significantly higher levels of well-being and lower levels of sadness and worries in Grade 4 compared to peers with less proficient social and emotional competencies (Thomson et al., 2021). Generally, children go through a period of rapid developmental change in social and emotional competencies as they enter the preschool years and the first years of traditional schooling, approximately ages three to seven (Blair & Raver, 2015; Denham, Bassett, Way, et al., 2012). During this time, providing explicit environmental supports that nurture social and emotional development becomes particularly important (Bierman et al., 2018). For example, warm and supportive caregiving has been found to be fundamental to social and emotional development in infancy and early childhood (Harrington et al., 2020; Lopez et al., 2021). Caregivers also play a critical role in the development of children’s self-regulation skills in the early years by helping them co-regulate when they are upset or distressed by soothing children, helping them recognize and describe their emotions, and modelling strategies for self-regulation (Housman, 2017). 11 The recognition that social and emotional competencies play a crucial role across multiple contextual domains has contributed to a long-standing interest among researchers and practitioners in SEL to better understand how children acquire new social and emotional skills. There is clear evidence that SEL programs promote social and emotional development in early childhood and beyond (Blewitt et al., 2018; Taylor et al., 2017). Empathy and prosocial behavior have been shown to be especially important predictors of children’s healthy social and emotional development and success at school and beyond (Jones et al., 2015; Spinrad & Eisenberg, 2017). Developmental scientists posit that the development of prosocial behavior and empathy are influenced by children’s self-regulation and supportive caregiving (Spinrad & Gal, 2018). In the following section, a discussion of definitions and measurement for each of these concepts is put forth. 2.2 Defining and Measuring Student-Teacher Relationship Quality Drawing from research on attachment theory (Ainsworth et al., 1978; Bowlby, 1977; Sroufe, 2005), research over the last three decades has demonstrated that, similar to parents, teachers can serve as attachment figures for children (Zee et al., 2020). Closeness and conflict with teachers have been shown to be particularly important predictors of outcomes for young children (for reviews see Pianta, 2016; Roorda et al., 2011). Closeness describes a secure, warm, and affectionate relationship with a student, from the teacher’s perspective, with open communication between the two (Pianta, 1999). Conflict describes a relationship in which the teacher struggles with the student, perceives the student as angry or confrontational, and feels emotionally drained from their interactions (Pianta, 1999). Closeness and conflict are conceptually aligned with secure attachment and insecure-avoidant attachment styles respectively (Zee et al., 2020). Teachers’ responsiveness, sensitivity to children’s cues, and 12 warm, caring interactions with children facilitate a sense of closeness with their students whereas harsh and punitive interactions facilitate conflict with students (Ansari & Pianta, 2018). Research suggests that dyadic relationships are particularly influential on social and emotional development in early childhood, even more so than overall classroom climate (Rucinski, et al., 2018; Vandenbroucke et al., 2018). Thus, the focus of the present study is on closeness and conflict in student-teacher dyads. 2.3 Defining and Measuring Self-Regulation Self-regulation has been described and defined in multiple ways, each emphasizing different aspects of the multidimensional concept (see Nigg, 2017 for a discussion). Generally, the term self-regulation encompasses a variety of related concepts, including executive functions (EFs; Diamond, 2016), effortful control (Rothbart et al., 2011), self-control, (Duckworth & Kern, 2011), behavioral self-regulation (McClelland & Cameron, 2011), and emotion regulation (Blair et al., 2004), to name a few. Indeed, in their review of the literature, Burman and colleagues (2015) identified 88 concepts related to self-regulation. Blair and Diamond (2008), integrate the multitude of perspectives in their oft-cited definition of self-regulation: Self-regulation refers to the primarily volitional cognitive and behavioral processes through which an individual maintains levels of emotional, motivational, and cognitive arousal that are conducive to positive adjustment and adaptation, as reflected in positive social relationships, productivity, achievement, and a positive sense of self (p. 900). Current theories of self-regulation support this multidimensional conceptualization, positing a bidirectional and reciprocal interaction between cognitive and emotion systems (Nigg, 2017; Ursache et al., 2012). Self-regulation likely involves the interaction of cognitive, top-down regulatory responses (i.e., cool self-regulation skills or cool EFs), which are largely volitional, 13 and bottom-up physiological and emotional regulatory responses (i.e., hot self-regulation skills or hot EFs), which tend to be more automatic (Ursache et al, 2012; Zelazo, 2020). The top-down, cognitive components of self-regulation (i.e., EFs) are especially important predictors for school readiness and learning (Malachini et al., 2018; Raver & Blair, 2016; Zelazo, 2020). Self-regulation can be influenced by external factors, such as co-regulation with others (Housman et al., 2018; Nigg, 2017). EFs (described below), are theorized to play a fundamental role in all volitional dimensions of self-regulation, including behavior regulation and emotion regulation (Diamond, 2013; McClelland et al., 2014; Zelazo et al., 2016). These cognitive components of self-regulation have been shown to predict other important outcomes throughout childhood, adolescence, and adulthood (Blair & Raver, 2015). For example, a recent meta-analysis of 150 studies of cognitive aspects of self-regulation, broadly defined as “the ability to inhibit dominant impulses to modify thought, feelings, and behavior,” examined associations and outcomes in more than 200,000 people (Robson et al., 2020, p.13). They found that children who had better self-regulation skills at age four demonstrated fewer internalizing and externalizing behaviors at age eight. These children also demonstrated better social competence and academic performance and were less likely to experience peer victimization in elementary school (Robson et al., 2020). Moreover, researchers found that benefits related to cognitive self-regulation skills in childhood extended into adulthood. Higher self-regulation in early childhood was associated with lower incidences of mental or physical health symptoms, unemployment, and criminal behavior at age 38 (Robson et al., 2020). These findings echo those observed in large cohort studies that have examined self-control in early childhood and its relations across more than thirty years of development (see Moffit et al., 2011). 14 Executive Functions. Perhaps the most commonly researched area of cognitive self-regulation falls under the term executive functions (EFs; Diamond & Ling, 2016). Executive functions (EFs) refer to a family of higher cognitive skills that enable individuals to volitionally inhibit automatic reactions to stimuli, hold relevant information in the working memory, and flexibly shift attention from one focus to another (Diamond, 2016; Zelazo et al., 2016). EFs are fundamental for focusing attention, exercising discipline and self-control, problem solving, planning, reasoning, and managing emotions (Raver & Blair, 2016). Theorists have identified two core components of EFs: Working memory and inhibitory control (Diamond, 2016). Working memory is involved whenever individuals are engaged in tasks that require them to hold information in their mind, update the information as necessary, and manipulate or work with the information in some way, for example applying rules to a game (Willoughby et al., 2019). Inhibitory control (also referred to as cognitive control, executive control, and impulse control in different literatures) involves volitionally and purposefully focusing one’s attention and suppressing prepotent behavioral responses in adaptive ways according to the situation at hand (Diamond, 2013). This is the neurocognitive activity theorized to underlie self-control, allowing people to stay on task, resist temptation, delay gratification, and wait their turn (Duckworth & Kern, 2011). Working memory and inhibitory control are theorized to provide the foundation for cognitive flexibility: The ability to switch tasks as needed and be able to consider different perspectives related to a situation (Diamond, 2013). Together these foundational EFs are theorized to set the stage for higher-level EFs, such as reasoning, planning, problem-solving, and metacognition (Diamond, 2016). EFs begin to develop in infancy with a rapid acceleration of development generally taking place between the ages of three to six (Carlson & Wang, 2009). Their development is 15 profoundly influenced by early experiences and caregiving, both positive and negative (Zelazo et al., 2017). Exposure to stress, trauma, and long-term adversity, such as poverty and discrimination, can negatively impact the development of EFs (Blair & Raver, 2012). Deficits in EFs have been noted in children diagnosed with emotional and behavioral differences, such as attention deficit and hyperactivity, autism, and a variety of learning differences that can make learning in typical educational settings challenging (Zelazo, 2020). When children are in the care of attuned and supportive adults who provide appropriate levels of support and challenge, however, development of EFs flourish (Raver & Blair, 2016). Proficiency in EFs can be scaffolded by caregivers when they explicitly teach self-regulation strategies and provide opportunities for repeated practice through engaging activities that offer progressive and continuous challenges (Diamond & Lee, 2011; Takacs & Kassai, 2019). Behavioral Self-Regulation: EFs in Action. In the field of education, there has been a call for the use of global assessments of self-regulation that allow researchers to investigate how the different underlying cognitive components of self-regulation are applied in action (Liew et al., 2018). That is, instead of trying to isolate separate EF proficiencies using tasks that may not translate into behavior (e.g., computer-based tasks), researchers are interested in a more ecologically valid measure of EFs that assess children’s ability to apply EFs to self-regulation tasks that are similar to the everyday activities in which they engage (McClelland & Cameron, 2011). This is referred to in the literature as behavioral self-regulation (e.g., Cameron Ponitz et al., 2008; Howard & Vasseleu, 2020; Jacob et al., 2019). Notably, unlike EF measures, measurements of behavioral self-regulation do not aim to differentiate between different aspects of self-regulation; rather they are a global measurement of children’s ability self-regulate 16 behavior by utilizing multiple dimensions of self-regulation together to achieve a learning goald (McClelland et al., 2014). In the present study, we included both teacher-ratings of EFs (Behavior Rating Inventory of EFs – BRIEF; Gioia et al., 2003) as well a direct assessment of behavioral self-regulation (Head, Toes, Knees, and Shoulder task; McClelland et al., 2014. (See Measures section below for more details). These measures were chosen because they were designed to tap into different dimensions of the multidimensional self-regulation construct in classroom settings. Having two different methods for measuring self-regulation also provided insight to the influence of shared measurement variance, both common and uncommon, on observed outcomes (see Spector et al., 2019 for a discussion). 2.4 Defining and Measuring Empathy As with most complex concepts, empathy has been defined in myriad ways, and there continues to be much discussion on how to define, operationalize, and measure the multidimensional concept of empathy and empathy-related responses, such as sympathy and personal distress (see Schonert-Reichl, 2011; Zhou et al., 2019 for in-depth discussions on defining and measuring of empathy). For the purposes of the present study, we define empathy as one’s ability to recognize another person’s emotional state and feel similar emotions (Zhou et al., 2019). Empathy, therefore, involves both and cognitive (emotion identification) and affective components (affect sharing; Coll et al., 2017). Children’s capacity for empathy varies greatly in early childhood, even among children of the same chronological age (Eisenberg et al., 2014). In research conducted in elementary schools, empathy can be measured via teacher ratings on empathy-related behaviors observed in children, sometimes referred to as empathy-related responding (Spinrad & Eisenberg, 2017). Empathy-related responding is a global 17 construct that includes both cognitive and affective dimensions of empathy, which may also involve sympathy – a feeling of concern for others that is not necessarily accompanied by experiencing a similar emotion to that person (Malti et al., 2016). Teacher reports of empathy-related responding are particularly useful in research with young children in which self-reported empathy is less reliable; teacher reports are also less likely to be biased by social desirability than parent reports of their children’s empathy (Zhou et al., 2019). Moreover, teachers have the opportunity to observe children’s empathy-related responding in context over periods of time, and thus may have better ecological validity than empathy-related responses elicited through experimental tasks (Zhou et al., 2019). Thus, the focus of the present study is on children’s empathy-related responding as observed by teachers, henceforth referred to simply as empathy. In general, atypical development of empathy in children has been linked to behavioral issues, whereas improvements in empathy are related to increased prosocial action (see Malti et al., 2016 for a review). Experimental studies have demonstrated that young children’s empathic responding positively predicted their prosocial behavior as assessed via the number of stickers children gave away in a dictator game (Decety et al., 2017; Williams et al., 2014). Moreover, higher teacher-ratings of empathy have been found to be associated with lower levels of bullying behavior in elementary school children (Elliot et al., 2019). Extant research suggests that self-regulation skills may promote empathy-related responding in children (Eisenberg & Eggum, 2009). Self-regulation skills facilitate children’s ability to avoid being overwhelmed by emotional responses in the face of challenging situations so that they can respond to others with empathy rather than stress-induced reactions, such as aggressive “fight” reactions or avoidance “flee” reactions due to feelings of personal distress (Yan et al., 2020). For example, in an experimental study conducted with children ages 9 to 11 in 18 Germany, children responded to interview questions about stimulus vignettes describing a child who experienced hardship, such as losing lunch money, or getting a flat tire while biking (Hein et al., 2018). After responding to questions designed to assess children’s empathy and prosocial tendencies to the first vignette, they were guided to take part in an imagery task that induced negative affect by asking them to think and write about a time in their life when they experienced sadness. Then, they were asked to respond to questions about a second stimulus vignette. Children who scored higher on a measure of emotion regulation (a dimension of self-regulation) were more likely to respond with empathy and prosocial tendencies to stimulus vignettes after the sadness-inducing activity than children with lower scores on the measure of emotion regulation (Hein et al., 2018). These findings suggest that children with more self-regulation strategies to apply in emotion-inducing situations are better able to relate to others experiencing hardship with empathy than children without self-regulation strategies. Supportive caregiving also promotes empathy (Kim & Konchanska, 2017; Spinrad & Gal, 2018). For instance, in a longitudinal study conducted in the USA, children who demonstrated secure attachments to caregivers at 15 months demonstrated greater empathy at 25–52 months when their caregiver feigned distress in a play scenario than children with insecure attachment (Kim & Konchanska, 2017). Relationships with teachers that are high in closeness and low in conflict are also linked to greater empathy in children (Wilkinson & Bartoli, 2021). Despite empirical evidence that self-regulation and quality of relationships play an important role in empathy, to our knowledge no studies have examined the joint associations of self-regulation and student-teacher relationship quality to young children’s empathy. 19 2.5 Defining and Measuring Prosocial Behavior Prosocial behavior refers to voluntary, self-directed behavior aimed at benefiting others, such as kindness, cooperating, sharing, helping, and comforting others (Spinrad & Gal, 2018). Relationship quality with parents and self-regulation appear to jointly influence the development of prosocial behavior (Eisenberg et al., 2017). Theoretical models posit that supportive relationships facilitate the development of children’s ability to self-regulate in emotionally-charged situations, which in turn allows children to respond prosocially rather than with reactive emotions, such as anger or frustration (Eisenberg, 2010). For example, a large longitudinal study conducted with children from ages 2 to 7 found that the relation between warm, supportive caregiving in toddlerhood was directly related to children’s self-regulation, as reported by parents, which in turn predicted teacher ratings of prosocial behavior when children entered school (Williams & Berthelsen, 2017). Another study found a link between parent-child relationship quality and student-teacher relationship quality in relation to children’s prosocial development (Ferreira et al., 2016). The quality of preschool children’s relationship their teacher was significantly and positively related to children’s prosocial behavior, as rated by teacher and parents, but no direct association between preschooler’s relationship quality with their mother and prosocial behavior was found (Ferreira et al., 2016). There was an indirect relationship, however, between quality of relationship with mothers and their children’s prosocial behavior that was mediated by children’s relationship with teachers. That is, children’s relationship quality with mothers predicted their relationship quality with their teacher, which in turn predicted children’s prosocial behavior. These findings suggest that children’s relationships with their mothers may influence their relationships with their teachers, yet it is the relationships with teachers that appear to directly influence prosocial behavior. Much less is known about the joint 20 associations between self-regulation and quality of student-teacher relationships remain, however. Teacher ratings of children’s prosocial behaviors have been shown to be linked to important short- and long-term outcomes for young children (e.g., Shi et al., 2021; Sorensen et al., 2016). For example, Jones and colleagues (2015) demonstrated that kindergarten teachers’ ratings of children’s prosocial behavior predicted the number of years children required special education services throughout elementary school and high school, the number of years repeated throughout elementary and high school, whether children graduated from high school on time, and whether individuals completed a college degree and obtained full time work as young adults. Teacher reports of warmth and conflict in early childhood have also been shown to predict subsequent teacher-ratings of prosocial behavior throughout elementary and high school in a 12-year longitudinal study (Shi et al., 2021). Thus, the present study examined teacher ratings of children’s prosocial behavior with peers. 2.6 Student-Teacher Relationships and Social and Emotional Competencies Interactions between teachers and students are among the most important influences on early childhood development and learning, especially as children begin to spend longer hours in school settings (Pianta et al., 2016). Decades of research provide strong evidence that quality of relationship with teachers can either bolster or hinder children’s learning, development, and well-being (for reviews see Lei et al., 2018; Roorda et al., 2020; Vandenbroucke et al., 2018; M. Wang et al., 2020). Supportive and close relationships with teachers are especially important for kindergarten children, given that kindergarten is children’s introduction to school life (McGrath & VanBergen, 2015). Children’s quality of relationships with kindergarten teachers has been linked to developmental and school-related outcomes in later elementary school years as well 21 (Jerome et al., 2009; Lee & Bierman, 2018). For example, children who experience conflict with kindergarten teachers are more likely to experience conflict with teachers in subsequent years, whereas children who experience closeness with teachers in kindergarten are more likely to experience closeness with teachers in subsequent grades. (Jerome et al., 2009). Intervention studies indicate that programs aimed at improving the quality of student-teacher relationships have a positive impact on young children’s development and experiences at school (e.g., Ansari & Pianta, 2018; García Bacete et al., 2019; Jones et al., 2013). A convergence of research over the last three decades indicates that student-teacher relationship quality in early childhood is related to children’s development of social and emotional competencies (e.g., Birch & Ladd, 1998; Lee & Bierman, 2015; Nucifora & Walker, 2021; Pianta et al., 2020). On average, young children who have closer dyadic relationships with teachers demonstrate better social skills and more prosocial behavior (e.g., Berry & O’Conner, 2010; Ferreira et al., 2016; Glüer & Gregoriadis, 2016; Zendarski et al., 2020). Students with close relationships to their teachers also exhibit more cooperative participation in school activities (Ladd & Burgess, 2001) and positive peer relationships (Sette et al., 2013; Verschueren et al., 2012). Young children who experience conflict with teachers, however, tend to demonstrate less cooperative participation and more behavioral issues than their peers (e.g., Birch & Ladd, 1998; Roorda et al., 2020; Sette et al., 2013). For instance, Lee and Bierman (2018) found that mean levels of conflict teachers reported experiencing with children throughout kindergarten through Grade 3 predicted teacher ratings of children’s aggression in Grade 5 even after controlling for levels of aggression children demonstrated upon school entry. Student-teacher relationships also are related to stress management and stress reactivity, important aspects of the self-management core competence (Mahoney et al., 2020; see Table 22 2.1). During the transition to schooling, young children experiencing closer dyadic relationships with teachers and a more positive classroom climate have demonstrated lower physical reactivity to stress whereas conflictual relationships and negative classroom climate have been linked to increased physical reactivity to stress in studies conducted in Germany and the US (Ahnert et al., 2012; Roubinov et al., 2019). Young children’s self-concept (i.e., their perceptions of their own competence) is also related to quality of student-teacher relationships. Close relationships with teachers was found to predict first graders’ academic self-concept (Verschueren et al., 2012), preschoolers’ general self-concept (Colwell & Lindsey, 2003) and second graders’ social self-concept (Leflot et al., 2010). Quality of student-teacher relationships is also associated with children’s self-regulation proficiency. For example, direct assessments of self-regulation on the Preschool Self-Regulation Assessment (Smith Donald et al., 2007) were moderately related to closeness with teachers and strongly related to conflict with teachers in children ages 3 to 6 (Acar et al., 2021). Student-teacher relationship quality is also related specifically to young children’s EFs. Data from a large longitudinal cohort study conducted with 18,200 US children found that teacher-child closeness in kindergarten was a promotive factor for children’s inhibitory control, working memory, and cognitive flexibility, cognitive proficiencies thought to underlie children’s self-regulation (Suntheimer & Wolf, 2020). Having a close relationship with a teacher also served as a protective factor for working memory skills, but not inhibitory control or cognitive flexibility, in kindergarten children exposed to multiple adversities (Suntheimer & Wolf, 2020). Another recent study of student-teacher relationship quality conducted with 1498 pre-kindergarten children in the US echoed these findings. Pianta and colleagues (2020) found that higher quality teacher-student relationships were associated with higher scores on a direct task of children’s 23 working memory. They also found that higher quality of student-teacher interactions, as rated by third-party observers, predicted lower teacher-reported conflict with students (Pianta et al., 2020). Intervention studies indicate that both the quality of student-teacher relationships and children’s social and emotional competencies improve when teachers and children take part in SEL programs (e.g., Bierman et al., 2014; Jones et al., 2013; Sheridan et al., 2019; Sutherland et al., 2018). For example, a recent study of 565 preschool children (ages 48 to 72 months) in Turkey found that the quality of student-teacher relationships (as rated by children and third-party observers) improved in classrooms that implemented the Promoting Alternative Thinking Strategies (PATHS) program compared to classrooms that did not implement the program (Seyhan et al., 2019). Implementing the program also improved children’s social and emotional competencies on average, as rated by their teachers and third-party observers, when compared to classrooms that did not implement the program. Few intervention studies have examined processes involved in observed changes, however (cf., Jones et al., 2013). 2.7 Self-Regulation and Social and Emotional Competencies Similar to quality of student-teacher relationships, extant research suggests that self-regulation skills in early childhood are associated with other social and emotional competencies (Rademacher & Koglin, 2019; Robson et al., 2020; Valiente et al., 2020). Self-regulation is related to social competence (Pandey et al., 2019; Razza & Raymond, 2013), prosocial behavior (Diamond et al., 2019; Williams & Berthelsen, 2017), social problem-solving (Denham et al., 2014), and emotion knowledge and understanding (Valiente et al., 2020; Von Salisch et al., 2015). Deficits in self-regulation skills are linked to a host of social and emotional issues, such as aggression, anxiety and other externalizing and internalizing behavioral issues (e.g., Allan & 24 Lonigan, 2014; Bierman & Sanders, 2021; Kim et al., 2013; Poland et al., 2016; Willoughby et al., 2011). For example, a longitudinal study that followed 1364 children in China found that children with low executive function proficiency at school entry (M = 5.36 years old) also had higher rates of internalizing and externalizing behavioral problems than their classmates with better EF proficiency (Y. Wang & Liu, 2020). Moreover, externalizing behavioral issues had a low rate of decline over six years in children who demonstrated low EF proficiency at the time they entered school. The observed relation between EF proficiency and behavioral issues was mediated by children’s social competence; that is, EF proficiency was directly related to children’s social competence, which in turn predicted children’s behavioral issues across the six years (Y. Wang & Liu, 2020). Preliminary evidence suggests that universal SEL programs for early childhood settings that focus on building self-regulation can, indeed, improve self-regulation skills alongside other social and emotional competencies (for reviews see Gagne & Nwadinobi, 2019; Pandey et al., 2019). For instance, kindergarten children at risk for developing emotional and behavioral disorders who took part in the Social and Emotional Learning Foundations (SELF) intervention, which focuses on building self-regulation skills alongside other social and emotional skills, experienced significantly greater teacher-rated self-regulation and improved social and emotional competencies compared to children who did not participate in the program (Daunic et al., 2021). 2.8 Joint Contributions of Student-Teacher Relationships Quality and Self-Regulation Research over the last decade has demonstrated joint effects of self-regulation and quality of student-teacher relationships on school-related outcomes, such as academic learning, school adjustment, and student engagement (e.g., Cadima et al., 2016; Hernández et al., 2017; Jones et al., 2013). For example, self-regulation and quality of student-teacher relationship were joint 25 predictors of kindergarten children’s behavioral engagement in school, which in turn predicted their behavioral engagement in Grade 1 (Cadima et al., 2015). Higher EFs and more positive relationships with teachers in preschool jointly predicted higher levels of math ability in kindergarten (Blair & McKinnon, 2016). Another study found that kindergarten children with closer relationships with their teachers were more engaged in school and had fewer self-regulation issues throughout the school year, and thus better academic competence in Grade 1 (Portilla et al., 2014). More conflict with teachers, however, was related to poorer self-regulation and less engagement across the school year. When the researchers examined the joint effects of relationship quality and self-regulation skills on engagement and academic competence, they found that the combination of teacher conflict and low self-regulation skills predicted decreased school engagement one year later, which in turn was related to lower academic performance. Moreover, students who entered kindergarten with poor self-regulation skills were more likely to experience conflict with teachers throughout the entire school year. A small number of studies have also observed conditional effects of student-teacher relationship quality on the relation between self-regulation and school outcomes. For example, researchers found that the quality of student-teacher relationships moderated the correlation between inhibitory control and predictions of math and reading achievement one year later in a study of 761 students (Liew et al., 2010). For children with high quality of relationships with teachers, inhibitory control was not related future math or reading scores. For children with low quality student-teacher relationship, however, inhibitory control at Time 1 was a significant predictor of academic performance at Time 2, with higher task-accuracy scores on inhibitory control tasks predicting higher math and reading scores one year later. For children with low accuracy on the inhibitory control task at Time 1, those with a more positive relationship with 26 their teacher performed equally well on academic tasks a year later as their peers with who demonstrated higher accuracy on the inhibitory control task, outperforming low-accuracy peers with poorer quality student-teacher relationships on reading and math assessments (Liew et al., 2010). Similarly, student-teacher relationship quality moderated the correlation between EFs and kindergarten readiness in a study of 139 preschoolers who demonstrated externalizing behavioral problems (Graziano et al., 2015). The relation between EFs and kindergarten readiness was only significant for children with lower quality relationships with teachers (i.e., high closeness and low conflict). For these children, lower EFs predicted lower kindergarten readiness. For children with higher quality relationships with teachers, however, EFs were not a significant predictor of kindergarten readiness. Findings from these two studies suggest that student-teacher relationship quality may serve as a protective factor for children with low self-regulation proficiency on school-related outcomes. In a more recent study, a conditional of effect of closeness with teachers was observed on the association between preschool children’s EF proficiency and their learning behaviors in 140 children from a disadvantaged neighbourhood in Istanbul (Acar et al., 2021). The study looked at two different dimensions of self-regulation: hot and cool. Hot self-regulation skills are theorized to be involved in stressful or emotionally salient situations to mitigate stress reactions in the autonomic nervous system that contribute to dysregulation (Backer-Grøndhal et al., 2019; Willoughby et al., 2011). Cool self-regulation skills are theorized to be the cognitive self-regulation skills involved in emotionally or motivationally neutral situations, such as working memory, focused attention, or planning (Montroy et al., 2019). Differential findings were observed for measures of hot and cool self-regulation (Acar et al., 2021). Moreover, findings 27 were heterogenous depending on whether closeness or conflict was the moderator. Although conflict was a significant and negative predictor for learning behaviors, it did not moderate the correlation between self-regulation (hot or cool) and learning behaviors. Similarly, whereas closeness was a significant and positive predictor of learning behaviors, it did not moderate the association between cool self-regulation and learning behaviors. Closeness was, however, a significant moderator for the correlation between hot self-regulation and learning behavior (Acar et al., 2021). Contrary to the previously described studies, the correlation between hot self-regulation and learning behavior was only significant for children with high levels of closeness (+1 SD and greater) but not for those with lower closeness. For children with high levels of closeness with teachers, higher self-regulation predicted higher learning behaviors, but hot self-regulation was not a significant predictor for children with lower levels of closeness with teachers. In summary, although joint influences of self-regulation and student-teacher relationship quality have been observed on children’s academic and learning outcomes in early childhood, much less is known about the joint influence of the two predictors on children’s social and emotional competence. Although it makes theoretical sense that children’s self-regulation proficiency and quality of relationships with teachers would impact their SEL similar to academic learning, there is a paucity of research that has examined self-regulation, quality of relationships, and social and emotional competencies concurrently. Moreover, findings have been heterogenous based on the dimension of student-teacher relationship examined, how self-regulation is measured, and which outcomes are examined. The present study aims to address these gaps by investigating the joint influences of self-regulation and student-teacher relationships on kindergarteners’ social and emotional competencies, and specifically, their 28 empathy and prosocial behavior. Moreover, we aim to investigate whether conditional effects of closeness or conflict are present in separate linear regression models using two different measures to estimate different dimensions of self-regulation proficiency: behavioral self-regulation and EFs. 2.9 Individual Differences in Self-Regulation in Early Childhood There is evidence that different developmental trajectories exist in self-regulation proficiency, with individual children developing at vastly different rates throughout early childhood leading to large differences in self-regulation proficiency. For example, in their study examining individual developmental trajectories for self-regulation in 2,421 children across three sites in the US, Montroy and colleagues (2016) noted three separate groups: early developers, intermediate developers, and late developers. Early developers described children who had higher initial self-regulation skills on the Head-Toes-Knees-Shoulder (HTKS) task of self-regulation (McClelland et al., 2014) when they entered preschool at age three and demonstrated earlier rapid gains in skills than their later-developing peers. Late developers came into preschool with low initial self-regulation skills and experienced their rapid gain in self-regulation skills much later, closer to age 7. Late developers were more likely to be boys or have mothers with lower education than the other groups (a common marker of socio-economic status). The group with largest number of children was the intermediate developers, who demonstrated low self-regulation skills as they entered preschool but experienced rapid gains before entering kindergarten or early in the kindergarten year. Another study examined self-regulation in relation to other social and emotional competencies in 275 four-year old children to create SEL profiles that were used to predict early school adjustment and academic learning in kindergarten (Denham, Bassett, Mincic et al., 2012). 