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Effects of mental health agency partnerships in school climate

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Effects of mental health agency partnerships in school climate
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Novelli, Ana ( author )
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Denver, CO
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University of Colorado Denver
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Mental health ( fast )
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For decades, public school systems have partnered with outside entities such as non-profits, community mental health centers, and school based health centers to provide therapeutic services to children within the school. During the same time, the understanding that school climate has wide ranging impacts on students has blossomed. There exists little evidence that providing outside therapeutic services can impact the school climate. To help administrators and school mental health professionals decide if contracting partner agencies that provide individual therapy for their school would be beneficial, this study was developed to evaluate the connection between these outside services and school climate. An analysis of covariance was used to analyze surrogate marker data from 63 elementary schools, of which 22 had outside provider therapists during the 2013-2014 school year. The results concluded that there were no statistically significant findings for any marker of school climate when controlling for confounding demographic data. Recommendations for further areas of study as well as practical applications follow the results.
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Thesis (Ph. D.)--University of Colorado Denver ; 2018.
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by Ana Novelli.

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Copyright Ana Novelli. Permission granted to University of Colorado Denver to digitize and display this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
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i EFFECTS OF MENTAL HEALTH AGENCY PARTNERSHIPS ON SCHOOL CLIMATE by ANA NOVELLI B.A., University of Colorado Boulder, 2011 A thesis submitted to the Faculty of the Graduate School of the University of Colorado in partial fulfilment of the requirements for the degree of Doctor of Psychology School Psychology Program 2018

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ii This thesis for the Doctor of Psychology degree by Ana Victoria Corinna Novelli has been approved for the School Psychology Program by Dr. Franci Cre peau Hobson, Chair Dr. Bryn Harris Date: 5/12/20 18 Novelli, Ana (Psy. D., School Psychology)

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iii Effects of Mental Health Agency Partnerships on School Climate. Thesis directed by Associate Professor Bryn Harris ABSTRACT For decades, public school systems have partnered with outside entities such as non profits, community mental health centers, and school based health centers to provide therapeutic services to children within the school. During the same time, the understanding that school climate has wide ranging impacts on students has blossomed. Th ere exists little evidence that providing outside therapeutic services can impact the school climate. To help administrators and school mental health professionals decide if contracting partner agencies that provide individual therapy for their school woul d be beneficial this study was developed to evaluate the connection between these outside services and school climate. An analysis of covariance was used to analyze surrogate marker data from 63 elementary schools, of which 22 had outside provider therapists during the 2013 2014 school year. The results concluded that there were no statistically significant findings for any marker of school climate when controll ing for confounding demographic data. Recommen dations for further areas of study as well as practical applications follow the results. The form and content of this abstract are approved. I recommend its publication. Approved: Bryn Harris

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iv TABLE OF CONTENTS CHAPTER I. INTRODUCTION ................................ ................................ ................................ ... 1 History of Mental Health Treatment and Government Involvement .......... 1 Providers in Schools ................................ ................................ .................... 4 Data Based Decision Making and Capstone Goals ................................ ...... 5 II. LITERATURE REVIEW ................................ ................................ ...................... 7 Mental Health Outcomes in Schools Worldwide ................................ ......... 7 Community Mental Health and School Climate ................................ .......... 8 School Climate Definitions and Surrogate Markers ................................ .... 9 Conclusion ................................ ................................ ................................ 11 III. METHODS ................................ ................................ ................................ ............ 12 Participants ................................ ................................ ................................ 13 Intervention ................................ ................................ ................................ 14 Procedure ................................ ................................ ................................ ... 14 IV. RESULTS ................................ ................................ ................................ ............. 12 V. DISCUSSION ................................ ................................ ................................ ....... 15 Discussion ................................ ................................ ................................ .. 21 Limitations ................................ ................................ ................................ 21 Implications for Future Study ................................ ................................ .... 22 REFERENCES ................................ ................................ ................................ ............................. 24 APPENDIX ................................ ................................ ................................ ................................ 31

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1 CHAPTER I INTRODUCTION History of Mental Health Treatment and Government Involvement Mental health struggles affect children in schools all over our country; as school psychologists, we must work from evidence based practice to help children who struggle with mental health difficulties Over the course of the last twenty years, there has been an increase in needs, but according to multiple investigations the country is still failing to provide comprehensive support (Knitzer, 1982; U.S. Public Health service, 2000; Tolan, et al 2001 ; New Freedom Commission on Mental Health, 2003 ; Tolan & Dodge, 2005 ) Of th e children who receive mental health treatment, 11.8 % receive support in the school setting ( U.S. Substance Abuse an d Mental Health Administration, 2009). To provide these services, the government has worked and reworked many possible solutions. The passa ge of the Commun ity Mental Health Act (1963), shift ed services from institutionalization to community focused mental health. This act funded centers that provided mental health preventative services as well as diagnosis and treatment (Shef field, 2013). Ac cording to the a ct, each center was required to provide a minimum of five services: consultation and education on mental health, inpatient services, outpatient services, emergency response, and partial hospitalization (Sheffield, 2013) This act was intend ed to decrease the rate of institutionalization and required cities and counties to provide more services for people with less significant mental health needs than the more traditional patient. The act laid the foundation for mental health services to move from large and disconnected institutions to community mental health centers (CMHs) that had a deeper connection to the needs of their population s At the same time as the Community Mental Health Act was driving funding and legislation to provide

