Effects of School Belonging on Internalizing Symptom

EFFECTS OF SCHOOL BELONGING ON INTERNALIZING SYMPTOM

TRAJECTORIES AMONG LATINX YOUTH

A Dissertation

OSCAR WIDALES-BENITEZ

Submitted to the Office of Graduate and Professional Studies of Texas A&M University In partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

Chair of Committee, Cynthia Riccio Co-Chair of Committee, Sara Castro-Olivo Committee Members, Lisa Bowman-Perrott Robert W. Heffer, Jr. Oi-Man Kwok Head of Department, Shanna Hagan-Burke

August 2019

School Psychology

ABSTRACT

Latinx and Latinx ELL youth are among the fastest growing student populations in the nation’s schools. Despite consistent efforts to address the achievement gap that exists between these youths and their non-Latinx and non-ELL counterparts, these youth continue to consistently underperform across academic areas. While most empirical work has focused on identifying the academic needs of these youth in an effort to address this underperformance, recent research has identified the unique social-emotional needs of these student populations.

Using Growth Mixture Modeling (GMM), the current study explored trajectories of internalizing symptoms among two samples of Latinx and Latinx ELL students in an effort to develop a better understanding of the social-emotional well-being of these youths. Furthermore, the study explored the predictive ability of early school belonging on trajectory placement as well as the ability of these trajectories to predict future victimization.

Consistent with results from previous studies working with broad student samples, results from the current study describe the presence of various internalizing problem trajectories among

Latinx and Latinx ELL youth. Trends observed were consistent with those found in other literature exploring the development of internalizing problems among children and adolescents.

School belonging was identified as being a significant predictor of internalizing symptom trajectory placement. Youth reporting elevated levels of school belonging were more likely to be placed in trajectories characterized by mild or decreasing levels of internalizing problems over time. Similarly, trajectories significantly identified youth who self-reported elevated levels of overt and relational victimization. Namely, youth belonging to trajectories characterized by increasing or consistently elevated levels of internalizing problems were more likely to report

experiencing elevated levels of victimization. Implications for school based mental health services are discussed including approaches to increase school belonging among Latinx youth.

iii

DEDICATION

Para mi mama, mi papa, y mi hermana que me han apoyado desde el principio y más cuando

decidí irme a estudiar fuera de Laredo hace ya casi seis años. ¡Si se puede, y si se pudo!

ACKNOWLEDGEMENTS

Thank you to my committee chair, Dr. Riccio, and my committee co-chair, Dr. Castro-

Olivo. Your commitment to student success and advancement of knowledge in the field of school psychology is inspiring. Thank you to my committee members, Dr. Kwok, Dr. Heffer, and Dr. Bowman-Perrott, for your guidance and support throughout this entire process.

I also want to thank my friends both those that I knew before graduate school and those that I met during this journey. Christine and Asha, you both were constant sources of support and inspiration. This journey would have been way more difficult if either of you had not been part of it. Danielle, it’s crazy how close we grew throughout this wild process! “Rapid cycling” at

Bolt EaHo and Bricks & Scones will always be some of my favorite memories. Stephanie EA

Mendez, thank you for making me laugh when it was the last thing on my mind. A part of my heart will always be in Laredo, Santa Barbara, College Station, and Los Angeles.

CONTRIBUTORS AND FUNDING SOURCES

Contributors

This work was supported by a dissertation committee consisting of Dr. Cynthia Riccio, committee chair, Dr. Sara Castro-Olivo, committee co-chair, Dr. Oi-Man Kwok, and Dr. Lisa

Bowman-Perrott from the Department of Educational Psychology as well as by Dr. Robert W.

Heffer Jr. from the Department of Psychology.

The data analyzed for Chapter IV was provided by Dr. Jan Hughes whose study was funded by the National Institute of Child and Human Development (Grant HD039367). Dr.

Maria A. McCameron and Dr. Oi-Man Kwok provided guidance and support throughout the analysis of this data.

All other work conducted for this dissertation was completed by the student independently.

Funding Sources

Graduate study was supported by the Pathways to the Doctorate Fellow of Texas A&M

University.

TABLE OF CONTENTS

Page

ABSTRACT ...... ii

DEDICATION...... iv

ACNOWLEDGEMENTS ...... v

CONTRIBUTORS AND FUNDING SOURCES ...... vi

TABLE OF CONTENTS ...... vii

LIST OF FIGURES ...... ix

LIST OF TABLES ...... x

CHAPTER I INTRODUCTION ...... 1

Current Study ...... 2 Research question 1 ...... 3 Research question 2 ...... 3 Research question 3 ...... 4 Research question 4 ...... 4 Research question 5 ...... 4 Research question 6 ...... 4 Implications ...... 5 Definition of Terms ...... 5 English Language Learner (ELL) ...... 5 Hispanic/Latinx ...... 6 Internalizing disorders ...... 6 School belonging ...... 6 Peer victimization ...... 6

CHAPTER II LITERATURE REVIEW ...... 7

English Language Learners ...... 7 Internalizing Problems ...... 10 Latinx youth and internalizing problems ...... 12 Outcomes of internalizing problems ...... 13 Trajectories of internalizing problems ...... 14 School Belonging ...... 15 Outcomes of school belonging ...... 16 School belonging and internalizing problems ...... 17 School belonging and Latinx youth ...... 18

vii

Victimization ...... 21 Prevalence of peer victimization ...... 22 Outcomes of peer victimization ...... 23 Peer victimization and internalizing problems trajectories ...... 24

CHAPTER III METHOD ...... 26

Research Design ...... 26 Participants ...... 26 Measures ...... 27 Demographic information ...... 27 Internalizing symptoms ...... 28 School belonging ...... 29 Peer victimization ...... 30 Procedures ...... 30 Statistical power ...... 31 Missing data ...... 31

CHAPTER IV RESULTS ...... 32

Descriptive Statistics ...... 32 Model Selection ...... 33 Predictive Ability of School Belonging ...... 38 Victimization Distal Outcome ...... 39

CHAPTER V SUMMARY ...... 42

Key Findings ...... 42 Growth Trajectories ...... 43 Research question 2 ...... 43 Research questions 3 and 4 ...... 44 School Belonging ...... 47 Research question 5 ...... 47 Victimization ...... 50 Research question 6 ...... 50 Implications for School-Based Mental Health Supports ...... 51 Limitations & Future Directions ...... 55

REFERENCES ...... 58

APPENDIX A ...... 77

APPENDIX B ...... 89

viii

LIST OF FIGURES

FIGURE Page

1 GMM examining trajectories of internalizing symptoms in the general sample ...... 35

2 GMM examining trajectories of internalizing symptoms including race and ELL status covariates ...... 38

3 Mean value plot of four class model for general student sample ...... 89

4 Mean value plot of three class model for Latinx student sample ...... 90

5 Mean value plot of two class model for Latinx ELL student sample ...... 91

6 CFA results for 18-items of the PEQ ...... 92

LIST OF TABLES

TABLE Page

1 Descriptive Statistics for General Student Sample ...... 77

2 Descriptive Statistics for General Student Sample II ...... 78

3 Descriptive Statistics for Latinx Student Subsample ...... 78

4 Descriptive Statistics for Latinx Student Subsample II ...... 79

5 Descriptive Statistics for Latinx ELL Student Subsample ...... 79

6 Descriptive Statistics for Latinx ELL Student Subsample II ...... 80

7 Tests of Normality ...... 80

8 Fit Indices for Growth Mixture Model with General Student Sample ...... 81

9 Fit Indices for Growth Mixture Model with Latinx Sample ...... 81

10 Fit Indices for Growth Mixture Model for Latinx ELL Sample ...... 82

11 Class Counts and Proportions for Selected Model General Student Sample ...... 82

12 Class Counts and Proportions for Selected Model with Latinx Sample ...... 82

13 Class Counts and Proportions for Selected Model for Latinx ELL Sample ...... 82

14 Effects of Gender Covariate for Final Growth Mixture Model General Sample ..... 83

15 Effects of School Belonging Covariate for Final Growth Mixture Model General Sample ...... 83

16 Effects of Gender Covariate for Final Growth Mixture Model for Latinx Sample. . 83

17 Effects of School Belonging Covariate for Final Growth Mixture Model for Latinx Sample ...... 84

18 Effects of Gender Covariate for Final Growth Mixture Model for Latinx ELL Sample ...... 84

19 Effects of School Belonging Covariate for Final Growth Mixture Model for Latinx ELL Sample ...... 84

20 Four-Factor Solution and Item Factor Loading for PEQ ...... 85

21 Means and Standard Deviations of Distal Outcome for Each Class in General Sample ...... 85

22 Means and Standard Deviations of Distal Outcome for Each Class in Latinx Sample ...... 86

23 Means and Standard Deviations of Distal Outcome for Each Class in Latinx ELL Sample ...... 86

24 Equality Tests of Mean Reported Overt Victimization Across Classes in General Sample ...... 86

25 Equality Tests of Mean Reported Relational Victimization Across Classes in General Sample ...... 87

26 Equality Tests of Mean Reported Overt Victimization Across Classes in Latinx Sample ...... 87

27 Equality Tests of Mean Reported Relational Victimization Across Classes in Latinx Sample ...... 87

28 Equality Tests of Mean Reported Overt Victimization Across Classes in Latinx ELL Sample ...... 88

29 Equality Tests of Mean Reported Relational Victimization Across Classes in Latinx ELL Sample ...... 88

CHAPTER I

INTRODUCTION

Students whose home language is one other than English are often identified as English

Language Learners (ELLs). Currently, ELLs are considered one of the fastest growing student subgroups in the nation’s schools and make up approximately 10% of the overall school-aged population (National Center for Education Statistics [NCES], 2017). The size of the ELL population largely varies across states with ELLs making up 1.0% of the student population in

West Virginia and 22.7% of California’s student population. Of the approximately 4.6 million

ELL students in the nation, an estimated 3.7 million or 77.1% of ELLs report Spanish as their home language (NCES, 2017). Considering the magnitude of this student subgroup, there is an increasing need to develop a better understanding of both the academic and social adversities these youth face. Among other academic challenges and despite numerous efforts, ELLs have continuously scored lower on mathematics and reading state achievement tests than non-ELLs with no measureable difference between the current achievement gap and that found at the turn of the century (National Assessment of Educational Progress, 2014). Furthermore, ELLs are known to have higher dropout rates and various negative, social outcomes with risk for some of these increasing the longer youth continue to be classified as such (Bowman-Perrott, Herrera, &

Murry, 2010; Kim, 2011). While their academic difficulties are typically attributed to their limited English proficiency, recent empirical work has begun to shed light on the necessity to develop a better understanding of the social-emotional needs of this student subpopulation

(Castro-Olivo, Preciado, Sanford, & Perry, 2011).

Current Study

The purpose of the current study is to develop a better understanding of the social- emotional well-being of Latinx ELLs, who make up approximately 80% of the nation’s ELL population (NCES, 2017). Considering that Latinx youth have been identified as being at-risk for the development of internalizing difficulties and as reporting higher levels of internalizing symptomatology (e.g. anxiety and depression; Albeg, 2010; McLaughlin, Hilt, Nolen-Hoeksema,

2007; Twenge & Nolen-Hoeksma, 2002), this study will seek to identify the trajectories of internalizing symptoms among a sample of Latinx ELLs. Recent literature has found that while internalizing problems seem to begin developing during the early adolescent years, different developmental trajectories exist (e.g., Hill, Pettit, Lewinsohn, Seeley, & Klein, 2014; Morin,

Maïano, Nagengast, Marsh, Morizot, & Janosz, 2011; Stoolmiller, Kim, & Capaldi, 2005). For example, some youth who enter adolescence with elevated symptoms continue to experience them through adulthood while others show a decreasing pattern suggesting the development of coping mechanisms during their teenage years (Hill et al., 2014). Studies that have identified the developmental trajectories of internalizing problems have done so with broad samples of children and adolescents; as such, the proposed study will be the first to explore the existence of these with a sample of Latinx youth and a sample of Latinx ELLs. It is hypothesized that, as is the case with their non-Latinx and non-ELL peers, various internalizing symptom trajectories will exist for ELL youth.

Furthermore, the present study will seek to investigate a potential predictor of these trajectories, namely school belonging. School belonging or the extent to which students feel welcomed and supported in their school setting (Goodenow & Grady, 1993) is a developing construct within the literature that has been found to be associated with student social-emotional

wellbeing (e.g., Shochet, Smith, Furlong, & Homel, 2011). Existing studies provide evidence to indicate an association between school belonging and internalizing problems, yet no study to date has examined potential subgroups of adolescents who may be differentially impacted by school belonging. Furthermore, there is evidence to indicate that school belonging may serve as a protective factor for a number of both academic and social outcomes. Despite this, there have been no studies exploring the impact of school belonging on developmental trajectories of internalizing problems any student population. It is hypothesized that school belonging will be a significant predictor of internalizing symptom trajectories for the general student population, for

Hispanic youth, and for Hispanic ELLs. Finally, peer victimization, a known predictor of internalizing problem trajectories (Hill et al., 2017), will be explored as a distal outcome of these trajectories. Research questions to be addressed are as follows:

Research question 1. Do Latinx and Latinx ELLs within the current sample report significantly different levels of internalizing symptoms when compared to their non-Latinx, non-

ELL counterparts? Based on prior research, it is hypothesized that ELL youth will report higher levels of internalizing problems than their peers, as they have been identified to be at particular risk for developing such symptoms.