29 Researchers used cluster analysis to identify three distinct SEL profiles. The SEL risk group included students who demonstrated low self-regulation skills, low emotion knowledge, lower social problem-solving skills and more aggressive behavior, indicating that self-regulation skills are indeed related to other social and emotional competencies. The other two SEL “competent” groups were similar in self-regulation skills and emotion knowledge, but they differed in social problem solving and social behavior. The SEL competent-social/expressive group demonstrated better social problem-solving skills and more prosocial behavior than their peers in the SEL competent-restrained group. Students in the SEL Risk group had the lowest scores on the Student-Teacher Relationship scale compared to peers, as well as lower scores on teacher-ratings of school adjustment and academic learning in kindergarten (Denham, Bassett, Mincic et al., 2012). A recent longitudinal study that followed children in an economically disadvantaged families in the US examined how preschool children’s self-regulation profiles interacted with the quality of relationships to their preschool teacher to predict their academic and social outcomes in kindergarten and Grade 2 (Bayly & Bierman, 2021). The researchers investigated whether different self-regulation profiles exist in preschoolers via latent profile analysis of cognitive and behavioral self-regulation measures. Cognitive self-regulation was measured via four direct assessments of EFs that targeted inhibitory control, working memory, and attention shifting. Behavioral self-regulation was measured using preschool teacher ratings of self-control and disruptive/aggressive behaviors in the classroom. They found four distinct profiles, The pervasive dysregulation group (30%) scored low on all measures of self-regulation. The behavioral dysregulation group (22%) had equivalent scores to the pervasive dysregulation group on measures of behavioral self-regulation but scored significantly higher on EF tasks. The 30 two other groups were combined into a single regulated group for subsequent regression analyses to investigate differences in academic and social outcomes in elementary school. Self-regulation group membership predicted children’s reading achievement and attention problems in kindergarten and reading achievement in Grade 2, but not their social competence, whereas closeness with preschool teachers predicted significantly higher scores in all four outcomes, including social competence (Bayly & Bierman, 2021). The two dysregulated groups had significantly lower scores in all areas compared to the regulated group but there were no significant differences between the two dysregulated groups. A distinction between the two dysregulated groups became evident when student-teacher relationship quality with preschool teachers were taking into account, however. Researchers reported that the correlation of student-teacher relationship quality to attention and reading achievement was conditional on children’s self-regulation profile. Close relationships with preschool teachers predicted significant decreases in future attention problems for all children except those in the pervasive dysregulation group (i.e., the children with the lowest EF proficiency). Conflict with preschool teachers had a negative association to children’s future reading achievement and academic performance for children in the behavioral dysregulation group only (i.e., those with low behavioral self-regulation yet average EF proficiency). The correlation between student-teacher relationship quality in preschool and kindergarten and Grade 2 social competence was not contingent on children’s self-regulation profile, however. Although this study provides important insights as to how children’s self-regulation proficiency and quality of relationship with their teacher in preschool may relate to later academic outcomes, it does not shed light on how self-regulation proficiency and quality of student-teacher relationships in kindergarteners relate to contemporaneous social and emotional 31 competencies. Arguably children’s quality of relationship with their current teacher may play a greater role on children’s social competence in the classroom than relationships with previous teachers. Moreover, self-regulation proficiency develops rapidly during the preschool years (Montroy et al., 2016). It is unclear whether children’s self-regulation profile may have changed from preschool to Grade 2 given that self-regulation proficiency in kindergarten and Grade 2 were not included in the models (Bayly & Bierman, 2021). Furthermore, although self-regulation and student-teacher relationships were examined as individual predictors for later academic and social outcomes, the study did not evaluate the joint contributions of these two predictors. Finally, this study focused on children in economically disadvantaged communities. It is unclear whether similar patterns are evident in children who lived in average or above-average income neighbourhoods, limiting the generalizability of the study (Bayly & Bierman, 2021). The present study aims to address these limitations by examining how kindergarteners’ self-regulation and quality of student-teacher relationship jointly related to their concurrent social and emotional competencies in schools located in communities with a representative range of incomes (low to high). In sum, these studies indicate that individual differences in the development of self-regulation skills exist in early childhood. There is a paucity of research, however, that specifically examines how kindergarten children with low self-regulation skills, and specifically low EF skills, might differ from their peers in their social and emotional competencies and quality of relationships with teachers in public school settings (Y. Wang & Liu, 2020). Yet, understanding how developmental differences in EFs may be related to these other important areas is critical for knowing how to support children who struggle with self-regulation as they transition into formal schooling. 32 2.6 Research Questions and Hypotheses As is evidenced by the previous review of the literatures, it is clear that both self-regulation and quality of student-teacher relationships are related to the development of social and emotional competencies in early childhood. There is a paucity of research, however, that has specifically investigated how kindergarten children with low EF proficiencies fare in comparison to their more proficient peers in relation to their social and emotional competencies and quality of relationships with teachers in public school settings (Y. Wang & Liu, 2020). Moreover, few studies have investigated potential processes involved in SEL and development; instead, most research has focused on single-variable predictors of social and emotional competencies rather than using joint variables as a means of investigating interactions among variables (Denham & Brown, 2010). The present study aims to contribute to the literature on social and emotional development in early childhood by addressing these gaps and limitations. Firstly, we investigated individual differences in EFs by comparing how children with low EF proficiency fare in their quality of student-teacher relationships and social and emotional competencies when compared to their classmates with proficient EFs in a sample of Canadian kindergarteners situated in eight public schools in neighbourhoods from a range of SES. Next, after controlling for observed group differences in EF proficiency, we employed a series of linear regression models to investigate self-regulation and quality of student-teacher relationships as individual and joint predictors of kindergarteners’ empathy, prosocial behavior, and a composite variable of general social and emotional competence (henceforth SEC). 33 2.6.1 Study Aim 1 Hypotheses The first aim of the study was to explore differences in social and emotional competencies and quality of student-teacher relationships between children with low EF proficiency compared to children in the sample with proficient EFs. To do this, we created two groups based on teacher-rated observations of executive function problems on the Behavior Rating Inventory of Executive Functions – Preschool Version (BRIEF-P; Gioia et al., 2003). The low EF group consisted of children who scored at or above the clinical cut off for EF dysfunction on the BRIEF-P, and the comparison group consisted of children who scored below the clinical cut off. Based on extant research, we hypothesized that, on average, children in the low EF group would demonstrate significantly more teacher-reported conflict with teachers and significantly less teacher-rated closeness than their peers with proficient EFs in the comparison group. Additionally, we hypothesized that children in the low EF group would demonstrate significantly lower social and emotional competencies than those in the comparison group. 2.6.2 Study Aim 2: Research Questions The second aim of the study was to examine the individual and joint associations of quality of student-teacher relationships and self-regulation proficiency to students’ social and emotional competencies using a series of linear regression models. Given the exploratory nature of this inquiry, we put forth research questions rather than hypotheses. Specifically, we aimed to answer the following research questions: 1. After controlling for age, gender, and EF group, how well does children’s self-regulation proficiency estimate social and emotional competencies? 34 2. How much does the addition of the student-teacher relationship closeness and conflict variables to the regression model add to the estimation of social and emotional competencies above and beyond self-regulation? 3. Does student-teacher relationship quality have a conditional effect on the association between self-regulation proficiency and social and emotional competencies? 35 Chapter 3: Method This chapter describes the method of the present study. First, the context is described in which the study took place and the recruitment process. Following this is a description of the study participants follows, as well as details of the informed consent process and administration of surveys and tasks. Finally, the measures employed in the present study are outlined. 3.1 School Recruitment and Participants Participants were recruited from public elementary schools in a large urban school district in Western Canada that consists of 89 elementary schools serving 28,000 students from kindergarten to Grade 7. The school district is among the most ethnically diverse in Canada. There are 140 languages spoken among students in the district and 44% of students in the district speak a language other than English at home. To obtain a cross-section of schools that represent the socioeconomic diversity of students in the district, a targeted approach was used to identify neighbourhoods with a range of socio-economic statuses based on median income for families with children that shared the same postal code as the school (Canadian Census Data, 2016). We sought to enroll schools from below-average SES level neighbourhoods, average SES neighbourhoods, and above-average neighbourhoods. The Canadian average for median total income is $89, 610 CND for couple-parent families and $45,220 CND for lone-parent families (Canadian Census Data, 2016). As per school district policy, principals from public elementary schools were contacted first to request permission to contact teachers. Twelve principals were initially contacted via an email outlining the purpose of the study and inviting participation from one kindergarten classroom teacher per school (see Appendix A). Eight principals responded and identified kindergarten teachers who were interested in participating. For each of eight schools, eight 36 teachers, one per school, (100%) provided consent to participate and permission to visit their classrooms to explain the study to children. Two teachers were in schools in a neighbourhood with below-average median family income ($71,879 CND), two teachers were in schools in a neighbourhood with higher-than-average median family income ($103,906 CND), and four teachers were in schools in neighbourhoods with average median family income (range $87,384 - $91,354 CND). 3.1.1 Child Participants From the eight kindergarten classrooms, of 152 children eligible to participate across the eight classrooms, 139 parents/guardians (91%) provided consent for their children to participate, 139 children assented to have their teachers report on their learning and behavior, and 14 children chose not to participate in the direct task of assessment. (See Procedure section for a detailed description of informed-consent process for children participants). Hence, the recruited final sample included 139 kindergarten students (43% girls) in eight classrooms at eight different public elementary schools from the large urban school district in Western Canada. Participants ages ranged from 60 months to 72 months (M = 65.37, SD = 3.35). In regard to children’s first languages learned, teachers reported that 99 children (71%, M = 0.71, SD = 0.45) learned English as a first language and 53 children (39%) learned other languages. Ten percent of children learned more than one language. 41 children (29%) did not learn English as a first language. In addition to English, 16 other native languages were reported, reflecting the rich cultural and ethnic diversity of the public school district in which the study took place (see Table 3.1). Mandarin (16%) and Cantonese (7%) were the most frequently reported languages after English. 37 To obtain a measure of children’s English language comprehension, teachers were asked to rate children’s ability to understand English on a four-point scale with 1 = Very Hard and 4 = Very Easy (M = 3.51, SD = 0.79). Results indicated that the majority of children found it easy (20%) or very easy (67%) to understand English. Teachers reported that 10% of children found it hard to understand English and 3% found it very hard. Regarding family composition, teachers reported that 86% of participating children live in couple-parent families. For children living in lone-parent families, teachers reported that 13% lived full time with one parent and 1% of children lived part time with two different parents. No children were reported by teachers as living in foster care. 38 Table 3.1 Child Participants’ First Languages First Language Number of Children Percentage of Children English 99 71% Mandarin 22 16% Cantonese 10 7% Japanese 4 3% Portuguese 2 1% Spanish 2 1% Tamil 2 1% Vietnamese 2 1% Dutch 1 <1% German 1 <1% Hebrew 1 <1% Polish 1 <1% Punjabi 1 <1% Russian 1 <1% Sesotho 1 <1% Taiwanese 1 <1% Ukrainian 1 <1% Note. 10% of children spoke more than one first language, thus the percentage total is greater than 100. 39 3.1.2 Teacher Participants Of the eight participating teachers, seven described themselves as women and one as a man. Regarding their ethnicity, five teachers described themselves as Caucasian/White (63%), two as East Asian (25%), and one as South East Asian (13%). Years of teaching experience ranged from less than a year to 32 years, with the majority of teachers (n = 7, 87%) having 12 or more years teaching experience (M = 15.48, SD = 9.05). Three teachers reported having Bachelors of Education degrees, four had post baccalaureate degrees in Education, and one had a graduate degree in Education. 3.2 Procedure The study was approved by UBC’s Behavioral Research Ethics Board and the School Board of the participating region. Careful consideration was given to the informed consent process to facilitate children and teachers’ understanding of the purpose of the study and their research rights. The following provides a detailed description of the study procedure, including recruitment, informed consent, and administration of surveys and tasks. 3.2.1 Procedure for Recruiting Teacher Participants Teachers were first provided with written descriptions of the study (see Appendix B for flyer). For teachers who expressed interest in the study, we visited with each of the kindergarten teachers in person to explain the purpose of the study and provide consent forms (see Appendix C). Teachers were asked to take home the consent forms (Appendix E) to read and consider before deciding whether to participate or not. 3.2.2 Procedure for Recruiting Child Participants For the purposes of the present study, we took into account current ethical guidelines for research with young children. Specifically, research has demonstrated that informed consent can 40 be obtained from very young children if researchers take the time to build trusting relationships with children and use developmentally-appropriate approaches to describing the purpose of research and children’s research rights (Mayne et al., 2016). Informed consent for research participants can only be obtained if children have a clear understanding of the purpose of the research, their role within it, and their research rights (Docket & Perry, 2011). To facilitate the process, researchers should use language that children are familiar with and engage in dialogue with children to find out what they know about the topic of research and invite their questions (Harcourt & Conroy, 2011.) This allows the researcher to take note of language that the children use when discussing the topic so that they can use the same language when describing the study. Researchers can also situate children as experts on their own lives and let them know that the researchers would like to learn from the children. In doing so, they demonstrate that they recognize children as capable social agents as opposed to objects of study (Mayne et al., 2016). The informed-consent process with children takes time to build trusting relationships between researcher and children, skillful communication, and researcher reflexivity to recognize when research aims may be overriding the informed-consent process (Mayne et al., 2016). Taking this research ethical research with children into account, we discussed the purposes of the study and children’s research rights with them on three occasions to facilitate the informed consent process. To allow the children to get to know the research team before the study, we visited each classroom prior to handing out parental/guardian consent forms to facilitate a group discussion about the study (see Appendix D for recruitment visit protocol and scripts). Children were asked to share what they knew about universities (“they are a school for grown-ups”) and what researchers do there (“they search for answers to important questions. That’s why they are called researchers.”). We shared that our research question was “how do 41 kindergarteners learn best?” and that we were searching for ways to make kindergarten even better for everyone. We recognized the children as experts on kindergarten. We then elicited their ideas for how we might learn more about how kindergarteners learn. In all eight classes, children mentioned “asking their teacher” and “watching them learn something” as potential ways to discover how kindergarteners learn best. These suggestions allowed us to segue into the methods used in the present study: teacher ratings of children’s observed behavior and researchers watching child participants learn a new game: the Head-Toes-Knees-Shoulders-Extended task (McClelland et al., 2014; see description below). We then reviewed important aspects of their research rights, emphasizing that they had a choice whether to participate or not, that we would not be upset if they chose not to participate, and that even if they said yes to participating in the research study, they could change their mind at any time. We concluded by letting them know that what we learned from them was important information that could help make kindergarten even better for everyone. Students were encouraged to give the consent form to their parents or guardians and discuss the research study together with them to see if taking part was a good choice for their family. We explained that if they and their parents/guardians decided yes, that meant that their teacher could answer questions about how they learn, but they could still decide whether to play the game or not. To play the game, they had to have a “yes” on their permission slip from their “grown-up” at home. We told them that everyone would receive a small gift when we returned to play the game, whether they chose to take part in the study or not, as a thank you for letting us visit their class. Children were then invited to ask us any questions they liked to help them get to know the research team better and to ask any questions they had about the research study. Visits typically lasted 15 to 30 minutes depending on the length of discussion. 42 3.2.3 Procedure for Administration of Teacher-Report Measures Teachers were asked to complete a self-report questionnaire outlining their own demographics, level of education, and teaching experience (see Appendix H). Additionally, they completed a seven-page questionnaire describing children’s demographic information, their social-emotional competencies, and EF proficiency (see Appendix I). The questionnaire took approximately 15 minutes to complete per child (approximately 5 hours in total for classes in which all students participated). Teachers were provided with a full day on-call teacher to allow for the time it took to fill out the surveys. They also were provided with a $50 honorarium. Surveys were provided to teachers in December 2019 and retrieved in early January 2020. 3.2.4 Procedure for Administration of Child Direct Assessment of Self-Regulation On the day of the administration of the direct assessment, the research team was reintroduced by the classroom teacher. We reminded children of the study details and explained what the procedure would be. We reminded them it was their choice whether they wanted to try the “game” (i.e., HTKS-E see description in Measures section below) or not. Before engaging in the direct assessment, we went over children’s research rights one more time (see Appendix K), and we asked whether they wanted to “try the game” to obtain their assent. We obtained assent from 117 students. Fourteen students chose not to participate in the HTKS-E task, six children did not understand the instructions for the task, and eight children were absent during the visit. The HTKS-E task was administered to each participating student individually. Teachers were consulted to find out any pertinent information that may impact students’ participation, such as English language level, anxiety, and developmental differences. All children were invited to play the game regardless of this information, but the information was noted to better understand children’s participation and performance on the task. Teachers scheduled visit dates and 43 suggested the order for taking students from class so that students would not be taken during important or pleasurable activities. The task took place in quiet spaces in the school where participants would not be observed by others (e.g., empty classrooms, resources rooms, libraries that were not in use). Trained research assistants with experience working with young children walked students from class while engaging in ice-breaking conversation and describing to them where they were going, and what they would be doing. The author administered all of the HTKS-E tasks. Additionally, three trained research assistants served as second raters. Data were collected over six weeks (December 2019 to mid-January 2020). All students in each classroom received a sticker regardless of whether they took part in the task or not. 3.3 Measures Teachers reported their own demographics and child demographics for participants in their class. Student-teacher relationships were measured by teachers’ perceptions of dyadic relationships with each child. Children’s social and emotional competencies were measured via teacher report measures of children’s social and emotional competence, social behavior, empathy, peer acceptance, and EFs (see Appendix I). All of the measures have been utilized in previous studies conducted with samples of kindergarten children, demonstrating good psychometric properties. Each measure is described in detail in the following sections. 3.3.1 Direct Assessment of Child Self-Regulation The Head-Toes-Knees-Shoulders-Extended (HTKS-E) task is a self-regulation task that has been used in research with children ages 4 to 8 (Cameron Ponitz, 2009; McClelland et al., 2014). The HTKS-E is theorized to be a measure of EFs in action. In order to be successful at the task, children need to be able to volitionally focus their attention to learn the rules of the game, engage their working memory to remember and apply rules, inhibit prepotent responses by doing 44 the opposite of what they administrator says, and make use of cognitive flexibility to disregard previous rules and shift to a new set of rules as the game gets progressively more challenging (McClelland et al., 2014). The measure and online training for its use are available at no cost through Oregon State University (oregonstate.qualtrics.com). Unlike most direct assessments of self-regulation that require the inhibition of fine motor skills, the HTKS-E requires children to inhibit gross motor activity by challenging them to touch a different body part than is directed by the task administrator, with increasingly challenging demands on cognitive self-regulation skills as the game progresses. The HTKS-E is comprised of three parts (described in detail below). Part 1 is the original version of the assessment: The Head to Toes Task (HTT; Cameron Ponitz et al., 2008). Part 2 was added to the HTT to address ceiling effects to create the Head-Toes-Knees-Shoulder (HTKS) task (Cameron Ponitz et al., 2009). The HTKS-E, is an extended version of the task which includes a third part designed to offer an increased challenge for EFs by switching the rules of the task, thus allowing researchers to utilize the measure with a greater range of ages and abilities (McClelland & Cameron 2014). Each part begins with opportunities to practice first (5 or 6 trials per part), in which children are provided feedback on their performance (i.e., positive feedback when they choose the correct response, and a reminder of the rules when they choose an incorrect response). Practice items are followed by 10 trials in which children receive no feedback whether they got the item correct or not. Scores are based on task accuracy: 0 for inaccurate responses, 1 for initially inaccurate responses that children self-correct, and 2 for correct responses. Children who score less than four points on one part do not advance to the next part and receive a score of 0 for all subsequent items. The HTKS-E has 30 trial items. 45 Scores are summed to create a final composite score out of 60 (Lewis & McClelland, 2015). Higher scores represent higher self-regulation skills. In the first part of the task, children are presented with a pair of two rules. They are instructed to touch their head when the task administrator says, “touch your toes” and touch their toes when the task administrator says, “touch your head.” In the second part, the challenge is increased by adding a new pair of rules into the mix: Touch knees when the administrator says, “touch your shoulders” and touch shoulders when the administrator says, “touch your knees.” In Part 2, children must apply all four rules, adding additional challenges to the working memory because it requires children to remember the rules from the previous round as well, thus having to keep four different rules in mind. The third part introduces an additional challenge by switching the rules to create four new rules. For example, when the administrator says, “touch your head,” children are instructed to disregard the previous rule of touching the toes and touch their knees instead. When the administrator says, “touch your toes,” children disregard the previous rule of touching head, and touch shoulders instead (Cameron et al., 2014). The HTKS has been translated into 18 languages and has been employed in studies in many countries as well as cross-cultural research (Lewis & McClelland, 2015). The HTKS-E is currently one of the most widely used measures of self-regulation in early childhood studies (Robson et al., 2020). In a previous validation study conducted on the current three-part version of the measure, interrater reliability was strong (κ = .79) and internal consistency was good, with ordinal alpha coefficients for three-part measure ranging from .92 to .94 across four waves of the study (McClelland et al., 2014). Test developers also reported good test-retest stability with test performance in the fall of kindergarten significantly predicting 46 scores in the spring (McClelland et al., 2014). For the current sample, the ordinal alpha was .97 and interrater reliability was 91% (κ = .80). 3.3.2 Teacher-Reported Measures of Children Teacher Reports of Child EFs. The Behavior Rating Inventory of Executive Function- Preschool Version (BRIEF-P; 2003) is a teacher-reported measure of problematic behavior related to children’s EF proficiency. The measure includes five theoretically-derived clinical subscales that describe behaviors related to different dimensions of EFs: Inhibitory Control, Working Memory, Attention Shifting, Cognitive Flexibility, and Emotion Control, as well as a Global Composite score that sums all items. The 63-item measure was designed to assess deficits in EFs in children ages 2 to 6 by asking teachers to rate how often a child engages in problematic behaviors linked to low EF proficiency. Thus, higher scores on the scales indicate lower EF proficiency The written instructions for teachers were adapted from instructions in BRIEF-P Professional Manual, emphasizing that teachers should report the degree to which the behavior is a problem and not the frequency of the behavior, given that most children in early childhood will exhibit the described behaviors some of the time (Gioia et al., 2003; p.7). The following instructions were provided: “While many of these behaviors are common among kindergarteners, we would like to know how often this child has had problems with these behaviors during the past 4 weeks.” Although the BRIEF-P typically asks raters to consider behavior over the last six months for clinical decision-making, four weeks is the minimum time period for consideration suggested by test developers (Gioia et al., 2003), and this time frame has been used in other empirical studies of EFs in kindergarten that aim to assess EF ability in the short-term (e.g., Thierry et al., 2016). 