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2 services to a broader section of the public, important legislative changes were occurring in the public school sector. In 1975, the first iteration of the Individuals with Disabilities Education Act (IDEA), Public Law 94 142 was passed. It preserved the rights of students with disabilities and enacted into federal law the provision of services to students with physical and mental disabilities. This requirement led to an increase in the need for mental health services provided to students within the context of spec ial education (Thomas & Texidor, 1987). Additionally, IDEA s pecifically outlined jobs that school p sychologists were able to perform, many of which took time away from providing individual counseling to general education students. As schools were realizing the limitations of IDEA and the challenges of providing services to students, community mental health centers were growing in size and number. These decades old a cts helped set the stage for the patchwork of mental health services we see system. More recently, mental health services have been recognized as b eing less than optimal. In 2003, former President George W. Bush established the New Freedom Com mission on Mental Health. This C ommission then published a report, that addressed the fragmented mental health services provided to children. The goal of this Commission was to create a more cohesive mental health service provision system and reduce the stigma surrounding mental health treatment by developing 19 recommendatio ns for improving mental health services in the United States (New Freedom Commission on Mental Health, 2003). Additionally, former President Bush passed the No Child Left Behind Act (NCLB) This act made student achievement a priority but did not address s ocial and emotional learning and competencies (Daly et al 2006). Although the New Freedom Commission had recommended further mental health supports the No Child Left Behind Act failed to provide a framework for these services. In December 2015, former

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3 p resident Obama signed the Every Student Succeeds Act (ESSA) that replace d the NCLB ESSA ushered in more funding for mental health services in the schools, including access to comprehensive mental health services, an area that had been underfunded in the NCLB (National Association of School Psychologists, 2015). The value of good mental health has become increasingly recognized as crucial for optimal functioning of s tudents within the school system ( Friedman, 1993; Schorr, 1997 ; Thoran & Dodge, 2005) As a result, states have begun to establish their own recommendations to ensure mental health services are provided within schools including Colorado. According to the Colorado Special Education Advisory Committee (2013), schools in Colorado should: Provid e counseling and skills that teach parents to improve function and success for their children in their school settings. Provide a continuum of mental health services within schools for students with challenging emotional and behavioral needs. Partner wit h community agencies to maximize the use of community resources designed to improve mental health for all children, with a particular focus on children with special health care needs. To reach these goals with limited resources, many schools have partnere d with community based mental health providers. These outside providers are typically skilled health care workers and include counselors, therapists and social workers who prov ide mental health treatment and preventative services within the school to meet the needs of students. By partnering with school based health clinics, community mental health providers and nonprofit organizations are better able to meet both the needs of the students and the legal requirements of service provision. According to Merik angas et al. (2010), one in five children will experience a serious mental disorder in his or her lifetime. Of these children, only about 40% receive the mental health support they need. Of the children who do receive support, two thirds access that suppor t

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4 in school (National Association of School Psychologists, 2016). Schools are uniquely positioned to offer mental health services as children spend a majority of their day at school and school based support does not require time or money from parents. The National Association of School Psychologists suggests that a community and school partnership is essential to provide a complete continuum of services (National Association of School Psychologists, 2016). Reporting suggests schools are partnering with a mu ltitude of outside agencies including local mental health agencies (both community mental health centers and nonprofit agencies), local hospitals, mental health professionals, school based health clinics and managed care organizations (n.a., 2004). Despite these anecdotes and the legal requirements that are in place, it is difficult to ascertain exactly how mental health services are being provided across the country. Providers in Schools According to Dryfoos (1988 ), school based health clinics were among the first organizations to offer outside provider psychological services in the schools. They began by providing health services such as immunizations, but quickly started implementing mental health programs for teenagers and adolescents who were pregnant or parenting, or had alcohol and drug problems. These services expanded from approximately 150 school based clinics nationally, in 1987 to over 500 by 1993. As of the 2013 2014 census of school based health clinics performed by the School Based Health All iance, these services had expanded to 2,315 clinics in 49 states ( National Census of School Based Health Centers, n.d.) As the school based health clinics grew, so did their mental health support services. Around 75% of these clinics have mental health se rvices housed within them (Keeton, Soleimanpour & Brindis, 2012). Thus school based health clinics continue to grow both in number of clinics and in breadth of mental health services