Research question 2. Do different internalizing symptom trajectories exist within the general, current sample? Based on previous research, it is hypothesized that at least two different subgroup developmental trajectories of internalizing problems will exist; namely, it is hypothesized that one subgroup exhibiting a trajectory characterized by stable mild and characterized by stable elevated symptoms will exist in the present sample. That is, at least two groups of students will be identified: one that displays a tendency for elevated internalizing

problems that are maintained over time and one that displays a tendency for mild internalizing problems that are also maintained over time.

Research question 3. Do different internalizing symptom trajectories exist within the

Latinx youth in the current sample? As with the general student sample, it is hypothesized that at least two subgroup trajectories (i.e., stable mild and stable elevated) will be identified within the

Latinx youth sample with a larger proportion of these youth belonging the stable elevated group based on previous research that has, as indicated earlier, identified Latinx youth as being at higher risk for developing internalizing problems.

Research question 4. Do different internalizing symptom trajectories exist within the

Latinx ELL youth in the current sample? As with the general student sample and the Latinx youth sample, it is hypothesized that at least two subgroup trajectories (i.e., stable mild and stable elevated) will be identified within the Latinx ELL youth sample with a larger proportion of these youth belonging the stable elevated group based on previous research that has, as indicated earlier, identified Latinx ELLs as being at higher risk for developing internalizing problems.

Research question 5. To what extent does school belonging individually predict membership to the hypothesized trajectories of internalizing problems for all three populations of interest (e.g. overall sample, Latinx youth, Latinx ELLs)? It is hypothesized that school belonging will be a predictor of membership of symptom trajectory for all three subgroups considering the previous literature indicating that a relationship between school belonging and internalizing problems.

Research question 6 How do the different trajectories found through GMM relate to self-reported victimization at Time 9 as measured by the PEQ? It is hypothesized that peer

victimization will be a distal outcome of those group trajectories where students display a tendency for elevated internalizing problems considering previous literature that has established a relationship between internalizing problems and victimization.

Implications

Developing a better understanding of the social-emotional wellbeing of the ELL population has several implications for practice including screening, assessment, and intervention/prevention services. First, having an understanding of potential predictors of internalizing symptom trajectories can inform the screening and assessment practices of mental health professionals. Mental health professionals will be better able to determine factors to be considered in relation to an individual’s internalizing symptoms. Similarly, having better knowledge regarding the mental health of these youth can lead to better provision of both prevention and intervention services. Potential differences between the internalizing symptom developmental trajectories of these youth and their non-ELL peers may continue to highlight the need for culturally-sensitive approaches geared at addressing the unique experiences and needs of these students. Finally, the identification of different internalizing symptom trajectories can help school based mental health professionals better identify individuals who may best benefit from services, which are often limited in school settings.

Definition of Terms

English Language Learner (ELL). For the purpose of this study, ELLs are defined as students whose home language is one other than English and who has limited English language proficiency. The term “Limited English Proficient” (LEP) is often used interchangeably with

ELL (Texas Education Agency, 2012).

Hispanic/Latinx. Hispanic is a term used to identify individuals who are from Spanish cultures (e.g. Mexican, Cuban, Central or South American) regardless of race (Humes, Jones, &

Ramirez, 2011). Throughout this study, the terms “Hispanic” and “Latinx” will be used interchangeably, as it common throughout existing literature (United States Department of

Commerce, 2010).

Internalizing disorders. Internalizing disorders are often defined as symptoms of anxiety and depression, withdrawn behaviors, and somatic complaints (Bongers, Koot, van der

Ende, & Verhulst, 2003) in the present study.

School belonging. While the construct of school belonging has been operationalized in numerous ways across existing literature, Goodenow and Grady’s (1993) definition of the construct will be utilized in the present study. Thus, school belonging is defined as “the extent to which students feel personally accepted, respected, included, and supported by others in the school social environment” (Goodenow & Grady, 1993; p. 80).

Peer victimization. Tsaousis (2016) drew a distinction between bullying, bullying perpetration, and peer victimization. Tsaousis conceptualized bullying as being a broad term used to encompass both perpetration and victimization. This includes bullying behavior characterized by aggressive behavior that occurs within the context of a power imbalance, has an intention to cause harm, and occurs repeatedly. Bullying perpetration and peer victimization, then, are used to describe the individual experiences of bullying. That is, bullying perpetration is used to describe the actions engaged in by those who seek to bully others, and peer victimization is used when discussing the experience of being bullied (Tsaousis, 2016). These distinctions will be used throughout the present study.

CHAPTER II

LITERATURE REVIEW

English Language Learners

Current literature indicates that school support for ELLs is particularly focused on their language development with little or no attention placed on these students’ social emotional development and that the slow academic progress of ELLs may in fact be at least partially attributed to unmet social-emotional needs (Castro-Olivo et al., 2011). In fact, literature addressing the social-emotional and psychological well-being of this subpopulation is rather limited, and a literature search across databases indicates a general under-exploration of this topic. The existing empirical work indicates, however, that many ELLs experience various life stressors and are at particular risk for negative social-emotional health outcomes (Blanco-Vega,

Castro-Olivo, & Merrell, 2008; Castro-Olivo, et al., 2011). Taking on a sociocultural/ model of development, Blanco-Vega et al. (2008) describe a variety of ecological factors that contribute to both the development and the maintenance of risk and negative outcomes, including internalizing disorders, among the immigrant-Latinx, adolescent population. As in Bronfenbrenner’s (1977,

1979) ecological systems model, which indicates the existence of various systems (i.e. microsystem, mesosystem, exosystem, and macrosystem) that impact human behavior, Blanco-

Vega et al. (2008) describe the existence of contextual factors that impact both the academic and social-emotional wellbeing of these youth. These include personal factors (e.g. age and gender), microsystemic factors (e.g. family acculturative gaps), as well as exosystemic factors (e.g. legal and residency status). This developmental model proposed by Blanco-Vega et al. (2008) will serve as a guide for describing various contextual risk factors experienced by Latinx youth particularly Latinx ELLs.

The process of second language acquisition and the adjustment to a new culture has been described as a complex procedure that requires intricate coping skills from ELLs (Gersten,

1996). Despite the academic difficulties resulting from second language acquisition, ELLs must also cope with a number of social hardships including perceived discrimination, social isolation, and a perceived inability to fully take part in school activities or organizations because of their language limitations (Blanco-Vega, et al., 2008). Furthermore, because many ELLs are foreign born, the stressors of the immigration experience often compound the stresses experienced by these students at school. For example, there is evidence to indicate that increased length of

American residence can ultimately lead to decreased academic achievement and academic aspirations in Latinx adolescents (Suarez-Orozco, 2009). Similarly, longitudinal work has shown decreases in school belonging among Latinx ELL youth while levels of school belonging were consistent among their non-ELL peers (Morrison, Cosden, O’Farrell, & Campos, 2003).

Working with 57 Latinx youth where 26 of whom were classified as ELL, Morrison and colleagues (2003) sought to identify factors associated with school belonging among these students. Data on school belonging and factors hypothesized to contribute to it including self- perceptions of academic and peer competence as well as language proficiency were collected when the students were in fourth grade and again when in sixth grade. Their findings indicate that being classified as an ELL and teacher evaluations had detrimental effects on a student’s sense of school belonging during fourth grade. They hypothesize that the mismatch between an

ELL’s home language and language proficiency and the language emphasis of their schools ultimately has a negative effect on the school belonging. Thus, the authors advocate for emphasis to be placed on how these students feel regarding their connection to school. In sixth grade, however, their findings indicated that school belonging was no longer affected by ELL status or

teacher evaluations but instead seemed to be influenced by peer relationships. The authors discuss the impact of peer relationships to school belonging indicating that negative peer relationships may exacerbate the connections ELL students have to their schools.

These findings, though, have at times been contradicted by literature that has found no differences when comparing the social-emotional health of ELL and non-ELL students. For example, in a study by Rodriguez, Ringler, O’Neal, and Bunn (2009), ELL and non-ELL elementary school students reported similar levels of academic-self beliefs. A study by Niehaus and Adelson (2014) indicated that Spanish speaking ELLs reported higher levels of academic self-concept than English proficient students in several academic areas including reading and mathematics. In a similar study, however, ELLs reported beliefs of being less academically capable than their non-ELL peers (LeClair, Doll, Osborn, & Jones, 2009). Part of the reason behind these mixed findings can be attributed to the broad scope taken when defining the ELL population. Despite the fact that ELLs are a complex, heterogeneous population, they are many times grouped in studies aiming to explore differences between them and non-ELL peers (NCES,

2017). Additionally, many of these studies have primarily worked with national datasets, which include ELLs from a wide range of backgrounds and in a wide variety of settings (Niehaus &

Adelson, 2014). Furthermore, Niehaus & Adelson (2014) indicated that few studies have explored ELLs’ perceptions of their personal socio-emotional well-being. Because of the well- grounded connection between social-emotional well-being and positive outcomes (Berger,

Alcalay, Torretti, & Milicic, 2011), it is imperative to develop a better understanding of the perceptions of social-emotional health of ELLs, as such an understanding can lead to the implementation of services that better meet the needs of this population. Additionally, the heterogeneity of the ELL population seems to indicate a need to explore subgroups (e.g., Latinx

ELLs) within this student group. A breakdown of the ELL population may help eliminate some of the contradictory findings common within the ELL literature and ultimately lead to the development of more focused, culturally responsive intervention and prevention services to address the needs of these youth.

Internalizing Problems

Internalizing disorders (i.e. anxiety and depression) are the most commonly diagnosed mental illnesses in the United States among adolescents with at least one in ten teenagers between the ages of 12 to 17 reporting having had a major depressive episode within the past year (Lipari, Hughes, & Williams, 2016). Prevalence rates for anxiety disorders are equally elevated (Merikangas et al., 2010). For example, in a report for the National Institute of Health seeking to assess the life time prevalence of mental disorders among US adolescents, Merikangas et al. (2010) indicated that almost one in three teenagers met diagnostic criteria for an anxiety disorder and that severe anxiety disorders were present in 8.3% of their total sample. Similarly, the Anxiety and Depression Association of America (ADAA) indicates that anxiety disorders affect one in eight children in the nation (ADAA, n.d.). Anxiety and depression in childhood have been found to be strongly related (Essau, 2003). Some sources have indicated that children with a diagnosis of anxiety disorders are 29 times more likely to be diagnosed with depression at some point in their lifetime than are children without an anxiety disorder (Costello, Mustillo,

Erkantli, Keeler, & Angold, 2003). The co-occurrence of anxiety and depressive disorders is so prevalent that some scholars have suggested that both of these disorders be combined under a general, broad disorder, yet there seems to be a lack of consensus on this topic (Frick, Barry, &

Kamphaus, 2010). Considering their common reoccurrence, symptoms of anxiety and depression

have often explored alongside somatic complaints and social withdrawal and are broadly referred to as internalizing symptoms (Bongers et al., 2003).

Available data describing the percentage of students receiving special education services under the category of emotional disturbance does not indicate the percentage of youth who are found eligible for services based on internalizing symptomatology. Section 300.8 (Child with a

Disability) of the Individuals with Disabilities Education Act (IDEA, 2006) defines a “serious emotional disturbance” as follows:

Emotional disturbance means a condition exhibiting one or more of the following

characteristics over a long period of time and to a marked degree that adversely affects a

child’s educational performance: a) An inability to learn that cannot be explained by

intellectual, sensory, or health factors; b) an inability to build or maintain satisfactory

interpersonal relationships with peers and teachers; c) inappropriate types of behaviors or

fears under normal circumstances; d) a general pervasive mood of unhappiness or

depression; e) a tendency to develop physical symptoms or fears associated with personal

or school problems. Emotional disturbance includes schizophrenia. The term does not

apply to children who are socially maladjusted, unless it is determined that they have an

emotional disturbance.

The final three indictors (i.e. c, d, and e) within the criteria for qualification of a serious emotional disturbance seem to most align with the definition of internalizing symptoms described earlier. To the knowledge of this author, there is no specific information regarding the number of school age youth receiving special education services specifically within these three subcategories of the definition. Nevertheless, information provided by the National Center of

Educational Statistics (NCES, 2018) indicates that approximately 5% of the 6.7 million students receiving special education services do so under general category of emotional disturbance.

Latinx youth and internalizing problems. Latinx youth are frequently identified as being at particular risk for the development of internalizing problems (Twenge & Nolen-

Hoeksma, 2002). For example, using meta-analytic approaches to explore differences across various racial, socioeconomic, and age groups in scores on the Children’s Depression Inventory

(CDI; Kovacs, 1985, 1992), Twenge and Nolen-Hoeksma (2002) reported that Latinx youth scored significantly higher on the CDI (i.e., reported experiencing more symptoms) than did their

White and Black counterparts. Likewise, increases in self-reported depressive symptoms were identified during adolescence with depressive symptoms reported as being stable for both boys and girls between the ages of 8 to 11 with increases observed, particularly in female respondents, after the age of 12. Similarly, findings have been reported in other studies (e.g. Hankin &

Abramson, 2001; Nolen-Hoeksema & Girgus, 1994), identifying Mexican-American youth as having higher rates of depression when compared to their peers (Roberts, Roberts, & Chen,

1997). These findings seem to indicate that Latinx adolescents may be at specific risk for developing internalizing problems at higher prevalence rates than the overall population.