47 Teachers responded using a three-point scale with 1 = Never indicating that the behavior was never a problem, 2 = Sometimes indicating that the behavior was sometimes a problem, and 3 = Often indicating the behavior was often a problem. Example items include: “Is impulsive;” “Has trouble putting the brakes on his/her actions even after being asked;” “When sent to get something, forgets what he/she is supposed to do;” “Has trouble with activities or tasks that have more than one step;” “Has troubling changing activities;” “Has trouble thinking of a different way to solve a problem or complete an activity when stuck;” and “Is easily overwhelmed or overstimulated by typical daily activities.” The BRIEF-P is a widely used measure; it has appeared in more than 250 published peer reviewed studies since its inception (Greene et al., 2019). It has been shown to have excellent reliability, with Chronbach’s alpha coefficients for the Global Composite score being reported as .97 in more than one study (Giola et al., 2003; Ezpeleta et al., 2014). Limited convergent validity evidence exists for the BRIEF-P. The global composite score of the BRIEF-P was strongly and positively correlated with teacher ratings of Inattention (r =.80) on the Hyperactivity and Impulsivity (r = .76) on the ADHD Rating Scale IV-Preschool in a normative sample of 40 preschoolers (Gioia et al., 2003). There is also evidence of weaker correlations of the BRIEF-P to direct assessments of EF conducted with larger community samples of three- to five-year olds (Graziano et al., 2015; Tamm & Peugh, 2015). BRIEF-P scores have been shown to be consistently higher in children with diagnoses related to EF deficits, such as ADHD, oppositional defiance disorder, and autism spectrum disorder (Ezpeleta & Granero, 2015; Gioia et al., 2003; Greene et al., 2019; Mahone & Hoffman, 2007). The BRIEF-P is a copyrighted measure and researchers must pay per use through PAR (parinc.com). The BRIEF-P demonstrated excellent reliability with the current sample. For the Global 48 Composite score, a = .97. The internal reliability for the subscales were good: Inhibit (α = .96), Shift (α = .91), Emotional Control (α = .92), Working Memory (α = .93), and Plan/Organize (α = .89). All analyses in the present study use the Global Composite score. Teacher Reports of Student-Teacher Relationship Quality. To measure the quality of student-teacher dyadic relationships with each individual student, teachers completed the Student-Teacher Relationship Scale – Short Form (STRS; Pianta, 2001). The STRS is a 15-item scale consisting of two subscales that measure different student-teacher relationships qualities: Closeness and Conflict. The seven-item closeness subscale assesses teachers’ perceptions of the degree of positive affect and warmth they experience with child, as well as the child’s comfort level for approaching the teacher for help. Example items include “I share an affectionate, warm relationship with this child,” “When I praise this child, he/she beams with pride,” and “If upset, this child will seek comfort from me.” The eight-item conflict subscale assesses challenging interactions and negative rapport with the child, including items such as “This child and I always seem to be struggling with each other,” and “When this child is in a bad mood, I know we’re in for a long and difficult day.” Instructions for the assessment asked teachers to “Please reflect on the degree to which each of the following statements currently applies to your relationship with this child. Using the scale below, circle the appropriate number for each item.” The five-point rating scale ranges from 1 = Definitely Does Not Apply to 5 = Definitely Applies. The STRS-short form has been used widely in studies of kindergarten children across many different countries with good psychometric properties (Sabol & Pianta, 2012). The internal reliability for each of the two subscales for the present study was good: Conflict a = .90 and Closeness a = .88. 49 Teacher Reports of Child Social and Emotional Competencies. As a measure of children’s social and emotional competencies, teachers completed the Teachers’ Rating Scale of Social Competence (TRSC; Kam & Greenberg, 1998). The TRSC is comprised of 29 items which make up four distinct subscales related to different aspects students’ social and emotional competencies: Attention and Concentration, Social and Emotional Competence (SEC), Aggressive Behaviors, and Oppositional/Dysregulated Behaviors. For the present study, only the SEC subscale was included in analyses. Teachers are provided with behavioral descriptions and asked how often a child engages in the particular behavior in comparison to their peers. Teachers respond using a six-point rating scale, with 1 = Almost Never and 6 = Almost Always. Teachers are provided with the following prompt: “Compared to other boys/girls at this grade level how often does this student…” Example items include: “recognize and label his/her feelings and those of others appropriately;” “initiate interactions and joins in with others in a positive manner;” “takes turns, plays fair, and follows rules of the game.” The TRSC has been used in previous studies with kindergarteners with good reliability (e.g., a = .88 – .95; Blair et al., 2018). For the present sample internal reliability for the SEC subscale was excellent (a = .93). Teacher Reports of Child Prosocial Behavior with Peers. Teachers completed the Prosocial with Peers subscale of the Child Behavior Scale (CBS; Ladd & Profilet, 1996). The subscale consists of eight items describing prosocial behavior, such as “is kind towards classmates;” “compromises in conflicts with classmates;” and “offers help or comfort when classmates are upset.” Teachers are asked to “rate the behavior described in each item in terms of how characteristic or “applicable” it is for the child you are rating.” The response format includes a three-point rating scale in which 1 = Doesn’t Apply (child seldom displays the behavior), 2 = Applies Sometimes (child occasionally displays the behavior), and 3 = Certainly 50 Applies (child often displays the behavior). The measure has been widely used in studies over the last two decades and has demonstrated good psychometric properties, similar to those observed in the initial validation study conducted with kindergarten children, which ranged from .91 to .92 (Ladd & Profilet, 1996). The internal consistency for the Prosocial Behavior with Peers scale for the present sample was excellent (a = .92). Teacher Reports of Child Peer Acceptance. Teachers completed the three-item Peer Acceptance subscale on Eisenberg et al.’s (2000) measure of social competence. Teachers rated children’s acceptance by peers on a five-point scale on which 1 = Never to 5 = Always. Statements included: “This child is popular with others his/her age;” “This child has a lot of friends;” and “This child finds it hard to make friends” (reverse scored). This measure has been used in previous studies of social and emotional competencies in early childhood with excellent reliability (e.g., a = .93; Eisenberg et al., 2003). The internal consistency for the Peer Acceptance scale was excellent in the present sample (a = .93). Teacher Reports of Child Empathy. Teachers completed the six-item empathy scale (Eisenberg et al., 1991). Teachers rated children’s empathy on a five-point scale on which 1 = Never to 5 = Always. Example items included: “This child usually feels sorry for other children who are being teased” and “This child usually comforts others who are upset or hurt.” Eisenberg and colleagues’ (1996) employed this measure in a study of empathy with kindergarteners, reporting good reliability using a shortened three-item version of the scale (a = .86). For the present sample, the internal reliability of the Empathy scale was excellent (a = .92). 3.3.3 Covariates Teachers reported children’s birthdate (month and year) and gender (How does this child describe their gender? Boy, Girl, In Another Way). Gender and age have been linked to 51 children’s social and emotional competencies in the extant literature (e.g., Bouchard et al., 2020; Zakszeski et al., 2020). Thus, controlling for these variables allows us to examine any additional variance in social and emotional competencies explained by self-regulation and student-teacher relationships above and beyond age and gender. 52 Chapter 4: Results In the present study, we set out to examine between-group differences in quality of student-teacher relationships, self-regulation proficiency, and social and emotional competencies between kindergarten children in public schools who met a clinical cut off for low EF proficiency compared to their classmates who did not meet the cut off. Then, controlling for these two groups, we explored whether self-regulation proficiency and quality of student-teacher relationship explained additional variance in children’s social and emotional competencies using linear regression models. Specifically, we examined the individual and joint contributions of student-teacher relationships and self-regulation on teacher reports of children’s empathy, prosocial behavior with peers, and general SEC. The following section outlines the analytic plan for each of the two study aims. First, we describe how we addressed missing data in the study. Then, details of analytic plans and results are reported in three sections: (1) Preliminary Analysis, (2) Aim 1 Results, and (3) Aim 2 Results. Results for Aim 2 are organized by dependent variable to facilitate comparison across different regression models. Overview of Analytic Aims To answer the question of whether kindergarteners with low EF proficiency are at a disadvantage to their peers with proficient EFs, we tested the hypothesis that children who met a clinical cut off for EF deficits would demonstrate significantly lower scores on a direct assessment of behavioral self-regulation proficiency and teacher ratings of children’s social and emotional competencies. Furthermore, we hypothesized that children in the low EF group would score significantly lower on teacher-ratings of student-teacher closeness and significantly higher on student-teacher conflict. To test these hypotheses, we conducted independent t- tests to compare mean differences between the two groups. 53 The second aim of the present study was to identify important predictors of social and emotional competencies to inform intervention efforts. Theories of social and emotional development in early childhood posit that children’s self-regulation skills and quality of relationships with caregivers form the foundation of SEL to build social and emotional competence (Denham & Brown, 2010; Loomis, 2021). If these theories are correct, it serves to reason that self-regulation and quality of student-teacher relationships together would explain more variance in social and emotional competence than either predictor alone. Moreover, it is possible that student-teacher relationship quality may have a conditional effect on the relationship between self-regulation and social and emotional competence, given that close and supportive relationships with teachers is linked to higher self-regulation (e.g., Suntheimer & Wolf, 2020) whereas conflict with teachers is linked to lower self-regulation (e.g., Acar et al., 2020). Thus, it is possible that the strength of the correlation between self-regulation and indicators of social and emotional competence depends on the level of closeness or conflict in student-teacher relationships. Hence, Aim 2 was to explore the individual and joint contributions of self-regulation proficiency and student-teacher relationship quality to indicators of children’s social and emotional competence by employing OLS linear regression models. All analyses were conducted using SPSS Version 27 (IBM, 2020). Preliminary analysis included examining descriptive statistics and bivariate analysis of relations among variables. Spearman’s rank correlation coefficients were employed for variables measured using either ordinal or continuous response scales (deWinter et al., 2016). Relations to categorical variables, such as gender, were examined using Pearson correlations (deWinter et al., 2016). 54 4.1 Missing Data Overall, 18% of data was missing, all of which was from the HTKS-E direct assessment of self-regulation. Reasons for missingness included 14 children who chose not to participate in the task, 11 children who stopped the task early, and 8 children who were absent during initial and make-up visits. Thus, we had complete teacher-reported data for all 139 participants and complete HTKS-E data for 106 participants. Chi Square for Little’s Missing Completely at Random (MCAR) test was not significant (χ2 = 22.37, p = .32.). Therefore, we accepted the null hypothesis that data is missing completely at random. Comparisons of demographics between students with missing data and those without indicated that there were significantly more boys in the missing data group than girls (57.6%, χ2= 7.25, p < .01). There were no significant differences in age, teacher-rated English language comprehension, or having English as a first language. To address missing data, we employed multiple imputation, which is the preferred method for multivariate research (Blackwell et al., 2017). Multiple imputation calculates estimates for missing data based on the characteristics of non-missing data, which allows for less biased estimates than complete case analysis. Complete case analysis, which involves deleting cases that do not have complete data, often leads to biased and unreliable estimates and increased standard errors (Little & Rubin, 2019). It can decrease statistical power, particularly if more than 10 % of data is missing, as is the case in the present study (J. Wang & Johnson, 2019). Conversely, multiple imputation allows the use of the entire sample so that power is not decreased. Following recommendations made by J. Wang and Johnson (2019) based on their examination of multiple imputation procedures, we generated 25 iterations of 1000 draws of 55 imputed data in SPSS Version 27. All of the covariates, predictor variables, and outcome variables were included because this provided the lowest fraction of missing information (FMI; see Madley-Dowd et al., 2019). Analyses were conducted using pooled variance to account for sampling error. A sensitivity analysis examining the FMI and relative efficiency for analyses using multiple imputation indicated that the pooled variance coefficients offered improved efficiency gains1 over coefficients from complete case analysis of HTKS-E data (Little & Rubin, 2019; Madley-Dowd et al., 2019). 4.2 Preliminary Analysis Descriptive statistics for independent and dependent variables are presented in Table 4.1. Reliability, measured by ordinal alpha scores, for all measures was excellent, ranging from .88 to .97. For all measures, we used mean scores in the analyses. To understand the nature of relations among variables of interest, we examined bivariate correlations (see Section 4.4.2.2). 4.3 Aim 1: Between Group Comparisons The first study aim was to investigate differences between children who met the clinical cut off for EF deficits on the BRIEF-P (i.e., low EF group) and those who did not (i.e., comparison group). We hypothesized that children in the low EF group would exhibit significantly lower SEC, empathy, prosocial behavior with peers, peer acceptance, and closeness to their teachers than children in the comparison group. We also hypothesized that they would demonstrate significantly higher conflict with their teacher than children in the comparison group. To determine which children met the clinical cut off on the BRIEF-P, we used the Global Executive Composite score, which sums the scores from all five subscales on the BRIEF-P: 1 I conducted the same series of analyses using both multiple imputation and complete case analysis to compare findings. Findings were similar among the two analyses. The only difference was that some of the results which trended on significance using complete case analysis became significant using the MI dataset in which the full power of the sample was retained. 56 Inhibit, Shift, Emotion Control, Working Memory, and Plan/Organize (see Measures section for a more detailed description of each scale). Scores were transformed to T-scores. Scores at or above 65 indicate potential clinical significance (Gioia et al., 2003) and thus were included in the low EF group. Children with T-scores 64 and below were included in the comparison group. 4.3.1 Aim 1: Analytic Plan Aim 1 of the study was to test the hypothesis that children with low EF proficiency would demonstrate significantly lower closeness and higher conflict with teachers, and significantly lower SEC, empathy, prosocial behavior, and peer acceptance than their peers with proficient EFs. To test this hypothesis, we compared differences in means on continuous variables between the low EF group (n = 15) and the comparison group (n = 124), we conducted independent t-tests. Although it is ideal to have equally sized groups when conducting t-tests because it allows for optimal power, it is often not feasible in applied educational research that aims to evaluate real world school settings (Rusticus & Lovato, 2014). Such is the case in the present study. Researchers in the field have frequently used t-tests for unequal-sized groups, however, even when one group is several times larger than other with the caveat that analyses are more susceptible to Type 2 error (Rusticus & Lovato, 2014). Increased Type 1 error in independent t-tests is not a concern in unequal sample sizes between two groups so long as researchers report results from the “equal variances not assumed” column in SPSS if tests for homogeneity of variance between the two groups are not met (Rusticus & Lovato, 2014). Effect sizes for continuous outcomes were measured using Cohen’s d with 95% confidence intervals (Fritz et al., 2012). Recent empirically derived benchmarks for Cohen’s d based on meta-analyses of applied psychological research suggests that d values of 0.15, 0.36, and 0.65 be interpreted as small, medium, and large, respectively (Lovakov & Agadullina, 2021). Differences in gender were 57 tested via a Chi square test of independence, a non-parametric test that is appropriate for comparing differences in categorical data even when sample sizes are uneven (McHugh, 2012). 4.3.2 Aim 1: Results Table 4.1 presents skewness and kurtosis values for each of the variables of interest. Examination of skewness and kurtosis for all variables indicated that they were well within the normality range given the present sample size. For two-tailed t-tests, it is recommended that skewness falls within -2.08 and 2.77 in samples of 105 – 555 people to avoid Type 1 error inflation, whereas kurtosis has little influence on t-tests and can be as large as +/- 95.75 in educational and psychological research without influencing Type 1 error rate (Cain et al., 2017). Skewness values ranged from -0.38 for empathy to 1.70 for conflict. Kurtosis ranged from -0.11 behavioral self-regulation and 2.83 for conflict. 58 Table 4.1 Descriptive Statistics and Reliability for Variables of Interest Variable M SD Range Reliability (a) Skewness Kurtosis Minimum Maximum STRS Closeness 4.31 0.66 1.57 5.00 .88 -1.26 1.48 STRS Conflict 1.84 0.67 1.00 4.43 .90 1.70 2.83 BRIEF-P 1.32 0.34 1.00 2.69 .97 1.33 1.77 HTKS-E 1.11 0.50 0 1.97 .97 -0.71 -0.11 Empathy 3.60 0.87 1.33 5.00 .92 -0.38 -0.22 Prosocial Behavior 2.54 0.48 1.38 3.00 .92 -0.80 -0.47 SEC 4.52 1.08 1.71 6.00 .93 -0.51 -0.52 Peer Acceptance 3.76 1.00 1.33 5.00 .93 -0.55 -0.51 Note. STRS = Student-Teacher Relationship Scale (Pianta, 2001). BRIEF-P = Behavior Rating Inventory of Executive Function – Preschool Version (Gioia et al., 2003). HTKS-E = Head, Toes, Knees, Shoulders – Extended direct assessment of behavioral self-regulation (McClelland et al., 2014). SEC = Social and Emotional Competence. High scores on the BRIEF-P represent low EF proficiency. Out of the sample of 139 students, 15 (11%) met the clinical cut off on the BRIEF-P to form the low EF group with the remaining 124 (89%) forming the comparison group2. Levine’s test for equality of variances indicated that, despite the unequal group size, the assumption for independent t tests of equal variance was met for all but one variable: conflict. Table 4.2 displays the results of the independent t-tests for the between-group comparisons of children who met the 2 A comparison of descriptive descriptives by gender and by EF can be found in Appendices P and Q respectivelys. 59 clinical cut off for EF behavioral issues (low EF group) and those who did not (comparison group). Values were reported from the “equal variances not assumed” column for the conflict variable given that violation of the equal variance assumption can make analyses more vulnerable to Type 2 error (Rusticus & Lovato, 2014) although mean differences were statistically significant even when equal values were assumed (see Table 4.2). As hypothesized, there were statistically significant differences in quality of student-teacher relationships and indicators of social and emotional competence between the two groups. Children in the low EF group scored significantly lower on the HTKS-E direct assessment of behavioral self-regulation and teacher-ratings of SEC, empathy, prosocial behavior, and peer acceptance. They also scored significantly lower in teacher-rated closeness and significantly higher in conflict (see Table 4.2). Table 4.3 outlines effect sizes for between-group mean differences calculated using Cohen’s d, along with their 95% confidence intervals. Effects sizes ranged from moderate to large (Lovakov & Agadullina, 2021). In sum, children who met the clinical cut off on for EF deficits had significantly lower quality of student-teacher relationships, significantly lower scores on the direct assessment of self-regulation, and significantly lower scores in all teacher-reported measures of social and emotional competence compared to children who did not meet the cut off. Effect sizes for all teacher-reported variables were large and the effect size for the direct assessment of behavioral self-regulation was moderate. These findings support our a priori hypotheses. 60 Table 4.2 Independent Samples t-Test Statistics for Equality of Means Variable Comparison N = 124 Low EF N = 15 t-test for Equality of Means Confidence Interval of M difference (95%) M SD M SD t df Mean Difference Standard Error of Difference LL UL HTKS-E 1.14 0.50 0.86 0.42 2.12* 137 0.29 0.13 0.02 0.55 SEC 4.68 0.99 3.21 0.98 5.44** 137 1.47 0.27 0.93 2.00 Empathy 3.72 0.80 2.64 0.81 4.95** 137 1.08 0.22 0.65 1.52 Prosocial 2.60 0.44 2.03 0.49 4.75** 137 0.57 0.12 0.34 0.81 Closeness 4.37 0.63 3.83 0.75 3.04** 137 0.54 0.18 0.19 0.89 Conflicta 1.75 0.55 2.63 1.06 -3.17** 14.91 -0.88 0.28 -1.47 -0.29 Peer Accept. 3.89 0.92 2.67 0.97 4.83** 137 1.22 0.25 0.72 1.72 Notes. a = t statistic adjusted for unequal variances. * p = 0.04. ** = p. < .01. HTKS-E = Head, Toes, Knees, Shoulders – Extended direct assessment of self-regulation (McClelland et al., 2014). SEC= social and emotional competence. 61 Table 4.3 Effect Sizes for Between-Group Mean Differences Variable Effect size Confidence interval (95%) Cohen’s d LL UL HTKS-E 0.58 0.04 1.12 SEC 1.49 0.92 2.05 Empathy 1.35 0.79 1.91 Prosocial 1.30 0.74 1.86 Closeness 0.83 0.29 1.37 Conflict -1.43 -1.99 -0.86 Peer Acceptance 1.32 0.76 1.88 Notes. HTKS-E = Head, Toes, Knees, Shoulders Extended direct assessment of self-regulation proficiency (McClelland et al., 2014). SEC = social and emotional competence. LL = lower level and UL = upper level of the confidence intervals. Empirically derived guidelines for interpreting Cohen’s d effect sizes in applied psychology research are 0.15, 0.36, and 0.65 as small, medium, and large respectively (Lovakov & Agadullina, 2021). 4.4 Aim 2: Linear Regression Models The second aim of the study was to explore individual and joint associations of self-regulation proficiency and quality of student-teacher relationships to indicators of children’s social and emotional competencies over and above variance explained by age, gender, and EF group based on theoretical models that posit children’s self-regulation proficiency and quality of relationships with caregivers form the foundation for the development of social and emotional competencies in early childhood (Denham & Brown, 2010; Loomis, 2021). We also examined whether closeness or conflict with teachers moderated the association between self-regulation 62 proficiency and social and emotional competencies. Our exploratory analysis set out to answer the following questions: 1. After controlling for age, gender, and EF group, how well does children’s self-regulation proficiency estimate social and emotional competencies? 2. How much does the addition of the student-teacher relationship closeness and conflict variables to the regression model add to the estimation of social and emotional competencies above and beyond self-regulation? 3. Does student-teacher relationship quality have a conditional effect on the association between self-regulation proficiency and social and emotional competencies? 4.4.1 Aim 2: Analytic Plan To answer questions one and two, we employed hierarchical linear regression models using ordinary least squares (OLS) regression. Hierarchical regression analysis is useful for theory testing because it allows the researcher to enter variables in a predetermined order which aligns with the theoretical model of interest (Nathans et al., 2012). To answer question three, we investigated conditional processes by employing multiple linear OLS regression using a single-degree-of-freedom equation (Hayes & Matthes, 2009). Although it is possible to explore conditional effects in hierarchical regression models by adding interaction terms into the model as an additional block, doing so leads to a miscalculation of degrees of freedom that reduces power and thus increases the chance of Type 2 errors, especially since conditional effects tend to be of small magnitude in applied psychological research (Aguinis et al., 2005; Hayes, 2018). Moreover, the addition of interaction variables as an additional step in the hierarchical linear model artificially inflates F values, which can increase chances of Type 1 error (Nathans et al., 2012). Examining conditional effects of student-teacher relationship on relations between self- 63 regulation and indicators of social and emotional competencies in multiple linear regression model, in which self-regulation and relationship quality were quantified as a single regression coefficient, allowed for the correct calculation of degrees of freedom while also providing a more accurate F value (Rockwood & Hayes, 2020). Hierarchical Linear Models. Hierarchical linear regression models are useful in theory-building because they allow the researcher to enter variables into regression equations in an order that is relevant to the theoretical model guiding the analysis, while controlling other variables in order to examine the amount of variance explained by predictors over and above other variables (Nathans et al., 2012). This allows the researcher to examine the incremental predictability for each variable added to the model as well as changes to explained variance in the dependent variable (Nathans et al., 2012). Researchers can also separate the influence of single predictors on the dependent variable while holding other predictors constant to allow for a comparison of the relative importance of each predictor in explaining variation in the dependent variable (Rockwood & Hayes, 2020). Moreover, hierarchical regression models allow researchers to understand how predictor variables work in conjunction with one another to influence dependent variables (Hayes, 2018). Previous studies have demonstrated differential outcomes related to teacher-reported self-regulation and direct assessments of self-regulation (Howard et al., 2021; Robson et al., 2020). Thus, we compared two different models that separately examined teacher reports of self-regulation versus a direct assessment of self-regulation. Table 4.5 outlines the two different hierarchical OLS regression models utilized in the present study. The two models were applied to each of the dependent variables of interest: SEC, empathy, and prosocial behavior for a total of six separate models. Because peer acceptance did not meet the assumptions for OLS 64 regression and because it was strongly correlated with each of the other three dependent variables (see Table 4.4), peer acceptance was omitted from the series of regression analyses. In all models, age and gender were entered in the first block as control variables given that extant research indicates they are related to the dependent variables (e.g., Bouchard et al., 2020; Montroy et al., 2016; Zakszeski et al., 2020). We also included EF group as a control variable from the Aim 1 between-group analysis in Model 1 because we were interested whether behavioral self-regulation and quality of student-teacher relationships explained additional variance over and above the variance explained by EF group membership (i.e., whether students met the clinical cut off on the BRIEF-P or not).3 3 Because EF groups were determined using the clinical cut off score on the BRIEF-P (Gioia et al., 2003), EF group was not included as a control variate in Model 2, which included continuous BRIEF-P scores as a predictor variable. 65 Table. 4.4 Hierarchical Linear Regression Models Model 1 Model 2 Block 1: Control variables age, gender, EF groupa age, gender Block 2: Self-regulation proficiency HTKS-Eb BRIEF-Pc Block 3: Student-teacher relationship quality closenessd, conflicte closeness, conflict Note. a = EF group refers to whether students are in the Low EF group or comparison group in the between-group analysis from Aim 1. b = Head, Toes, Knees, Shoulders-Extended (McClelland et al., 2014), a direct assessment of behavioral self-regulation. c = Behavior Rating Inventory of Executive Function- Preschool Version (Gioia et al., 2003), teacher reports of EF proficiency. d = Closeness subscale on the teacher-reported Student-Teacher Relationship Scale (Pianta, 2001). e = Closeness subscale on the teacher-reported Student-Teacher Relationship Scale. Each model was regressed separately on dependent variables of empathy, prosocial behavior, and SEC. We entered mean scores for individual self-regulation proficiency in Block 2. We entered mean scores for quality of student-teacher relationships in Block 3 given extant research and theory that indicates children’s ability to self-regulate in the classroom is conditional upon their relationship quality with their teacher (Acar et al., 2021; Denham & Brown, 2010; Graziano et al., 2015; Liew et al., 2010). Specifically, in Model 1, children’s self-regulation proficiency as measured by the HTKS-E direct assessment was entered in the second block. In Model 2, children’s self-regulation proficiency as measured by teacher-rated EF proficiency via the BRIEF-P was entered in the second block. In both models, closeness and conflict with teachers were entered in the third block to examine whether the context of the student-teacher relationship quality explained additional variance in the dependent variable over and above individual self- 66 regulation proficiency. All continuous variables except for age were standardized by transforming them to z scores, which facilitated interpretation and meaningful comparisons among dependent variables. Relative importance of predictor variables was evaluated by examining the standardized regression co-efficients (β) to measure direct effects and zero-order correlations to measure indirect effects (see Nathan et al., 2012). These have been shown to perform comparably to other methods for evaluating relative importance of predictors, such as Pratt’s and Johnson’s methods, in similar sample sizes to the present study (Whittaker et al., 2002). Multiple Linear Regression Models. To answer the third research question of closeness or conflict with teachers moderated the correlation between children’s self-regulation proficiency and their social and emotional competencies, conditional effects were examined using separate multiple linear OLS regression models for each of the two self-regulation proficiency variables (i.e., BRIEF-P, HTKS-E) with each of the two indicators of student-teacher relationship quality (i.e., closeness, conflict) while controlling for age, gender, and EF group4 (see Hayes & Matthes, 2009; Hayes, 2018). Figure 4.1 depicts the moderation model. We used the PROCESS macro (Hayes, 2018) in SPSS Version 27 to estimate conditional effects using a single-degree-of-freedom interaction as depicted using the equation: Ŷ = a + b1X + b2W + b3(XW) + b4C + b5C + b6C 4 As previously mentioned, EF group was included as a control variable in models that included the HTKS-E direct assessment of behavioral self-regulation, but not in models that included teacher-rated EFs on the BRIEF-P because BRIEF-P scores were used to determine EF groups. 67 in which Ŷ represents the estimated social and emotional competence (i.e., SEC, empathy, or prosocial behavior), X represents the focal predictor (i.e., self-regulation proficiency), W represents the moderator (i.e., closeness or conflict), and C represents the control variables. In this equation, b3 estimates how the effect of self-regulation on the indicator of social and emotional competence changes as the quality of student-teacher relationship (i.e., closeness, or conflict) changes by 1 SD while holding constant age, gender, and EF group. Conditional effects for each of the predictors of interest were plotted graphically with the moderator variables (W = closeness, conflict) plotted at the 16th, 50th, and 84th percentiles as suggested by Hayes (Hayes, 2018; Rockwood & Hayes, 2020). Using the PROCESS macro for SPSS, we employed the Johnson-Neyman (J-N) technique as an inferential method to test for significance of the moderating effect of relationship quality on each indicator of social and emotional competence at various values of the moderator (Hayes, 2018). The J-N technique computes conditions and values at which a moderator exhibits statistically significant slopes in non-parallel regression lines (Hayes & Matthes, 2009). The J-N technique is more precise than analysis of simple slopes (see Aiken & West, 1991) in which researchers pick representative values of the moderator variable (e.g., mean, +1 SD, - 1 SD) and subsequently estimate effects of the focal predictor at each of the chosen values (Rockwood & Hayes, 2020). Although the pick-a-point approach allows the researcher to test for significance of a conditional effect for the chosen values, it does not test for significance across the range of moderator scores, whereas the J-N technique does, thus providing more precise estimates for the range of scores for which the moderator has a conditional effect on the relation between the focal predictor and outcome (Hayes & Matthes, 2009). When interpreting results, we considered alpha levels of p < .05 as significant. Following recent studies (Bayly & Bierman, 2021; Rucinski et al., 2018), we also 68 acknowledged moderation effects that trended on significance up to alpha levels of p < .10, given that effect sizes for interactions tend to be very small in applied psychological research (median f2 < .002 in a 30-year review of studies) and, thus, may not reach significance in sample sizes similar to the present study (Aguinis et al., 2005). 69 Figure 4.1 Moderation Model Notes. X = Independent Variable (self-regulation proficiency), W = Moderator Variable (quality of student-teacher relationship), Y = Dependent Variable (indicator of social and emotional competence). This model depicts the conditional effects of student-teacher relationship quality (W) on the correlation between self-regulation proficiency (X) and indicators of social and emotional competencies (Y). X W Y 70 Calculating Effect Sizes for Linear Regression Models. An informative standardized measure of effect size to measure the magnitude of the effect for both the overall regression model and individual predictors is Cohen’s f2 (Cohen, 1988; Selya et al., 2012). Cohen’s f2 can be calculated using the formula !! = $#$%!1 − $#$%! in which R2inc denotes the increase in R2 for a set of predictors over another set of predictors. Although few statistical software outputs include f2, due to its growing popularity for its utility with regression models, there exist online calculators that calculate the statistic and their confidence intervals. When calculating f2 for the entire regression model, f2 is equal to R2 because the fitted model is compared to a model with no predictors (Pituch & Stevens, 2016). Cohen’s (1988) benchmarks for interpreting f2 effect sizes for individual predictors are 0.02, 0.15, and 0.35, representing small, medium, and large effect sizes respectively. Confidence intervals for R2 were calculated using an online calculator that employed the formula $! ± ((1 − * 2 , - − . − 1)01&' in which R2 is the squared multiple correlation, a is the confidence interval percentage, SER2 is the standard error of R2, t is a t-value, k is the number of predictors in the regression model, and n is the total sample size (Cohen, 1988; Soper, 2021). 