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5 provided. These clinics were among the first, and continue to be some o f the most widespread areas where children can access mental health services. Although there has been an increase in these school based services, the number of mental health professionals employed full time by schools is limited. According to a 2013 survey the median number of students served by the employees of the district analyzed in the study in a school was 311.2 students but with a range of 130.1 500.6 students ( Green et al., 2013). School service providers are obviously stretched thin. To mee t the growing need of the student population and stay within their tight budgets, schools have begun to contract the work A lower cost option is a to hire mental health providers through the collaboration between schools and community mental health organi zations part time In this model, a team of behavioral health professionals partner with the mental health team (if one exists) at the school to create and implement a comprehensive mental health support program (Richardson, Morrisette & Zucker, 2012). Ma ny schools that partner with community mental health providers are under resourced and utilize these providers to meet the mental health needs of the pupils ( Markle, Splett, Maras & Weston, 2014). In addition to these partnerships some non profit organiz ations have created programming to provide mental health services in schools. Non profit and school partnerships seem to be a new cooperative model of mental health support and are an area of where further investigation is warranted. In 1992, a Colorado p ublic school system began a partnership with two outside organizations herein referred to as Provider A and Provider B, to provide quality therapeutic interventions in the school setting. The goal of these partnerships was to remove barriers to care (MDCC 2016; JFS, 2016). These partnerships have not been included in the

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6 scant research examining therapy provided by outside services and very little is known regarding their effect on school climate. Data Based Decision Making and Goals of Capstone The Nat ional Association of School Psychologists (NASP) practice model requires that school psychologists utilize data based decision making, provide a continuum of mental health and behavioral supports, and provide preventative and responsive services while prac ticing in a legal and ethical manner ( NASP n.d.). Within the schools there exist multiple mental health fields, such as school social workers and counselors, psychologists are uniquely positioned within the administration system to help make systemic decisions. To work within these domains and to ensure decision making is data driven, we must understand the ramifications of the use of outside service providers within the school setting, and we must determine if these outside service providers are having affecting the school climate Without such data, we cannot be certain that the re are unintended positive or negative effects in the schools that contract outside providers. T hus we cannot argue for the use or termination of these services. This C apstone project aims to collect and evaluate data that can sh ed light on the effects on school climate by comparing schools with an outside provider therapist and schools without such services. With this foundational analysis, we can begin to understand how these outside pro viders affect school climate. Specifically this evaluation will determine if s chools with an outside provider have any significantly different discipline, attendance and academic success rates than schools that do not have an outside provider. By controlling for factors such as socioeconomic stat us, race, ethnicity and school size we can better isolate the effect of the outside provider s on school climate, and determine if there are any measurable differences in these performance characteristics between

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7 schools with outside mental health provider s and schools with mental health providers native to the school system. CHAPTER II LITERATURE REVIEW Mental Health Outcomes in Schools Worldwide The effectiveness of therapeutic interventions in schools has been researched extensively and there is eviden ce that they result in generally positive outcomes for students (Armbruster & Lichtman, 1990; Hussey &Guo, 2003; Owens et al., 2008) A meta analysis published in 2010 (Baskin et al.) found that 132 counseling interventions showed positive mental health ou tcomes. Inclusion criteria for this analysis was the following: students ages 5 18, based in the schools, and include statistical analysis of outcomes. The analysis found that adolescents, when compared to the school aged children, were more likely to see a decrease in disruptive mental health symptoms from counseling. Furthermore, children working with licensed professionals had better outcomes than those working with graduate students; they also noted outcomes were more positive in single gender groups ra ther than mixed gender groups. Another meta analysis of 42 studies compared counseling outcomes for children with depression, who received counseling in the school to children receiving services in a clinical setting (Erford et al., 2011). The study found that overall therapy in both settings provided positive results. Moreover they found that there was no difference between therapy conducted in school settings and therapy conducted in outpatient settings (Erford et al., 2011). Cooper et al. (2013) assesse d the efficacy of Partners for Change Outcome Management System (PCOMS) in Irish school when implemented by outside counselors within the school setting. The PCOMS system is a clinical process that identifies clients who are not responding to

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8 typical clini cal approaches and addresses them positively while seeking new ways to engage and help the client (Duncan, 2012). This study indicated that outside counselors using the PCOMS intervention could improve the outcomes with students with depression. Although t his study indicates improvements for students who are seen by outside counselors in the school setting, it did not address change in the school climate Additionally, the authors identified a further limitation to this study is the variability of the thera py being practiced. The outside counselors employed a variety of techniques in addition to the systemic feedback (Cooper et al. 2013). Community Mental Health and School Climate Research specific to community mental health and school partnership outcomes in regards to school climate is limited A recent investigation into absenteeism related to service provision in schools in Philadelphia found that children who participated in services this had reduced school suspension rates but did not reduce l evels of absenteeism (Kang Yi, Mandell, & Hadley, 2013). Another study performed i n the Southeast United States in an individual school compared attendance, discipline rates, and achievement scores for a pilot program school and matched control school. The outcomes indicated that students who received counseling from a community mental health partner did not show differences when compared with the control school in any area other than a small increase in reading scores in the intervention school ( Powers, We gman, Blackman, & Swick, 2014). A pilot program which attempted to enhance the provision of school based mental health services in schools through collaboration in Southern California had limited data but suggested that both the school system and the commu nity mental health provider were happy with the progress of students over the course of one year (Capp, 2015).