Despite the elevated prevalence estimates of internalizing disorders, it is often claimed that these figures may be conservative, as internalizing disorders are among the most difficult to diagnose because of their internal nature (Frick, Barry, & Kamphaus, 2010; Neil & Christensen, 2009).

Frick, Barry, and Kamphaus (2010) specified that these disorders take a larger toll on the children experiencing them than on those around them and that these children’s experiences may ultimately go unnoticed and their conditions untreated. Some sources state that only one out of every five children with an anxiety disorder will go on to receive treatment (Essau, 2003) and

that treatment is usually sought between six to 14 years after the initial onset of the disorder and impact to different aspects of a child’s life (Kessler, Olfson, & Berglund, 1998). Thus, it seems possible that prevalence rates of internalizing difficulties among Latinx youth may be even more elevated than current estimates indicate particularly when considering the stigma surrounding mental illness within the Latinx community (Interian, Ang, Gara, Link, Rodriguez, & Vega,

2010). In fact, sources have reported on racial/ethnic disparities in mental health access and service. Gudiño, Lau, Yeh, McCabe, and Hough (2009), for example, indicated that these differences are more prevalent when comparing access to care of youth experiencing internalizing versus externalizing problems. Results from their study indicate that non-Hispanic,

White youth experiencing internalizing difficulties are more likely to receive mental health supports and services than youth of color with similar concerns. No differences were identified when comparing unmet needs of youth experiencing externalizing difficulties, although youth of color were identified as having more need for supports in this area. Findings of this study further highlight the tendency of Latinx youth experiencing internalizing difficulties to be underserved.

Outcomes of internalizing problems. Symptoms associated with internalizing problems have been linked to an array of negative outcomes for those experiencing them. For example, high levels of anxiety in children have been associated with academic underachievement and difficulties with peer relationships and social competence (Ialongo, Edelsohn, Werthamer-

Larsson, Crockett, & Kellam, 1996; Van Ameringen, Mancini, & Farvolden, 2003). Similarly, adolescents with anxiety disorders have been shown to be at higher risk for drug dependencies, early school dropout, suicide, and unemployment, all of which may persist onto adulthood (Ost

& Treffers, 2001; Thibodeau, Welch, Sareen, & Asmundson, 2013; Woodward & Ferguson,

2001). Outcomes for children and adolescents who experience depression are similar.

Harrington (1996), for example, reported that childhood and adolescent depression are associated with a number of negative adult outcomes. Specifically, results from this study indicated that alongside a family history of psychiatric difficulties, adolescent onset depression, and severe depression in childhood were found to be significant risk factors for major depression in adulthood. Studies indicate that adolescent onset depressive symptoms are associated with a high rate of recurrence and may ultimately be indicative of a chronic course (Dunn & Goodyer,

2006). Similar findings have been reported for anxiety disorders, which are often described as being insidious in nature considering their tendency to reoccur later in life (Keller, Lavori,

Wunder, Beardslee, Schwartz, & Roth, 1992).

Trajectories of internalizing problems. Despite these findings indicating the tendency of internalizing problems to reoccur, recent evidence has identified different trajectories for adolescent depressive and anxiety symptoms. For example, a recent study by Hill, Mellick,

Temple, and Sharp (2017) identified four different trajectories of depressive symptomatology in a diverse sample of 1042 high school students who were followed for four years. Analyzing their data using growth mixture modeling, Hill et al. (2017) described the four trajectories as a) with mild and stable depressive symptomatology, b) with stable, elevated symptoms, c) with increasing depressive symptoms, and d) with decreasing symptoms. The authors indicated significant baseline differences across all groups except for the group with decreasing symptoms and the group with elevated depressive symptomatology. Other studies have shown similar findings (e.g., Hill et al., 2014; Morin et al., 2011; Stoolmiller et al., 2005) with some studies identifying three, (Yaroslavsky, Pettit, Lewinsohn., Seeley, & Roberts, 2005), four (Stoolmiller et al., 2005), and up to five (Morin et al., 2011) trajectories for internalizing problems.

While less explored, a number of factors have been identified as predictors of these different developmental trajectories including gender, a family history of psychopathology, bully victimization, and exposure to school violence (Hill et al., 2017; Morin et al., 2011; Stoolmiller et al., 2005; Yarolavsky et al., 2013). The exploration of these predictors has been a relatively recent academic endeavor, and there is still a need to identify potential predictors for these varying developmental trajectories of internalizing problems during adolescence. The identification of these predictors as well as different trajectories of internalizing problems in adolescence could help mental health professionals better provide prevention and early intervention services (Hill, Yaroslavsky, & Pettit, 2015), which may be the most appropriate approach for working with internalizing problems considering their tendency to reoccur and the challenges often associated with their identification and treatment. To this day, there have been no studies particularly focused on identifying the existence of internalizing symptom trajectories specifically within the ELL population. Identifying these may help inform future intervention work within the ELL population and provide further insight into their socio-emotional development as well as identify risk and protective factors for trajectory placement.

School Belonging

A general sense of belonging has long been understood to be foundational to human functioning. Maslow (1943) first identified belonging through his hierarchy of needs as one of the key factors necessary for human motivation and eventual self-actualization. In fact, a heightened sense of belonging consistently has been identified to be tied to a number of positive psychological and physical outcomes (e.g. Wadsworth, Thomsen, Stalzman, Connor-Smith, &

Compas, 2001). For children and adolescents, there is perhaps no setting other than home that proves to be more influential to development and that provides more opportunities to form

connections and ultimately belong than does school. The construct of school belonging, has often been explored in the literature. In their literature review on the topic, Slaten, Ferguson,

Allen, Brodrick, and Waters (2016) indicated that there seems to be more consistency in the way school belonging has been operationalized than in what it has been called. These authors indicate that a number of terms have been used in the literature to describe this construct (e.g. school connectedness, sense of community, and school attachment). Despite the variety of terms used to describe this construct in the literature, “school belonging” will be utilized throughout the present study to describe this construct and will be treated as a global term used to describe the various terms used to identify these constructs.

Outcomes of school belonging. School belonging has been associated with a range of academic and social variables as both a predictor and an outcome (Allen, Kern, Vella-Brodrick,

Hattie, & Waters, 2016). In fact, a heightened sense of school belonging has been identified as being associated with a wide-array of positive outcomes in students (Anderman, 2003; Newman,

Newman, Griffen, O’Connor, & Spas, 2007; Shochet, Smith, Furlong, & Homel, 2011; Sirin &

Rogers-Sirin, 2004). For example, using a multi-level approach, Magen-Nagar and Shachar

(2016) found that higher levels of student satisfaction and sense of school belonging lowered the impact of students’ individual characteristics (e.g. socio-economic status) on dropout risk highlighting school belonging as a protective factor for this outcome. Similar findings have highlighted the impact of school belonging on academic outcomes including academic performance. Working with a large sample of African American youth and their mothers, Sirin and Rogers-Sirin (2004) explored the relationship between academic achievement and various theorized predictors including school engagement, which they conceptualized as partially assessing a student’s sense of belonging to his/her school. Results from their study indicated that

educational expectations and school engagement were the two strongest predictors of academic performance for their sample. These findings indicate the existence of a relationship between school belonging and a number of indicators of student academic well-being. Nevertheless, the literature exploring the relationship between school belonging and indicators of social-emotional well-being have been more limited (Allen et al., 2016).

School belonging and internalizing problems. Although small in comparison to the size of the literature exploring school belonging and academic variables, an emerging body of literature has explored the relationship between school belonging and indicators of mental health.

Of particular importance for the present study is the work of Newman and colleagues (2007) whose findings indicated a negative relationship between school belonging and depressive symptomatology in adolescence. The authors found that school belonging tended to decrease during the transition between middle school to high school and that this decrease in belonging is accompanied by an increase in depressive symptoms. Further, some studies have found that school belonging itself may serve as a protective factor to negative mental health outcomes for adolescents. Shochet, Dadds, Ham, and Montague (2006), for example, found that school connectedness negatively predicted anxiety symptoms for girls and depressive symptoms for boys and girls one year later. School connectedness also positively predicted general functioning one year later for boys. The authors indicate that school belonging continued to be significant negative predictor of negative affect even when controlling for initial levels of negative affect.

Furthermore, the reverse relationship was not established. Namely, prior mental health was not predictive of school belonging for either boys or girls in the study. Thus, the authors conclude that school belonging may be an underemphasized and underutilized predictor of youth mental health particularly youth depressive symptomatology. In a prospective, longitudinal study

investigating the relationship between different factors of school belonging (i.e. Caring

Relations, Acceptance, and Rejection) and negative affect, Shochet, Smith, Furlong, and Homel

(2011) found that each of these three factors were significant predictors of negative affect.

Acceptance was found to be a significant negative predictor of negative affect at all three times of data collection for both boys and girls with lower levels of acceptance being associated with higher levels of negative affect. Rejection and Caring Relations significantly predicted negative affect in two and in all three time points for boys and girls respectively. The authors specify the findings provide further support to the idea that girls are more relationship orientated during the teenage years and that they may thus be differentially impacted by school belonging than boys.

Despite this, though, the work of Shochet and colleagues (2011) provides further evidence regarding the relationship between school belonging and mental health particularly that school belonging may serve as positive indicator of mental health and may further serve as a protective factor for school-aged youth.

School belonging and Latinx youth. As with most literature regarding school belonging and underrepresented youth, there is limited literature exploring this construct within the Latinx student population (Slaten et al., 2016). Nonetheless, some argue that a sense of school belonging may be particularly salient to Latinx and other minority youth (Blanco-Vega et al.,

2008). Blanco-Vega and colleagues (2008) describe schools as important “cultural gates” (p. 56) that not only provide all students opportunity to develop prosocial skills to become proactive citizens in American society, but they are also the only source of social and cultural learning for

Latinx immigrant youth. The type of belonging experienced in their school setting, they indicate, is likely to determine both the relationships and the outcomes these youths will have with the larger American culture. Blanco-Vega et al. (2008) further allude that Latinx youth are likely to

feel more welcome in schools where their cultural identity is not at risk and where they are allowed to express their cultural values.

Current literature has established that school belonging is, in fact, significantly related to a number of both positive and negative outcomes when working with Latinx and immigrant students (e.g. Cupito, Stein, & Gonzalez, 2015; Maurizi, Ceballo, Epstein-Ngo, & Cortina,

2013). These findings have been consistent across qualitative and quantitative work. For example, Davison Avilés, Guerrero, Barajas Howarth, and Thomas (1999) found that a low sense of school belonging was attributed as a primary factor for Latinx youth deciding to stop attending school. The youth in this study reported feeling left out of their school’s mainstream culture indicating that a significant portion of their Latinx peers were transferred into remedial/alternative educational settings. Similarly, Ibañez, Kuperminc, Jurkovic, and Perilla

(2004) found that a significant relationship between school belonging and perceived academic competence and academic aspirations and expectations among Latinx teenagers. Their findings showed a positive relationship among these variables indicating that higher levels of school belonging were related to higher levels of perceived academic confidence, academic expectations, as we all as higher levels of academic aspirations.

The literature regarding the impact of school belonging on the social-emotional well- being on Latinx youth has been less explored. Nevertheless, existing work seems to be primarily focused on the relationship between school belonging and acculturative stress (i.e. the tension experienced by members of a minority group as they acculturate to the dominant culture; Berry,

1997) with findings indicating a negative relationship between these two constructs (e.g. Roche

& Kuperminc, 2012). Despite being limited, the existing literature on school belonging and internalizing problems among Latinx youth indicates the presence of a negative relationship

between these variables (e.g., Cupito et al., 2015; Georgiades, Boyle, & Fife, 2013; Maurizi et al.

2013).

For example, working with 202 Latinx adolescents from low-income, urban neighborhoods and using structural equation modeling, Maurizi et al. (2013) identified factors

(i.e. teacher and school peer support) that helped to increase Latinx adolescent’s sense of school belonging. Furthermore, these authors explored the relationship between school belonging and community belonging and various indicators of academic and psychological well-being. Their findings indicated the presence of significant, positive relationships between all academic indicators including academic aspirations, academic expectations, grades, educational values, and school effort. Similarly, their results indicate that increases in school belonging were associated with decreases in psychological distress. Namely, school belonging was negatively associated with symptoms of both anxiety and depression. While community belonging was also negatively associated with symptoms of depression, it was only school belonging that displayed a negative relationship with both indicators of internalizing problems. These findings seem to provide support the work of Blanco-Vega et al. (2008) indicating that school belonging may be particularly salient and ultimately be a protective factor for Latinx and other minority youth.