4.4.2 Aim 2: Results The following section outlines results from each of the regression models. First, we describe the process for checking assumptions and diagnostics of regression models. Then, we present results for the hierarchical regression models to answer research questions one and two. 71 Last, we present multiple linear regression models to answer research question three. Results are organized by dependent variables SEC, empathy, and prosocial behavior to allow for comparison and evaluation of regression models. 4.4.2.1 Checking Assumptions and Diagnostics for Regression Models All assumptions for OLS linear regression were met for models that included SEC, empathy, and prosocial behavior as dependent variables (see Tabachnick & Fidell, 2019 for a detailed description of assessing assumptions and diagnostics for regression analyses). The assumptions for normal distribution of errors and equal variances were not met for peer acceptance, however. It was, therefore, omitted from the regression analyses. The assumption of linearity was confirmed graphically by plotting residuals against predicted values of the dependent variable for each model. Normal distribution of errors was confirmed by examining quantile-quantile (q-q) plots of individual errors. The assumption for equal variances was checked by examining scatterplots of standardized errors against predicted values of the dependent variable. Multicollinearity was assessed by examining the variance inflation factor (VIF). VIFs larger than 4 may signal concerns with multicollinearity, which is common when independent variables are correlated and can contribute to Type 2 error, leading to the null hypothesis being falsely accepted (Lavery et al., 2019). VIFs for the independent variables in all models were 1.90 or lower providing confidence that multicollinearity was not a concern. Potential influential cases were examined given that OLS regression is particularly sensitive to outliers (Cohen et al., 2003). We identified multivariate outliers by examining cases with a Cook’s Distance higher than 1 or with residuals +/- 3 SD. We identified high leverage cases by examining leverage values and box plots for each of the independent variables. Models were fit with and without potentially influential cases to examine potential differences. There 72 were no discernable differences between models when potential influential cases were removed, so all cases were included in the final fitted models. 4.4.2.2 Correlations among Independent and Dependant Variables Table 4.5 presents the correlations among the independent and dependent variables. The most commonly cited benchmarks for interpreting correlation coefficient magnitudes were made by Cohen (1988), who suggested that coefficients around .10 are considered small, .30 are considered medium, and .50 or larger are considered strong. Cohen (1988) himself, however, suggested that these benchmarks should only be used as estimates in the absence of empirical benchmarks specific to the area being studied. Cohen’s benchmarks for correlational effect sizes have been shown in several meta-analyses in behavioral psychology to be over-estimates (Hemphill, 2003; Ferguson, 2009; Lovakov & Agadullina, 2021). A recent study that examined effect sizes from 134 published meta-analyses in social psychology suggested empirical benchmarks for behavioral variables as .12, .24, and .41 as small, medium, and large respectively (Lovakov & Agadullina, 2021). The benchmarks are applied in the present study when variables were measured using different methods. However, given that the common method variance in teacher ratings artificially inflates the strength of correlations (see Spector et al., 2019), the more conservative benchmarks set by Cohen (1988) were applied in interpretation of effect sizes between two teacher-reported variables. The HTKS-E direct assessment of behavioral self-regulation and BRIEF-P teacher ratings of EF were significantly and negatively related (rs(137) = -.28, p <.001, 95% CI [-.43, -.12]). The correlations were in the expected direction given that high HTKS-E scores represent high behavioral self-regulation whereas low BRIEF-P scores represent high EFs. The correlation was of medium magnitude (Lovakov & Agadullina, 2021). Behavioral self-regulation was most 73 strongly related to teacher-rated closeness with students, (rs(137) = .32, p <.001, 95% CI [.16, .46]), whereas it was not significantly related to teacher-rated conflict with students (rs (137) = .04, p = .63, 95% CI [-.13, .21]). EF proficiency, however, was significantly related to both closeness (rs (137) = -.35, p <.001, 95% CI [-.49, -.20]) and conflict (rs(137) = .53, p <.001, 95% CI [.40, .64]) with medium effect sizes, respectively (Cohen, 1988). EFs were also significantly related to teacher-ratings of SEC, empathy, prosocial behavior, and peer acceptance with large effect sizes (Cohen, 1988; see Table 4.2). Behavioral self-regulation was significantly and positively related to teacher ratings of children’s empathy with a medium effect size (rs(137) = .26, p = .002, 95% CI [.10, .41]). Positive correlations of small magnitude were observed between behavioral self-regulation and SEC (rs(137) = .14, p = .10, 95% CI [-.03, .30]), prosocial behavior (rs(137) = .10, p = .24, 95% CI [-.07, .26]), and peer acceptance (rs(137) = .12, p = .15, 95% CI [-.02, .31]), albeit not statistically insignificant at the alpha level p <.05. As expected, all indicators of social and emotional competence were significantly and positively related (see Table 4.2) and were of large magnitude (Cohen, 1988). 74 Table 4.5 Correlations Among Variables Variable 1 2 3 4 5 6 7 8 9 10 1. Age -- 2. Gender -.03 -- 3. BRIEF-P -.08 -.31** -- 4. HTKS-E .24** .16 -.28** -- 5. Closeness -.03 .23** -.35** .32** -- 6. Conflict -.03 -.18* .53** .04 .13 -- 7. Empathy -.06 .29** -.54** .26** .75** -.04 -- 8. Prosocial -.07 .26** -.70** .10 .45** -.46** .71** -- 9. SEC .01 .20* -.65** .14 .63** -.32** .79** .80** -- 10. Peer Acceptance -.04 .11 -.54** .12 .55** -.17* .62** .59** .69** -- Note. N = 139. **= p <.001 (2-tailed). *= p <.05 (2-tailed). Age measured in months. Gender dummy codes were Boys = 0, Girls = 1. BRIEF-P = Behavior Rating Inventory of Executive Function – Preschool Version (Gioia et al., 2003). High scores on BRIEF-P = low EF proficiency. HTKS-E = Head, Toes, Knees, Shoulder – Extended direct assessment of behavioral self-regulation (McClelland et al., 2014). SEC = Social and Emotional Competence. All variables were reported by teachers except HTKS-E. 4.4.2.3 SEC General social and emotional competence was measured using the SEC composite from the Teachers’ Rating Scale of Social Competence measure (Kam & Greenberg, 1998), which includes items pertaining to children’s intrapersonal and interpersonal social and emotional competencies to create a total score representing children’s overall SEC (see Appendix I for items). BRIEF-P + Student-Teacher Relationship Quality Models. Table 4.6 presents coefficients and statistics for the hierarchical linear model examining the joint contributions of 75 EF proficiency and quality of student-teacher relationship on SEC. The F-test for the hierarchical regression model explaining variance in teacher-rated SEC in children was significant (F(5, 133) = 47.06, p < .001, R2 = .64, 95% CI [.54, .72]) indicating that regression model that included EFs and quality of student-teacher relationship as independent variables fit the data better than the intercept-only model (i.e., model without independent variables, see Table 4.6). Empirically derived guidelines for interpretation of R2 values in social science research suggest that .04 represents the minimum practically significant effect size, .25 represents a moderate effect, and .64 represents a strong effect (Ferguson, 2009). EF proficiency explained 34% more variance than covariates alone (see Table 4.7) with R2 shifting from 4% of variance explained to 38% of the variance in SEC (F change(1, 135) = 74.85, p < .001, f2 = 0.52, 95% CI [0.28, 0.87]). Adding student-teacher relationship quality to the model explained an additional 26% of variance in SEC (F change(2, 133) = 47.32, p <.001, f2 = 0.35, 95% CI [0.16, 0.61]), indicating that the joint contributions of the two predictors explained more variance than either predictor alone. The most important predictor in the model was closeness (see Table 4.8). Although the direct effect of EF proficiency and closeness were of the same magnitude (r(137) = -.62 and + .62 respectively), closeness had a larger total effect (β = 0.55) compared to EF proficiency (β = -.0.31). Neither closeness nor conflict had a significant moderating effect on the correlation between EFs and SEC (F(1, 132) = 0.04, p = .84, f2 = 0.001, 95% CI [-0.01, 0.01]; F(1, 132) = 0.37, p = .44, f2 = 0.003, 95% CI [-0.01, 0.02], respectively). Thus, the significant and negative relation between EF deficits and SEC did not depend on levels of student-teacher closeness or conflict. (See Appendix M for graphs depicting the conditional models.) 76 Table 4.6 Regressing BRIEF-P and STR Quality on SEC Variable B SE B β t p 95% CI for B R2 Adj R2 SE F(5, 133) LL UL .64 .63 0.61 47.06*** Constant 0.13 1.03 0.13 .99 -1.90 2.16 Age 0.00 0.02 0.00 -0.07 .95 -0.03 0.03 Gender -0.15 0.11 -0.07 -1.31 .19 -0.37 0.07 BRIEF-P -0.31 0.07 -0.31 -4.34** .001 -0.45 -0.17 Closeness 0.55 0.06 0.55 9.60** .001 0.44 0.67 Conflict -0.27 0.07 -0.27 -4.06** .001 -0.40 -0.14 Note. *** = p > .001. B = Unstandardized Beta Coefficient. SE = standard error of the regression estimate. Β = Standardized Beta Coefficients. LL = lower level and UL = upper level of the confidence interval. BRIEF-P = Behavior Rating Inventory of Executive Function- Preschool Version (Gioia et al, 2003). High scores on the BRIEF-P indicate low EF proficiency. For every SD increase in teacher ratings on the BRIEF-P, predicted scores of teacher-rated SEC decreased by 0.31 SD on average after taking age and gender into account. For every SD increase in teacher-rated closeness with students, predicted scores of teacher-ratings of children’s SEC increased by 0.55 SD on average after taking age, gender, and BRIEF-P score into account. For every SD increase in teacher-rated conflict with students, predicted teacher-ratings of student SEC decreased by 0.27 SD on average after taking age, gender, BRIEF-P score, and teacher ratings of closeness with students into account. 77 Table 4.7 Model Fit and Effect Size: BRIEF-P + STR Quality on SEC Model R2 CI (95%) Adj R2 SE R2Change f2 dfs F Change p (F Change) LL UL Block 1: Age, Gender .04 -.02 .10 .03 0.99 .04 0.04 2, 136 2.78 .07 Block 2: BRIEF-P .38 .26 .50 .37 0.79 .34 0.45 1, 135 74.85** <.001 Block 3: STR .64 .55 .73 .63 0.61 .26 0.35 2, 133 47.32** <.001 Note. BRIEF-P = Behavior Rating Inventory of Executive Function- Preschool Version (Gioia et al, 2003). STR = student-teacher relationship quality. Cohen (1988) suggested effect sizes for f2 as 0.02, 0.15, and 0.35 as small, medium, and large respectively. Table 4.8 Predictor Importance: BRIEF-P + STR Quality on SEC Predictor Total Effect: β 95% CI for β Direct Effect: r 95% CI for r LL UL LL UL Age -0.00 -0.03 0.03 .01 -.16 .18 Gender -0.07 -0.37 0.07 .20 .03 .35 BRIEF-P -0.31 -0.45 -0.17 .62 .51 .71 Closeness 0.55 0.44 0.67 .62 .51 .71 Conflict -0.27 -0.40 -0.14 -.43 -.56 -.28 Note. BRIEF-P = Behavior Rating Inventory of Executive Function- Preschool Version (Gioia et al, 2003). High scores on the BRIEF-P indicate low EF proficiency. STR = student-teacher relationship quality. Total effect is measured by standardized beta weights (β), which indicate the contribution of each predictor to the regression equation while holding all other predictors constant. Direct effect is measured by zero-order correlations (r) which indicate the magnitude and direct of the relationship between predictors and dependent variables without taking other variables into account. Empirically derived guidelines for effect size interpretations of r in 78 applied psychological research are .12, .24, and .41 as small, moderate, and large, respectively (Lovakov & Agadullina, 2021). HTKS-E + STR Quality Models. Table 4.9 presents coefficients and statistics for the hierarchical linear model examining the joint contributions of behavioral self-regulation and quality of student-teacher relationship on SEC. Table 4.10 presents model comparisons with effect sizes. Although the F test for the hierarchical linear model that included HTKS-E scores of behavioral self-regulation and student-teacher relationship quality was significant for SEC (F(6, 132) = 33.35, p < .001, R2 = .60, 95% CI [.50, .70]), HTKS-E scores did not explain any additional variance (see Table 4.11) over and above age, gender, and EF group (F change(1, 134) = .36, p = .55, f2 = 0.002, 95% CI [-0.01, 0.02]). Student-teacher relationship quality, however, explained an additional 41% of variance above and beyond covariates (F change(2, 132) = 68.02, p < .001, f2 = 0.70, 95% CI [0.41, 1.13]). The most important predictor in the model was closeness, which had the largest total and direct effects in the model (see Table 4.11). When examining conditional effects of closeness and conflict on the relation between behavioral self-regulation proficiency and SEC, neither closeness nor conflict had a significant moderating effect. (F(1, 132) = 1.04, p = .31, f2 = 0.004, 95% CI [-0.02, 0.03]; F(1, 132) = 2.61, p = .11, f2 = 0.01, 95% CI [-0.02, 0.04], respectively). Thus, there was no significant relation between behavioral self-regulation and SEC, even after accounting for moderating effects of closeness or conflict. 79 Table 4.9 Regressing HTKS-E and STR Quality on SEC Variable B SE B β t p 95% CI for B R2 Adj R2 SE F(6,132) LL UL .60 .58 0.65 33.35*** Constant -0.58 1.12 -0.50 .62 -2.77 1.66 Age 0.01 0.02 0.03 0.56 .58 -0.02 0.04 Gender -0.06 0.12 -0.03 -0.50 .62 -0.29 0.17 EF Group -0.37 0.20 -0.12 -1.83 .07 -0.78 0.03 HTKS-E -0.09 0.06 -0.09 -1.41 .16 -0.20 0.03 Closeness 0.64 0.06 0.64 10.49** <.001 0.51 0.76 Conflict -0.40 0.06 -0.40 -6.55** <.001 -0.52 -0.28 Note. *** = p > .001. B = Unstandardized Beta Coefficient. SE = standard error of the regression estimate. β = Standardized Beta Coefficients. HTKS-E = Heads, Toes, Knees, Shoulders – Extended (McClelland et al., 2014). High scores on the HTKS-E indicate high behavioral self-regulation proficiency. For every SD increase in teacher-rated closeness with students, predicted teacher-ratings of student SEC increased by 0.64 SD on average after taking age, gender, EF group, and HTKS-E score into account. For every SD increase in teacher reports of conflict with students, predicted teacher-rated SEC decreased by 0.40 SD on average after taking age, gender, EF group, HTKS-E score, and teacher-rated closeness with students into account. 80 Table 4.10 Model Fit and Effect Size: HTKS-E + STR Quality on SEC Model R2 CI (95%) Adj R2 SE R2Change f2 dfs F Change p (F Change) LL UL Block 1: Covariates .19 .08 .30 .17 0.91 .19 0.23 3, 135 10.61*** <.001 Block 2: HTKS-E .19 .08 .30 .17 0.91 .002 0.002 1, 134 .36 .55 Block 3: STR .60 0.50 0.70 .58 0.64 .41 0.70 2, 132 68.02*** <.001 Note. HTKS-E = Head, Toes, Knees, Shoulders- Extended direct assessment of self-regulation (McClelland et al., 2014).STR = student-teacher relationship quality. Cohen (1988) suggested effect sizes for f2 as 0.02, 0.15, and 0.35 as small, medium, and large respectively. Table 4.11 Predictor Importance: HTKS-E + STR Quality on SEC Predictor Total Effect: β 95% CI for β Direct Effect: r 95% CI for r LL UL LL UL Age 0.01 -0.02 0.05 .01 -.16 .18 Gender -0.06 -0.30 0.17 .20 .03 .35 EF Group -0.12 -0.82 0.02 -.42 -.55 -.27 HTKS-E -0.09 -0.20 0.03 .13 -.04 .29 Closeness 0.64 0.52 0.76 .62 .51 .71 Conflict -0.40 -0.52 -0.28 -.43 -.56 -.28 Note. HTKS-E = Head, Toes, Knees, Shoulders- Extended direct assessment of self-regulation (McClelland et al., 2014). STR = student-teacher relationship quality. Total effect is measured by standardized beta weights (β), which indicate the contribution of each predictor to the regression equation while holding all other predictors constant. Direct effect is measured by zero-order correlation (r) which indicate the magnitude and direct of the relationship between predictors and dependent variables without taking other variables into account. Empirically derived guidelines 81 for effect size interpretations of r in applied psychological research are .12, .24, and .41 as small, moderate, and large, respectively (Lovakov & Agadullina, 2021). In sum, EFs, closeness, and conflict were all significant individual predictors of SEC, whereas behavioral self-regulation was not. The joint contributions of EFs, closeness, and conflict were additive, in that they explained more variance in the model together than on their own. Together they accounted for 63% of variance in the model, a moderate effect by empirically derived guidelines for interpretations of R2 (Ferguson, 2009). No significant moderation effects were observed for student-teacher relationship quality on the correlations between EFs and SEC or between behavioral self-regulation and SEC. Closeness was the most important predictor in both models, having the largest total and direct effects on SEC. 4.4.2.4 Empathy BRIEF-P + Student-Teacher Relationship Quality Models. Table 4.12 presents coefficients and statistics for the hierarchical linear model examining the joint contributions of EF proficiency and quality of student-teacher relationship on empathy. The F-test for the model was significant (F(5, 133) = 45.56, p < .001, R2 = .63, 95% CI [.54, .72]), indicating that regression model that included EFs and quality of student-teacher relationship as independent variables fit the data better than the intercept-only model (i.e., model without independent variables, see Table 4.12). EF proficiency explained 24% more variance than covariates alone (see Table 4.13) with R2 shifting from 9% of variance explained to 33% of the variance in empathy (F change(1, 135) = 48.58, p < .001, f2 = 0.32, 95% CI [0.14, 0.57]). Adding student-teacher relationship quality to the model doubled the variance in empathy explained by the 82 model to 63 % (F change(2, 133) = 54.71, p <.001, f2 = 0.43, 95% CI [0.21, 0.74]), indicating that the joint contributions of the two predictors were additive (Cohen et al., 2003). The most important predictor in the model was closeness (see Table 4.14). Conflict was not a significant predictor of empathy after taking age, gender, and closeness into account (see Table 4.12). When examining conditional effects of closeness and conflict on the correlation between EF proficiency and empathy, neither closeness nor conflict had a significant moderating effect (F(1, 132) = 1.07, p = .30, f2 = .002, 95% CI [-0.01, 0.02] ; F(1, 132) = 1.15, p = .28, f2 = .01, 95% CI, -0.02, 0.04), respectively). Thus, the significant and negative relation between EF deficits and empathy did not depend on levels of student-teacher closeness or conflict. 83 Table 4.12 Regressing BRIEF-P + STR Quality on Empathy Variable B SE B β t p 95% CI for B R2 Adj R2 SE F(5, 133) LL UL .63 .62 0.62 45.56*** Constant 1.25 1.04 1.20 .23 -0.81 3.30 Age -0.20 0.02 -0.07 -1.24 .22 -0.05 0.01 Gender 0.08 0.11 0.04 0.74 .46 -0.14 0.31 BRIEF-P -0.37 0.07 -0.37 -5.05** .001 -0.51 -0.22 Closeness 0.59 0.06 0.59 10.09** .001 0.47 0.70 Conflict 0.001 0.07 0.001 0.02 .99 -0.13 0.14 Note. *** = p < .001. B = Unstandardized Beta Coefficient. SE = Standard Error of the regression. β = Standardized Beta Coefficients. LL = lower level and UL = upper level of the confidence interval (CI). BRIEF-P = Behavior Rating Inventory of Executive Function- Preschool Version (Gioia et al, 2003). High scores on the BRIEF-P indicate low EF proficiency. STR = student-teacher relationship quality. For every SD increase in teacher reports of EF deficits, predicted teacher-rated empathy in children decreased by 0.37 SD on average, after taking age and gender into account. For every SD increase in teacher-rated closeness with students, predicted teacher-rated student empathy in children increased by 0.59 SD on average after taking age, gender, and BRIEF-P score into account. Conflict was not a significant predictor in the model. 84 Table 4.13 Model Fit and Effect Sizes: BRIEF-P + STR Quality on Empathy Model R2 CI (95%) Adj R2 SE R2 Change f2 dfs F Change p (F Change) LL UL Block 1: Age, Gender .09 .001 0.18 .07 0.96 .09 0.10 2, 136 6.42* .002 Block 2: BRIEF-P .33 .21 .45 .31 0.83 .24 0.32 1, 135 48.58** <.001 Block 3: STR .63 .54 .72 .62 0.62 .30 0.43 2, 133 54.71** <.001 Note. BRIEF-P = Behavior Rating Inventory of Executive Function- Preschool Version (Gioia et al, 2003). STR = student-teacher relationship quality. Cohen (1988) suggested effect sizes for f2 as 0.02, 0.15, and 0.35 as small, medium, and large respectively. Table 4.14 Predictor Importance: BRIEF-P + STR Quality on Empathy Predictor Total Effect: β 95% CI for β Direct Effect: r 95% CI for r LL UL LL UL Age -0.07 -0.05 0.01 -.06 -.11 .22 Gender 0.04 -0.14 0.31 .29 .13 .44 BRIEF-P -0.37 -0.51 -0.22 -.55 -.66 -.42 Closeness 0.59 0.47 0.70 .71 .62 .78 Conflict 0.001 -0.13 0.14 -.21 -.36 -.05 Note. BRIEF-P = Behavior Rating Inventory of Executive Function- Preschool Version (Gioia et al, 2003). High scores on the BRIEF-P indicate low EF proficiency. STR = student-teacher relationship quality. Total effect is measured by standardized beta weights (β), which indicate the contribution of each predictor to the regression equation while holding all other predictors constant. Direct effect is measured by zero-order correlations (r) which indicate the magnitude and direct of the relationship between predictors and dependent variables without taking other variables into account. Empirically derived guidelines for effect size interpretations of r in 85 applied psychological research are .12, .24, and .41 as small, moderate, and large, respectively (Lovakov & Agadullina, 2021). HTKS-E + Student-Teacher Relationship Models. Table 4.15 presents coefficients and statistics for the hierarchical linear model examining the joint contributions of behavioral self-regulation and quality of student-teacher relationship on empathy. The F test for the hierarchical linear model that included HTKS-E scores of behavioral self-regulation and student-teacher relationship quality was significant for empathy (F(6, 132) = 30.20, p < .001, R2 = .56, 95% CI [.46, .66]), indicating that the model that was significant from the intercept only model. Adding behavioral self-regulation to the model had a small, yet significant, increase in the amount of variance explained in children’s empathy scores (see Table 4.16). Closeness was the most important predictor, having the largest direct and total effect (see Table 4.17). 86 Table 4.15 Regressing HTKS-E and STR Quality on Empathy Variable B SE B β t p 95% CI for B R2 Adj R2 SE F(6, 132) LL UL .58 .56 0.66 30.20*** Constant 0.99 1.16 0.86 .39 -1.29 3.28 Age -0.02 0.02 -0.05 -0.88 .38 -0.05 0.02 Gender 0.16 0.12 0.08 1.35 .18 -0.08 0.40 EF Group -0.49 0.21 -0.15 -2.35** .02 -0.91 -0.08 HTKS-E 0.01 0.06 0.01 0.09 .93 -0.12 0.13 Closeness 0.65 0.06 0.65 10.43** <.001 0.53 0.78 Conflict -0.15 0.06 -0.15 -2.32* .02 -0.27 -0.02 Note. *** p < .001. B = Unstandardized Beta Coefficient. SE = Standard Error of the regression. β = Standardized Beta Coefficients. LL = lower level and UL = upper level of the confidence interval. HTKS-E = Heads, Toes, Knees, Shoulders - Extended. High scores on the HTKS-E indicate high self-regulation proficiency. t = trending towards significance. For every SD increase in teacher-rated closeness with students, predicted scores of teacher-rated empathy in children increased by 0.65 SD on average after taking age, gender, EF Group, and HTKS-E score into account. For every SD increase in teacher reports of conflict with students, predicted scores of teacher-rated empathy in children decreased by 0.15 SD on average after taking age, gender, EF group, HTKS-E score, and closeness with teachers into account. 87 Table 4.16 Model Fit and Effect Size: HTKS-E + STR Quality on Empathy Model R2 CI (95%) Adj R2 SE R2Change f2 dfs F Change p (F Change) UL LL Block 1: Covariates .20 .08 .32 .19 .90 .20 0.25 3, 135 11.54** <.001 Block 2: HTKS-E .23 .11 .35 .21 .89 .03 0.03 1, 134 4.34* .04 Block 3: STR .58 .48 .68 .56 .66 .35 0.54 2, 132 54.72** <.001 Note. HTKS-E = Head, Toes, Knees, Shoulders- Extended direct assessment of self-regulation (McClelland et al., 2014). STR = student-teacher relationship quality. Cohen (1988) suggested effect sizes for f2 as 0.02, 0.15, and 0.35 as small, medium, and large respectively. Table 4.17 Predictor Importance: HTKS-E + STR Quality on Empathy Predictor Total Effect: Standardized Beta (β) 95% CI for β Direct Effect: Zero-Order r 95% CI for r LL UL LL UL Age -0.02 -0.05 0.02 -.06 -.11 .22 Gender 0.16 -0.08 0.40 .29 .13 .44 EF Group -0.15 -0.91 -0.08 -.39 -.52 -.24 HTKS-E 0.01 -0.12 0.13 .23 .07 .38 Closeness 0.65 0.53 0.78 .71 .62 .78 Conflict -0.15 -0.27 -0.02 -.21 -.36 -.05 Note. HTKS-E = Head, Toes, Knees, Shoulders- Extended direct assessment of self-regulation (McClelland et al., 2014). STR = student-teacher relationship quality. Total effect is measured by standardized beta weights (β), which indicate the contribution of each predictor to the regression equation while holding all other predictors constant. Direct effect is measured by zero-order correlations (r) which indicate the magnitude and direct of the relationship between predictors and dependent variables without taking other variables into account. Empirically derived 88 guidelines for effect size interpretations of r in applied psychological research are .12, .24, and .41 as small, moderate, and large, respectively (Lovakov & Agadullina, 2021). When examining conditional effects of closeness and conflict on the association between behavioral self-regulation and empathy, conflict was a significant moderator (F(1, 132) = 6.15, p = .01, f2 = 0.03, 95% CI [0.01, 0.09]). J-N tests to probe significance regions of moderator values indicated that the relation between behavioral self-regulation and empathy was significant for children with low and average levels of conflict with teachers (conflict range -1.25 to -0.04 SD, p = .001 and .05 respectively) but not for children with above-average conflict levels (see Appendix N). For children who experienced higher than mean-level conflict scores (0.02 SD and above), behavioral self-regulation did not significantly predict children’s empathy. Conditional effects of closeness on the association between behavioral self-regulation and empathy trended on significance (F(1, 132) = 3.05, p = .08, f2 = .01, 90% CI [0.01, 0.04]). (See Appendix M for a graph depicting the conditional model). Cohen (1998) suggested effect sizes for f2 as 0.02, 0.15, and 0.35 as small, medium, and large respectively. Effect sizes for interaction effects are typically less than 0.01 in applied psychological research, however (Aguinis et al., 2005). 89 Figure 4.2 Conditional Effects of Conflict on Correlation of HTKS-E and Empathy Note. Lines represent fitted regression lines for predicted teacher-rated empathy, controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of closeness scores. MSE = standard error of the regression estimate. HTKS-E = Head, Toes, Knees, Shoulder-Extended direct assessment of self-regulation proficiency (McClelland et al., 2014). Conflict significantly moderated the relation between HTKS-E and empathy for children in the low and mid ranges of conflict but not for children with above mean conflict levels. In sum, different results were observed depending on whether self-regulation proficiency was measured via teacher-ratings of EF or the direct assessment of behavioral self-regulation. In the hierarchical linear regression model that examined joint effects of EFs and student-teacher relationship quality, EFs and closeness were significant predictors after taking age, gender, and EF group into account, but conflict was not. The effect of EFs and closeness were additive in that R2 = .27, MSE = 0.77 F(6, 132) = 7.95 p < .001 90 including both predictors in the model explained more variance in empathy than individual predictors alone (Cohen et al., 2003). Conflict had a significant moderating effect on the correlation between behavioral self-regulation and empathy, however. The association between behavioral self-regulation and teacher-rated empathy was significant for children with low to average amounts of conflict but not for children with above-average conflict with teachers. 4.4.2.5 Prosocial Behavior with Peers BRIEF-P + STR Quality Model. The coefficients and statistics for the hierarchical linear model examining the joint contributions of EF proficiency and quality of student-teacher relationship on prosocial behavior with peers is presented in Table 4.18. The F-test for the model was significant (F(5, 133) = 30.98, p < .001, R2 = .54, 95% CI [.43, .65]) indicating that regression model that included EFs and quality of student-teacher relationship as independent variables fit the data better than the intercept-only model (i.e., model without independent variables). From examining R2 values in the hierarchical linear model (see Table 4.19), EF proficiency explained 35% more variance than covariates alone with R2 shifting from 7% of variance explained to 42% of the variance in prosocial behavior (F change(1, 135) = 81.43, p < .001, f2 = 0.54, 95% CI [0.29, 0.91]). Adding student-teacher relationship quality to the model increased the explained variance in prosocial behavior to 54% (F change(2, 133) = 16.80, p <.001, f2 = 0.14, 95% CI [0.02, 0.26]). The most important predictor in the model was EF proficiency which had the largest total and direct effect (see Table 4.20). 91 Table 4.18 Regressing BRIEF-P and STR Quality on Prosocial Behavior Variable B SE B β t p 95% CI for B R2 Adj R2 SE F(5, 133) LL UL .54 .52 0.69 30.98** Constant 1.75 1.16 1.50 .14 -0.55 4.05 Age -0.03 0.02 -0.09 -1.53 .13 -0.06 0.01 Gender 0.04 0.13 0.02 0.31 .75 -0.21 0.29 BRIEF-P -0.36 0.08 -0.36 -4.46** <.001 -0.52 -0.20 Closeness 0.34 0.07 0.34 5.20** <.001 0.21 0.47 Conflict -0.29 0.08 -0.29 -3.84** <.001 -0.44 -0.14 Note. *** = p > .001. B = Unstandardized Beta Coefficient. SE = standard error of the regression estimate. β = Standardized Beta Coefficients. LL = lower level and UL = upper level of the confidence interval. BRIEF-P = Behavior Rating Inventory of Executive Function- Preschool Version (Gioia et al., 2003). High scores on the BRIEF-P indicate low EF proficiency. For every SD increase in teacher reports of EF deficits, teacher ratings of student prosocial behavior decreased by 0.36 SD on average after taking age and gender into account. For every SD increase in teacher-rated closeness with students, teacher-ratings of student prosocial behavior increased by 0.34 SD on average after taking age, gender, and BRIEF-P score into account. For every SD increase in teacher-rated conflict with students, teacher-ratings of student prosocial behavior decreased by 0.29 SD on average after taking age, gender, BRIEF-P score, and teacher ratings of closeness with students into account. 92 Table 4.19 Model Fit and Effect Size: BRIEF-P + STR Quality on Prosocial Behavior Model R2 CI (95%) Adj R2 SE R2Change f2 dfs F Change p (F Change) LL UL Block 1: Age, Gender .07 .01 .15 .06 0.97 .07 0.08 2, 136 5.29** .01 Block 2: BRIEF-P .42 .32 .56 .41 0.77 .35 0.54 1, 135 81.43** <.001 Block 3: STR .54 .46 .66 .52 0.69 .12 0.14 2, 133 16.80** <.001 Note. BRIEF-P = Behavior Rating Inventory of Executive Function- Preschool Version (Gioia et al, 2003). STR = student-teacher relationship quality. Cohen (1998) suggests effect sizes for f2 as 0.02, 0.15, and 0.35 as small, medium, and large respectively. Table 4.20 Predictor Importance: BRIEF-P + STR Quality on Prosocial Behavior Predictor Total Effect: β 95% CI for β Direct Effect: r 95% CI for r LL UL LL UL Age -0.03 -0.06 0.01 -.07 -0.23 0.10 Gender 0.04 -0.21 0.29 .26 .10 .41 BRIEF-P -0.36 -0.52 -0.20 -.64 -.73 -0.53 Closeness 0.34 0.21 0.47 .45 .31 .57 Conflict -0.29 -0.44 -0.14 -.45 -.57 -0.31 Note. BRIEF-P = Behavior Rating Inventory of Executive Function- Preschool Version (Gioia et al, 2003). High scores on the BRIEF-P indicate low EF proficiency. STR = student-teacher relationship quality. Total effect is measured by standardized beta weights (β), which indicate the contribution of each predictor to the regression equation while holding all other predictors constant. Direct effect is measured by zero-order correlations (r) which indicate the magnitude and direct of the relationship between predictors and dependent variables without taking other variables into account. Empirically derived guidelines for effect size interpretations of r in 93 applied psychological research are .12, .24, and .41 as small, moderate, and large, respectively (Lovakov & Agadullina, 2021). When examining conditional effects of student-teacher relationship quality on the association between EFs and prosocial behavior with peers, both closeness (F(1, 132) = 5.52, p = .02, f2 = .02, 95% CI [0.001, 0.07) and conflict (F(1, 132) = 11.91, p = .001, f2 = .05, 95% CI [0.01, 0.13]) were statically significant moderators. J-N tests for regions of statistical significance revealed no statistically significant transition points over the range of closeness scores, indicating that the moderating effect of closeness on the association between EFs and prosocial behavior was significant across the range of closeness scores (i.e., low, mid, and high; see Appendix N). EFs were the strongest predictor of prosocial behavior for children with low closeness. As closeness increased, the strength of the correlation between of EFs and prosocial behavior decreased, although the correlation remained significant, even for children with high closeness (see Figure 4.4). As conflict decreased, the correlation between EFs and prosocial behavior became stronger (See Figure 4.5). J-N tests for regions of statistical significance of the conditional effect of conflict on the correlation between EFs and prosocial behavior revealed that the correlation between EFs and prosocial behaviour was insignificant for children with very high levels of conflict (+ 1.80 SD and greater). 