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9 Finally, Provider A produced effectiveness data to recruit potential new schools. pre and post test data on the Social Skills Improve ment System (SSIS) provide individual level data which is then analyzed. The results of this analysis are then utilized for outreach to potential schools who will want to implement the program and large scale donors. According to the providers analysis, SS IS evaluations, during the 2013 2014 school year students who participated in the program saw a 65% improvement in social skills, a 63% reduction in serious problem behaviors and a 50% improvement in academic competence (MDCC 2016). Although this data is non representative (children participate if they are receiving therapy, parents give consent, and the same informer can be used for both pre and post test ) and limited in scope, it does indicate that these programs are helping students reduce problem behav iors, feel better at school and increase their academic performance. These three very limited studies, and basic data from Provider A do not demonstrate a robust understanding ng and performance. These data show an exciting indication that services provided by outside entities can yield excellent individual outcomes, but without further evaluation, broad application of these conclusions is problematic further it is unknown if t hese partnerships have unintended negative effects on school climate School Climate Definitions and Surrogate Markers The National School Climate Council or NSCC (2016), defines school climate as the quality and character of school life. School climate is based on patterns of students', parents' and school personnel's experience of school life and reflects norms, goals, values, interpersonal relationships, teaching and learning practices, and organizat identifies 12 dimensions within these areas which include: rules and norms, sense of physical

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10 security, sense of social emotional security, support for learning, social and civic learning, respect for diversity, social support for adults and students, school connectedness/engagement, physical surroundings, leadership and professional relationships. Excellent performance in these areas of school climate lead to a healthy school system. In recent years, school climate has become a topic of significant scrutiny in the school psychology community; positive school climate leads to lower dropout rates, increased student self esteem, lower drug use rates in high school age children, and is predictive of better psychological wel l being (Dynarski et al., 2008; Hoge, Smit, & Hanson, 1990; LaRusso et al., 2008; Ruus et al., 2007; Shochet et al., 2006; Virtanen et al., 2009 in Thapa, Cohen, Guffey, & Higgins D'alessandro 2013). Thus, promoting a positive school climate is beneficial in almost all areas of functioning for students. According to a recent review of relevant school climate literature implementing violence prevention programs and positive behavior supports ( Olweus, Limber, & Mihalic, 1999; Meraviglia et al., 2003; Caldarella, et al. 2011), utilizing classroom management techniques and alternative discipline strategies (Mitchell & Bradshaw, 2013), having a positive organizational climate and readiness to implement support programs (Malloy et al., 2015) all improve s chool climate. Therapeutic services at an individual level may be able to add to the positive behavior supports on a school wide level There is no consensus regarding how to quantitatively measure school climate on a state or nationwide level In additio n is extremely difficult to ascertain school climate from just one data point in a sch ool; as such surrogate markers were developed from the NSCC paradigm (2016) First, the NSCC states that a major indicators of school climate is Safety Safety and school are strongly related (Benbenishty et. al., 2016, Espelage et al., 2013). An aspect of school climate as the rules and norms and the sense of physica l and social emotional safety. Therefore,

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11 it c an be concluded that school with more violence have less posi tive school climates. To measure school violence as a marker of school climate this study will utilize school reported in school suspensions, out of school suspensions, and total discipline incidents. An additional domain as described by the NSCC is the T eaching and Learning domain. T he NSCC advises that major indicators are support for learning and social and civic learning. These areas can be measured in this study the Transitional Colorado Assessment Program and high p erformance on assessments has been linked to a more positive school climate ( Benbenishty et. al., 2016; Berkowitz et. al., 2015; Lacey & Cornell, 2016; McCoy, Roy & Sirkman, 2013; McEvoy & Welker, 2000). Another domain within the school climate is the Institutional Environment. This is indicated as school connectedness, engagement and physical surroundings. Absenteeism in schools can be directly related to feelings of school connectedness by the student body (Centers for Disease Control and Prevent ion, 2010; Rosenfeld Richman, Bowen, 1998). A bsenteeism is inverse ly related to school climate or, a more positive climate results in less truancy and higher attendance rates (Brookmeyer, Fanti, & Henrich, 2006; Hendron & Kearney, 2016). The final two do mains of school climate, Interpersonal Relationships and Staff Only, are includes social supports for adults and children, respect for diversity, leadership and professional engagement (NSCC, 2016) However, the school district analyzed in this study did no t collect data on teacher satisfaction (L. Steffans, personal communication, 2017) thus study will not include these two domains within in this analysis C onclusion To date there has been little research that connects individual counseling services provided by external school partners to school climate. One study conducted in the 1997 1998

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12 school year indicated no significant difference in general school climate in m atched elementary schools with and without outside therapy services (Bruns et al., 2004) indicating that these outside therapists were not making either a positive or negative impact on school climate. More recent research has focused on school wide positi ve behavior supports but f ails to discuss the effect of individual services can have an impact on school climate (Calderella et al., 2011; Bosworth & Judkins, 2014). Providing our students mental health services is a priority. From the Community Mental Hea lth Act of 1963 to Every Student Succeeds Act of 2015, practitioners have been charged with incorporating a continuum of mental health services for each and every child. School psychologists and administrators are in a unique position to provide these serv ices to both children with and without disabilities; and while administrators choose how to spend mental health dollars, school psychologists can influence those decisions. It is important that mental health programs within the school are research based an d have demonstrated effectiveness. The research is clear that school based interventions can have positive outcomes for students, but the research regarding performance of outside providers and school partnerships is lacking. By assessing how these partner ships with mental health service providers are affecting school climate, we can begin to spend these dollars in a more productive way, therefore providing the best quality and care for our students. CHAPTER II I METHODS To analyze the effect that outsi de providers have on overall school climate first it was necessary to identify the school with and without providers and understand how each program provided mental health support. To identify these schools each provider was first informed of the goals of the study, implications and confidentiality requirements of the Capstone. They were