While cross-sectional studies have provided insight into the potential dynamics between school belonging and internalizing problems, there has been limited longitudinal work exploring the dynamics between school belonging and indicators of mental health. Furthermore, existing literature seems primarily limited to cross-sectional studies that have established correlational relationships between school belonging and a number of academic and social-emotional constructs, which do not allow for the establishment of causal relationships or the directionality of this relationship. The limited existing longitudinal work with school belonging (e.g. Shochet

et al., 2011), however, provides some understanding into the directionality of this relationship while indicating the need for further exploration of this topic. Furthermore, no studies have analyzed the impact of school belonging on internalizing symptom trajectories. As indicated earlier, there are a number of benefits to the identification of potential predictors of internalizing symptom trajectories. There may be, however, particular benefits to the use of positive indicators of well-being, such as school belonging, including the reduction of stigma often associated with reporting and eventually identifying psychological problems. Similarly, the assessment of an individual’s psychological and social strengths may help identify potential protective factors against negative developmental outcomes (Furlong, Dowdy, Carnazzo, Bovery, & Kind, 2014).

Furthermore, exploration of these longitudinal relationships specifically within a Latinx and

Latinx ELL sample could help provide insight into the potentially unique experiences of these youth.

Victimization

Peer victimization, the type of bullying of interest for the present study, often has been broken down into three subtypes: peer exclusion, social victimization, and overt victimization

(Sandstrom & Cillessen, 2003). Overt victimization, as its name implies, refers to bullying behavior that is more observable and, thus, is characterized by physical assault (e.g., hitting and kicking) and verbal threats (Hoglund & Leadbetter, 2007). Social victimization, on the other hand, refers to aggressive behavior that is geared at damaging an individual’s interpersonal relationships or to hurt someone’s social status within a peer group (Paquette & Underwood,

1999). Although there is some emerging evidence to indicate that social victimization may actually be a multidimensional construct composed of both verbal and nonverbal victimization, these findings have been rather preliminary and not thoroughly explored in the literature (Blake,

Sook Kim, Sohn McCormick, & Hayes, 2011). At times described as being a subtype of social victimization, Buhs and Ladd (2001) described peer exclusion as efforts to marginalize an individual from peer groups (e.g., not inviting to events). While cyberbullying or victimization that occurs through electronic mediums has more recently emerged among the literature and has been identified as a new and common form of bullying associated with a number of negative outcomes (Kowalksi & Limber, 2007; Raskauskas & Stoltz, 2007), this study will focus on non- electronic forms of victimization, and thus, cyberbullying will not be further discussed.

Prevalence of peer victimization. National reports indicate peer victimization is a pervasive problem with some sources revealing that as many as 36% of adolescents report having been victimized within the past two months (Wang, Iannotti, & Nansel, 2009). Working with a nationally representative sample of over 7,000 youth in grades sixth through tenth who were part of the Health Behavior in School-aged Children (HBSC) study and completed the

Olweus Bully/Victim Questionnaire, Wang et al. (2009) found that a significantly large portion of their participants reported being involved in bullying/victimization behaviors. When asked to indicate their experience with victimization within the past two months, 12.8% of participants indicated being physically victimized (e.g., hitting, kicking, pushing, shoving around, or locking indoors), 36.5% reported experiencing verbal aggression (e.g., general name calling as well as name calling based on race or religion or making fun or teasing in a hurtful manner), and 41.0% of these youth reported experiencing relational bullying (e.g., being socially excluded or having rumors spread about them) at least once. Similar findings have been found in other studies with estimates indicating that approximately one third of school-aged youth will be victimized in one way or another during an individual school year (DeVeo & Bauer, 2010).

Certain student subgroups, particularly those who are viewed as being different from the majority group within a certain setting, have been found to be at risk for peer victimization

(Davies, 2006; Phillips, 2007). Thus, racial and ethnic minorities seem to be particularly at risk of being the targets of bullying behavior if the majority of the school is the dominant culture.

For example, there is evidence to indicate that racial minority youth are often times the target of harassment because of certain physical traits (Peskin, Tortolero, & Markham, 2006) and that minority youth are more likely to report being victimized than those who are part of the majority

(Graham & Juvonen, 2002). The limited literature focused on the victimization experienced by

ELLs, who are at times referred to as language minority youth, indicates these youths experience victimization at times related to their unique characteristic. Mendez, Bauman, and Guillory

(2012), through qualitative work, found that Mexican-American immigrant youth, for example, reported being frequently victimized because of their difficulties with the English language and placement in English as a Second Language classrooms, which were described as leading to social isolation. In a similar study that instead employed quantitative approaches, Sulkowski,

Bauman, Wright, Nixon, and Davis (2014) explored differences in victimization experiences of immigrant and non-immigrant youth. Among other findings, the authors reported that youth from immigrant families reported being physically victimized more often than youth from non- immigrant families. Moreover, immigrant youth were more likely to be victimized because of their religion, race, or family income (Sulkowski et al., 2014). Thus, it seems likely that ELLs, many of which are immigrants, may be at higher risk of experiencing victimization in the school setting than those of the majority culture.

Outcomes of peer victimization. The prevalence of victimization within the nation’s schools is particularly concerning considering the array of negative outcomes associated with

being victimized. Victimization has been reported to impact the academic well-being of youth including association with decreases in performance and attendance, as well as leading to the perception of hostility in the school setting (Eisenberg, Neumark-Sztainer, & Perry, 2003).

Similarly, peer victimization has been shown to be associated with increases in psychopathology in the form of both internalizing and externalizing difficulties (Reijntjes, Kamphuis, Prinzie,

Boelen, van der Schoot, & Telch, 2011; Reijntjes, Kamphuis, Prinzie, & Telch, 2010). These outcomes have been found to exist even when controlling for emotional and behavioral difficulties in childhood. Similarly, in a recent meta-analytic study, Klomek, Sourander, and

Elonheimo (2015) found that victimization during childhood is associated with increases in psychopathology, criminality, and suicidality in adulthood. Focusing only on prospective longitudinal studies, the authors specified that negative outcomes are associated with engagement in bullying behavior both as a bully and a victim but specified that victims are at a particularly high risk for internalizing problems. Others have indicated that teenagers who are frequently victimized are two to three times more likely than their non-victimized peers to develop an anxiety disorder and several other internalizing difficulties (Stapinsky et al., 2014).

Peer victimization and internalizing problems trajectories. It is not until recently, however, that empirical work has sought to explore the impact of bullying behavior, particularly victimization, on trajectories of internalizing problems. Hill et al. (2017) reported that bully victimization was a significant predictor of the four identified trajectories in their study.

Namely, the authors indicate that participants with mild and with decreasing depressive symptoms reported significantly less victimization than did participants in the increasing or elevated trajectory groups. Their findings implied that while some adolescent bully victims may not show elevated depressive symptoms initially, they may over time develop these symptomatic

behaviors. As such, they advise that mental health professionals may consider intervening to address the victimization these youths are experiencing but also may consider providing the victim with depression prevention services. This evidence thus indicates that peer victimization may serve as a predictor of internalizing symptom development. Nonetheless, there is evidence to indicate the existence of a reciprocal relationship between internalizing problems and victimization (e.g., Reijntjes et al., 2010). Using meta-analytic approaches, Reinjtjes and colleagues (2010) sought to explore the direction of effects between victimization and internalizing problems by compiling data from longitudinal studies looking at the relationship between these variables. Namely, the study sought to determine if internalizing problems were either an antecedent, consequence, or both an antecedent and consequence of peer victimization.

Findings from the 18 studies analyzed in this study indicate that internalizing problems are both antecedents and consequences of peer victimization. In other words, youth who are victimized are more likely to develop internalizing problems yet youth with internalizing problems are also more likely to be victimized. The authors indicate that this reciprocal relationship is indicative of a vicious cycle between these variables that ultimately leads to the maintenance of high levels of victimization. Despite these findings, no study to date has examined peer victimization as a distal outcome of different internalizing problems trajectories. As such, the present study will seek to determine if victimization is an outcome of certain internalizing trajectories.

CHAPTER III

METHOD

Research Design

The present study is a quantitative, retrospective longitudinal study that will use pre- existing data made available through Project Achieve. The primary purpose of the study was to explore the existence of different growth trajectories of internalizing problems within a sample of Latinx youth as well as well as with a smaller subsample of Latinx ELLs and to explore school belonging as a possible predictor of trajectory placement. Furthermore, this study explored peer victimization as a distal outcome of internalizing problems particularly among

Latinx youth. The participants of the current study did not subject any experimental conditions.

As such, no adverse experiences or reactions were expected. Approval for the present study was obtained from the Institutional Review Board (IRB) at Texas A&M University.

Participants

Participants were drawn from a larger sample of 784 children who were originally recruited for a longitudinal study seeking to examine the impact of grade retention on academic achievement. They were initially drawn from three school districts in central-west Texas in two sequential cohorts during their first-grade years in the fall of 2000 and 2001 (Time 1). School

District A had a student population of 13, 558 and the following ethnic distribution: 38% White,

37% Latinx, 25% African American, and less than 1% other. District B’s had a total student population of 24,429 with an ethnic distribution of 35% White, 30% Latinx, 30% African

American, and 5% other. District C’s student population of 7, 424 had an ethnic distribution of

67% White, 12% Latinx, 12% African American, and 9% other. More information detailing the recruitment process of the 784 participants can be found in Hughes and Kwok (2006).

Eligibility for the original study was based on being identified as at-risk for academic difficulties through a state approved, school administered measure of literacy. Students were identified after scoring at or below the median on a state-approved measure of literacy in either

May of their kindergarten year or September of their first-grade year. Furthermore, to be included in the study, the child could not have previously been retained in first grade, not have been previously identified for special education services other than speech and language, and had to speak either English or Spanish.

Some questions for the present study focused on specific student subpopulations.

Specifically, demographic data was used to identify Hispanic/Latinx students and, within that subgroup, Latinx ELLs. At Time 1 of data collection, 293 students were identified as

Hispanic/Latinx with 152 (52.22%) being male. Of the Hispanic students, 114 were identified as being ELL based on their Bilingual Education Status. As data were collected longitudinally, attrition occurred and not all students from Time 1 continued to be in the study through the time of interests for the current study. For purposes of this study, only those students who were still part of the original longitudinal study at Time 9 were considered.

Measures

Multiple measures were used across the project years. The measures of interest in this study are the Peer Experiences Questionnaire (PEQ; Prinstein et al., 2001), the Psychological

Sense of School Membership (PSSM; Goodenow, 1993), and the Strengths and Difficulties

Questionnaire (SDQ; Goodman, 1997).

Demographic information. Demographic information collected at Time 1 from school archival data was used to identify the gender, race, and ELL status of participating youth.

Internalizing symptoms. Students completed the Strengths and Difficulties

Questionnaire (SDQ; Goodman, 1997). The SDQ, in its various forms (e.g. teacher, parent, and self-report) is one of the most widely used screening tools for adolescent mental health

(Rothenberger & Woerner, 2004). The self-report version of the SDQ is a 25-item questionnaire designed to be completed by youth between the ages of 11-17. The measure is composed of four problem subscales (i.e., peer problems, hyperactivity-inattention, emotional symptoms, and conduct problems) and one strengths scale (i.e., prosocial behavior; SDQinfo.org, n.d.). Each subscale consists of five items where respondents are asked to state how true the presented items have been for them in the past six months using a three-point Likert scale: (0) not true, (1) somewhat true, (2) certainly true. Responses to the four problem subscales can be summed to give a total difficulty score. The psychometric properties of the SDQ in all its versions have been explored thoroughly nationally and internationally (e.g., Bourdon, Goodman, Rae,

Simpsons, & Koretz, 2005; Goodman, 2001; Yao, Zhang, Zhu, Jing, McWhinnie, & Abela,

2009). Overall, the SDQ was found to be an efficient and effective screener for child and adolescent mental health problems. Reliability estimates for the self-report version of the SDQ have been deemed satisfactory across a number of studies (e.g., Goodman, 2001; Mellor, 2004;

Mellor & Stokes, 2007).

For purposes of this study, the Emotional Symptoms subscale of the SDQ was used to measure internalizing problems. Items in this subscale ask respondents to indicate to what extent they felt unhappy, worried, anxious, or fearful. Scores on the Emotional Symptoms subscale show strong correlations with clinical assessments of related diagnoses (e.g., separation anxiety disorder and generalized anxiety disorder; Hawes & Dadds, 2004). The self-report of the SDQ was administered in years 6 through 9 and all data years were used in the current study.

School belonging. Students completed the Psychological Sense of School Membership

(PSSM; Goodenow, 1993). The PSSM is an 18-item self-report questionnaire designed to be completed by middle and high school youth ages 12 to 18. The measure is an assessment of the youth’s perception of belonging and being engaged in their school. Responses are based on a 5- point Likert scale with a range from 1 (Not at All True) to 5 (Completely True). Five items on the PSSM are reverse scored and all item scores are summed up for a global score (Goodenow,

1993). The measure has been identified as yielding reliable scores with Cronbach’s alpha ranging between .78 and .95 across varied samples of middle and secondary school students

(Goodenow, 1993). Similarly, the results yielded by the PSSM have been shown to have high test-retest reliability (.78) at four weeks (Hagborg, 1994). Results of the PSSM were found to be negatively correlated to measures of depression as measured by the Child Depression Inventory

(r = -.67 to -.74), as well as scores from the SDQ (r = -.60 to -.68; Shochet at al., 2006).

Similarly, the scores have been found to correlate positively with positive life expectations (Kia-

Keating & Ellis, 2007) and school success (Goodenow, 1993). Thus, the PSSM demonstrates both convergent and discriminant validity.