94 Figure 4.3 Conditional Effect of Closeness on Correlation of EFs and Prosociality Note. Lines represent fitted regression lines for predicted teacher-rated prosocial behavior with peers, after controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of closeness scores. MSE = standard error of the regression estimate. EFs were a significant predictor of prosocial behavior regardless of closeness levels with teachers, but EFs were the strongest predictor for children with low closeness with teachers. As closeness scores with teachers increased, the strength of the correlation between EFs and prosocial behavior decreased. R2 = .51, MSE = 0.51 F(5, 133) = 27.39 p < .001 95 Figure 4.4 Conditional Effect of Conflict on Correlation of EFs and Prosociality Note. Lines represent fitted regression lines for predicted teacher-rated prosocial behavior with peers, after controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of closeness scores. MSE = standard error of the regression estimate. BRIEF-P scores were a significant predictor of prosocial behavior with peers for children with low and mid conflict with teachers but not for children who had conflict scores of 1.80 SD or greater. HTKS-E + STR Quality Models. Table 4.21 presents coefficients and statistics for the hierarchical linear model examining the joint contributions of behavioral self-regulation and quality of student-teacher relationship on prosocial behavior with peers. Although the F test for the hierarchical linear model that included HTKS-E scores of behavioral self-regulation and student-teacher relationship quality was significant for prosocial behavior (F(6, 132) = 20.07, p < .001, R2 = .48, 95% CI [.37, .59]), HTKS-E scores did not explain any additional variance over and above age, gender, and EF group (see Table 4.22). Student-teacher relationship quality, R2 = .49, MSE = 0.53 F(5, 133) = 25.52 p < .001 96 however, explained an additional 29% of variance above and beyond covariates (F change(2, 132) = 36.82, p < .001, f2 = 0.41, 95% CI [0.20, 0.71]). Closeness and conflict were equally important predictors in the model, although conflict had a marginally higher total effect than closeness (see Table 4.23). When examining conditional effects of closeness and conflict on the correlation between behavioral self-regulation proficiency and prosocial behavior neither closeness nor conflict were significant moderators (F(1, 132) = .90, p = .35, f2 = .005, 95% CI [-0.02, 0.03]; F(1, 132) = 2.28, p = .13, f2 = .01, 95% CI [-0.02, 0.04] , respectively). Thus, there was no significant relation between behavioral self-regulation and prosocial behavior, even after accounting for moderating effects of closeness or conflict (see Appendix M for graphs depicting conditional models). 97 Table 4.21 Regressing HTKS-E and STR Quality on Prosocial Behavior Variable B SE B β t p 95% CI for B R2 Adj R2 SE F(6, 132) LL UL 0.48 0.45 0.74 20.07** Constant 0.93 1.32 0.71 .48 -1.68 3.54 Age -0.02 0.02 -0.05 -0.74 .46 -0.05 0.03 Gender 0.14 0.14 0.07 1.02 .31 -0.13 0.41 EF Group -0.29 0.24 -0.09 -1.20 .23 -0.77 0.19 HTKS-E -0.07 0.07 -0.07 -1.05 .30 -0.21 0.07 Closeness 0.44 0.07 0.44 6.08** <.001 0.30 0.58 Conflict -0.46 0.07 -0.46 -6.48** <.001 -0.60 -0.32 Note. *** = p > .001. B = Unstandardized Beta Coefficient. SE = standard error of the regression estimate. β = Standardized Beta Coefficients. LL = lower level and UL = upper level of the confidence interval. HTKS-E = Heads, Toes, Knees, Shoulders – Extended (McClelland et al., 2014). High scores on the HTKS-E indicate high self-regulation proficiency. For every SD increase in teacher-rated closeness with students, teacher-ratings of student prosocial behavior increased by 0.44 SD on average after taking age, gender, EF group, and HTKS-E score into account. For every SD increase in teacher reports of conflict with students, teacher-rated empathy is predicted to decrease by 0.46 SD on average after taking age, gender, EF group, HTKS-E score, and teacher-rated closeness with students into account. 98 Table 4.22 Model Fit and Effect Size: HTKS-E + STR Quality on Prosocial Behavior Model R2 CI (95%) Adj R2 SE R2Change f2 dfs F Change p (F Change) UL LL Block 1: Covariates .19 .08 .30 .17 .91 .19 0.23 3, 135 10.23** <.001 Block 2: HTKS-E .19 .08 .30 .16 .92 .001 0.001 1, 134 .003 .96 Block 3: STR .48 .37 .59 .45 .74 .29 0.41 2, 132 36.82** <.001 Note. HTKS-E = Head, Toes, Knees, Shoulders- Extended direct assessment of self-regulation (McClelland et al., 2014). STR = student-teacher relationship quality. Cohen (1998) suggests effect sizes for f2 as 0.02, 0.15, and 0.35 as small, medium, and large respectively. Table 4.23 Predictor Importance: HTKS-E+ STR Quality on Prosocial Behavior Predictor Total Effect: β 95% CI for β Direct Effect: r 95% CI for r LL UL LL UL Age -0.02 -0.05 0.03 -.07 -0.23 0.10 Gender 0.14 -0.13 0.41 .26 .10 .41 EF Group -0.09 -0.77 0.19 -.38 -.51 -0.23 HTKS-E -0.07 -0.21 0.07 .08 -.09 0.24 Closeness 0.44 0.30 0.58 .45 .31 .57 Conflict -0.46 -0.60 -0.32 -.45 -.57 -0.31 Note. HTKS-E = Head, Toes, Knees, Shoulders- Extended direct assessment of self-regulation (McClelland et al., 2014). STR = student-teacher relationship quality. Total effect is measured by standardized beta weights (β), which indicate the contribution of each predictor to the regression equation while holding all other predictors constant. Direct effect is measured by zero-order correlations (r) which indicate the magnitude and direct of the relationship between predictors and dependent variables without taking other variables into account. Empirically derived guidelines for effect size interpretations of r in applied psychological research are .12, .24, and .41 as small, moderate, and large, respectively (Lovakov & Agadullina, 2021). 99 In sum, results for regression models were heterogeneous for models with EFs and behavioral self-regulation. The correlation between behavioral self-regulation and prosocial behavior remained insignificant even after taking conditional effects of closeness and conflict into account. There were significant correlations between EFs and prosocial behavior, however, that were moderated by student-teacher relationship quality. The relation between EFs and prosocial behavior was significant regardless of children’s level of closeness with teachers. EFs, however, were a stronger predictor of prosocial behavior for children with lower closeness with teachers. As the degree of closeness increased, the strength of the correlation between EFs and prosocial behavior decreased. When examining conflict as a moderator, the correlation between EFs and prosocial behavior was significant for all but those who experience very high conflict with their teachers. As conflict between students and teachers decreased, the strength of the correlation between EFs and prosocial behavior increased. 4.5 Results Summary In sum, our hypothesis that children with low EF proficiency would demonstrate significantly lower student-teacher relationship quality and social and emotional competencies, on average, compared to their classmates with more proficient EFs was confirmed. We also observed that student-teacher relationship quality and children’s self-regulation proficiency jointly predicted more variance in indicators of social and emotional competence than either predictor alone. Closeness was the strongest individual predictor in most models. Finally, we observed a conditional effect of student-teacher relationship quality on the correlation between self-regulation and social and emotional competence in some, but not all, models. Closeness and conflict were significant moderators of the correlation between EFs and prosocial behavior, 100 whereas conflict was a significant moderator of the correlation between behavioral self-regulation and empathy. 101 Chapter 5: Discussion Kindergarten is a pivotal transition in a child’s life. Children’s experiences in kindergarten set the stage for subsequent school experiences, including the quality of their interactions with teachers and peers, their sense of belonging at school, and their academic achievement for many years to come (Blair & Raver, 2015; Pelletier & Corter, 2019; West, 2017). Of particular importance to a successful transition to formal schooling and a positive kindergarten experience are children’s social and emotional competencies (Hunter et al., 2018; Rademacher et al., 2021; Wenz-Gross et al., 2018). The results from the present study confirm those of previous research that children’s quality of relationships with teachers and their self-regulation proficiency are strong individual predictors of children’s social and emotional competence in kindergarten (Lee & Bierman, 2018; Rademacher & Koglin, 2019; Zendarkski et al., 2020). A novel and important addition to the field is our finding that the joint contribution of student-teacher relationship quality and children’s self-regulation proficiency explained significantly more variance in social and emotional competencies than either predictor alone. Children with more proficient self-regulation skills and higher quality relationships with teachers also had higher scores on teacher ratings of SEC, empathy, and prosocial behavior. These findings buttress theoretical models of social and emotional development in the early years, which posit that, together, supportive relationships with teachers and children’s individual self-regulation skills serve as the foundation for SEL at school (Denham & Brown, 2010; Lopez et al., 2021). Our findings lend support to extant research and theory which suggests that in the context of safe and supportive relationships with caregivers, children are better able to self-regulate, which in turn promotes their SEL (Valiente et al., 2020; Williams & Berthelsen, 2017). 102 The results from the present study clearly indicate that teachers’ ratings of their relationship quality with children are strongly related to how teachers perceive children’s social and emotional competencies. In particular, closeness with teachers was the strongest individual predictor of teachers’ perceptions of children’s social and emotional competencies in most regression models in the present study. This is an important finding in its own right, given that teacher ratings of young children’s social and emotional competence have been shown to forecast important outcomes for children throughout childhood, adolescence, and adulthood. For example, a study that examined preschool teachers’ ratings of children’s SEC on the same measure employed in the present study found that teachers’ perceptions of children’s SEC in preschool predicted children’s academic outcomes, behavioral problems, difficulties with peers, and need for supplemental services in both kindergarten and grade one, even after accounting for children’s academic skills in preschool (Hunter et al., 2018). Higher teacher-ratings of empathy have been shown to be related to lower instances of bullying behavior in elementary-school children (Elliot et al., 2019). Teacher’s ratings of prosocial behavior in the classroom also have been shown to be an important predictor of outcomes in adolescence and adulthood in a longitudinal study that followed children for 19 years (Jones et al., 2015). Researchers found that teacher-ratings of children’s prosocial behavior in kindergarten were a significant predictor of the number of years a child required medication to address internalizing or externalizing behaviors throughout high school. Teacher’s perceptions of children’s prosocial behavior also predicted whether children graduated from high school, completed a university degree, engaged in criminal activity, and found full-time, stable employment as young adults. The present study extends previous research that has observed a conditional effect of student-teacher relationship quality on the relation between children’s self-regulation and 103 kindergarten readiness (Graziano et al., 2015), learning behaviors (Acar et al., 2021), and academic performance (Suntheimer & Wolf, 2020). We observed a similar pattern in examining outcomes of children’s social and emotional competence. We found that student-teacher relationship quality moderated the correlation between behavioral self-regulation and children’s empathy and between EFs and children’s prosocial behavior. As children’s closeness with teachers increased, the strength of self-regulation as a predictor of prosocial behavior with peers decreased. Our findings suggest that children’s self-regulation proficiency may have a greater influence on how teachers perceive children’s prosocial behavior for students with whom teachers experience less closeness. Children with high closeness yet low EF proficiency were predicted to have prosocial behavior scores more than 1 SD higher than children with similarly low EF proficiency and low closeness with teachers. Although causal conclusions are precluded by the use of cross-sectional data in present study, this pattern buttresses theoretical models that suggest having close and supportive relationships with teachers may serve as a protective factor for children with low self-regulation proficiency in relation to their social competence (Loomis et al., 2021). Conflict also was observed to be a significant moderator for the correlation between behavioral self-regulation and empathy and between EFs and prosocial behavior. Whereas EFs were a significant predictor of prosocial behavior for children with low and average amounts of conflict with teachers, it was not for children with high levels of conflict with teachers. Similarly, behavioral self-regulation significantly predicted empathy in children with conflict levels below the mean but not for children with above-mean levels of conflict with teachers. For children who experienced high amounts of teacher-rated conflict, it did not matter whether they had low or high scores on measures of self-regulation; teachers still perceived them as having low empathy 104 and prosocial behavior with peers. This pattern suggests that high levels of conflict with teachers may be a risk factor for how teachers perceive children’s social competence, although, as mentioned previously, causal and directional conclusions are precluded by the cross-sectional observations in the present study. Nevertheless, our findings are of particular importance given the observation in the present study that children with low EF proficiency had significantly lower closeness with teachers and significantly higher conflict, putting them at a distinct disadvantage for how teachers perceive their empathy and prosocial behavior in the classroom. Significant findings for the conditional effects of student-teacher relationship quality on self-regulation differed, however, depending on how self-regulation was measured. Whereas closeness and conflict were found to moderate the correlation between teacher-ratings of EFs and prosocial behavior, they did not moderate the correlation between the direct assessment of behavioral self-regulation and prosocial behavior. Conversely, whereas closeness (marginally) and conflict moderated the correlation between scores on the direct assessment of behavioral self-regulation and empathy, student-teacher relationship quality did not moderate the correlation between teacher-rated EFs and empathy. The heterogenous findings were not wholly unexpected; previous research has consistently found differential results depending on whether self-regulation was measured using teacher-reports or direct assessments, which tend to be, at best, modestly correlated to one another (Howard et al., 2021; Robson et al., 2020; Tamm & Peugh, 2015). Consequently, recommended best practice for measuring self-regulation is to include both teacher reports and direct assessments to gain a fuller perspective of children’s self-regulation proficiency (Howard et al., 2021; Tamm & Peugh, 2015), a recommendation followed in the present study. 105 Two theories have been put forth to explain heterogenous findings among different self-regulation measures: One that focuses on the method of measurement (e.g., Howard et al., 2021) and the other that focuses on the construct being measured (e.g., Montroy et al., 2019). Regarding differential findings being linked to method of measurement, teacher reports of self-regulation are posited to be more ecologically valid than direct assessments because they take into account how self-regulation skills are applied in classroom contexts over a period of time (McCoy et al., 2019). Conversely, direct assessment tasks are decontextualized and measure children’s self-regulation at one point in time and are, thus, considered to have less ecological validity (Wallisch et al., 2018). Researchers have suggested that whereas direct assessments measure children’s capacity for self-regulation, teacher-ratings measure children’s self-regulation skills as applied in the classroom (Tamm & Peugh, 2015). Thus, the results from the present study might be interpreted that while teachers’ observations of children’s self-regulation skills in the classroom were a significant predictor of empathy regardless of the quality of student-teacher relationship, children’s capability for self-regulation was a significant predictor of empathy only for children with below-average conflict with teachers. Additionally, whereas children’s capacity for self-regulation did not significantly predict prosocial behavior with peers, teacher’s observations of children’s self-regulation in the classroom did, and the strength of correlation differed depending on the quality of relationship with teachers. Another explanation for the heterogenous findings may be that the BRIEF-P and HTKS-E measure different dimensions of self-regulation. Self-regulation is a multidimensional construct for which the definition and measurement have undergone much discussion and debate (e.g., Camerota et al., 2020; Karr et al., 2018; Rademacher & Koglin, 2020). In particular, there are differing perspectives in the field whether self-regulation in general, and EFs specifically, 106 should be measured as unidimensional or multidimensional constructs in early childhood (c.f., Lin et al., 2019; Montroy et al., 2019). For example, the BRIEF-P has five individual subscales designed to measure different dimensions of self-regulation: Inhibit, Working Memory, Shift, Plan/Organize, and Emotion Control. The authors suggest that the scales may be employed individually to look at specific dimensions of self-regulation or summed to create a single unidimensional score that represents overall executive functioning (Gioia, et al., 2003). There is evidence that in early childhood, EFs are not yet differentiated, and, thus, a unidimensional approach to measurement is preferred (Bardikoff & Sabbagh, 2017). The unidimensional perspective has been supported by studies that have found a single factor model is the best fit for factor analyses that examine multiple measures designed to tap into different dimensions of EFs (e.g., Karr et al., 2018; Lin et al., 2019). Others have posited that self-regulation in early childhood is more accurately measured as two dimensions: hot self-regulation and cool self-regulation (Acar et al., 2021; Montroy et al., 2019). This theory posits that top-down cognitive EFs, such as working memory, planning, and problem-solving, become impaired when bottom-up stress responses of the autonomic nervous system are activated, for example in situations of conflict (Blair & Raver, 2015). In such emotionally salient situations, hot self-regulation skills, such as inhibitory control and emotion regulation, are necessary to down-regulate the automatic responses of the sympathetic nervous system so that people can make use of their top-down cognitive self-regulation skills to access their working memory, pay attention, and make sound decisions (Raver & Blair, 2016). Extant research has found that cool and hot self-regulation tasks are related to different outcomes. For example, one study found that hot tasks predicted behavioral issues, but cool tasks predicted effortful attention and academic performance in preschoolers (Kim et al., 2013). 107 Although the HTKS-E direct task of behavioral self-regulation employed in the present study is theorized to measure both hot (inhibitory control) and cool (working memory, cognitive flexibility) dimensions of EFs together in action (Gonzales et al., 2021), a recent study found that the HTKS-E task loaded with other cool self-regulation tasks, not hot EF tasks, in a factor analysis (Rademacher & Koglin, 2020). The global composite score of EF proficiency on the BRIEF-P, however, includes subscales pertaining to both hot EFs (Inhibit, Emotion Control) and cool EFs (Working Memory, Shift, Plan/Organize). Indeed, examination of the correlations between HTKS-E scores and individual subscales on the BRIEF-P in the present study indicated that HTKS-E scores were most strongly related to subscales of cool EFs on the BRIEF-P (Working Memory, Shift, Plan) and only weakly related to subscales of hot EFs (Inhibit and Emotion Control; see Appendix R). Thus, it is possible that our heterogenous findings may reflect differences in how student-teacher relationship quality interacts with hot and cool self-regulation. From this perspective, our result might be interpreted as such: The relation between cool self-regulation and empathy were conditional on student-teacher relationship quality, but a combined measure of cool and hot self-regulation significantly predicted empathy regardless of relationship quality. Whereas the combined measure of cool and hot self-regulation predicted prosocial behavior with peers, a measure of cool self-regulation alone did not. This interpretation is partially supported by a recent study that examined whether student-teacher relationship quality moderated hot or cool self-regulation differentially in relation to learning in early childhood (Acar et al., 2021). Closeness with teachers significantly moderated the association between scores on hot self-regulation tasks and preschoolers’ learning behaviors. Hot self-regulation skills were significant predictors of children’s learning behaviors in those with high levels of closeness with teachers, but not for children with average or low levels of 108 closeness. No moderating effect between hot self-regulation and learning behaviors was observed for conflict, however. Moreover, neither closeness nor conflict were found to moderate relations between cool self-regulation and learning behaviors. Cool self-regulation was a significant predictor of learning behaviors regardless of student-teacher relationship quality. Another inconsistency in our findings was that quality of student-teacher relationship was not found to moderate the relation of EFs or behavioral self-regulation to the composite variable of SEC. One possible explanation for this finding might be that the conditional effect of student-teacher relationship quality differs depending on the specific social and emotional competence being examined, as was seen in the present study with empathy and prosocial behavior. For example, a study that examined preschoolers SEL profiles found three distinct groups: One that was proficient in neither interpersonal nor intrapersonal competencies (SEL risk group) and two SEL competent groups: SEL competent - constrained and SEL competent - social/expressive (Denham et al., 2012). The constrained group had more proficient intrapersonal competencies (e.g., self-regulation and emotional knowledge) but less proficient interpersonal competencies (e.g., prosociality) than the children in the social/expressive group. The social/expressive group was more proficient in intra- and interpersonal competencies (Denham et al., 2012). Relationship quality with teachers differed significantly among the three different groups. These findings indicate that individual differences in specific social and emotional competencies exist and relate to student-teacher relationships differentially (Denham et al., 2012). Hence, a general composite variable of SEC that integrates both intra- and interpersonal competencies into one total score may convolute findings. It may be more informative in future studies to examine specific social and emotional competencies individually. 109 5.1 Similarity of Results to Extant Research Our findings that children with low EF proficiency are at a disadvantage in the kindergarten classroom compared to their classmates with adequate EF proficiency echo those found in extant literature. To date, much of the research in this area has focused on social and emotional deficits and disorders, however (e.g., Brocki et al., 2019; Nucifora & Walker, 2021; Wang & Liu, 2020). The present study extends this work by investigating between-group differences in children’s social and emotional competencies. As hypothesized, teachers reported significantly less close and significantly more conflictual relationships with students who met the clinical cut off for low EF proficiency (i.e., low EF group) on the BRIEF-P compared with students who did not meet the cut off (i.e., comparison group). This finding aligns with extant research that has demonstrated that children with low EFs tend to have lower quality of relationships with their teachers (e.g., Acar et al., 2021; Ansari & Pianta, 2018; Bayly & Bierman, 2021; Hajovsky et al., 2021; Loomis, 2021). Our results substantiate previous findings that teachers’ perceptions of their relationships quality with children are significantly and positively linked to children’s self-regulation (e.g., Suntheimer & Wolf, 2020). Similarly, our results align with decades of research that has found relationship quality with teachers to be positively related to children’s social and emotional competencies (Pianta et al., 2016). For instance, children’s closeness with teachers, from both the teacher and the student perspective, was found to significantly predict prosocial behavior in children ages 4 to 9, after controlling for age and gender (Longobardi et al., 2021). Zendarski and colleagues (2020) found that higher quality of student-teacher relationships (high closeness, low conflict) was related to Grade 1 children’s prosocial behavior in children with and without ADHD. High closeness and low conflict in student-teacher relationships was found to be related 110 to empathy in elementary school students (Wilkinson & Bartoli, 2021). Similarly, in a recent person-centered analysis, Rademacher and colleagues (2021) found that children with high self-regulation skills and high empathy fell into the same profile, whereas children with low self-regulation skills and low empathy fell into the same profile. The finding in the present study that empathy was significantly related to both teacher-reports and a direct assessment of self-regulation provides greater support for the link between self-regulation and empathy in early childhood (Eisenberg, et al., 1996; Hein et al., 2018; Yan et al., 2020). The present study extends this body of research with the finding that the degree to which children’s self-regulation predicts empathy and prosocial behavior may depend on the quality of relationship teachers have with children. Similar to previous studies that have examined joint associations of self-regulation and student-teacher relationship on other school-related outcomes (Blair & McKinnon, 2016; Cadima et al., 2015; Portilla et al., 2014), we observed that joint contributions differed depending on the outcome examined. In some cases, the joint influence of student-teacher relationship quality and self-regulation proficiency was additive, in that they predicted more variance jointly in the indicator of social and emotional competence that either predictor alone. In other cases, closeness and conflict were found to moderate the correlations between self-regulation and indicators of social and emotional competencies. When examining SEC, EFs and student-teacher relationship quality were additive. Together higher quality student-teacher relationships and higher EFs predicted higher SEC. Like SEC, we observed that the joint contributions of EF proficiency and closeness predicted higher empathy scores. These findings extend those of extant research that has primarily focused on individual connections between self-regulation and empathy (e.g., Hein et al., 2018; Wolf & 111 McCoy, 2019; Yan et al., 2020) to suggest that student-teacher closeness may serve as a promotive factor over and above self-regulation for children’s empathy. In models that included teacher-ratings of EF, conflict offered no additional explanatory power for children’s empathy scores, however. Notably, the BRIEF-P asks teachers to report whether children’s EF-related behavior in the classroom is problematic and BRIEF-P scores were highly related to teacher-ratings of conflict. Thus, it seems that teacher ratings of conflict did not explain additional variance over and above teachers’ observations of EF deficits in children. Conditional effects of student-teacher relationship quality on the relation of behavioral self-regulation to empathy and EFs to prosocial behavior were observed, however. Similar to previous studies that examined student-teacher relationship quality as a moderator of the relations between EFs academic outcomes in early childhood (Graziano et al., 2015; Liew et al., 2010) we found that EFs were the strongest predictor of prosocial behavior for children with lowest teacher-rated closeness ratings. As EF proficiency increased, so too did ratings of prosocial behavior. Unlike previous studies of academic outcomes, however, which found no significant relations between self-regulation and academic outcomes for children with higher levels of student teacher-relationship quality, we found that EFs continued to be a significant predictor of prosocial behavior across all levels of closeness. The strength of the correlation between EFs and prosocial behavior diminished as closeness increased, however. Taken together, the findings suggest that closeness with teachers may serve as a protective factor for kindergarten children with low self-regulations skills in terms of academic performance and prosociality in the classroom. Experimental research in related areas has provided strong evidence that young children’s self-regulation proficiency is indeed dependent on relational contexts. For example, researchers 112 studying young children’s inhibitory control in delay-of-gratification tasks have found that children have a greater ability to exhibit inhibitory control when they trust the adult they are working with (Kidd et al., 2013; Michaelson & Munakata, 2016). Intervention studies that target quality of student-teacher relationships have demonstrated that when quality of relationships with teachers improve, so too does children’s self-regulation proficiency (Jones et al., 2013). The large magnitude of the correlation between student-teacher closeness and children’s performance on a self-regulation task in the present study provides further support for these experimental findings. Taken together, these results offer optimistic evidence that children who enter kindergarten with lower self-regulation proficiency need not necessarily be at a disadvantage in regard to how teachers perceive their social and emotional competence. Our results suggest that helping teachers build closer relationships with students with low self-regulation proficiency may positively influence teachers’ perceptions of students’ social and emotional competence. Minimizing teacher conflict with students of below-average EF proficiency may be especially important in relation to how teachers perceive students’ empathy and prosocial behavior. Similarly, providing opportunities for children to build self-regulation skills, which are particularly malleable at this age (Montroy et al., 2016) may serve children in forming closer relationships and reducing conflict with teachers (Blair & Raver, 2015). 5.2 Implications Our results have important implications for children who enter kindergarten with lower EF proficiency. More than ten percent of children in our public-school sample met the clinical cut off for EF deficits, the majority of whom were boys. These children were perceived as having significantly lower quality relationships with teachers, lower peer acceptance, and lower social 113 and emotional competencies than their other classmates. There are a variety of reasons why children enter kindergarten with lower EF proficiency. Exposure to chronic stress, trauma, and early life adversity impedes the development of EFs (Blair & Raver, 2012; Loomis, 2021; Lopez et al., 2021). Children with neurological differences, such as ADHD and autism, have been found also to have lower EF proficiencies than their peers without these designations (Nucifora & Walker, 2021). Montroy and colleagues (2016) found that self-regulation proficiency, as measured by the HTKS-E, typically develops throughout early childhood between the ages of 3 and 7, with as many as 35% of children being classified as “later developers” who experience gains in self-regulation proficiency around the age of six. Boys also are more likely to exhibit low EF proficiency in kindergarten (Zakszeski et al., 2020). Hence, providing extra supports for building close relationships with teachers may be especially important for these children who, may be at risk for poorer relational and social and emotional outcomes in kindergarten classrooms, according to our findings. For instance, one small randomized controlled trial found that when parents and teachers of children with disruptive behavioral problems participated in a program designed to boost positive parent-teacher relationships and student-teacher relationship quality during the first three months of kindergarten, children’s internalizing and externalizing behaviors improved (Eisenhower et al., 2016). Furthermore, parent and teacher behavior-related referrals significantly decreased in classrooms that received the intervention compared to those who did not. Findings revealed that student-teacher relationship quality improved for children with initially low teacher-reported closeness (-1 SD). Results from this study suggest that finding ways to support teachers, for example by building more positive parent-teacher relationships, is 114 another important area of inquiry regarding how to improve quality of student-teacher relationships. Together our results suggest that SEL programs which explicitly target quality of student-teacher relationship and self-regulation in conjunction with other social and emotional competencies may be especially effective. Reviews of evidence-based SEL programs have indicated that while many SEL programs explicitly target self-regulation skills, few explicitly target quality of student-teacher relationships and self-regulation together (for reviews see Blewitt et al., 2020; Gagne & Nwadinobi, 2019; Takacs & Kassai, 2019). A recent meta-analysis of the efficacy of school-based interventions that aim to improve student-teacher relationship quality, however, found that programs which included strategies to promote supportive relationships, repair relationships after negative interactions, and build children’s self-regulation and social and emotional competencies among the most effective for improving student-teacher relationship quality (see Kincade et al., 2020). Some examples of evidence-based programs that have been shown to simultaneous improve quality of student-teacher relationships, self-regulation, and social and emotional competence in young children include Promoting Alternative Thinking Strategies (PATHS; Fishbein et al., 2016; Seyhan et al., 2019), Tools of the Mind (Blair et al., 2018), and the REDI Head Start preschool program that integrates PATHS alongside SEL-focused literacy instruction (Bierman et al., 2017). Future research on SEL programs should examine outcomes for student-teacher relationship quality, self-regulation, and social and emotional competence in order to better understand the contributions of each to social and emotional development as well as the processes involved. SEL programs that target student-teacher relationships and self- regulation may be especially important for children with low EF proficiency who have a tendency toward more 115 internalizing and externalizing behavioral issues (Bierman & Sanders, 2021). To date, most programs designed to support children with low EF proficiency focus on targeting disruptive behavior in the classroom (Clifford et al., 2020). Such programs may be falling short of supporting children with low EF proficiency, however, because they are not sufficient to promote social and emotional competence in the classroom nor quality of relationships with teachers and peers (Bierman & Sanders, 2021). Our findings that children who met the clinical cut off for EF deficits had significantly lower scores in their quality of student-teacher relationships, behavioral self-regulation, and social and emotional competencies than their classmates, suggest that it may be important to understand how interventions affect this group of children specifically. For example, Flook and colleagues (2015) found that their SEL program had a larger effect on preschool children with low EF proficiency on their social competence than their classmates with adequate EF proficiency. Thus, universal intervention studies aimed at promoting social and emotional development should explicitly examine results for children with low EF proficiency separately to better understand program effects for children who are most at risk for poor relationship quality and social and emotional deficits. Important patterns may go undetected if it is assumed that SEL programs work for all children similarly. Greenberg and colleagues (2017) have discussed the value of universal SEL programs in schools as a public health approach for not only protecting children like those included in the low EF group from deleterious outcomes, but also for promoting well-being among the general population. Universal programs that target protective and promotive factors for public health have the potential to affect widespread positive influence even when only small numbers of people may be at risk because the programs reach such a wide population (see Greenberg et al., 2017 for a discussion of the prevention paradox). Our results suggest that targeting the quality of 116 student-teacher relationships and self-regulation in conjunction may not only protect children with low EF proficiency from negative social and emotional outcomes, but they also may promote positive outcomes for children who enter kindergarten with proficient EFs. Thus, SEL programs that target quality of student-teacher relationships and self-regulation may be especially effective as universal public health interventions, leading to a cascade of positive outcomes that impact people’s mental health, success at school, and social life both in childhood and throughout the lifespan (Greenberg et al., 2017; Jones et al., 2015; Sorensen et al., 2016). 