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13 then asked to furnish a list of schools that utilized the program in the 2013 2014 school year. This year was identified as the most recent year with all data available pub lically. The programs also provided information in the form of brochures on how they functioned. Program A schools will typically have one to two part time intern therapists who work with 7 15 children individually and will run one or two groups. The pro gram aims to provide early intervention for students of low socioeconomic status, those exposed to trauma, and children who may not otherwise receive care. Provider A has maintained quality, individual level outcome data for students but has not yet provid ed data that supports a school wide change in school climate or an increase in positive outcomes for schools. In addition to this partnership, the school district has cultivated partnerships with other service providers who provide similar services utilizi ng licensed practitioners (Provider B) in place of students on their internship year, (MDCC, 2016; JFS, 2016). Participants Schools were selected that employed an intern or licensed therapist during the academic year 2013 2014 Of the 178 schools in the p ublic school system in this analysis 22 schools contracted with 2 outside providers who performed individual therapy within the school setting. The outside providers furnished a list of schools that had participated in their programs during the school yea r (MDCC, 2016; L. Rincon, personal communication, 2017) Demographic and outcome data was collected through published, de identified data is available in an online center. This data was collected, aggregated and published by the state department of education. (Colorado Department of Education, n.d.).

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14 Intervention ntern and social work training programs in the Denver metro area ; t hese programs focus on family and coupl es counseling, psychotherapy, somatic and contemplative therapy styles. Over the course of the 2013 2014 school year interns were trained in play therapy as well as topics such as running groups and grief and loss counseling. Intern therapists are encour aged to use play therapy techniques with their clients at the sites. Additionally, Provider B contract licensed clinical social workers and professional counselors to provide individual therapy for their schools. Therapists work with a small caseload of ch ildren within that sc hool. C hildren who work with both providers are referred for multiple reasons including behavior and academic struggles. The direct intervention was provided through weekly sessions with each student typically lasting 30 45 minutes (MD CC, 2016; JFS 2016 ). Procedure Data for each measure of school climate was collected. Surrogate measures of school climate were utilized for this study as follows: attendance of students, academic performance (math and r eading scores), and school violence ( total in school suspensions, tota l out of school suspensions, total discipline incidents) and attendance (attendance ; or the number of excused absences per total days attended, and truancy rates or the number of unexcused absences per th e total days attended, ) These data were collected through the state Department of Education School View Data Center from June 2017 August 2017 and the School Dashboard, both websites which are accessible to the public (CDE, n.d.). After this data was min ed, an Analysis of Covariance (ANCOVA) was run The null hypothesis for this question states that outside providers will have no effect on school climate, while the alternative hypothesis states that

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15 outside providers will have an effect on school climate. To ascertain if the partnership between the urban public school system and outside therapy providers im pact the overall school climate multiple factors were analyzed. The ANCOVA statisti cal test is used when comparing independent variables, in th is case with or without outside services while controlling for covariates of school size, ethnic diversity of the population, percent age of students receiving Free and Reduced lunch percent age of students wh o are English language learners, and percent age of students in Special Education these covariates are not part of the main research question but could influence dependent variables and therefore are controlled within the current study ( Rothwell, n.d.) It allows for the statistical significance to be ascertained without requiring similar demographic groups in the independent and dependent variables by controlling for these factors that may influence the outcome of a statistical test that does not control fo r these variables. CHAPTER IV RESULTS To ascertain if contracting an outside provider to perform individual therapy affects school climate within elementary schools in the target public school system and control for confounding variables an ANCOVA was p erformed. A total of 9 out of several hundred data points were identified as outliers (1987) three quartile range definition of outlier removal. The data violated the assumption of normality in 4 of 15 variables. This violation is acceptable due to the robustness of the ANCOVA statistical test. All other assumptions were met after the removal of outliers in the data.

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16 A comparison of the demographic char acteristics of the schools with (Table 1.1) and without (Table 1.2) outsi de providers show that they possessed similar characteristics Additionally, schools had similar on surrogate marker data as demonstrated in Table 1.4 and 1.5 found below. Table 1.1 Demographic Characteristics of Outside Pro vider Schools Outsider Provider School Demographic (n=22) Mean Median Standard Deviation Population (POP) 513.54 304 252.43 Other Ethnicity % (ETH) 7.65 4.00 6.21 Black % (ETH) 11.77 1.40 1 3.93 Hispanic % (ETH) 53.83 9.50 32.78 White % (ETH) 26.72 8.55 27.40 English Language Learner % (ELL) 38.33 42.35 22.69 Free and Reduced Lunch % (FRL) 72.41 86.85 29.83 Special Education % (SPED) 11.00 10.80 2.78