The factor structure of the PSSM has been less explored but studies have, at times, found inconsistencies (You, Ritchey, Furlong, Shochet, & Boman, 2011). For example, with a sample of 240 students, Hagborg (1994) reported a three-factor structure with belonging, rejection, and acceptance being identified as factors. Most items on the PSSM loaded onto the belonging factor, and that factor accounted for the majority of the variance. Few items loaded onto the remaining two factors. Because of this and cross-factor loadings, Haborg (1994) went onto describe the PSSM as a multidimensional structure with a main factor (belonging) and two factors that had limited applicability. Through exploratory and confirmatory factor analysis, You

et al., (2011) concluded that the PSSM is a multidimensional instrument with three factors: caring relationships, acceptance, and rejection. Despite these findings, typically the PSSM has been used as a unidimensional measure of a student’s perception of belonging to their school.

The PSSM was administered from years 4 through 9; data from year 4 was utilized in the present study in an effort to explore early levels of school belonging. A total score was computed and used an indicator of school belonging for these youths.

Peer victimization. The revised Peer Experiences Questionnaire (PEQ; Prinstein et al.,

2001) is an 18-item self-report measure that explores students’ engagement in bullying perpetration and victimization behaviors. The revised PEQ consists of four scales: overt and social aggression, as well as overt and social victimization. For purposes of this study, only the victimization scales will be used. Participants were asked to rate the frequency with which they experienced overt (e.g., physical or verbal aggression) and social victimization (e.g., peer exclusion) within the past year using a five-point Likert scale ranging from never (1) to a few times a week (5). The victimization subscales of the revised PEQ demonstrate adequate reliability and validity (Prinstein et al., 2001). Both subscales correlate significantly with peer reports of victimization and are mildly correlated. Furthermore, both subscales were significant predictors of adolescent depressive symptoms (Prinstein et al., 2001). The PEQ was administered to the student sample only at Time 9.

Procedures

The larger longitudinal study was approved by University Institutional Review Board as well as each school district’s research advisory committee. Student demographic information including age, gender, race/ethnicity, etc. was collected from school district records. All measures used in this study were completed individually by students. Trained graduate and

undergraduate students, who received training in measure administration, formed part of the research staff and served as primary assessors. All future assessors initially received 20 hours of training, and additional training was provided until proficiency in administration was achieved.

A school psychology doctoral student and an undergraduate research assistant reviewed all protocols for accuracy.

Statistical power. The growth model analyses, which are discussed in the sections below, performed in the present study are power intensive. Nevertheless, considering their exploratory nature, there is no direct approach to compute their needed power (Ram & Grimm,

2007). Based on a review of literature assessing for internalizing symptom trajectories among youth, most GMM analyses have been conducted with relatively large sample sizes with some including approximately 1000 participants (e.g. Hill et al., 2017) and others as having smaller sample such (Stoolmiller et al., 2005) who worked with 206 men. Thus, it was determined that the current study would be sufficiently powered to complete the proposed GMM analysis with the estimated sample of 500 students within the general sample and approximately 200 youth in the Latinx and Latinx ELL subsamples.

Missing data. Item-level missing data and attrition in the longitudinal analyses are the two forms of missing data anticipated in the current study. Mplus 23 performs model estimation using Full Information Maximum Likelihood (FIML; Enders & Bandalos, 2001), which allows item-level missing data assuming that the data is missing at random. As indicated earlier, not all students who initiated the study (Time 1) continued to be enrolled at the times of interest for the current study namely Time 4 through Time 9. Only data for students who continued to be part of the larger longitudinal study at Time 9 were used. Sensitivity analysis did not indicate significant differences among final and initial samples in the variables of interest.

CHAPTER IV

RESULTS

This chapter describes the results of the analysis, including descriptive statistics for the three student samples used in the study, and whether or not the hypothesis described earlier were supported.

Descriptive Statistics

Prior to conducing the GMM analysis to identify trajectories, descriptive information was examined for the overall sample and for each of the two subsamples (i.e. Latinx youth and Latinx

ELLs.) Tables 1-6 in Appendix A provide a summary of the descriptive statistics obtained using

SPSS 25 for the variables of interest for the present study. Significant findings include the tendency for the distribution of various variables including those assessing internalizing problems, school belonging, and victimization to deviate from normal. Namely, student reports of internalizing problems through the Emotional Problems subscale of the SDQ, of school belonging reported through the items of the PSSM, and the victimization scales of the PEQ were generally positively skewed within the general student sample as well as the two subsamples.

Tests of normality (see Table 7) using the Shapiro-Wilk statistic verified these findings for variables. Considering the analysis of interest (i.e. GMM) and aligned with recommendations by

Muthen (2009), who indicates that mixture modeling is by nature designed to capture non- normal outcomes and that transforming variables to meet normality assumptions associated with other analysis would lead to the loss of substantively important latent classes that are potentially present, data were not transformed. As such data were utilized throughout the analysis without any modifications. Analysis of Variance (ANOVAs) were used to determine whether differences existed among the non-Latinx student sample, the Latinx student sample, and the Latinx ELL

student sample’s self-reported internalizing problems across each of the four-time points of interest (i.e. T6, T7, T8, and T9). It was hypothesized that Latinx ELL youth would report significantly higher levels of internalizing difficulties than their Latinx and non-Latinx peers.

Similarly, it was hypothesized that Latinx youth would report significant higher levels of internalizing difficulties than their non-Latinx peers. Findings of these analyses did not support the hypothesized results, as no significant differences were found between self-reported internalizing problems among any of the three student subgroups throughout the four-time points.

Model Selection

The fit statistics for the GMM series for each of the three subgroups of interest are shown in tables 8, 9, and 10. The following paragraphs describe the decision-making process used to establish the best model fit. A series of models was fit into the overall student data (see Figure

1). Based on previous research, it was hypothesized that at least two different subgroup developmental trajectories would emerge; namely, it was hypothesized that one subgroup would have a trajectory exhibiting a stable mild level of internalizing symptoms and another would have a trajectory exhibiting stable but elevated internalizing symptoms in the overall sample.

GMM was used to explore the possible existence of different trajectories of internalizing problems. Muthén and Muthén (2000) describe GMM as a person-centered statistical approach that can be used to detect heterogeneity within data by extracting existing latent classes. GMM, then, allows different groups of individuals to vary around mean growth curves instead of considering their variation only around individual mean growth curves. GMM also allows for probability estimates to determine the likelihood of class membership for each individual. All analysis were performed using SPSS 25 and Mplus version 7.3 (Muthén & Muthén, 1998-2014).

Procedures followed for this analysis and for all analysis considering the presence of growth trajectories were guided by the work of Ram and Grimm (2009) who suggest a four-step process to conducting a GMM analysis. First, individual trajectories were examined for the presence of outliers. Then, to help determine if the present growth in internalizing problems was best described by linear or nonlinear (e.g. quadratic) trends, a single class growth curve will be fitted on the data. Third, model estimation occurs. Namely, the number of latent-class trajectories was determined using both information-based criteria and nested-model likelihood ratio tests

(Nylund, Asparouhov, & Muthén, 2007). Finally, the trends and differences between the newly obtained latent groups were examined. Considering the limited time points in the current data

(i.e. four), only linear trends were explored. With each subgroup of interest, class enumeration began with a one class solution and was followed by an exploration of additional models with more latent classes as recommended by Muthen & Muthen (2009). Classes were labeled based on the general trajectory they followed according to their mean values throughout the four time points. Figures 3 – 5 in Appendix B are the mean value plots for each of the three models.

Fit indices produced for the general student population support a four-class solution as the optimal growth mixture model, as it yielded significant BLRT and LMR p-values (p < .001 for both indices) indicating the model provided significantly better fit to the data than did a three- class solution (see Table 8). Similarly, the BLRT and LMR values for the five-class model were non-significant indicating it did not significantly improve model fit. Furthermore, the four-class solution provided the lowest BIC (BIC = 7937.35) and ABIC (ABIC = 7870.68) values compared to the all other models. The four-class model identified two trajectories displaying an increase in internalizing problems over time, which differed in the initial levels of reported difficulties. Namely, one group initially identified mild levels of internalizing problems on the

SDQ (b = 3.21, p < .001) and the second initially identified elevated levels of internalizing difficulties (b = 5.45, p < .001). These classes composed approximately 16% and 7% of the sample respectively (see Table 11 for a breakdown of class percentages). The three-class model did not distinguish these two classes and instead appeared to combine them into one.

Considering that a score of “5” is considered to be the clinical cut off for the Emotional

Problems subscale of the SDQ (SDQ info, nd), the four-class solution appeared to also be theoretically most appropriate, as it provided four interpretable classes. As expected, this model indicated a majority of youth or approximately 68% of the sample belonged to a trajectory characterized by reporting “Stable-Mild” internalizing symptomatology over time (b = 2.22, p <

.001; m = -0.34, p <.001). The model also included a trajectory composed of youth who reported a general decrease of internalizing symptoms over time (b = 6.08, p < .001; m = -1.18, p < .001), named “Decreasing”, which composed of approximately 10% of the sample.

Int. Problems Int. Problems Int. Problems Int. Problems T6 T7 T8 T9

Intercept (IP) Slope (IP)

Figure 1. GMM examining trajectories of internalizing symptoms in the general sample.

As with the general student sample, it was hypothesized that at least two growth trajectories would emerge describing the development of internalizing problems in the sample of

Latinx youth. Latinx youth within the larger subsample were identified and used as for this second part to the model selection process. Namely, only youth identified as Latinx in Time 1 and who continued to be part of the study at Time 9 were incorporated into the Latinx model.

Table 9 provides the fit statistics of four models on this sample. The three-class solution was identified as best fitting the data, as provided a statistically significant BLRT (p < .001) value and the lowest Adjusted BIC score. While the two-class solution similarly led to statistically significant BLRT and LMR values (p < .001 and p < .01, respectively), indicating it demonstrated better fit than the one class solution, and yielded the lowest BIC value, the model obscured the existence of a distinct and important class demonstrating a trajectory for increasing internalizing problems, which is illustrated in Figure 4. Thus, based on substantive theory and fit indices, the three-class solution was identified as best modeling the data (see Table 12). The

“Increasing” class (b = 3.72, p < .001; m = 0.50, p < .001) composed approximately 14% of the sample (n = 29). Surprisingly, the three-class solution also demonstrated the existence of a trajectory characterized by a low intercept (b = 2.53, p < .001; m = 0.56, p < .001) that further decreased over time and, and as with the general youth sample, a “Stable Mild” class (b = 2.87, p

< .001; m = 0.09, p = .45), which composed 33% of the sample (n = 70).

Similar analyses were conducted with the Latinx ELL sample with an aim to explore the emergence of trajectories of internalizing problem development among these youths. Latinx ELL youth within the larger subsample were identified and used as for this this part of the model selection process. Namely, only youth identified as Latinx and ELL in Time 1 and who continued to be part of the study at Time 9 were incorporated into the Latinx ELL model. Unlike

the previous samples, the number of Latinx ELL students was smaller than those samples described in previous studies using GMM to explore trajectories of internalizing problem development. Thus, as indicated earlier, these results were intended to be exploratory in nature.

Table 10 describes the fit statistics for the three models used to identify trajectories within this sample. It was hypothesized that at least two classes would emerge in the process. A two-class solution was identified as having the best fit for the Latinx ELL sample, as it yielded the lowest

BIC and statistically significant BLRT (p < .05) and LMR (p < .01) values indicating the model provided statistically better fit than the one-class model. Similarly, the two-class solution offered the lowest BIC value (BIC = 1248.86), and while the three-class solution yielded the lowest

ABIC value, it identified a third class that compromised a very small portion of the student sample (i.e. less than 3%). Similarly, it led to statistically insignificant BLRT and LMR values when compared to the two-class solution further providing evidence for the fit offered by the two-class model. Table 13 describes the class counts and proportions for each of these classes.

Class 1 (Stable Mild) compromised approximately 77% of the sample (b = 2.08, p < .001; m = -

0.21, p < .05). Class 2 (Stable Elevated) compromised the remaining 33% of the youth sample (b

= 4.95, p < .001; m = -0.26, p = .21. Figure 5 is the mean plots for the two-class solution.

Figure 2. GMM examining trajectories of internalizing symptoms including race and ELL status covariates.

Predictive Ability of School Belonging

After the identification of the most appropriate model for each of the three samples of interest, an additional growth mixture model analysis was conducted with each of the three identified models with covariates using the Bolck, Croon, and Hagenaars (BCH) three step method (Asparouhov & Muthén, 2014; Bolck, Croon, & Hagenaars, 2004). The optimal GMM model was selected before inputting covariates to prevent the auxiliary variables from biasing the class enumeration process (Nylund-Gibson & Masyn, 2016). Considering previous research indicating the predictive ability of gender to growth trajectory placement (e.g. Hill et al., 2017), gender was included as a covariate alongside analyses when assessing the predictive ability to school belonging. A dichotomous variable identifying gender (Male = 1) was used for this analysis. Tables 14 and 15 summarize the logits, standard errors (SE), p-values, and odds ratios for each of the covariates included in the four-class model with the general student sample.

Significant gender effects were evident for the first and second class (p = .02) such that female students were more likely to belong to class 2 or the “Increasing-Elevated” class than their male counterparts. School belonging, however, was not observed to have a statistically significant effect on class membership for the general student sample.