5.2 Strengths and Limitations The following sections outlines some of the strengths and limitations of the present study. Strengths included the diverse sample of study participants, the close attention paid to children’s informed consent and children’s rights in research, the inclusion of multiple methods for measuring self-regulation, and the novel contribution of the exploration of joint influences of self-regulation and student-teacher relationship on kindergarteners’ social and emotional competence. Conclusions from the study are limited by the cross-sectional design, the reliance on teacher-ratings for measurement of student-teacher relationship quality and indicators of social and emotional competence, and the sample size, which did not offer enough power to detect small effect sizes. Each of these are discussed in turn below. 5.2.1 Generalizability A strength of the present study was the close attention paid to obtaining a representative sample to support the generalizability of the findings. We recruited teachers from schools situated in neighbourhoods with income levels that ranged from below the Canadian median to above. Our sample included both English and French-language classrooms, consisting of children who spoke 19 different languages as first language learned, an indicator of the range of 117 linguistic diversity in our sample. The diversity of our sample provides confidence that our findings can be generalized to a larger Canadian population of kindergarteners in urban public schools. 5.2.2 Children’s Research Rights and Informed Consent Our research design focused on children’s research rights. In addition to receiving parental/guardian consent for children’s participation, as required by the university and school district ethics boards, we also sought children’s informed consent. In our review of studies that involved self-regulation tasks with children, we found no mention of employing an informed consent process with children. Yet, research indicates that children in early childhood are capable of understanding the purpose of research studies and their research rights, both of which are necessary for informed consent, if researchers ensure a developmentally-appropriate process (Docket & Perry, 2011). We paid close attention to the informed consent process, and in particular children’s right to choose to participate in the direct assessment task and their right to stop the task at any time (see Methods section and appendices for a description). The fact that children chose to exercise these rights is evidence of their understanding of their research rights. We achieved higher reliability in HTKS-E scores than those in the original validation study (see McClelland et al., 2014), which may be linked to the informed consent process. Our study offers further evidence that kindergarten-aged children can participate in an informed consent process. As such, we recommend that future studies engage young children in a developmentally appropriate informed-consent process regardless of whether it is required of the university ethics or not. Doing so honours children’s rights as research participants and may also contribute to higher quality data. 118 5.2.3 Measurement Strengths and Limitations A strength of the present study is the inclusion of multiple methods for the measurement of self-regulation. Including both a teacher-report of self-regulation and a direct assessment allowed us to still include those children who chose not to participate in the HTKS-E task in our analysis through multiple imputation while also honouring children’s research rights. By including teacher ratings of self-regulation and social and emotional competencies in the multiple imputation, we were able to obtain more efficient estimates than using complete case analysis, while also retaining the full power of our sample. Extant research has found that adult reports and task-based assessments may tap into different aspects of the multidimensional self-regulation construct, and thus it is recommended that both be used in conjunction in early childhood research (Howard et al., 2021), a recommendation followed in the present study. Moreover, including multiple methods for measuring self-regulation is best practice for addressing the influence of method variance (i.e., the variation in dependent variables that results from method of measurement rather than the self-regulation construct itself; Tehseen et al., 2017). Whereas the magnitude of the correlations between teacher-rated EFs and teacher-rated indicators of social and emotional competencies was artificially inflated due to common method variance, the magnitude of correlations between the HTKS-E task and teacher-rated social and emotional competencies was attenuated as the result of uncommon method variance (see Spector et al., 2019 for a discussion on how method variance influences effect sizes). By comparing mono- and hetero-methods of measurement of self-regulation, we gained a clearer estimation of true effect sizes in the population of the relation between self-regulation and other indicators of social and emotional competence (i.e., effect sizes in the true population are likely greater than 119 the observed effect sizes for the HTKS-E direct assessment of self-regulation and smaller than the effect sizes observed for teacher-rated EFs). A measurement limitation in the present the study was a floor effect for the HTKS-E task, with 6% of participants (n = 8) scoring 0 on the measure. Floor effects decrease sensitivity in a measure and increase bias and uncertainty in results (Simkovic & Trauble, 2019). They can also prevent the detection of individual and joint effects in regression models (Simkovic & Trauble, 2019). A revised version of the HTKS task (HTKS-Revised) has recently been published to address this limitation (Gonzales et al. 2021). The HTKS-Revised offers a significant decrease in floor effect compared to the HTKS-E and better variability among children with lower EF proficiency (Gonzales et al., 2021). Thus, future research that employs the revised version of the measure will shed light on the magnitude of correlations between HTKS-R and indicators of social and emotional competence. A further measurement limitation is the use of teacher reports for both student-teacher relationship quality and indicators of social and emotional competence. We urge caution when interpreting these findings given that they may reflect teacher bias. It is conceivable that teachers may overestimate the social and emotional competency of children with whom they have greater closeness and underestimate the confidence of children with whom they experience greater conflict. Moreover, as previously discussed, common method variance between teacher-reported independent variables (i.e., student-teacher relationship quality, teacher-rated EFs) and teacher-reported dependent variables (i.e., SEC, empathy, prosocial behavior, and peer acceptance) artificially inflated effect sizes, thus providing overestimates of effect sizes in the true population (Tehseen et al., 2017). Future research using multiple methods for measuring student-teacher relationship quality would allow for the examination of both common and uncommon method 120 variance so as to gain a more accurate understanding of effect size of the influence of student-teacher relationship quality on kindergarteners’ social and emotional competencies. For example, several studies have utilized a drawing task with young children in which children are asked to depict themselves with their teacher (e.g., McGrath et al., 2017; Zee et al., 2020). Drawings are analyzed and coded for two positive and six negative dimensions of student-teacher relationship quality, which have been shown to be significantly related to teacher-ratings of closeness and conflict with students (Harrison et al., 2007). Similarly, empathy and prosocial behavior were measured solely using global teacher-rated assessments. Including multiple methods of measurement of these variables, for example parent, self, and peer reports, would not only address the statistical limitation of common method variance, but it would also incorporate multiple perspectives on children’s social and emotional competencies. In particular, having peer ratings of children’s social and emotional competencies would allow for multiple insider observations of children’s behavior that may capture behaviors of which teachers may not be aware (Boyce et al., 2020; Hughes & Im, 2016). Using a global assessment of empathy-responding behavior also did not allow for a more nuanced understanding of how student-teacher relationship quality might influence different dimensions of empathy. Future research would benefit from examining different aspects of empathy separately (e.g., cognitive, affective, personal distress; see Malti et al., 2016 for a discussion). 5.2.4 Strength and Limitations of Study Design A strength of our study design was that it allowed for comparisons between children with low EF proficiency to their classmates. The significant difference between the two EF groups suggests that children may be of two separate populations. Not accounting for these differences in an analysis may convolute findings, similar to not accounting for age or gender differences. 121 Accounting for EF group in the subsequent regression analyses in models that included the HTKS-E task allowed us to examine effects of quality of student teacher relationship and self-regulation while controlling for variance explained by the group differences between children with clinical scores of EF deficiency and those with proficient EFs. A limitation, however, is the small sample of children in the EF group. Future studies with larger samples would allow for the examination of the models for these two groups separately. Similarly, given the observed differences based on gender, a larger sample size would allow for the examination of models for different genders separately. Another strength is the use of the Johnson-Neymen technique in the present study to evaluate statistical significance of conditional effects of the moderator (i.e., closeness or conflict) on the correlation between self-regulation and indicators of social and emotional competence. Although it is common to use the “pick-a-point” approach to evaluate statistical significance of simple slopes at different arbitrarily chosen values (e.g., -1 SD, M, +1 SD; Aiken & West, 1991), this technique is not recommended because it does not allow for significance testing across the entire range of the moderator scores (Hayes & Matthes, 2009; Hayes & Rockwood, 2020). Yet, each of the studies reviewed here that examined moderation models employed this approach (Acar et al., 2021; Graziano et al., 2015; Liew et al., 2010). Consequently, it is unclear at which specific values the conditional effects of moderator shift from significance to insignificance. For example, Acar and colleagues (2021) found that the conditional effect of closeness on the relation between hot self-regulation and learning behavior was statistically significant for children with a score of 1 SD above the mean on closeness, but not for children with mean scores or scores at -1 SD below the mean. It is unclear, however, at which point between the mean and 1 SD the conditional effect transitions from insignificant to significant and whether the effect 122 remains significant beyond 1 SD. By employing the Johnson-Neymen test of significance across all regions of moderators, we were able to provide precise estimates for statistically significant conditional effects (See Appendix N). Despite the conditional process models employed in the present study being causal models, conclusions from the study were limited by its cross-sectional design, which precludes any pronouncements regarding directionality of predictions or causative influence. Although our findings provide empirical support for models of social and emotional development in early childhood, such as Denham and Brown’s (2010) prism theory of SEL, they are limited to a single point in time. The correlational design should be kept at the forefront when interpreting our findings, and we emphasize that the study design does not allow for conclusions that quality of relationships and self-regulation affect change in social and emotional competencies. Indeed, recent studies point to a much more complicated process in which student-teacher relationship quality, self-regulation, and social and emotional competence are transactional, with each influencing the other in a dynamic interplay (e.g., Goetz et al., 2021; Hajovsky et al., 2021; Lopez et al., 2021). Extant research suggests that children play an active role in their individual self-regulation while also influencing, and being influenced by, their changing environment (Lerner & Overton, 2008). Future studies should examine the directionality of the links between quality of student-teacher relationships and self-regulation in relation to children’s social and emotional competence. Studies should include multiple time points throughout early childhood, including before, during, and after kindergarten, to have a clearer picture of the processes involved in social and emotional development during this important transitional period. Cross-lagged models would allow for the investigation of reciprocal links. Findings from the present study indicate that these larger, more complex study designs are warranted. 123 Finally, findings with small effect sizes are inconclusive due to insufficient sensitivity as a result of sample size. Post hoc power analysis determined that, while there was sufficient power to identify medium and large magnitude effect sizes in all of our analyses, there was not sufficient power (i.e., sensitivity) to detect small effect sizes, which are especially common when employing two different methods of measurement. Moreover, effect sizes for conditional effects in applied psychological research tend to be very small (Aguinis et al., 2005). Thus, the insignificance of small effect sizes may be a result of Type II error and should be interpreted with caution. 5.3 Future Directions Future research should delve deeper into the investigation of processes and mechanisms involving quality of student-teacher relationships, self-regulation, and social and emotional competence in social and emotional development with sufficient sample sizes to detect small effects. In the interest of parsimony, the present study utilized a global composite of EFs, which aligns with research that suggest EFs are largely undifferentiated in early childhood and become more distinct as children age (see Bardikoff & Sabbagh, 2017). To date, however, there is still much debate regarding the differentiation of EFs in early childhood, and how EFs are specified in measurement models (see Camerota et al., 2020). Thus, future studies that examine different dimensions of EFs separately would be informative. In addition to teacher reports, studies should include direct assessments designed to measure both hot EFs (i.e., inhibitory control, emotion regulation) and cool EFs (working memory, cognitive flexibility, planning) so as to gain a clearer understanding of whether student-teacher relationship quality has a differential impact on different dimensions of EFs. Moreover, the trajectory and influence of these variables for 124 children with low EF proficiency in kindergarten should be examined as a separate group in longitudinal studies. The focus of the present study was to examine proximal outcomes linked to student-teacher relationship quality and self-regulation. Longitudinal designs would allow also for the examination of distal outcomes, such as mental health and well-being. Our results suggest that children who enter kindergarten with low EF proficiency may be at risk for poor relational and social and emotional outcomes. Thus, understanding how quality of student-teacher relationships and self-regulation skills training may impact the social and emotional development of these children, and related distal outcomes across their lifespan, may be of particular importance. Research suggests that children with low EF proficiency may need additional support beyond universal programs (Bierman & Sanders, 2021). Future studies should investigate whether children identified as having low EF proficiency in kindergarten would benefit from additional targeted interventions to improve quality of relationships with teachers and to build self-regulation skills. For example, programs such as Establish-Maintain-Restore (Cook et al., 2018; Duong et al., 2018) may be an effective way to enhance student-teacher relationship quality with students with lower self-regulation proficiency. The Fast Track Program (Conduct Problems Prevention Group, 2010) also has had great success by combining the universal PATHS program with a targeted intervention for children with higher incidence of aggression (Bierman et al., 2017). A similar model for children with low EF proficiencies might be beneficial in which children with low EF proficiency receive more concentrated time in activities found to promote self-regulation. For example, physical activity that also builds EFs, such as martial arts, yoga, team sports, and dance, has been shown to be especially important for the development of EFs (Diamond & Ling, 2016). Mindfulness practices for children ages 4 and up 125 also have been found to promote EFs (Flook et al., 2015; Schonert-Reichl et al., 2015; Thierry et al., 2016). For instance, a randomized controlled trial compared Canadian kindergarten children who took part in mindfulness program with those who did not found that children in the mindfulness program experienced significant improvements in teacher reports of prosocial behavior and hyperactivity and in children’s performance on HTKS task of direct assessment than the control group (Viglas & Perlman, 2017). Children need to enjoy the activity, however, and consistent and frequent practice are necessary as children are introduced to increasingly gradual challenges to see improvements in EFs (Diamond, 2013). For example, fun and engaging self-regulation games have demonstrated short-term improvements in the preschool classroom compared to a control group, with lasting effects observed at a four-month follow up (Keown et al., 2020). Importantly, to be most effective, teachers need to believe that children will succeed at the activities (Diamond & Ling, 2016). Future research should also examine other systemic influences that may influence student-teacher relationship quality, self-regulation, and social and emotional competencies. These include other influences from the home and school domains, such as children’s and teachers’ relationships with parents/guardians and the role of classroom and school climate. Additionally, larger systemic influences should be investigated, such as class size, support for teachers, and ideological perspectives, such as attitudes towards SEL. Experimental designs that include SEL interventions which target quality of student-teacher relationship and self-regulation will be especially informative. Ideally, these studies should include multiple informants. Most notably, children’s perspectives were absent in the present study. Previous research has demonstrated that not only can young children reliably report on the quality of their relationships with teachers, but their perspectives also differ from 126 those of teachers (Split et al., 2010; Walker & Graham, 2021; White, 2016). Moreover, previous studies have found that child and teacher perspectives of relationship quality differentially predict children’s outcomes (Rucinski et al., 2018; White, 2016; Whitehead-Arruda, 2021). Hence, future research should also examine whether children’s perceptions of student-teacher relationship quality are linked to their self-regulation and social and emotional competencies. Peer perspectives on student-teacher relationships and children’s social and emotional competencies could also be of value. Peer nominations allow for multiple perspectives on classroom climate and children’s behaviors (Hughes & Hee, 2016). They can be obtained reliably from children as young as four (Ladd & Mars, 1986). Outside observers’ perspectives would also be informative. For example, the Classroom Assessment Scoring System (CLASS; Pianta et al., 2008) has been employed in several studies that examine the relations of classroom climate to quality of student-teacher relationships, children’s self-regulation, and social and emotional competence (e.g., Abry et al., 2017; Ansari & Pianta, 2018; Walker & Graham, 2021). Finally, studies that include qualitative methods could provide further insight into the nature of student-teacher relationship quality, and how to improve it. It may be particularly beneficial to investigate student-teacher relationship quality with children identified as having low EF proficiency, given our finding that they have significantly lower quality relationships with teachers than their classmates. For example, McGrath & Van Bergen (2017) conducted interviews with kindergarten teachers regarding their relationships with disruptive students to investigate why some teachers had close relationships with these students and other teachers did not. They found that teachers’ attributions for disruptive behavior and emotional competence influenced student-teacher relationship quality. These qualitative findings suggest that similar investigations are warranted into whether building teacher literacy surrounding the 127 developmental differences in children’s self-regulation proficiency may influence teachers’ relationship quality with children with low EF proficiency. To understand young children’s perspectives of their relationship quality with teachers, studies have found that children’s drawings depicting themselves with their teachers accurately depict the emotional quality of their relationship and that their drawings align with teacher reports of student-teacher relationships quality (e.g., Harrison et al., 2007; McGrath et al., 2017). Conducting studies with children identified as having low EF proficiency could offer important insights into how to improve their relationship quality with teachers, particularly if they include perspectives of both teachers and students. 5.4 Conclusion Early childhood has been recognized as a sensitive developmental period in which foundational skills, such as self-regulation and social and emotional competencies, can be fostered when provided with supportive relational contexts (Harrington et al., 2020). Understanding children’s experiences in kindergarten is of primary importance as children begin to spend a large amount of their day at school. The transition to kindergarten poses novel demands on children’s social and emotional competence (Housman, 2017). Moreover, the transition to kindergarten is children’s introduction to formal schooling, which can impact school experiences and outcomes in subsequent years (Pelletier & Corter, 2019). Our intention with this study was to identify potential areas that may be important targets for interventions designed to promote social and emotional competence in early childhood. The results from the present study provide support for the importance of quality of student-teacher relationships and self-regulation in early social and emotional development. Our findings suggest that professional development for teachers on how to build close and supportive relationships 128 with their students may be one means of supporting children’s social and emotional development, especially for children who enter kindergarten with low EF proficiency. Helping children practice self-regulation strategies may offer a solid foundation on which to build other social and emotional competencies and enhance the quality of relationships children experience with teachers and peers. Building on a growing body of research that has examined quality of student-teacher relationships and self-regulation separately as important predictors of social and emotional competencies, our findings suggest that targeting the two areas simultaneously in SEL programs may be an effective framework for social and emotional development, especially during the sensitive period of development between ages 3 and 6 (Bierman et al., 2018). In turn, this positive foundation established in early childhood may be the impetus for a cascade of positive outcomes across children’s lifespan affecting their physical and mental health, learning, and behavior (Sege et al., 2017). Hence, introducing SEL programs that focus on relationships and self-regulation in kindergarten may offer an effective and cost-efficient public health strategy to address the growing epidemic of mental illness and promote social and emotional health and well-being across the population (Greenberg et al., 2017). The results presented here are especially pertinent given the rise in social and emotional difficulties and mental health issues in children since the onset of the COVID-19 pandemic, especially for children with preexisting special educational needs and behavioral issues (Asbury et al., 2021; Cost et al., 2021; Creswell et al., 2021). 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Ordinal versions of coefficients alpha and theta for likert rating scales. Journal of Modern Applied Statistical Methods, 6(1), 21–29. https://doi.org/10.22237/jmasm/1177992180 167 Appendix A: Initial Contact Letter for Principals CALM Study 2019: [H18-03740] Initial Letter of Contact – Version 1: February 21, 2019 Page 1 of 2 Promoting Young Children’s Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of “The CALM Curriculum” Research Study March 2019 Dear Greetings! I am writing to invite you to participate in a research study that I am conducting in kindergarten classrooms in the Vancouver School District. The research study that I am conducting is evaluatinge the CALM curriculum, a social and emotional learning (SEL) program designed to promote kindness and self-regulation in kindergarten children. CALM is a Canadian play-based universal social and emotional learning program. The educational program is designed to help children learn how to get along with their peers and adults, feel and show empathy for others, understand and regulate their emotions, and be successful in school. This study has received approval from UBC and VSB. (we only one kindergarten We are interested in developing an understanding of whether or not the “CALM Curriculum” has an effect on children’s relationship skills, development of empathy, emotional understanding, and success in school. To do so, we will be conducting a randomized controlled study; this means that half of the participating classes will be randomly chosen to participate in the “CALM Curriculum” and half will continue with their regular classroom curriculum. About CALM The CALM Curriculum is designed to promote healthy social-emotional development and prevent negative outcomes associated with poor social-emotional skills. It includes activities that research has found promote social-emotional skills, such as self-regulation, emotion awareness, self-control, and positive social behaviours, such as empathy and kindness. The “CALM Curriculum” covers the five competencies of Social and Emotional Learning (SEL) as delineated by the Collaborative for Academic, Social, and Emotional Learning (CASEL; www.casel.org) that include self-awareness, social awareness, self-management, relationships skills, and responsible decision-making. Attached is a flyer that describes some of the critical information for teachers. Could you please share this flyer with your Kindergarten teachers? Any teachers who are interested in participating may contact me (either by e-mail: Kimberly.schonert-reichl@ubc.ca OR phone 604-822-2215) or my project coordinator (jennaw@mail.ubc.ca). **As an incentive for participation in this important study, I will be happy to do a presentation (Pro-D) for your school staff or parents on topics related to students’ kindness, social and emotional learning, and ways to promote social and personal competency! Study Details: 1. Randomization: Half of the participating classes will be randomly chosen to participate in the CALM curriculum and half will continue with their regular classroom curriculum. A randomized controlled study is considered to be the best way to find out whether the program causes any changes. Teachers randomized to implement CALM will be provided with a one-day training session and be asked to implement CALM across 10 weeks. 2. Research activities: All teachers who choose to participate in the study will be asked to complete questionnaires on their students (in March & June), whether or not their class has been randomly chosen to take part in the CALM program. In classrooms randomly chosen to implement the CALM program, participating students will be asked to fill out a student satisfaction questionnaire about CALM in June. Approximately 10 students in each classroom that implements CALM will be asked to participate in an additional brief interview in June. All teachers will be asked to complete a CALM or SEL implementation diary across the 10 week of curriculum implementation. 