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17 Table 1.2 Demographic Table No Outside Provider Schools No Outsider Provider School Demographic (n=41) Mean Median Standard Deviation Population (POP) 511.41 499.00 109.38 Other Ethnicity % (ETH) 6.72 5.30 4.07 Black % (ETH) 12.35 5.50 14.62 Hispanic % (ETH) 57.53 66.20 30.89 White % (ETH) 23.39 5.40 28.50 English Language Learner % (ELL) 40.85 43.90 23.05 Free and Reduced Lunch % (FRL) 72.38 90.40 32.67 Special Education % (SPED) 10.00 9.70 3.30

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18 Table 1.3 Surrogate Marker Aggregated Data Outside Provider Schools With Outsider Provider School Surrogate Marker (n=22) Mean Median Standard Deviation Percent of Reading Proficiency Scores on State Standardized Test (READ) 54.96 53.32 20.63 Percent of Math Proficiency Scores on State Standardized Teste (MATH) 57.01 52.34 19.29 Total Discipline Incidents (ISS, OSS, and Other TOT) 38.81 20.00 39.06 Total In School Suspension (ISS) 11.81 7.00 15.99 Total Out of School Suspension (OSS) 21.81 9.00 27.84 Attendance Rate ( Total Student Days/ Total Possible ATTEND) 93.76 93.82 1.39 Truancy Rate ( Total Unexcused/Total Possible TRUANCY) 3.37 3.17 2.07

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19 Table 1.4 Surrogate Marker Aggregated Data No Outside Provider Schools No Outsider Provider School Surrogate Marker (n=41) Mean Median Standard Deviation Percent of Reading Proficiency Scores on State Standardized Test (READ) 57.72 50.36 21.26 Percent of Math Proficiency Scores on State Standardized Teste (MATH) 57.24 54.13 19.08 Total Discipline Incidents (ISS, OSS, and Other Incidents TOT) 21.26 18.00 16.09 Total In School Suspension (ISS) 7.51 4.00 9.48 Total Out of School Suspension (OSS) 14.68 11.00 10.90 Attendance Rate ( Total Student Days/ Total Possible ATTEND) 94.04 94.08 1.28 Truancy Rate ( Total Unexcused/Total Possible TRUANCY) 3.37 3.37 1.64 Seven one way ANCOVAs were conducted to determine if differences existed in reading performance, math performance, attendance, truancy rates, in school, out of school suspension and total discipline incidents, between schools with and without outside ther apy providers while controlling for the confounding variables of school population (POP), ethnic make up of the school (ETH), percentage of students who receive Free and Reduced lunch (FRL), percentage of English Language Learners (ELL), and percentage of students who receive special education

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20 services (SPED). There was no significant difference in reading performance [F(1,61)=.142, p=.05] between schools, or math performance [F(1,61)=.260, p=.05] between schools. There was no significant difference in tota l discipline incidents, [F(1,61)=1.290, p=.05], out of school suspensions [F(1,61)=.158, p=.05], or in school suspensions [F(1,61=1.545, p=.05]. Finally, there was no significant difference in attendance [F(1,61)=1.047, p=.05] or truancy rates [F(1,61)=.08 1, p=.05] between schools with and without outside providers. See Table 1.6 below Table 1. 5 ANCOVA comparing school with outside and without outside providers (GROUP) to dependent variable (READ, MAT H, TOTAL, OSS, ISS, ATTEND, TRUA NCY) when controlling for confounding variables (POP, ETH, FRL, ELL, AND SPED) Independent Variable Dependent Variable dF F p value Partial Eta Squared Group READ 1, 61 .142 .708 .003 Group MATH 1, 61 .260 .612 .005 Group TOTAL 1, 61 1.290 .261 .025 Group OSS 1, 61 .158 .693 .003 Group ISS 1, 61 1.545 .220 .031 Group ATTEND 1, 61 1.047 .311 .020 Group TRUANCY 1, 61 .081 .777 .002 Note : p=.05

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21 CHAPTER V DISCUSSION AND IMPLICATIONS Discussion As schools in the United States have become more aware of the impact of the mental health of our students and children many steps have been taken to include support systems for accessing services. One manner of providing these services has the institution a partner ship between schools and outside mental health providers This study focused on the school outside provider partnership and its relation to school climate. It was found that school s with an outside provider therapist and without outside provider did not ha ve any significant differences between surrogate markers of school climate. Thus, in this specific system of elementary schools for the 2013 2014 school year, it appears that the contracted therapists made no difference, either positive or negative, in the overall climate of the school. These results correlate with r esults from Bruns et al., 2004, who found no significant difference in matched elementary school with and without outside providers. Limitations This study had multiple limitations. First, the narrow scope of the sample size could have led to a type II error in the results. Thus, due to the small sample of schools and limited time frame no significant difference was found, but in reality, there may exist a significant difference If multiple districts that utilize these types of services and multiple years were included the results may be more representative of the actual effect that these providers have and a statistical difference might become apparent Secondly, the Provider A and Provider B utilize different models of intervention. One uses licensed practitioners while the other trains interns through their program ( MDCC, 2016; JFS, 2016 ) To have more certainty of the effects it would be