A similar procedure was used to assess the predictive ability of gender and school belonging on the three-class model specific to Latinx youth and the two-class model for the

Latinx ELL youth. Tables 16 and 17 summarize the results of the Latinx youth analysis while

Tables 18 and 19 summarize the results for the Latinx ELL sample. Gender was not identified as being a significant predictor of class membership for the Latinx youth sample with the logit and odds ratio estimates yielding nonsignificant values. School belonging, however, was identified, to significantly distinguish membership between Class 1 (Increasing) and Class 3 (Decreasing

Mild) with youth in the Decreasing Mild class reporting significantly higher levels of school belonging (p = .02). Similar findings were observed for the Latinx ELL sample where gender was not identified as being a significant predictor of class membership but school belonging distinguished membership between the two observed classes. Namely, Latinx ELL’s in the

“Stable Elevated” class reported lower levels of school belonging when compared to their peers who displayed a “Stable Mild” internalizing problem trajectory (p = .02).

Victimization Distal Outcome

The Peer Experiences Questionnaire (PEQ; Prinstein et al., 2001) collected at Time 9, was used as an indicator of experiences of victimization. As indicated earlier, previous studies identified the existence of four subscales in the PEQ (Prinstein et al., 2001) namely two bullying scales (overt and relational) and two victimization scales (overt and relational). A confirmatory factor analysis (CFA) was conducted on the general student sample assessing for the fit of the

four-factor model identified by Prinstein and colleagues (2001). The CFA produced adequate fit and good factor loadings across the four factors (above .30; see Figure 6 and Table 20). It, however, also identified a strong correlation between the two victimization factors indicating that a three-factor solution may be most adequate for the data. Nonetheless, considering the established four-factor (i.e. Overt Aggression, Relational Aggression, Overt Victimization, and

Relational Victimization) model identified for this measure (Prinstein et al., 2011), this model was maintained for all future analysis. To examine the predictive validity of the classes yielded for each of the three samples, the overt and relational victimization subscales of the PEQ

(Prinstein et al., 2011) were used as distal outcomes for the three identified models and average trajectory victimization scores were examined. The manual BCH method was used for this process, as both covariates and the victimization factors were examined in the analyses. This approach allowed for the relation between the covariates (i.e. gender and school belonging) and the victimization distal outcomes to be controlled for. Tables 21, 22, and 23 each present the trajectory specific means and standard errors for both overt and relational victimization after controlling for the before mentioned covariates. As indicated earlier, the BCH method was used to test which classes differed in their mean outcome scores for both victimization scales of the

PEQ (Prinstein et al., 2011).

Chi-square statistics and their corresponding p-values are presented in Tables 24 - 29. A conservative p-value of .01 was used to adjust for increased error given the multiple tests run.

Within the general student sample, class specific differences were observed in both victimization scales. Namely, students in Class 2 (Increasing Elevated) on average reported significantly higher levels of overt and relational victimization than students in the Class 3 (Stable Mild).

Similarly, students in Class 1(Increasing Mild) on average reported significantly higher levels of

relational victimization than their peers in Class 3(Stable Mild). Within the Latinx sample class differences were observed in mean reported relational victimization with students in the

Increasing class reporting higher levels of victimization on average when compared to their peers in the Decreasing Mild class. Consistent results were observed within the Latinx ELL model with youth in the Stable Elevated class reporting significantly higher overt and relational victimization scores than their peers in the Stable Mild class. Across analyses, a general trend was observed where groups reporting stable high levels of internalizing problems or an increase in internalizing problems over time showing a tendency to report higher levels of both overt and relational victimization.

CHAPTER V

SUMMARY

This final chapter discusses this study’s key findings, explores possible explanations for these, reviews limitations and future directions, as well as implications for research and schools.

Key Findings

Although recent studies have explored the existence of internalizing problem trajectories using GMM within mainstream student samples (e.g. Hill et al., 2014; Yarolavsky et al., 2014), no study has to date explored the emergence of these trajectories among samples of Latinx or

Latinx ELLs as well as the relationship of these trajectories to student’s victimization experience and school belonging. Thus, the current study contributed to the growing body of literature by exploring the existence of internalizing problem trajectories using GMM among a sample of

Latinx and Latinx ELL youth. Specifically, the present student used GMM to identify the existence of internalizing problem trajectories among a general sample of students and then explored the stated subsamples within these. The results of the analysis provided support for the existence of three trajectories within the larger Latinx sample and two trajectories within the smaller Latinx ELL subsample. Differences were observed in the trajectories identified within the broader student sample and the two Latinx subsamples. Namely, models identified for the

Latinx and Latinx ELL sample consisted of less trajectories than those observed in the broader student sample (i.e., included Latinx youth alongside youth of various other races), although similar general trends were identified. Furthermore, the study explored the predictive ability of school belonging, a factor often identified as being significantly associated with positive youth development and various positive youth outcomes (e.g. Slaten et al., 2016), in determining trajectory placement. While previous studies have identified various predictors (e.g. gender,

victimization) of trajectory placement, no studies have explored a protective factor like school belonging. Regarding covariates (e.g. predictors of trajectory placement), gender did not significantly predict trajectory placement across all three samples, yet school belonging appears to predict trajectory placement only among the Latinx subsamples and not the broad, general student sample. Additionally, the study explored the predictive ability of trajectories in identifying youth with high levels of victimization, which is often identified as a predictor and outcome of internalizing difficulties (Reijntjes et al., 2010). Results indicate that youth belonging to internalizing trajectories characterized by an increasing trend as well as those who reported consistently high levels of internalizing problems over time tended to report significantly higher levels of both overt and relational victimization later in life. The following sections identify the major findings of the present study by research question and provide possible explanations for these.

Growth Trajectories

Research question 2. Growth Trajectories in Broad Student Sample: Using GMM and the four-step process of model selection described by Ram and Grimm (2009), the present study explored the existence of trajectories of internalizing difficulties in a broad student sample of at- risk youth and two Latinx subsamples. Consistent with previous studies (e.g. Rodriguez et al.,

2005, Stoolmiller et al., 2005, Hill et al., 2014), four trajectories were observed to describe the general trends of internalizing difficulties among the larger student subsample (i.e. Stable Mild,

Increasing Elevated, Increasing Mild, and Decreasing). Similar to results from other studies utilizing GMM to examine internalizing problems trajectories among school-aged youth (e.g.

Hill et al., 2014), the majority of students were found to belong to a class characterized by Stable

Mild levels of internalizing symptoms over time. This class encompassed 68% of the student

sample. The remaining 32% of the sample were identified as belonging to three different trajectories. Unlike results from other studies, one fourth of the sample was identified as exhibiting an increase trends in internalizing difficulties. Other studies have identified classes with similar trajectories but with significantly smaller portions of their samples belonging to them. Thus, the results from this study do not align with findings from other using similar approaches. It is important to note, however, that previous studies have used GMM with larger and more general student samples, while the sample studied in the present project consists of youth identified as being at significant risk for academic difficulties. Previous work has linked early academic difficulties and internalizing difficulties indicating that academic underachievement, particularly in the early school years, predicts both internalizing and externalizing problems later in life (van Lier, Vitaro, Barker, Brendgen, Tremblay, & Boivin,

2012). Numerous studies have identified similar relationships across student populations predicting statistically significant associations between these variables during early childhood

(Burt & Roisman, 2010) as well as showing long-term associations between these during adolescence (Carter, Garber, Ciesla, & Cole, 2006). Others have indicated the existence of a bidirectional relationships between poor academic performance and elevated internalizing difficulties (Vaillancourt, Brittain, McDourgall, & Duku, 2013) further associating these variables. Thus, results from the present study provide evidence to further support the identification of academically at-risk youth as also being at-risk for the development of internalizing difficulties.

Research questions 3 and 4. Growth Trajectories in Latinx and ELL Subsamples: A smaller number of internalizing problem trajectories were observed in the Latinx and Latinx ELL subsamples and these tended to display different trends than those identified with the larger

student group. Three trajectories emerged within the Latinx sample. Although a trajectory characterized by stable mild self-reported internalizing symptomatology emerged, it encompassed only one-third of the sample. In contrast, a trajectory demonstrating relatively mild baseline levels of internalizing problems with a tendency to decrease further encompassed more than half of the Latinx subsample. A similar trend was observed for the two trajectories that emerged within the Latinx ELL sample. Namely, the results of analysis on this subsample yielded two trajectories with distinct baseline values but similar trends of relatively stable but albeit slowly decreasing self-reported internalizing symptomatology.

The emergence of these trends appears to provide support for studies that have associated decreases in acculturative stress or the stress experienced by individuals as they adopt and adjust to a mainstream culture while maintaining their home culture (Romero, Martinez, & Carvajal,

2007) with increased psychological well-being particularly symptoms of depression (Torres,

2010) and evidence against the immigrant paradox, which indicates that increased time in the

United States is typically associated with increased psychological distress particularly for Latinx individuals (Vega, Sribney, Aguilar-Gaxiola, & Kolody, 2004). For example, Torres (2010) explored the impact of acculturation, acculturative stress, and coping in distinguishing levels of self-reported depressive symptoms. Results of his study found that self-reported increased pressure to be competent in the English language, which is commonly used to describe an individual’s level of acculturation, significantly predicted membership to groups characterized by higher levels of depressive symptomatology. Namely, individuals in a group with high level of depressive symptoms were more likely to report an increase English competency pressures than individuals belonging to a group with low levels of depressive symptoms. Thus, the author concludes that the demands of adjusting to a mainstream culture and the pressure of having to

acquire proficiency in a new language and develop effective communication skills increase the likelihood of experiencing mental health difficulties (Torres, 2010).

It is important to note that, in the present study, ELL status was assessed at “Time 1” and that the variables of interest for model creation and selection (i.e. self-reported internalizing problems) were assessed years later namely Time 6, Time 7, Time 8, and Time 9. Although no formal assessment of this occurred within the study, it seems likely that both Latinx subsamples experienced increased exposure to mainstream American values and increased proficiency in the

English language through their engagement at school and continued education. Piecing this information alongside reports associating length of stay in the United States as well as language proficiency and their associations with acculturative stress and psychological distress, it may be extrapolated that the decreasing trends of internalizing problems identified within the Latinx subsamples may at least in part be explained by increases in English competency and increased exposure to mainstream values and culture. Furthermore, Texas education law mandates ELLs be placed in bilingual education programs from kindergarten through the elementary years (Texas

Education Code, n.d.). After the elementary years, placement requirements for ELL youth are varied with school districts having the option of implementing English as a Second Language programs in lieu of bilingual education. That is, youth who continue to be classified as LEP or

ELL after the elementary school years are typically mainstreamed into general education classrooms with pull-out or content specific language supports embedded into their educational experience. While this may not be the academic experience of all the Latinx ELL youth in the current sample, the transition from a placement specifically designed to meet their educational needs with specialized instruction and with peers with similar language proficiency may help explain the general tendency for trajectories within the Latinx ELL sample to decrease over time.

That is, the general decrease of internalizing symptomatology within this subsample may be may be a reflection of the adjustment experience that these youths may be encountering, as they become more familiar with the general school system and the mainstream American culture.

School Belonging

Research question 5. School Belonging Predicting Trajectory Placement: The present study also explored the predictive ability of school belonging in determining trajectory placement. Considering the established association of school belonging as a protective factor for youth psychological well-being (Allen et al., 2016), it was hypothesized that self-reported levels of school belonging would help distinguish youth belonging to trajectories characterized by increasing or elevated levels of internalizing problems and those who belonged to trajectories displaying mild or low levels of internalizing difficulties. Results of the present analysis partially support this hypothesis. Although school belonging was not identified as being a significant predictor of class placement within the general student sample, it did help distinguish class membership within the two models for the Latinx subsamples (i.e. Latinx and Latinx ELLs). In both models, significantly higher levels of self-reported school belonging were reported by youth in trajectories characterized by trends of decreasing or mild internalizing problems when compared with youth belonging to trajectories characterized by high levels of internalizing problems. It is important to note that these findings were observed despite average levels of self- reported school belonging at Time 4 for the broad student sample (M = 69.66, SD = 12.16), the

Latinx subsample, (M = 69.50, SD = 10.76) and the ELL subsample (M = 69.68, SD = 11.59) not being statistically different.

These findings provide further evidence regarding the association between school belonging and internalizing difficulties particularly within the Latinx and Latinx ELL sample. As

indicated earlier, literature exploring this construct among these youth groups is limited but studies assessing contextual factors contributing to the psychological well-being of Latinx youth indicate that school belonging may be a particularly salient construct for this student population.

Schools have often been described as one of the primary and most valuable “cultural gates” (p.

56) (Blanco-Vega et al., 2008) for Latinx youth. Schools serve as a place where youth not only learn academic content but also build relationships, become proficient in the English language, and are exposed to mainstream cultural values and customs. Thus, a possible mechanism to explain the effects of school belonging on trajectory placement may be related to increases in this construct being associated with a reduction in acculturative stress, which has been identified as being significantly associated with internalizing difficulties among Latinx youth. That is, it could be possible that a sense of connection, support, and belonging to the school setting may be particularly important to both Latinx and Latinx ELL youth who may be acculturating to mainstream American culture unlike their non-ELL and non-Latinx peers.