3. Compensation: All participating teachers will receive a one-day TTOC and a $50 gift card. All students, whether participating or not, will get a small thank you gift. 168 Appendix B: Flyer for Prospective Teacher Participants Promoting Young Children’s Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of “The CALM Curriculum” Research Study What is the purpose of this study? The purpose of this study is to explore the feasibility of the CALM Curriculum – a Canadian play-based universal social and emotional learning program. The educational program is designed to help children learn how to get along with their peers and adults, feel and show empathy for others, understand and regulate their emotions, and be successful in school. The CALM Curriculum covers the five competencies of Social and Emotional Learning (SEL) as delineated by the Collaborative for Academic, Social, and Emotional Learning (CASEL; www.casel.org) that include self-awareness, social awareness, self-management, relationships skills, and responsible decision-making. The MindUP Program is a social and emotional learning program for children, designed to promote children’s social responsibility, psychological well-being, and academic success. Details & Timeline What will teachers be asked to do? Benefits of Participating What to do if you are interested in participating Please contact Research Coordinator, Jenna Whitehead (jennaw@mail.ubc.ca) and/or Principal Investigator, Dr. Kimberly Schonert-Reichl (Kimberly.schonert-reichl@ubc.ca), and we will set up a time to meet to discuss the research study with you. • You will receive a teacher-teaching-on-call (TTOC) to compensate for the time it takes to complete student assessments in November and again in May/June. • You will receive free CALM training and materials either during the study or after ($1600 value).. \ Dr. Kimberly A. Schonert-Reichl, Principal Investigator Jacqueline Maloney, MA, Co-Investigator • You will receive a token monetary honorarium as a thank you for participating. • Complete a teacher background survey (15 minutes) and a 20-minute survey per participating student, assessing their social behaviours at two timepoints (November 2019 & May 2020). • Coordinate with Project Coordinator, for a time that is convenient for data collection in your classroom: one day in fall 2019 & one day in spring 2020. • If randomized into CALM intervention group: o Attend a one-day (6-hour) CALM Training. o Implement the 10 CALM modules in the classroom over 20 weeks. o Complete a brief teacher satisfaction survey and interview in June (20 mins). • Complete a bi-weekly implementation diary, either about CALM (program group) or any SEL activities (control group) you implement over the course of this research study. Randomization: Half of the participating classes will be randomly chosen to participate in the CALM Curriculum and half will continue with their regular classroom curriculum. What will students be asked to do? All students who choose to participate in the study will be asked to participate in the following, whether or not their class has been randomly chosen to take part in the CALM curriculum: • 15-minute visit in October/November 2019 where we will hand out parental/guardian consent forms to students. • Two data collection classroom visits: one in November 2019 & one in May/June 2020, supervised by trained research assistants, where they will participate in a fun research game (5 – 10 minutes per student). Additionally, students in the CALM Curriculum classroom will also be invited to participate in individually-administered program satisfaction interviews (10 minutes each). • As a token of appreciation, we will provide small gifts of gratitude, for example a pencil or sticker, to all children after completion of the study. These gifts will be given to all children, whether they choose to participate in the research study or not. 169 Appendix C: Introductory Meeting with Perspective Teacher Participants KSR SEL LAB: Introductory Study Meeting Outline – CALM 2019 Study On arrival: • - Check in with Office Visitor Pass • - Connect with Principal if possible (make sure to know the Principal’s name!) List of Materials to Bring to Meeting: • Teacher consent forms • paper/electronic doc to get teacher’s preferred contact info • script • snacks (for example, cookies) Introduction • We hope we won’t take up too much of your time. Please feel free to eat your lunch or enjoy a snack as we describe the study. *Share snacks • Brief intro of everyone present Introduction of Kim & Lab’s work • Dr. Kim Schonert-Reichl has been working together with the Vancouver School Board on research studies for the last 20 years. Her lab has evaluated many different social and emotional learning programs, including Roots of Empathy and MindUP *Hand out flyer – if needed What is the current Study? • The purpose of our study is to evaluate a new play-based social-emotional learning program that has been created and piloted in British Columbia for the British Columbia context. The CALM Curriculum is aligned and linked with the BC & CASEL's Core Competencies. • It uses playful evidence-based activities to foster the skills children will need for life long success, including empathy, social responsibility and self-management. The CALM Curriculum is currently being implemented in schools in Chilliwack and Abbotsford. • We are interested in learning teacher and students’ thoughts about the program and how to make it better. We also want to know how the program compares to the regular kindergarten curriculum at promoting student self-regulation and social-emotional skills like self-awareness, problem-solving, and kindness. 170 • This study take a children’s right perspective; my dissertation Importance of this research 1. It is linked to BC curriculum’s social and personal competencies 2. It will help us further understand the importance of social and emotional learning in early childhood. 3. Through interviews, students also get to voice their opinions on important topics that affect their lives, • CALM video with teacher testimonials and connection to curriculum • CALM box of materials • Let’s look at this short video to give you some more information about the program and hear what other classroom teachers’ and principals’ experiences with the program. • Up until now the feedback has been anecdotal. This study is going to be the first systematic investigation of the program. 4. In past studies, students usually enjoy taking part in a research study and learning about the research process. Let us tell you a bit about the way the Study will work... ➢We also invite you to fill out questionnaires about each participating student: It will take approximately 15 minutes per student survey, and you will receive compensation for your time (either TTOC or an honorarium, whichever you prefer). ➢We will arrange a convenient time in the next few weeks to do a playful self-regulation game with each participating student to help us understand their self-regulation skills at the beginning and end of the research study. It’s a game based on the song Head and Shoulders, Knees and Toes. Students are challenged to try and do the opposite of the directions. This should take about 10-minutes per student, so we should be able to do this over one school day of your choice. ➢Once we collect this data, we will randomly choose teachers using a random computer generator to implement the CALM Curriculum or to continue with their regular curriculum. Half will be randomly chosen to do the program and half to continue business as usual, so you will have a 50/50 chance of implementing the program this school year. This type of study is called a randomized controlled trial, and it is considered the best way to determine whether a program is effective or not. Teachers who are randomly chosen to continue with their regular curriculum will still receive the CALM Curriculum training and materials after the training (a $1600 value) 171 ➢Teachers who are randomly chosen to implement the CALM Curriculum will participate in a one-day training in early January during a regular school day. We will provide you with an EOC for this day. ➢Teachers who are implementing the CALM Curriculum will do so over 20 weeks. They will have two weeks to implement each of the 10 modules. Based on feedback from teachers who have implemented the program, the program creators estimate that it take about 15 minutes of prep time and 45-minutes of classroom time over two weeks for each module. ➢During the 20 weeks, we’ll ask that every two weeks you complete a calendar the describes any social- emotional learning activities you did over the two weeks. Teachers implementing the CALM Curriculum will be asked to report on their experiences with each module. This should take about 15 minutes every two weeks. ➢At the end of the study (late May/early June), we will ask that teachers fill out surveys about participating students’ behavior again. Once again, we will compensate you for your time by providing you with an EOC or honorarium. We will also return to do the self-regulation game with participating students again. Students who receive the CALM Curriculum will also be provided with the opportunity to voice their opinions about the program in short one-on-one interviews at the end of the program (10 – 15 minutes). Important to know... • Our RAs have extensive experience doing research in schools. They have also run pilot studies with students this age. They will be administering the self-regulation game and interviews to participating students using kindergarten-friendly language. They will answer any questions students may have and provide support to those who need it. Students will be clearly explained their research rights, provided the choice to participate or not, and can stop any task at any time. • We will arrange all visits at your convenience so that students don't miss popular activities or events. • We will need a quiet room– to conduct the visits with students so we don’t disrupt the rest of your class and so students have privacy. ➢We’ll schedule a 15-minute visit to handout parental/guardian permission slips to students that we will ask you to please collect and return to us. Closing * hand out teacher consent forms * have teachers write down the email address and phone number they would like us to contact them at. Email these to Jenna after the meeting. 172 FAQs Will schools receive a report of the results? To protect teacher and student confidentiality, we do not provide reports on individual school results. However, we are happy to send you a copy of the overall results from the study upon your request after the analysis has been completed. Please email us with the request after the completion of the study. When will data collection visits take place? November/December 2019, May/June 2020 173 Appendix D: Permission Slip Visit Protocol Hi everyone! I’m happy to meet you. My name is [RA’s name] and I’m a researcher from the University of British Columbia. Do you know what a university is? (Invite participant to share ideas). The university is a school for grownups who want to learn more. Do you know what a researcher is? (Invite participants to share ideas). A researcher is someone from the university who wants to understand how things work and why they work that way. Researchers search for answers to important questions. For example, I wonder how kindergarten children learn new things. What do you think are some ways I could learn about Kindergarten children? (Invite student to share ideas). These are all great ideas, thank you! Because it has been a long time since I was in Kindergarten, and many things have changed since then, I would like to learn from you. You know the most about Kindergarten children because you are in Kindergarten right now! I would like to learn from you so we can make kindergarten better for everyone I wonder how Kindergarteners learn new things. What are some ways we could learn about how kindergarteners learn, do you think? (Ask children for ideas). Yes – one way could be to ask your teacher how you learn? Another way might be to watch you learn something new, like a new game. We will be doing both of these things in our research project. I am wondering if you’d like to take part. Before you decide whether you want to play the game or not, there are some important things for you to know to help you decide. - You need a grown up at home to sign a permission slip form to participate. We’ll be sending this home today. You can talk to your grown up to decide whether participating in the research project is right for you and your family. - It’s completely up to you whether you would like take part or not. Even if you decide you want to join, you can change your mind and stop whenever you want. No one will be upset if you change your mind. 174 - Also, the game we play is not a win-or-lose game. The game is just for fun. The goal is just to do the best you can. - We will not tell your teachers, principal, parents, or classmates how you did on the game. All of the information with your name on it will be kept in a locked room at the university. Let’s just make sure I’ve explained everything clearly. (Invite children’s response to each question.) - Do you have to participate in the research study? No! Please bring back your permission slip even if you decide not to participate just so we know your decision. - If you decide to take part in the study, can you stop any time you want? Yes! Anytime at all. - Does anyone have any questions? You can also ask us questions when we come back to play the game with you. If you do choose to participate: - You will get to play a fun game - What we learn from you and your teachers will help make school better for everyone. -Everyone in the class gets a small thank you present whether they choose to participate or not. Where is a good place to put your permission slip so you don’t forget to give it to your grown up today? Please ask them to read the permission slip, and then talk to them about the research project and see if it is something you might want to try. Please bring it back as soon as you have a chance to talk about 175 it with a grown-up at home. Please return it whether you decide yes or no so we know your decision. 176 Appendix E: Teacher Consent Form Page 1 of 9 TEACHER CONSENT FORM Promoting Young Children’s Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of “The CALM Curriculum” Research Study Principal Investigator: Kimberly A. Schonert-Reichl, PhD Professor, Department of Educational and Counselling Psychology, and Special Education Faculty of Education Director, Human Early Learning Partnership (HELP) University of British Columbia 604-822-2215 Co-Investigator: Jacqueline Maloney, MA Doctoral Student, Department of Educational and Counselling Psychology, and Special Education Faculty of Education University of British Columbia 778-227-2090 Sponsor: Fraser Valley Child Development Centre October 2019 Dear Teacher, We are writing to invite you to participate in a research study that we are conducting at your school. The study explores the feasibility and effectiveness of a social-emotional learning program, the CALM Curriculum, designed to promote social and emotional competence, including empathy and self-regulation, in young children. Our study, titled “Promoting Young Children’s Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of “’The CALM Curriculum’ Research Study,” will take place in elementary schools in the Vancouver School District from approximately October 2019 to June 2020. Your participation in voluntary 177 Page 2 of 9 Your participation is entirely voluntary, so it is up to you to decide whether or not to take part in this study. You have the right to refuse to participate in this study. If you decide to participate, you may still choose to withdraw from the study at any time without any negative consequences. Before you decide, it is important for you to understand what the research involves. This consent form will tell you about the study, why the research is being done, what will happen to you during the study, and the possible benefits, risks, and discomforts. Please take time to read the following information carefully before you decide. Your students’ participation is also voluntary. It is up to parents to decide whether or not to allow their child to take part in this study. They have the right to refuse to participate in this study or withdraw their child at any time. They need to sign the parental/guardian consent form before their child can participate. Trained research assistants with experiencing working with young children will explain the research activities to your students, as well as their research rights, in easy-to-understand language. Students will have the opportunity to decide whether to take part or not, even if they have received parental/guardian consent. Students can decide to stop the activities at any time. Who is conducting this study? This study is being organized by educators in the Vancouver School District and Dr. Kimberly A. Schonert-Reichl, a professor in the Faculty of Education at the University of British Columbia and Director of the Human Early Learning Partnership (HELP). This project is also linked to the BC Ministry of Education’s redesigned curriculum which includes a focus on promoting students’ social and personal competency, including empathy and self-regulation. Some of the data collected in the study will be used for the dissertation of Dr. Schonert-Reichl’s doctoral student, Jacqueline Maloney, to complete her PhD on children’s rights in research. We hope that the results of this study will help parents and educators better understand how to best promote young children’s emotional and social development and school success and therefore be better equipped to improve education for all. Listed below are several aspects of this project that we would like you to know. Who is funding this study? This study is being funded by the Fraser Valley Child Development Centre. What is the Purpose of this Study? The purpose of this study is to examine the feasibility and effectiveness of the “CALM Curriculum” – a Canadian play-based universal social and emotional learning program. The CALM educational program is designed to help children learn how to get along with their peers and adults, feel and show empathy for others, understand and regulate their emotions, and be successful in school. The CALM Curriculum is created to promote healthy social-emotional development and prevent negative outcomes associated with poor social-emotional skills. It includes activities that research has found to promote social-emotional skills, such as self-regulation, emotion awareness, self-control, and positive social behaviours, such as empathy and kindness through classroom lessons, games, and activities designed for young children. The 178 Page 3 of 9 “CALM Curriculum” covers the five competencies of Social and Emotional Learning (SEL) as delineated by the Collaborative for Academic, Social, and Emotional Learning (CASEL; www.casel.org) that include self-awareness, social awareness, self-management, relationships skills, and responsible decision-making. The “CALM Curriculum” incorporates the promotion of social and emotional competencies in every one of its ten modules. Teachers implement one module every two weeks and each module takes approximately 45 minutes of class time totally spread out over 2 weeks. More specifically, the program provides opportunities for children to enhance their social and emotional competence by engaging in self-regulation activities, songs, games, and through interactions with engaging puppets. Research on the different program components has shown them to promote the knowledge and skills associated with social and emotional competence, including an understanding of their energy levels and emotions, problem-solving strategies, impulse control, perspective-taking, and kindness. These social and emotional skills and knowledge have been shown to lead to increases in children’s positive social behaviours and school adjustment in other research studies. This new, innovative program was developed in British Columbia to fit our educational context. What will you be asked to do of you choose to participate in the study? In our research, we are interested in understanding whether or not the “CALM Curriculum” has an effect on children’s self-regulation, relationship skills, development of empathy, emotional understanding, and success in school. To do so, we will be conducting a randomized controlled study; this means that half of the participating teachers will be randomly chosen to implement the ten modules of the “CALM Curriculum,” beginning in January 2020 and half will continue with their regular classroom curriculum. All participating teachers will be asked to fill out questionnaires about participating students in their class as well as a background questionnaire and bi-weekly reports documenting any social-emotional learning programs being implemented in class. Specifically, study participation involves the following components. All participating teachers will be asked to complete the following: • Provide your written consent to participate in this study (see the end of this letter). • Coordinate times with the Research Coordinator that are convenient to distribute permission slips to students. (15 minutes) • Collect permission slips from the students. • Complete a brief questionnaire about yourself at two time points: November 2019 and May 2020. This questionnaire includes questions about your demographic background, teaching experience, and beliefs about social and emotional learning. Completing this questionnaire will take you approximately 20 minutes at both time points. All teachers are asked to complete this questionnaire, whether you are randomized into the CALM Curriculum group or business-as-usual group. • Complete a student-rating survey, both at the beginning and end of the study, for each of your participating students. Completing this questionnaire will take you approximately 20-30 minutes for each student at each time points. Note that you will be provided with a one-day teacher-teaching-on-call (TTOC) at each time point to allow you the time to complete the surveys. 179 Page 4 of 9 • Co-ordinate one day for each time point (fall 2019 and spring 2020) with the Research Coordinator for the researchers to come in to play a fun self-regulation game with participating students. Trained research assistants will conduct individual sessions with each participating student that will take approximately 5- 10 minutes. The self-regulation game is based on the song “Head and Shoulders, Knees, and Toes.” Similar to “Simon Says,” students will be asked to follow different directions like “touch your head” and “touch your toes. We will work closely together with you to schedule school visits at a time that is convenient for you and your class. • Complete a bi-weekly “implementation calendar” throughout the duration of the study. This is a brief survey in which you will be asked to answer questions and record modules related to any social and emotional learning activities that you implement during the duration of the study (approximately 10-15 minutes every two weeks). If you are randomly chosen to implement the “CALM Curriculum,” in addition to the above, you’ll be asked to: • Attend a 1-day training session (6-hour). This will be scheduled at your convenience, and (you will receive a TTOC to teach your class while you attend the training) • Implement the program as outlined in the curriculum. The program has 10 modules which are implemented over 20 weeks. Each module consists of approximately 45-minute of activities that are spread out over a two-week period. Prep time for each module takes about 15 minutes. • Complete a short participant satisfaction survey and phone interview about your experiences and perceptions of the “CALM Curriculum” (approximately 20 minutes). • Host research assistants in your class in May/June 2020 to conduct individually-administered (one-on-one) interviews with participating students, which will take approximately 15 minutes per student. Students will have a choice whether they want to participate in the interview or not. We will work closely together with you to schedule school visits at a time that is convenient for you and your class. What will students be asked to do as part of this study? Students will be asked to take home and return consent forms indicating whether parents/guardians give their permission for students to participate in the study, which includes collecting information from teacher surveys and school records related to school achievement and attendance. Students who receive consent from their parents will be invited to play a fun self-regulation game based on the song “Head and Shoulders, Knees and Toes” (5- 10 minutes). If you are randomly chosen to implement the “CALM Curriculum,” participating students in your class will also be invited to take part in individually-administered interviews with our trained research assistants, to gather more in-depth feedback about children’s perceptions of the “CALM Curriculum.” This approximately 10- minute interview will take place during one school day in May or June 2020. Students will be invited to use the program materials to respond to interview questions like, “What have you learned in the CALM Program?”, “Would you recommend the CALM Program to a friend?”, “What is your favourite thing about the program?”, and “What would you change about the CALM Program 180 Page 5 of 9 School records We will also be collecting information related to school achievement and attendance from students’ school records. What are the benefits of participating in this study? Teachers and students will have the opportunity to be part of an exploration into the feasibility of the implementing the “CALM Curriculum” and will help contribute to the growing knowledge about this SEL program for young children. All teachers who participate in this study, regardless of whether they are chosen to implement the program or not, will also receive all of the “CALM Curriculum” materials, including the lessons, books, Melvin the Monkey puppet, and Tucker the Turtle puppet. Teachers randomly chosen for the business-as-usual group will have the opportunity to complete the “Calm Curriculum” training and receive program materials after the study is over for the 2020/2021 school year. Will you be paid for participating in this research study? Teachers will receive a gift card in the amount of $50.00 as a token of appreciation for their time as well as 1-day TTOC at the beginning and end of the study to complete students’ assessments of behaviour. Are there any risks for participating in this research study? We do not think there is anything in this study that could harm or be bad for you. There are no known risks to teachers for completing these surveys. Your participation in this research study is voluntary. At any given time, you can decide to withdraw from participating in the study, even after signing this consent form. Refusing to participate or withdrawing from the study will not jeopardize your job or professional standing in any way. How will your privacy be maintained? Any personal information resulting from this research study will be kept strictly confidential. All documents will be identified by a code number only and kept in a secured information system and locked filing cabinet in Dr. Kimberly Schonert-Reichl’s research lab at UBC. The identity of the participants in this study (both teachers and students) will be entirely confidential. No information that discloses your or your students’ identities will be released or published without specific consent. Neither you nor your students or your school will be identified by name in any reports of the completed study. How will results be disseminated? Copies of the relevant data, which identify the participants only by code number, may be published in scientific journals, but no participant will be identified by name. However, research records identifying participants may be inspected in the presence of the Investigator or his or her designate by representatives of the UBC Research Ethics Board for the purpose of monitoring the research. Some of the data will be included in Ms. Maloney’s dissertation, which takes a children’s rights perspective and makes the argument for the importance of including children’s voices in research. 181 Page 6 of 9 Who can you contact if you have questions about the study? If you have any questions at any time during this project, you may contact Dr. Kimberly Schonert-Reichl at kimberly.schonert-reichl@ubc.ca, (604) 822-2215. You can also contact the research coordinator, Jenna Whitehead at jennaw@mail.ubc.ca (604) 603-3296 Who can you contact if you have any concerns or complaints about the study? If you have any concerns or complaints about your rights as a research participant and/or your experiences while participating in this study, contact the Research Participant Complaint Line in the UBC Office of Research Ethics at 604-822-8598 or if long distance e-mail RSIL@ors.ubc.ca or call toll free 1-877-822-8598. We would appreciate it if you could indicate on the slip provided on the attached page whether or not you would like to participate. Would you kindly sign and date the attached slip where indicated? Thank you very much for considering this request. Sincerely, Kimberly Schonert-Reichl, Ph.D. Principal Investigator Professor, Department of Educational and Counselling Psychology, and Special Education Faculty of Education, University of British Columbia E-mail: kimberly.schonert-reichl@ubc.ca Phone: (604) 822-2215 182 Appendix F: Parent/Guardian Consent Form Page 1 of 9 PARENT/GUARDIAN CONSENT FORM Promoting Young Children’s Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of “The CALM Curriculum” Research Study Principal Investigator: Kimberly A. Schonert-Reichl, PhD Professor, Department of Educational and Counselling Psychology, and Special Education Faculty of Education Director, Human Early Learning Partnership (HELP) University of British Columbia 604-822-2215 Co-Investigator: Jacqueline Maloney, MA Doctoral Student, Department of Educational and Counselling Psychology, and Special Education Faculty of Education University of British Columbia 778-227-2090 Sponsor: Fraser Valley Child Development Centre October 2019 Dear Parent/Guardian: We are writing to invite your child to participate in a research study that we are conducting at your child’s school. This study explores the feasibility and effectiveness of a social-emotional learning program, the CALM Curriculum, designed to promote social and emotional competence, including empathy and self-regulation, in young children. Our study, titled “Promoting Young Children’s Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of “The CALM Curriculum” Research Study,” will take place in elementary schools in the Vancouver School District from approximately October 2019 to June 2020. 183 Page 2 of 9 Your child’s participation is voluntary Your child’s participation is voluntary, so it is up to you to decide whether or not to allow your child to take part in this study. You and your child have the right to refuse to participate in this study. If you and your child decide to participate, you may still choose to withdraw from the study at any time without any negative consequences to education or other services to which you and your child are entitled or are presently receiving. If you wish for your child to participate in this study, you will be asked to sign this form. Before you decide, it is important for you to understand what the research involves. This consent form will tell you about the study, why the research is being done, what will happen during the study, and the possible benefits, risks, and discomforts. Please take time to read the following information carefully and discuss the study with your family before you decide. Even if you give your consent for your child to participate, your child can still choose whether or not to participate in any research activities directly involving your child. Trained research assistants will explain the research activities to your child, as well as their research rights, in easy-to-understand language, and your child will have the opportunity to decide whether to take part or not. Even if your child decides to take part in the research activities, your child can decide to stop the activities at any time. Please note that participation for teachers is also voluntary, and they may withdraw from the study any time, including teaching the CALM curriculum if the teacher feels it is not a good fit for the classroom. Who is conducting this study? This study is being organized by educators in the Vancouver School District and Dr. Kimberly A. Schonert-Reichl, a professor in the Faculty of Education at the University of British Columbia and Director of the Human Early Learning Partnership (HELP). This project is linked to the BC Ministry of Education’s redesigned curriculum which includes a focus on promoting students’ social and personal competency, including empathy and self-regulation. Some of the data collected in the study will be used for the dissertation of Dr. Schonert-Reichl’s doctoral student, Jacqueline Maloney, to complete her PhD on children’s rights in research. We hope that the results of this study will help parents, guardians, and educators better understand how to best promote young children’s emotional and social development and school success and therefore be better equipped to improve education for all. Listed below are several aspects of this project that we would like you to know. Who is funding this study? This study is being funded by the Fraser Valley Child Development Centre. What is the Purpose of this Study? The purpose of this study is to explore the feasibility and effectiveness of the “CALM Curriculum” – a Canadian play-based universal social and emotional learning program. The 184 Page 3 of 9 “CALM Curriculum” is designed to help children learn how to get along with their peers and adults, feel and show empathy for others, understand and regulate their emotions, and be successful in school. The “CALM Curriculum” is created to promote healthy social-emotional development and prevent negative outcomes associated with poor social-emotional skills. It includes activities that research has found to promote social-emotional skills, such as self-regulation, emotion awareness, self-control, and positive social behaviours, such as empathy and kindness through classroom lessons, games, and activities designed for young children. The “CALM Curriculum” covers the five competencies of Social and Emotional Learning (SEL) as described by the Collaborative for Academic, Social, and Emotional Learning (CASEL; www.casel.org) that include self-awareness, social awareness, self-management, relationships skills, and responsible decision-making. In our research, we are interested in understanding whether or not the “CALM Curriculum” has an effect on children’s self-regulation, relationship skills, development of empathy, emotional understanding, and success in school. To do so, we will be conducting a randomized controlled study; this means that half of the participating classes will be randomly chosen to receive the “CALM Curriculum” and half will continue with their regular classroom curriculum. Randomization of the classrooms into one of the two conditions (some classrooms will receive the “CALM Curriculum” and some classrooms will serve as a comparison group) will occur by using a random number generator. A randomized controlled study is considered to be the most effective way of determining whether the program is effective or not. Participating teachers and students will take part in the research activities whether or not their class is randomly chosen to implement the “CALM Curriculum.” What will your child be asked to do if you and your child agree to participate in the study? Teacher Surveys If you and your child agree to participate, your child’s teacher will be asked to complete surveys about your child’s social and emotional competence, social behaviours, and social relationships at 2 separate time points during the school year (approximately November 2019, and May/June 2020). Questionnaires will take approximately 20-30 minutes to complete per child. School Records In addition to obtaining information from your child’s teacher, if you and your child decide to participate, we will also be collecting information related to school achievement and attendance from students’ school records. Self-Regulation Game Your child will be invited to play a fun self-regulation game. Trained research assistants will play the game with your child. The game is based on the song “Head and Shoulders, Knees, and Toes.” Similar to “Simon Says,” children will be asked to follow different directions like “touch your head” and “touch your toes.” The game takes about 5 minutes per student. Program Satisfaction Interviews 185 Page 4 of 9 Participating students from each classroom that is implementing the “CALM Curriculum” will be invited to participate in one-on-one interviews with our trained research assistants to gather more in-depth feedback about children’s perceptions of the “CALM Curriculum.” This 15-minute interview will take place during one school day in May/June 2020. Your child will be invited to use the program materials to respond to interview questions like, “What have you learned in the CALM Program?”, “Would you recommend the CALM Program to a friend?”, “What is your favourite thing about the program?”, and “What would you change about the CALM Program?” What will children who are not participating in the study do during data collection sessions? Data collection with children will take place during regular class-time activities. Children not participating in the study will continue with regular class activities. Please note that agreeing or declining to have your child participate in this study applies only to the research portion of this project. This means that if you decline your child’s participation, they will not participate in any of the research activities involved in this study (games, interview). However, your child’s classroom teacher may still implement the “CALM Curriculum” and teachers who are randomly chosen to implement this program in their classroom will not exclude individual children from program activities, which align with the BC School Curriculum. What will your child’s class be learning if it is selected to receive the “CALM Curriculum”? To supplement your child’s regular school curriculum, the class will take part in 10 modules over a 20-week period. Each module takes approximately 45 minutes in total and is implemented across two weeks. In the “CALM Curriculum,” children learn about their energy levels, emotions, problem-solving strategies, self-control, perspective-taking, kindness, and more. This is done through fun activities, such as reading stories, singing songs, dramatic play, colouring worksheets, and playing “brain games.” In each module, children talk about different emotions, learn and practice different problem-solving strategies, and participate in activities to help them self-regulate. Module topics in the “CALM Curriculum” include: Module 1: Feeling Happy • Children explore the emotion happy. • Children learn to use the energy gauge to recognize how much energy their body has. • Children learn to use their breathing as a strategy for self-regulation. Module 2: Feeling Sad • Children explore the emotion sad. • Children participate in “brain games.” Module 3: Feeling Angry • Children explore the emotion angry. • Children learn problem-solving skills. 