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22 necessary to implement the same progr am throughout all schools that utilize outside therapists. Finally, incomplete measures were used as markers of school climate. On the whole, the data gathered and analyzed here is a step in the right direction to postulate as to the effectiveness of the s chool provider partnership. It remains only preliminary in developing more comprehensive understanding on the effect of outside providers on school climate. Implications and Future Study As budgets decrease and the need for mental health services increase s, school s must find cost effective ways to provide the best services and outcomes for their students. To do this administrators and other decision makers must know th e effectiveness of the ir programs in the setting of budgetary constraints The results of this study indicate that contracting outside service providers did not produce a significant change in school climate in the limited school system studied over the course of one year. It i s important to remember that each school is different and may have additional support services, or a lack of additional services with the school. As well as these differences, t here exists a body of evidence that a positive school climate leads to better o utcomes for students (Malloy et al., 2015; Mitchell & Bradshaw, 2013; Olweus, Limber, & Mihalic, 1999; Meraviglia et al., 2003; Caldarella, et al. 2011). The research is less congruent in regard to mental health services provided within the school setting with multiple studies have mixed results (Baskin et al., 2010; Cooper et al., 2013; Powers, Wegman, Blackman, & Swick, 2014; Capp, 2015; MDCC 2016). Fundamentally, the decision rests on a cost benefit analysis for students receiving outside services in comparison with the benefit to the school as a whole. It is the hope of this author that this study can aid in such analysis. In the interest of data driven practice, providers must do their due diligence to implement programs that will contribute to the success of their student body. Continued study is warranted

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23 to assess the effectiveness of school provider partnerships to provide the body of evidence necessary for these decision makers. To better understand the interaction between the two variables a l arge scale, a multiple district and longitudinal study which implemented a specific therapy intervention could provide the most convincing results. Presently, no such study has been undertaken. Providers are constantly striving to make the best choices to support their students on every level. As practitioners, we must utilize methods to support these students that are evi dence based and cost effective. Contracting outside services for individual therapy may provide some benefit to individual children, but fail to change the climate of the school and therefore must be carefully considered.

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24 REFERENCES Armbruster, P., & Lichtman, J. (1999). Are school based mental health services effective? evidence from 36 inner city schools. Community Mental Health Journal, 35(6), 493 504. doi:10.1023/A:1018755100381 Baskin, T. W., Slaten, C. D., Crosby, N. R., Pufahl, T., Schneller, C. L., & Ladell, M. (2010). Efficacy of Counseling and Psychotherapy in Schools: A Meta Analytic Review of Treatment Outcome Studies 1 7. The Counseling Psychologist, 38(7), 878 903. doi:10.1177/0011000010369497 Berkowitz, R., Glickman, H., Benbenishty, R., Ben Artzi, E., Raz, T., Lipshtadt, N., & Astor, R. A. (2015 ). Compensating, mediating, and moderating effects of school climate on academic achievement gaps in Israel. Teachers College Record 117 1 34. Berkowitz, R., Moore, H., Astor, R. A., & Benbenishty, R. (2017;2016;). A research synthesis of the associations between socioeconomic background, inequality, school climate, and academic achievement. Review of Educational Research, 87 (2), 425 469. doi:10.3102/0034654316669821 Benbenishty, R., Astor, R. A., Roziner, I., & Wrabel, S. L. (2016). Tes ting the causal links between school climate, school violence, and school academic performance: A cross lagged panel autoregressive model. Educational Researcher, 45 (3), 197 206. doi:10.3102/0013189X16644603 Bruns, E. J., Walrath, C., Glass Siegel, M., & Weist, M. D. (2004). School Based Mental Health Services in Baltimore: Association With School Climate and Special Education Referrals. Behavior Modification, 28(4), 491 512. doi:10.1177/0145445503259524 Bosworth, K., & Judkins, M. (2014). Tapping i nto the power of school climate to prevent bullying: One application of schoolwide positive behavior interventions and supports. Theory into Practice, 53(4), 300 307. doi:10.1080/00405841.2014.947224 Brookmeyer K. A.Fanti K. A.Henrich C. C. (2006). Scho ols, parents, and youth violence: A multilevel, ecological analysis. Journal of Clinical Child and Adolescent Psychology 35, 504 514. https://doi org.aurarialibrary.idm.oclc.org/10.1207/s15374424jccp3504_2