Similarly, cultural differences between the general student sample and the Latinx samples may also help explain the differences observed regarding the predictive ability of school belonging. Namely, that a general sense of belonging may be most salient for collectivist cultures, which includes the Latinx community. Latinx cultures have a tendency to display interdependency due to their value for collectivism (Triandis, MCcusker, & Hui, 1990), which places an emphasis on the general wellness of the larger community and a tendency to make personal sacrifices for other members of the group. This in turn may translate to classroom behavior characterized by an emphasis on the development of personal connections and a desire for belonging to the larger school community. In fact, research comparing school belonging across racial groups has identified differences in their perceptions of this. Goodenow and Grady

(1993), for example, assessed the relationship between student’s perception of school belonging and various other outcomes including expectancies for success and academic effort with a sample of Latinx, Black, and White middle and high school students. They report that while school belonging was significantly associated with academic outcomes, this relationship was strongest for Latinx youth compared to Black and White adolescents. They add that Latinx youth appeared to particularly be influenced by their perception of school belonging and advocate for further research in the area. The results of the present study provide additional support for the importance of school belonging for the psychological and social well-being of Latinx youth.

Unlike school belonging, gender was not identified a significant predictor of class membership, which is inconsistent with findings from various other studies using GMM trajectories of internalizing problems among youth (e.g. Rodriguez et al., 2005) as well as numerous studies describing the gender differences in internalizing difficulties (Hankin &

Abramson, 2001). A possible explanation for these findings may be associated with the primary unifying characteristic the study’s student sample. As indicated earlier, youth for the larger study were identified as being at-risk for academic difficulties. Research has often demonstrated a link between poor academic performance and internalizing difficulties although the direction of this relationship remains largely underexplored. More recent work, however, has sought to explore the direction of these effects. Deighton, Humphrey, Belsky, Boehnke, Vostanis, & Patalay

(2018), for example, explored longitudinal pathways between psychological difficulties (i.e. internalizing and externalizing problems) and academic performance. Findings of their study indicate that early externalizing problems predicted later academic difficulties in both early childhood and adolescence. This relationship was reversed when exploring the association between academic achievement and internalizing problems. That is, children and adolescents

who initially displayed low levels of academic achievement were more likely to later exhibit signs and symptoms of internalizing difficulties. This phenomenon is often referred to as the academic-incompetence model (Moilanen, Shaw, & Maxwell, 2010) wherein academic underperformance is described as leading to feelings of frustration, worthlessness, and low esteem all of which ultimately contribute to internalizing difficulties (Maughan, Rowe, Loeber,

& Stouthamer-Loeber, 2003). Some of these studies (e.g. Deighton et al., 2018) reported no observed gender differences in the impact of academic underachievement and internalizing difficulties. The findings of the present study provide further evidence to indicate that general academic difficulties may be a risk-factor for the development of internalizing problems in academically at-risk youth regardless of gender.

Victimization

Research question 6. Victimization as a Distal Outcome. As indicated earlier, Hill and colleagues (2014) study explored the predictive role of victimization on internalizing trajectories.

Namely, findings from this study indicated that lower levels of self-reported victimization were associated with trajectories characterized by mild levels of depressive symptoms. These findings provide some evidence that victimization may be an antecedent to internalizing problems. Unlike the work of Hill and colleagues (2014), this study explored victimization as a distal outcome of internalizing problems trajectories. Namely, we sought to explore if self-reported levels of internalizing difficulties could be predictive of future experiences of victimization. This study provided further evidence in support for the existing body of literature indicating the role of internalizing difficulties in experiences of victimization. Across subsamples, youth belonging to trajectories characterized by elevated or increasing self-reported internalizing difficulties were more likely to endorse experiencing overt and relational victimization. These differences were

observed across all three samples (i.e. general, Latinx, and Latinx ELL). That is, levels of self- reported victimization both overt and relational were significantly more elevated among youth belonging to trajectories characterized by elevated or increasing levels of self-reported internalizing problems. Findings of the study align with the extensive body of literature exploring the relationship between these two factors. That is, the results provide further evidence for the bi-directional relationship between victimization and internalizing problems. The findings of meta-analytic work (Reijntjes et al., 2010) exploring the relationship between these two factors has highlighted this dynamic between them. Their description of a cycle between these variables describes the tendency for youth who are victimized to be more likely to develop internalizing problems and for youth with internalizing problems to also be more likely to be victimized. This association appears to ultimately lead to high levels of victimization to be maintained among these youths.

Implications for School-Based Mental Health Supports

Results from the current study provide support for the use of school belonging as an indicator of youth social-emotional well-being particularly of minority youth. Throughout subsamples, school belonging was observed to successfully predict trajectory placement with high levels of school belonging making youth more likely to belong to trajectories characterized by mild levels of internalizing problems over time. These findings provide support to emphasize efforts to increase a sense of school belonging across youth groups but particularly among marginalized communities including Latinx and ELLs as well as the need for culturally responsive social-emotional learning programs and interventions targeting the needs of these student subgroup.

Despite the fact that the body of literature regarding school belonging is growing, a number of studies have identified factors associated with predicting school belonging including but not limited to school environment (Slaten et al., 2015) and opportunities to play and socialize

(Chan, 2008). Regarding school environment, studies have consistently indicated that increases in levels sense of school safety including student’s perceptions of teachers’ reactions to instances of bullying (Cunningham, 2017) have been associated with increases in school belonging. Not surprisingly, students who perceive their school as being a more welcoming, safe, and friendly environment are more likely to feel more connected to it. Similar results were found regarding teacher supports. Strong positive relations were observed between students who reported having positive relationships with their teachers and their self-reported sense of school belonging (e.g.

Anderman, 2003). Considering these findings alongside those of the present study, it is imperative to identify methods to improve student-teacher relationships not only in an effort to increase academic motivation and student’s sense of school belonging but to also improve their social-emotional well-being including potentially reducing internalizing symptoms across time.

One possible way to do so, as emphasized in the literature, is increasing teacher competence and sense of self-efficacy in classroom management and conflict resolution particularly management of instances of bullying (Cunningham, 2007). Given their specialized training in school-wide practices to promote learning as outlined by the National Association of

School Psychologists’ (NASP) Practice Model (NASP, 2010), school psychologists appear to be indicated individuals to help advocate for and provide teacher training to aide teachers in providing appropriate responses to instances bullying in the school setting. Felix, Green, and

Sharkey (2010) provide a thorough overview of strategies used in the prevention and intervention of bullying/victimization. Aside from this, other approaches can be fostered within

the school setting to promote student-teacher relationships and in turn foster students’ perception of school belonging. For example, Stevens, Hamman, and Olivarez (2007) report that an emphasis on content mastery goal orientation (e.g. development of individual student goals and focus on achieving this) as opposed to other forms of academic pressure fostered a sense of school belonging among youth Latinx youth.

Similar findings have been reported for peer relationships (e.g. Blomfield & Barber,

2010) and parent support (Kuperminc, Darnell, Alvarez-Jimenez, 2008). where higher levels of both of these variables were commonly associated with an increased sense of school belonging.

These findings may be particularly salient for Latinx and ELL Latinx youth, who as indicated earlier, often report lower levels of school belonging than their non Latinx and non-ELL counterparts. Fostering parent participation may be particularly important for Latinx youth, as parental involvement has been associated with numerous possible academic and social-emotional outcomes including educational performance (Barnard, 2004; Hamptom, Fantuzzo, Cohen, &

Sekino, 2004). Studies have demonstrated that parental involvement is varied by race and that parents whose culture and lifestyle is most similar to the school culture were most likely to be active participants in their children’s school (Lee & Bowen, 2006). Parents from less privileged backgrounds including Latinx parents are most likely to report both psychological barriers to school involvement as well as general lack of confidence in understanding the education system

(Reay, 1999). Thus, parents whose home culture is no congruent with mainstream school culture are less likely to be involved in their children’s school life, which may ultimately lead to their own children feeling less connected to their school experience. At times, this lack of parental involvement may be interpreted by school staff and personnel as a lack of interested in education, which studies have shown is not the case as parental education expectations and

aspirations have been found to be similar across racial groups (Lee & Bowen, 2006). These finding call for a need to openly extend services to underserved parents and to provide culturally sensitive intervention services to empower parents to be active participants within the general education system.

Furthermore, findings of the present study provide evidence for the possibility of using screenings of school belonging to help identify youth at risk for developing internalizing difficulties over time. Screeners of indicators of positive youth-development such as school belonging may be viewed less negatively and may be less stigmatized than screeners of internalizing difficulties by youth. Identifying a youth’s level of self-reported of school belonging may provide school-based mental health professionals including school psychologists with information needed to identify the type of support a youth may need. Screening approaches that incorporate this type of measure may help identify youth in need of preventative or early intervention services in an effort to reduce their risk of developing internalizing difficulties.

Finally, the ability of trajectories to predict levels of distal self-reported experiences of victimization provides insight regarding intervention work for youth experiencing internalizing difficulties. Namely, the inverse of the implications described by Hill et al. (2017) hold true as well. That is, youth in treatment or identified as at risk for internalizing problems may benefit from social skills and self-advocacy training to help them better manage current or future experiences of victimization or peer relationships. This preventative approach can help youth reduce experiences of victimization and help offset the cycle of internalizing problems and victimization described earlier.

Limitations & Future Directions

Despite the strengths and findings of the present study, various limitations warrant discussion. First, all reports in the study aside from demographic variables were obtained through self-reports. Although students were made aware of approaches to ensure confidentiality and privacy of information reported, social desirability may have impacted student responses to several of the constructs of interest for the current study particularly those assessing internalizing difficulties and victimization. Thus, future research should seek to incorporate various informants (e.g. parents, teachers) into longitudinal analysis assessing trajectories of internalizing difficulties among Latinx and Latinx ELL youth. Doing so may help provide a more accurate representation of the social-emotional functioning of these youths and help reduce the limitations commonly associated with a reliance on self-reports. The limited exploration of covariates previously demonstrated to significantly predict trajectory membership is another limitation of the present study. Although gender was included as covariate in the present study given its consistent identification as a significant predictor of trajectory placement, various other factors known to contribute to the onset and/or maintenance of internalizing difficulties were not measured (e.g. socioeconomic status, coping style). Thus, future studies should seek to incorporate a wider range of variables commonly associated with internalizing symptomatology.

Similarly, variables known to be associated with school belonging were not included in the current analysis. One that may be particularly salient for work within the Latinx and ELL community is that of school racial/ethnic composition. Numerous studies have identified the impact of this factor on school belonging (e.g. Benner & Graham, 2007; Georgiades, Boyle, &

Fife, 2013). In their short-term longitudinal study of students in the Los Angeles area, Benner and Graham (2007), for example, found that students who experienced greater levels of ethnic

incongruence within the school setting (i.e. indicated their peers were less racially and culturally similar to them) were more likely to reported lower levels of school belonging. In fact, the authors reported that decreases in racial congruence as students transitioned from middle school to high school and experienced shifts in school demographics also increased worry related to academic success. Other studies have demonstrated that racial composition and school diversity have impact student’s perception of school safety and experiences of victimization (Juvonen,

Nishina, & Graham, 2006). Considering the effects of racial congruence on the variables of interest within the present study, it is important that future work exploring school belonging, internalizing difficulties, and/or peer victimization consider school racial congruence.

Generalizability of the findings of the present student is rather limited considering the nature of the sample of interest for the larger student from which data is drawn. As indicated earlier, eligibility for the original study was based on being identified as at-risk for academic difficulties through a state approved, school administered measure of literacy, which is in itself, according to recent work, a risk factor for the development of internalizing problems. Similarly, the student sample was drawn from a limited geographic region namely Central-West Texas.

Related to the sample, results from the analysis specific to the ELL sample should be interpreted with caution given the small sample size. Although GMM has been utilized with samples of similar size and there are no guidelines regarding sample size (Ram & Grimm, 2009), the size of the ELL subsample is significantly smaller than the general student sample and the Latinx subsample. Given its smaller size, it is possible that the ELL subsample may have had more limited variance.

This is the first study known to the author that utilized GMM to explore the existence of internalizing problem trajectories among Latinx and Latinx ELL youth. Future studies should

seek to replicate these findings with larger samples of Latinx and Latinx ELL youth in an effort to provide more generalizable results as well as increase statistical power to capture findings that may have gone unnoticed in the current study. Developing a better understanding of the social- emotional well-being of these student populations is imperative considering the various risk factors often associated with them as well as the numerous negative outcomes that are often paired with these. Further developing our ability to comprehend the social-emotional profiles of these youth can help inform various areas of service and provide further evidence for the unique needs of these student subgroups. Doing so may help inform school-based prevention and intervention work for all students and particularly Latinx youth.