186 Page 5 of 9 Module 4: Tucker Turtle • Children learn the “Turtle Technique” for calming down. • Children learn more problem-solving skills. Module 5: Feeling Kind • Children explore the emotion kind. • Children do acts of kindness. • Children learn stretches for relaxation. Module 6: Super Friends • Children practice solutions for problem solving. • Children learn more stretches for relaxation. • Children learn new “brain games.” Module 7: Feeling Scared • Children explore the emotion scared. • Children continue to practice kindness, problem-solving, and self-regulation skills. Module 8: Feeling Lonely • Children explore the emotion lonely. • Children apply problem-solving skills to moral dilemmas. Module 9: Feeling Jealous • Children explore the emotion jealous. • Children continue to practice kindness, problem-solving, and self-regulation skills. Module 10: Feeling Loved • Children explore feeling loved. • Children continue to practice kindness, problem-solving, and self-regulation skills.What are the benefits of participating in this study? Your child’s participation will help contribute to the growing knowledge about social and emotional learning (SEL) in schools and help to determine whether SEL has an effect on students’ academic and social-emotional competence (such as kindness and emotion regulation) and well-being. This study will also give your child the opportunity to learn about what is involved in participating in a scientific research study. Are there any risks for participating in this research study? We do not think there is anything in this study that could harm or be bad for your child. There are no known risks for students who participate in the game and interview. Your child’s participation in the study is voluntary, and your child may withdraw from participating in the study at any time without penalty. Participants also do not have to answer any question that they do not want to answer. It is important for you to know that our interview is not a test and there are no right or wrong answers – we are not in any sense “testing” the children. We are only interested in finding out children’s opinions and feelings. We hope that the results of this study will help educators and parents better understand the way that early elementary school students think and feel, and lead to improvements in educational programs. 187 Page 6 of 9 How will your child’s privacy be maintained? The identity of the participants in this study (both teachers and students) will be entirely confidential. Their responses will be kept separate from their identities and will not be shared with their teachers or other school personnel. Your child’s responses may be published in research reports, but your child will not be identified by name, school, or city in any reports of the completed study. All documents will be identified only by a code number and kept in a secured information system and locked filing cabinet. Only the researchers and research assistants will know the identity of the participants in this study (both teachers and students). No information that discloses your child’s identity will be released or published without your consent unless required by law. Copies of the relevant data, which identify the participants only by code number, may be published in scientific journals, but no participant will be identified by name. However, research records identifying participants may be inspected in the presence of the Investigator or her designate by representatives of the UBC Research Ethics Board for the purpose of monitoring the research. Will your child be compensated for participating in the study? As a token of appreciation, we will provide small gifts of gratitude, for example a small toy or sticker, to all children after completion of the study. These gifts will be given to all children whether they choose to participate in the research study or not. How will results from the study be shared? Findings from the study, in which participants are not identified by name and only identified by code number, may be published in reports and scientific journals, and/or included in presentations. Some of the data will be included in Ms. Maloney’s dissertation, which takes a children’s rights perspective and makes the argument for the importance of including children’s voices in research. Who can you contact if you have questions about the study? If you have any questions at any time during this project, you may contact Dr. Kimberly Schonert-Reichl: kimberly.schonert-reichl@ubc.ca, (604) 822-2215 or research coordinator, Jenna Whitehead at jennaw@mail.ubc.ca, (604)-603-3296. Who can you contact if you have any concerns or complaints about the study? If you have any concerns or complaints about your rights as a research participant and/or your experiences while participating in this study, contact the Research Participant Complaint Line in the UBC Office of Research Ethics at 604-822-8598 or if long distance e-mail RSIL@ors.ubc.ca or call toll free 1-877-822-8598. We would appreciate it if you could indicate on the slip provided on the attached page whether or not your child has your permission to participate. Would you kindly sign and date the attached slip where indicated? We would appreciate it if your child could return the bottom portion of the slip to school tomorrow. 188 Page 7 of 9 Thank you in advance for considering this request. Sincerely, Kimberly Schonert-Reichl, Ph.D. Principal Investigator Professor, Department of Educational and Counselling Psychology, and Special Education Faculty of Education, University of British Columbia E-mail: kimberly.schonert-reichl@ubc.ca Phone: (604) 822-2215 189 Page 8 of 9 PARENT/GUARDIAN CONSENT FORM (KEEP THIS PORTION FOR YOUR RECORDS) You understand that your child’s participation in the above study is entirely up to you. You or your child have the right to refuse to participate. Even if you give your child permission to participate, you or your child are free to withdraw from the study at any time without any negative consequences. Your signature indicates that you consent for your child to participate in this study. PLEASE CHECK ONE YES, I agree to my child participating in this project. NO, my child does not have my permission to participate. Parent’s Signature Printed Name Date Child’s Name Study Title: Promoting Young Children’s Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of “The CALM Curriculum” Research Study Principal Investigator: Kimberly Schonert-Reichl, Ph.D. Principal Investigator. Professor, Department of Educational and Counselling Psychology, and Special Education Faculty of Education, UBC E-mail: kimberly.schonert-reichl@ubc.ca Phone: (604) 822-2215 Research Coordinator: Jenna Whitehead, M.A. Faculty of Education, UBC E-mail: jennaw@mail.ubc.ca Phone: (604) 603-3296 190 Page 9 of 9 (DETACH HERE AND RETURN TO SCHOOL) PARENT/GUARDIAN CONSENT FORM You understand that your child’s participation in the above study is entirely up to you. You or your child have the right to refuse to participate. Even if you give your child permission to participate, you or your child are free to withdraw from the study at any time without any negative consequences. Your signature indicates that you consent for your child to participate in this study. PLEASE CHECK ONE YES, I agree to my child participating in this project. NO, my child does not have my permission to participate. Parent’s Signature Printed Name Date Child’s Name Study Title: Promoting Young Children’s Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of “The CALM Curriculum” Research Study Principal Investigator: Kimberly Schonert-Reichl, Ph.D. Principal Investigator. Professor, Department of Educational and Counselling Psychology, and Special Education Faculty of Education, UBC E-mail: kimberly.schonert-reichl@ubc.ca Phone: (604) 822-2215 Research Coordinator: Jenna Whitehead, M.A. Faculty of Education, UBC E-mail: jennaw@mail.ubc.ca Phone: (604) 603-3296 191 Appendix G: Cover Letter for Teacher Surveys November, 2019 Dear Participating Teacher, Thank you for participating in the Promoting Young Children’s Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of “The CALM Curriculum” Research Study. We are thrilled that you have agreed to participate in this important new study evaluating the effectiveness of an SEL program for kindergarten children. Note that your participation is extremely important and valued, and is completely voluntary. There are no right or wrong answers to the questions, and you may opt out of answering any questions. Any information that you provide will be kept confidential. We will not be identifying any participants by name in any reports or publications. If you have any question, please contact Jacqueline at jacqueline.maloney@alumni.ubc.ca. In this package you will find the following: ❑ Teacher Background Questionnaire: Please complete this questionnaire that asks you about your educational background, well-being, and beliefs about students’ social and emotional learning in classrooms and schools. ❑ Teacher Ratings of Child Behaviour Scales: Please complete a questionnaire for each of the students in your classroom who have received parent/guardian consent to participate in this research project. Note that if a student does not receive parent/guardian consent to participate in the research, you should not complete the questionnaire for that student. ❑ Booking your TTOCs: In order to assist with completing these forms, we have made arrangements to provide you with a full-day TTOC for each time point (November/December and May/June). The research coordinator will contact you with details about options and procedures. Thank you again for completing these forms and participating in our research! We ask that you please complete these forms by December_____2019. When you have completed all of the forms, please feel free to call or email (number and e-mail address below) us so that one of the research team can come pick up these forms from you. Thank you in advance for your assistance! Sincerely, Kimberly Schonert-Reichl, Ph.D. Principal Investigator Kimberly.schonert-reichl@ubc.ca Jacqueline Maloney, MA, Co-Investigator Office: 778-227-2090 E-mail: jacqueline.maloney@alumni.ubc.ca 192 Appendix H: Teacher Demographic Survey CALM Study 2019: [H18-03740] Page 1 of 15 Teacher Demographic & Teaching Experiences Survey v1 February 21, 2019 Name: _____________________ Date: _____________________ Dear Participating Teacher, Thank you for participating in the Promoting Young Children’s Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of “The CALM Curriculum” Research Study. Your contributions are greatly appreciated. For this task, we ask that you please complete the questionnaire. We would appreciate it if you could complete this survey by___(DATE)_____________. Remember that your identity will remain confidential. This survey will only be identified by your unique classroom ID number. This is to ensure your confidentiality. We hope these safeguards will also give you confidence that you can respond honestly knowing that your identity will not be linked to your responses. Thank you for your participation! Dr. Kimberly Schonert-Reichl Principal Investigator and Research Team University of British Columbia, Vancouver, BC Email: kimberly.schonert-reichl@ubc.ca Phone: 604-822-2215 When you have completed the entire questionnaire: Please contact Jenna Whitehead Arruda by phone at (604) 603-3296 or by email at jennaw@mail.ubc.ca so we can arrange to pick it up from you. 193 1. What is your birth date? 2. Gender:_____________________ (optional) 3. I identify my Ethnicity or origin as: •  African / Black •  Caucasian / White •  East Asian (Chinese, Japanese, Korean) •  Eurasian or Central Asian (e.g., Armenian, Turkish) •  Hispanic / Latin American •  Indigenous (e.g., First Nations / Metis / Inuit / Native American) •  Middle Eastern / North African (e.g., Iranian, Iraqi, Syrian, Moroccan) •  Pacific Islander •  South Asian (e.g., Indian, Pakistani, Sri Lankan) •  Southeast Asian (e.g., Vietnamese, Filipino, Indonesian, Thai) •  Multiracial (Specify): _________________ •  Something else (Specify): ____________________ •  Prefer not to say PART One: Demographic Information 1. How many years have you worked as a school teacher? __________ years 2. How many years have you taught elementary school specifically? _______ years 3. Which grades have you taught? _______________________________________ 4. Any other information about your teaching experience that we should know? 5. What is your highest level of education? □ Some undergraduate coursework □ Bachelor Degree (other than B.Ed.) □ B.Ed. □ Post Baccalaureate Diploma □ Graduate Degree (M.A., M.Ed., M.Sc.) □ Doctorate (Ph.D., Ed.D.) □ Other (please describe): __________________ 194 Appendix I: Children Demographics Page 1 of 5 Promoting Young Children’s Social and Emotional Competence and School Success: Exploring Feasibility and Preliminary Outcomes of “The CALM Curriculum” Research Study TEACHER RATINGS OF CHILD BEHAVIOUR TIME 1 (Pre-test) Please answer the following questions for each student participating in the study. Do not overthink your answers. Go with your first instinct. It should take approximately 20-30 minutes per student to fill out the survey. THANK YOU!! STUDENT NAME: TEACHER ID: Date Please answer the following demographic questions about the above student (if known): DEMOGRAPHICS 1. Child’s birth date (only month & year required): Month Year 2. How does this student describe their gender? □ Boy □ Girl □ In another way. The way they describe their gender is: _______________ 3. Family Composition Which adults does this child live with most of the time? (examples: mother and father, part time with each parent, foster parent or caregiver, two mothers, father and father’s girlfriend or boyfriend, grandmother) (Check all that apply) □ Mother □ Father □ Stepfather □ Stepmother □ Grandmother □ Grandfather □ Second Mother □ Second Father □ Part time with each parent □ Foster parent(s) or caregiver(s) □ Other adults (write in the space, for example, mom’s boyfriend or girlfriend, dad’s boyfriend or girlfriend): ____________________________________________________ 4. Primary Language(s) spoken at child’s home (You can check more than one if you need to.) □ English □ Hindi □ Punjabi □ Cantonese □ Japanese □ Spanish □ Filipino/Tagalog □ Korean □ Vietnamese □ French □ Mandarin □ Other _____________________ □ Unknown 195 Page 2 of 5 5. Student’s first language learned (You can check more than one if you need to.) □ English □ Hindi □ Punjabi □ Cantonese □ Japanese □ Spanish □ Filipino/Tagalog □ Korean □ Vietnamese □ French □ Mandarin □ Other _____________________ □ Unknown 6. How difficult is it for this student to understand English? □ Very hard □ Hard □ Easy □ Very easy 196 Appendix J: Teacher-Ratings of Children’s Social and Emotional Competencies Page 3 of 5 Part I. Compared to other (boys/girls) at this grade level, how often does/is this student . . . Almost Never Rarely Sometimes Often Very Often Almost Always 1. Take others’ property 1 2 3 4 5 6 2. Yell at others 1 2 3 4 5 6 3. Fight 1 2 3 4 5 6 4. Stubborn 1 2 3 4 5 6 5. Control temper when there is a disagreement 1 2 3 4 5 6 6. Lie 1 2 3 4 5 6 7. Break rules 1 2 3 4 5 6 8. Tease classmates 1 2 3 4 5 6 9. Harm others 1 2 3 4 5 6 10. Obey classroom rules 1 2 3 4 5 6 11. Work hard 1 2 3 4 5 6 12. Easily distractible 1 2 3 4 5 6 13. Concentrate 1 2 3 4 5 6 14. Stay on task 1 2 3 4 5 6 15. Pay attention 1 2 3 4 5 6 16. Mind wanders 1 2 3 4 5 6 17. Easily irritated when he/she has trouble with some task (reading, math, etc.) 1 2 3 4 5 6 18. Disliked by classmates 1 2 3 4 5 6 19. Liked by classmates 1 2 3 4 5 6 20. Accept adult limits 1 2 3 4 5 6 21. Feel at ease to talk to you 1 2 3 4 5 6 22. Perform at grade level 1 2 3 4 5 6 23. Show empathy and compassion for other’s feelings 1 2 3 4 5 6 24. Provide help, shares materials, and acts cooperatively with others. 1 2 3 4 5 6 25. Take turns, plays fair, and follows the rules of the game. 1 2 3 4 5 6 26. Listen carefully to others. 1 2 3 4 5 6 27. Initiate interactions and joins in with others in a positive manner. 1 2 3 4 5 6 28. Stop and calm down when excited or upset. 1 2 3 4 5 6 29. Recognize and label his/her feelings and those of others appropriately. 1 2 3 4 5 6 30. Handle disagreements in a positive way. 1 2 3 4 5 6 31. Get angry when provoked by other children. 1 2 3 4 5 6 197 Page 4 of 5 PART 2: Rating of Child’s Social Behaviours Never Hardly Ever Sometimes Often Always 1. This child finds it hard to make friends. 1 2 3 4 5 2. This child usually comforts others who are upset or hurt. 1 2 3 4 5 3. This child often feels sorry for others who are less fortunate. 1 2 3 4 5 4. This child does not often become sad when reading or listening to a sad story. 1 2 3 4 5 5. This child feels sympathy for others. 1 2 3 4 5 6. This child is popular with others his/her age. 1 2 3 4 5 7. This child usually feels sorry for other children who are being teased. 1 2 3 4 5 8. This child has a lot of friends. 1 2 3 4 5 9. This child rarely feels sympathy for other children who are upset or sad. 1 2 3 4 5 PART 3: Rating of Teacher-Child Relationship Definitely does not apply Not really Neutral, not sure Applies somewhat Definitely applies 1. I share an affectionate, warm relationship with this child. 1 2 3 4 5 2. This child and I always seem to be struggling with each other. 1 2 3 4 5 3. If upset, this child will seek comfort from me. 1 2 3 4 5 4. This child is uncomfortable with physical affection or touch from me. 1 2 3 4 5 5. This child values his/her relationship with me. 1 2 3 4 5 6. When I praise this child, he/she beams with pride. 1 2 3 4 5 7. This child spontaneously shares information about himself/herself. 1 2 3 4 5 8. This child easily becomes angry with me. 1 2 3 4 5 9. It is easy to be in tune with what this child is feeling. 1 2 3 4 5 10. This child remains angry or is resistant after being disciplined. 1 2 3 4 5 11. Dealing with this child drains my energy 1 2 3 4 5 12. When this child is in a bad mood, I know we’re in for a long and difficult day. 1 2 3 4 5 13. This child’s feelings toward me can be unpredictable or can change suddenly. 1 2 3 4 5 14. This child is sneaky or manipulative with me. 1 2 3 4 5 15. This child openly shares his/her feelings and experiences with me. 1 2 3 4 5 198 Page 5 of 5 Part 4: Rate the behaviour described in each item in terms of how characteristic or "applicable" it is for the child you are rating. Doesn’t Apply Applies Sometimes Certainly Applies 1. Seems concerned when classmates are distressed 1 2 3 2. Is kind toward classmates 1 2 3 3. Listens to classmates 1 2 3 4. Compromises in conflicts with classmates 1 2 3 5. Is cooperative with classmates 1 2 3 6. Is friendly toward classmates 1 2 3 7. Shows concern for moral issues (e.g. fairness, welfare of others) 1 2 3 8. Offers help or comfort when classmates are upset 1 2 3 Thank you for taking the time to complete this survey! 199 Appendix K: Instructions for Behavior Rating Inventory of Executive Function – Preschool5 5 Note that the BRIEF-P is a copyrighted measure, and I do not have permission to share specific items. Contact PAR for purchase. December, 2019 Dear Participating Teacher, This last set of questions includes a list of statements that describe young children. While many of these behaviours are common among kindergarteners, we would like to know how often this child has had problems with these behaviours during the past 4 weeks. Think about the child as you read these statements and circle: N if the behaviour is Never a problem S if the behaviour is Sometimes a problem O if the behaviour is Often a problem For example, if having tantrums when told “No” is never a problems, you would circle N for this item: Has tantrums when told “No” N S O If you make a mistake or want to change your answer, please DO NOT ERASE. Instead, draw an X through the answer you want to change a circle the correct answer: Has tantrums when told “No” N S O Thank you for taking the time to complete this survey! Sincerely, Kimberly Schonert-Reichl, Ph.D. Principal Investigator Kimberly.schonert-reichl@ubc.ca Jacqueline Maloney, Co-Investigator Office: 778-227-2090 E-mail: jacqueline.maloney@alumni.ubc.ca 200 Appendix L: Head, Toes, Knees, Shoulders – Extended Task6 Assent Script 6 Note that the HTKS-E is a copyrighted measure. Contact Megan McClelland (megan.mcclelland@oregonstate.edu) or Claire Cameron (ccp2n@virginia.edu) for requests for permission to reproduce the Head-Toes-Knees-Shoulders task. . CALM 2019 Pre-test Child Assent Form Date: ______________ Student ID: _________ RA(s): ______________ Hi [Say child’s name]! I’m happy to meet you. My name is [RA’s name] and I’m a researcher from the University of British Columbia. Do you know what a university is? (Invite participant to share ideas). The university is a school for grownups who want to learn more. Do you know what a researcher is? (Invite participants to share ideas). A researcher is someone from the university who wants to understand how things work and why they work that way. This includes understanding more about people. For example, I am interested in learning more about how Kindergarten children learn and feel. What do you think are some ways I could learn about Kindergarten children? (Invite student to share ideas). These are all great ideas, thank you! Because it has been a long time since I was in Kindergarten, and many things have changed since then, I’d like to learn from you. You know the most about Kindergarten children because you are in Kindergarten right now! I wonder how Kindergarteners learn new things. One way I can learn more about this is by watching you play a game where you learn different rules. Then, if you choose, you could tell me what you think of the game afterwards. Before you decide whether you want to play the game or not, there are some important things for you to know to help you decide. [RA: make sure that you check each box below to confirm that the participant understood each point]: It’s completely up to you whether you would like take part or not. Even if you decide you want to try the game, you can change your mind and stop whenever you want. You just have to tell, me okay? No one will be upset if you don’t want to play the game or if you change your mind later and stop playing. You can also take a break any time you like. Does that make sense? Also, this is not a game you win or lose. The game is just for fun. The goal is just to do the best you can. We will not tell your teachers, principal, parents, or classmates how you did on the game or anything you tell us about the game. All of the information with your name on it will be kept in a locked room at the university. 201 Appendix M: Graphs of Conditional Effects of STR Quality Figure M.1 Conditional Effects of Closeness on Correlation of EFs and Empathy Note. Lines represent fitted regression lines for predicted teacher-rated empathy, controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of closeness scores. MSE = standard error of the regression estimate. There was no significant moderating effect of closeness on the relation between EFs and empathy (F(1, 132) = 1.07, p = .30, f2 = .002). R2 = .64, MSE = 0.37 F(5, 133) = 47.34 p < .001 202 Figure M.2 Conditional Effects of Conflict on Correlation of EFs and Empathy Note. Lines represent fitted regression lines for predicted teacher-rated empathy, controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of conflict scores. MSE = standard error of the regression estimate. Conflict was not a significant moderator of the relation between EFs and empathy (F(1, 132) = 1.15, p = .28, f2 = .006). R2 = .35, MSE = 0.68 F(5, 133) = 14.43 p < .001 203 Figure M.3 Conditional Effects of Closeness on Correlation of EFs and SEC Note. Lines represent fitted regression lines for predicted teacher-rated empathy, controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of closeness scores. MSE = standard error of the regression estimate. There was no significant moderating effect of closeness on the relation between EFs and SEC (F(1, 132) = 0.09, p = .77, f2 < .001). R2 = .60, MSE = 0.42 F(5, 133) = 38.87 p < .001 204 Figure M.4 Conditional Effects of Conflict on Correlation of EFs and SEC Note. Lines represent fitted regression lines for predicted teacher-rated empathy, controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of conflict scores. MSE = standard error of the regression estimate. There was no significant moderating effect of conflict on the correlation between EFs and SEC (F(1, 132) = 0.37, p = .54, f2 = .002). R2 = .39, MSE = .0.63 F(5, 133) = 17.04 p < .001 205 Figure M.5 Conditional Effects of Closeness on Correlation of HTKS-E and SEC Note. Lines represent fitted regression lines for predicted teacher-rated empathy, controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of closeness scores. MSE = standard error of the regression estimate. There was no significant moderating effect of closeness on the correlation between behavioral self-regulation and SEC (F(1, 132) = 1.04, p = .31, f2 = .004). R2 = .48, MSE = 0.55 F(6, 132) = 20.10 p < .001 206 Figure M.6 Conditional Effects of Conflict on the Correlation of HTKS-E and SEC Note. Lines represent fitted regression lines for predicted teacher-rated empathy, controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of conflict scores. MSE = standard error of the regression estimate. There moderating effect of conflict on the correlation between EFs and SEC was insignificant (F(1, 132) = 2.61, p = .11, f2 = .01). R2 = .29, MSE = 0.75 F(1, 132) = 8.79 p < .001 207 Figure M.7 Conditional Effects of Closeness on Correlation of HTKS-E and Prosociality Note. Lines represent fitted regression lines for predicted teacher-rated empathy, controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of closeness scores. MSE = standard error of the regression estimate. There was no significant moderating effect of closeness on the correlation between behavioral self-regulation and prosocial behavior with peers (F(1, 132) = 0.90, p = .35, f2 = .005). R2 = .31, MSE = 0.72 F(6, 132) = 9.83 p < .001 208 Figure M.8 Conditional Effects of Conflict on Correlation of HTKS-E and Prosociality Note. Lines represent fitted regression lines for predicted teacher-rated empathy, controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of conflict scores. MSE = standard error of the regression estimate. There was no significant moderating effect of conflict on the correlation between behavioral self-regulation and prosocial behavior with peers (F(1, 132) = 2.28, p = .13, f2 = .01). R2 = .33, MSE = 0.70 F(6, 132) = 10.74 p < .001 209 Figure M. 9 Conditional Effects of Closeness on Correlation of HTKS-E and Empathy Note. Lines represent fitted regression lines for predicted teacher-rated empathy, controlling for age, gender, and EF group at the 16th, 50th, and 84th percentiles of closeness scores. MSE = standard error of the regression estimate. The moderating effect of closeness on the relation between HTKS-E and empathy trended on significance (F(1, 132) = 3.05, p = .08, f2 = .01) for children with closeness scores ranging from -4.11 SD to -3.08 SD. R2 = .57, MSE = 0.45 F(6, 132) = 29.31 p < .001 210 Appendix N: J-N Tests for Regions of Significant for Conditional Effects Table N.1 Conditional Effects of Conflict on Correlation Between Behavioral Self-Regulation and Empathy _____________________________________________________ Conflict Effect SE t p UL LL _____________________________________________________ -1.2526 .4191 .1274 3.2892 .0013 .1670 .6711 -.9979 .3638 .1108 3.2838 .0013 .1446 .5829 -.7432 .3084 .0965 3.1978 .0017 .1176 .4992 -.4885 .2531 .0856 2.9562 .0037 .0837 .4225 -.2338 .1978 .0797 2.4812 .0143 .0401 .3555 -.0445 .1567 .0792 1.9781 .0500 .0000 .3134 .0209 .1425 .0798 1.7846 .0766 -.0155 .3004 .2756 .0872 .0860 1.0139 .3125 -.0829 .2572 .5303 .0318 .0970 .3283 .7432 -.1599 .2236 .7849 -.0235 .1114 -.2109 .8333 -.2438 .1968 1.0396 -.0788 .1281 -.6153 .5394 -.3322 .1746 1.2943 -.1341 .1463 -.9168 .3609 -.4235 .1553 1.5490 -.1895 .1655 -1.1446 .2544 -.5169 .1380 1.8037 -.2448 .1854 -1.3200 .1891 -.6116 .1220 2.0584 -.3001 .2058 -1.4579 .1472 -.7073 .1071 2.3131 -.3554 .2266 -1.5685 .1192 -.8037 .0928 2.5678 -.4108 .2476 -1.6586 .0996 -.9006 .0791 2.8225 -.4661 .2689 -1.7334 .0854 -.9980 .0658 3.0772 -.5214 .2903 -1.7961 .0748 -1.0956 .0528 3.3319 -.5767 .3118 -1.8495 .0666 -1.1935 .0401 3.5866 -.6320 .3334 -1.8955 .0602 -1.2916 .0276 3.8413 -.6874 .3552 -1.9353 .0551 -1.3899 .0152 ________________________________________________________ Note. Significant regions are bolded (p <.05). 211 Table N.2 Conditional Effects of Closeness on Correlation Between EFs and Prosocial Behavior with Peers _____________________________________________________ Closeness Effect SE t p UL LL _____________________________________________________ -4.1144 -1.7180 .3009 -5.7092 .0000 -2.3132 -1.1227 -3.8566 -1.6574 .2846 -5.8245 .0000 -2.2203 -1.0945 -3.5988 -1.5969 .2683 -5.9515 .0000 -2.1276 -1.0661 -3.3410 -1.5364 .2522 -6.0919 .0000 -2.0352 -1.0375 -3.0832 -1.4758 .2362 -6.2475 .0000 -1.9431 -1.0085 -2.8254 -1.4153 .2204 -6.4204 .0000 -1.8513 -.9792 -2.5676 -1.3547 .2049 -6.6128 .0000 -1.7600 -.9495 -2.3098 -1.2942 .1896 -6.8268 .0000 -1.6692 -.9192 -2.0520 -1.2337 .1746 -7.0641 .0000 -1.5791 -.8882 -1.7942 -1.1731 .1602 -7.3251 .0000 -1.4899 -.8563 -1.5363 -1.1126 .1462 -7.6075 .0000 -1.4019 -.8233 -1.2785 -1.0521 .1331 -7.9036 .0000 -1.3154 -.7887 -1.0207 -.9915 .1210 -8.1950 .0000 -1.2309 -.7522 -.7629 -.9310 .1102 -8.4463 .0000 -1.1490 -.7129 -.5051 -.8704 .1012 -8.5978 .0000 -1.0707 -.6702 -.2473 -.8099 .0946 -8.5656 .0000 -.9969 -.6229 .0105 -.7494 .0907 -8.2648 .0000 -.9287 -.5700 .2683 -.6888 .0900 -7.6574 .0000 -.8668 -.5109 .5261 -.6283 .0925 -6.7936 .0000 -.8112 -.4454 .7839 -.5678 .0980 -5.7933 .0000 -.7616 -.3739 Note. All regions are significant at p < .001. 212 Table N.3 Conditional Effects of Conflict on Correlation Between EFs and Prosocial Behavior with Peers _____________________________________________________ Conflict Effect SE t p UL LL _____________________________________________________ -1.2526 -.8451 .1248 -6.7727 .0000 -1.0920 -.5983 -.9979 -.7982 .1173 -6.8043 .0000 -1.0302 -.5661 -.7432 -.7512 .1116 -6.7337 .0000 -.9719 -.5305 -.4885 -.7043 .1078 -6.5311 .0000 -.9176 -.4910 -.2338 -.6573 .1063 -6.1817 .0000 -.8676 -.4470 .0209 -.6103 .1071 -5.6963 .0000 -.8223 -.3984 .2756 -.5634 .1102 -5.1108 .0000 -.7814 -.3453 .5303 -.5164 .1154 -4.4748 .0000 -.7447 -.2881 .7849 -.4695 .1224 -3.8353 .0002 -.7116 -.2273 1.0396 -.4225 .1309 -3.2269 .0016 -.6815 -.1635 1.2943 -.3755 .1407 -2.6689 .0086 -.6539 -.0972 1.5490 -.3286 .1515 -2.1688 .0319 -.6283 -.0289 1.6549 -.3090 .1562 -1.9781 .0500 -.6181 .0000 1.8037 -.2816 .1631 -1.7266 .0866 -.6042 .0410 2.0584 -.2346 .1753 -1.3382 .1831 -.5815 .1122 2.3131 -.1877 .1881 -.9977 .3203 -.5598 .1844 2.5678 -.1407 .2013 -.6990 .4858 -.5389 .2575 2.8225 -.0938 .2149 -.4364 .6633 -.5188 .3312 3.0772 -.0468 .2287 -.2047 .8381 -.4992 .4055 3.3319 .0002 .2427 .0007 .9995 -.4800 .4803 3.5866 .0471 .2570 .1833 .8548 -.4612 .5555 3.8413 .0941 .2714 .3466 .7294 -.4428 .6310 Note. Significant regions are bolded (p <.05) 213 Appendix O: Effect Sizes for Moderation Models Table O.1 Effect Sizes for Moderation Models Dependent Variable Fitted Model R2 SE of Regression Confidence Interval 95% Lower Level Upper Level Empathy BRIEF + Close .64 .38 .55 .73 BRIEF+ Conflict .36 .67 .24 .48 HTKS-E+ Closet .57 .45 .47 .67 HTKS-E+ Conflict* .27 .77 .15 .39 Prosocial BRIEF+ Close* .55 .47 .44 .66 BRIEF+ Conflict* .49 .53 .38 .60 HTKS-E+ Close .31 .72 .19 .43 HTKS-E+ Conflict .33 .70 .21 .45 SEC BRIEF+ Close .60 .42 .50 .70 BRIEF+ Conflict .39 .64 .27 .51 HTKS-E+ Close .48 .55 .37 .59 HTKS-E+ Conflict .29 .75 .17 .41 214 Appendix P: Descriptive Statistics by Gender Table P.1 Variable Means by Gender Note. BRIEF =Behavior Rating Inventory of Executive Functions – Preschool Version (Gioia et al., 2003.HTKS = Head, Toes, Knees, Shoulder – Extended Task (McLelland et al., 2014). STR = student-teacher relationship. 215 Appendix Q: Descriptive Statistics by EF Group Table Q.1 Variable Means by EF Group Note. BRIEF =Behavior Rating Inventory of Executive Functions – Preschool Version (Gioia et al., 2003.HTKS = Head, Toes, Knees, Shoulder – Extended Task (McLelland et al., 2014). STR = student-teacher relationship. 216 Appendix R: Correlations with BRIEF-P Subscales Table R.1 Correlations with BRIEF-P Subscales
Thesis/Dissertation
eng
Human Development, Learning, and Culture
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Schonert-Reichl, Kimberly
Student-teacher relationships, self-regulation, and social and emotional competencies in kindergarteners
Text