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APPENDIX A

Table 1 Descriptive Statistics for General Student Sample SDQ Emotional SDQ Emotional SDQ Emotional SDQ Emotional Problems Time 6 Problems Time 7 Problems Time 8 Problems Time 9 Std. Statistic Std. Std. Std. Statistic Error Error Statistic Error Statistic Error Mean 3.14 2.66 2.30 2.42 Variance 4.46 3.86 3.68 3.84 Std. Deviation 2.11 1.97 1.92 1.96 Minimum 0.00 0.00 0.00 0.00 Maximum 10.00 10.00 9.00 9.00 Range 10 10 9.00 9.00 Skewness .58 .11 .82 .11 .86 .11 .87 .11 Kurtosis -.10 .21 .47 .21 .22 .22 .35 .22

Table 2 Descriptive Statistics for General Student Sample II School Belonging Overt Victimization Relational Victimization Time 4 Time 9 Time 9 Statistic Std. Error Statistic Std. Error Statistic Std. Error Mean 69.63 6.19 7.50 Variance 139.45 5.73 8.66 Std. Deviation 11.81 2.39 2.94 Minimum 18.00 4.00 5.00 Maximum 90.00 19.00 23.00 Range 72 15.00 18.00 Skewness -1.02 .10 1.40 .11 1.70 .11 Kurtosis 1.51 .19 2.26 .22 3.23 .22

Table 3 Descriptive Statistics for Latinx Student Subsample SDQ Emotional SDQ Emotional SDQ Emotional SDQ Emotional Problems Time 6 Problems Time 7 Problems Time 8 Problems Time 9 Std. Statistic Std. Std. Std. Statistic Error Error Statistic Error Statistic Error Mean 2.94 2.49 2.15 2.24 Variance 3.96 3.25 3.06 3.14 Std. Deviation 1.99 1.80 1.80 1.75 Minimum 0.00 0.00 0.00 0.00 Maximum 9.00 8.00 8.00 8.00 Range 9 8 8.00 8.00 Skewness .57 .17 66 .18 .81 .18 .71 .18 Kurtosis -.01 .34 .23 .35 .15 .35 -.07 .35

Table 4 Descriptive Statistics for Latinx Student Subsample II School Belonging Overt Victimization Relational Victimization Time 4 Time 9 Time 9 Statistic Std. Error Statistic Std. Error Statistic Std. Error Mean 69.60 5.98 7.10 Variance 126.50 4.75 6.22 Std. Deviation 11.25 2.18 2.49 Minimum 18.00 4.00 5.00 Maximum 90.00 14.00 18.00 Range 72 10.00 13.00 Skewness -.85 .15 1.36 .18 1.64 .18 Kurtosis 1.32 .30 1.78 .36 3.01 .36

Table 5 Descriptive Statistics for Latinx ELL Student Subsample SDQ Emotional SDQ Emotional SDQ Emotional SDQ Emotional Problems Time 6 Problems Time 7 Problems Time 8 Problems Time 9 Statistic Std. Std. Std. Statistic Std. Error Error Statistic Error Statistic Error Mean 2.98 2.43 2.34 2.20 Variance 4.36 2.58 3.29 2.82 Std. Deviation 2.09 1.61 1.61 1.81 Minimum 0.00 0.00 0.00 0.00 Maximum 9.00 6.00 7.00 7.00 Range 9 6 7.00 7.00 Skewness .69 .26 .31 .27 .52 .27 .75 .27 Kurtosis -.04 .51 -.83 .53 -.54 .53 -.00 .53

Table 6 Descriptive Statistics for Latinx ELL Student Subsample II School Belonging Overt Victimization Relational Victimization Time 4 Time 9 Time 9 Statistic Std. Error Statistic Std. Error Statistic Std. Error Mean 69.50 5.72 6.64 Variance 115.86 4.28 4.26 Std. Deviation 10.76 2.07 2.06 Minimum 36.00 4.00 5.00 Maximum 88.00 14.00 14.00 Range 52 10.00 9.00 Skewness -.82 .24 1.61 .27 1.65 .27 Kurtosis .65 .47 2.80 .54 2.38 .53

Table 7 Tests for Normality Kolmogorov-Smirnov Shapiro-Wilk Statistic df p Statistic df p SDQ Time 6 .149 435 .000 .946 435 .000 SDQ Time 7 .150 435 .000 .933 435 .000 SDQ Time 8 .176 435 .000 .913 435 .000 SDQ Time 9 .184 435 .000 .910 435 .000 PSSM Time 4 .092 435 .000 .953 435 .000 PEQ Time 9 Overt .183 435 .000 .832 435 .000 PEQ Time 9 .218 435 .000 .798 435 .000 Relational

Table 8 Fit Indices for Growth Mixture Model with General Student Sample Number of Classes BIC Adj. BIC BLRT LMR Entropy 1 8035.91 7997.82 - - - 2 7955.66 7908.04 -3979.92*** -3979.92*** .79 3 7948.02 7890.87 -3939.29*** --3939.29** .78 4 7937.35 7870.68 -3916.96*** -3916.96*** .78 5 7948.72 7872.53 -3902.12 -3902.12 .80 Note. BIC = Bayesian Information Criterion; ABIC = Adjusted BIC; BLRT = Bootstrap Likelihood Ratio Test; LMR = Lo-Mendell-Rubin Likelihood Ratio Test. *p<.05 **p<.01 ***p<.001

Table 9 Fit Indices for Growth Mixture Model with Latinx Sample Number of Classes BIC Adj. BIC BLRT LMR Entropy 1 2968.02 2930.00 - - - 2 2956.36 2908.83 -1451.87*** -1451.87** .73 3 2959.03 2902.00 -1438.00*** -1438.00 .74 4 2966.57 2900.03 -1431.31. -1431.31* .80 Note. BIC = Bayesian Information Criterion; ABIC = Adjusted BIC; BLRT = Bootstrap Likelihood Ratio Test; LMR = Lo-Mendell-Rubin Likelihood Ratio Test. *p<.05 **p<.01 ***p<.001

Table 10 Fit Indices for Growth Mixture Model for Latinx ELL Sample Number of Classes BIC Adj. BIC BLRT LMR Entropy 1 1250.88 1213.01 - - - 2 1248.86 1201.52 -598.38* -598.38** .82 3 1255.60 1198.78 -590.60 -590.60 .79 Note. BIC = Bayesian Information Criterion; ABIC = Adjusted BIC; BLRT = Bootstrap Likelihood Ratio Test; LMR = Lo-Mendell-Rubin Likelihood Ratio Test. *p<.05 **p<.01 ***p<.001

Table 11 Class Counts and Proportions for Selected Model General Student Sample Latent Class Count Proportion

1 (Increasing-Mild) 93 .16

2 (Increasing-Elevated) 37 .07 3 (Stable Mild) 384 .68 4 (Decreasing) 52 .09

Table 12 Class Counts and Proportions for Selected Model with Latinx Sample Latent Class Count Proportion

1 (Increasing) 29 .14 2 (Stable Mild) 70 .33 3 (Decreasing Mild) 113 .53

Table 13 Class Counts and Proportions for Selected Model for Latinx ELL Sample Latent Class Count Proportion

1 (Stable Mild) 70 .77 2 (Stable Elevated) 21 .23

Table 14 Effects of Gender Covariate for Final Growth Mixture Model General Sample Trajectories Odds Ratio SE Est. – 1/ SE p-value

Class 1 vs. Class 2 0.42 0.26 -2.25 0.02*

Class 1 vs. Class 3 2.57 0.80 1.96 0.05 Class 1 vs. Class 4 1.75 0.89 0.84 0.40 Class 2 vs. Class 3 6.15 3.20 1.61 0.11 Class 2 vs. Class 4 4.20 2.79 1.15 0.25 Class 3 vs. Class 4 0.68 0.30 -1.07 0.28 *p<.05 **p<.01 ***p<.001

Table 15 Effects of School Belonging Covariate for Final Growth Mixture Model General Sample Trajectories Odds Ratio SE Est. – 1/ SE p-value

Class 1 vs. Class 2 1.01 0.02 0.58 0.56 Class 1 vs. Class 3 1.02 0.01 1.35 0.18 Class 1 vs. Class 4 1.01 0.02 0.69 0.49 Class 2 vs. Class 3 1.01 0.02 0.41 0.68 Class 2 vs. Class 4 1.00 0.02 0.11 0.91 Class 3 vs. Class 4 1.00 0.02 -0.26 0.79

Table 16 Effects of Gender Covariate for Final Growth Mixture Model for Latinx Sample Trajectories Odds Ratio SE Est. – 1/ SE p-value

Class 1 vs. Class 2 1.69 0.95 0.73 0.49 Class 1 vs. Class 3 3.59 1.89 1.34 0.18 Class 2 vs. Class 3 2.09 0.87 1.25 0.21

Table 17 Effects of School Belonging Covariate for Final Growth Mixture Model for Latinx Sample Trajectories Odds Ratio SE Est. – 1/ SE p-value

Class 1 vs. Class 2 1.03 0.02 1.47 0.14 Class 1 vs. Class 3 1.05 0.02 2.27 0.02* Class 2 vs. Class 3 1.02 0.02 0.901 0.37

*p<.05 **p<.01 ***p<.001

Table 18 Effects of Gender Covariate for Final Growth Mixture Model for Latinx ELL Sample

Trajectories Odds Ratio SE (Est. – 1)/SE p-value

Class 1 vs. Class 2 0.51 0.33 -1.50 0.13

Table 19 Effects of School Belonging Covariate for Final Growth Mixture Model for Latinx ELL Sample

Trajectories Odds Ratio SE (Est – 1)/ SE p-value

Class 1 vs. Class 2 0.93 0.03 -2.27 0.02* *p<.05 **p<.01 ***p<.001

Table 20 Four-Factor Solution and Item Factor Loading for PEQ Factors Items Overt Relational Overt Relational Aggression Aggression Victimization Victimization 1 .59 2 .54 3 .81 4 .90 5 .58 6 .64 7 .70 8 .62 9 .63 10 .63 11 .55 12 .70 13 .53 14 .54 15 .68 16 .62 17 .70 18 .62

Table 21 Means and Standard Deviations of Distal Outcome for Each Class in General Sample Class 1 Class 2 Class 3 Class 4 Increasing-Mild Increasing-Elevated Stable-Mild Decreasing Victimization Type (n = 93) (n = 37) (n = 384) (n = 52) Overt 6.53(0.30) 8.15(0.62) 5.75(0.13) 6.70(0.75)

Relational 8.13(0.42) 10.64(0.95) 6.79(0.15) 8.20(0.75)

Table 22 Means and Standard Deviations of Distal Outcome for Each Class in Latinx Sample Class 1 Class 2 Class 3 Victimization Type Increasing Stable Mild Decreasing Mild (n = 93) (n = 37) (n = 384) Overt 7.19(0.59) 5.98(0.28) 5.58(0.26)

Relational 9.07(0.77) 7.38(0.34) 6.25(0.24)

Table 23 Means and Standard Deviations of Distal Outcome for Each Class in Latinx ELL Sample Class 1 Class 2 Victimization Type Stable Mild Stable Elevated (n = 93) (n = 37) Overt 5.07(0.21) 7.57(0.62)

Relational 5.94(0.18) 8.64(0.70)

Table 24 Equality Tests of Mean Reported Overt Victimization Across Classes in General Sample Trajectories Chi-Square p-value

Class 1 vs. Class 2 4.76 .03

Class 1 vs. Class 3 5.11 .02 Class 1 vs. Class 4 0.05 .83 Class 2 vs. Class 3 14.21 <.001* Class 2 vs. Class 4 2.04 .15 Class 3 vs. Class 4 1.45 .23 *p<.001

Table 25 Equality Tests of Mean Reported Relational Victimization Across Classes in General Sample Trajectories Chi-Square p-value

Class 1 vs. Class 2 5.04 .03

Class 1 vs. Class 3 8.40 <.001* Class 1 vs. Class 4 0.01 .94 Class 2 vs. Class 3 16.11 <.001* Class 2 vs. Class 4 3.68 .06 Class 3 vs. Class 4 3.23 .07 *p<.001

Table 26 Equality Tests of Mean Reported Overt Victimization Across Classes in Latinx Sample Trajectories Chi-Square p-value

Class 1 vs. Class 2 3.14 .08

Class 1 vs. Class 3 6.08 .01 Class 2 vs. Class 3 0.89 .35

Table 27 Equality Tests of Mean Reported Relational Victimization Across Classes in Latinx Sample Trajectories Chi-Square p-value

Class 1 vs. Class 2 3.68 .06

Class 1 vs. Class 3 11.71 <.01* Class 2 vs. Class 3 5.66 .02 *p<.01, **p<.001

Table 28 Equality Tests of Mean Reported Overt Victimization Across Classes in Latinx ELL Sample Trajectories Chi-Square p-value

Class 1 vs. Class 2 13.23 <.001*

*p<.001

Table 29 Equality Tests of Mean Reported Relational Victimization Across Classes in Latinx ELL Sample Trajectories Chi-Square p-value

Class 1 vs. Class 2 12.89 <.001*

*p<.001

APPENDIX B 7

2 SDQ Emotional Problems Total Score Total Problems SDQ Emotional

0 1 2 3 4 Time Increasing Mild Increasing Elevated Stable Mild Decreasing

Figure 3. Mean value plot of four class model for general student sample.

2 SDQ Emotional Problems Total Score Score Total Problems SDQ Emotional 1

0 1 2 3 4 Time

Increasing Stable Mild Decreasing

Figure 4. Mean value plot of three class model for Latinx student sample.

Stable Mild Stable Elevated 3

2 SDQ Emotional Problems Total Score Total Problems SDQ Emotional

0 1 2 3 4 Time Figure 5. Mean value plot of two class model for Latinx ELL student sample.

Figure 6. CFA results for 18-items of the PEQ.