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25 Capp, G. (2015). Our Community, Our Schools: A Case Study of Program Design for School Base d Mental Health Services Children & Schools Children Schools, 37 (4), 241 248. doi:10.1093/cs/cdv030 Caldarella, P., Shatzer, R. H., Gray, K. M., Young, K. R., & Young, E. L. (2011). The effects of school wide positive behavior support on middle school climate and student outcomes. RMLE Online, 35(4), 1 14. doi:10.1080/19404476.2011.11462087 Cheema J. R., Kitsantas A. (2014). Influence of disciplinary classroo m climate on high school student self efficacy and mathematics achievement: A look at gender and racial ethnic differences. International Journal of Science and Mathematics Education, 12, 1261 1279. doi:10.1007/s10763 013 9454 4 Children First Program. (2016). Retrieved October 09, 2017, from http://www.mariadroste.org/what we do/programs/children first program/ Centers for Disease Control and Prevention. School c onnectedness: Strategies for increasing protective factors among youth. (2010). Reclaiming Children and Youth, 19(3), 20. Colorado Special Education Advisory Committee (CSEAC). (2013, July). Position Statement regarding Mental Health Issues and Students with Disabilities. Retrieved November 27, 2016, from https://www.cde.state.co.us/cdesped/mentalhealthpositionstatement Color ado Department of Education. (n.d.). SchoolView Data Center. Retrieved from: https://edx.cde.state.co.us/SchoolView/DataCenter/reports.jspx?_afrWindowMode=0&_a frLoop =900412759993712&_adf.ctrl state=pd9hjpf8z_4 Colorado D epartment of Education, (n.d.). School Dashboard. Retrieved from: http://www2.cde.state.co.us/schoolview/dish/schooldashboard.asp Cooper, M., Stewart, D., Sparks, J., & Bunting, L. (2013). School based coun seling using systematic feedback: A cohort study evaluating outcomes and predictors of change. Psychotherapy Research : Journal of the Society for Psychotherapy Research, 23 (4), 474 488. doi:10.1080/10503307.2012.735777

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26 Daly, B. P., Burke, R., Hare, I., Mills, C., Owens, C., Moore, E., & Weist, M. D. (2006). Enhancing no child left Behind School mental health connections. Journal of School Health, 76(9), 446 451. doi:10.1111/j.1746 1561.2006.00142.x Dryfoos, J. (1988). School Based Health Clinics: Three Years of Experience. Family Planning Perspectives, 20 (4), 193 200. doi:10.2307/2135800 Duncan, B. L. (2012). The partners for change outcome management system (PCOMS): The heart and soul of change project. Canadian Psychology/Psychologie Canadienne, 53 (2), 93 104. doi:10.1037/a0027762 Dynarski, M., Clarke, L., Cobb, B., Finn, J., Rumberger, R., & Smink, J. (2008). Dropout prevention: A practice guide. (NCEE 2008 4025). Erford, B. T., Erford, B. M., Lattanzi, G., Weller, J., Schein, H., Wolf, E., Hughes, E., Darrow, J., Savin Murphy, J., Peacock, E. (2011). Counseling Outcomes From 1990 to 2008 for School Age Youth With Depression: A Meta Analysis. Journal of Counseling & Development, 89(4) 439 457. doi:10.1002/j.1556 6676.2011.tb02841.x Espelage, D. L., Hong, J. S., Rao, M. A., & Low, S. (2013). Associations between peer victimization and academic performance. Theory Into Practice 52 (4), 233 240. Flaherty, L. T., Weist M. D., & Warner, B. S. (1996, August). School based mental health services in the united states: History, current models and needs. Community Mental Health Journal, 32(4), 341 352. doi:10.1007/bf0224945 Friedman R.M. (1993). Preparation of students t o work with children and families: Is it meeting the need? Administration and Policy in Mental Health; 20:297 310 Green, J. G., McLaughlin, K. A., Alegra, M., Costello, E. J., Gruber, M. J., Hoagwood, K., Kessler, R. C. (2013). School mental health resources and adolescent mental health service use. Journal of the American Academy of Child and Adolescent Psychiatry, 52(5), 501 510. doi:10.1016/j.jaac.2013.03.002

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27 Gottfredson, G. D., Gottfredson, D. C., Payne, A. A., & Gottfredson, N. C. (200 5). School climate predictors of school disorder: Results from a national study of delinquency prevention in schools. Journal of Research in Crime and Delinquency, 42 (4), 412 444. doi:10.1177/0022427804271931 Kang Yi, C. D., Mandell, D. S., & Hadley, T. (2013). School Based mental health program evaluation: Children's school outcomes and Acute mental health service use. Journal of School Health, 83(7), 463 472. doi:10.1111/josh.12053 Hendron, M., & Kearney, C. A. (2016). School climate and studen t absenteeism and internalizing and externalizing behavioral problems. Children & Schools, 38(2), 109 116. doi:10.1093/cs/cdw009 Hoaglin, D. C., & Iglewicz, B. (1987). Fine tuning some resistant rules for outlier labeling. Journal of the American Sta tistical Association, 82 (400), 1147 1149. Hoge, D. R., Smit, E. K., & Hanson, S. L. (1990). School experiences predicting changes in self esteem of sixth and seventh grade students. Journal of Educational Psychology, 82, 117 127. doi:10.1037//0022 0663 .82.1.11 Hussey, D. & Guo, S. (2003). Measuring behavior change in young children receiving intensive school based mental health services. Journal of Community Psychology, 31 (6), 629 639. doi:10.1002/jcop.10074 Keeton, V., Soleimanpour, S., & Brindis C. D. (2012). School Ba sed health centers in an era of health care reform: building on h istory. Current Problems in Pediatric and Adolescent Health Care, 42(6), 132 156. doi:10.1016/j.cppeds.2012.03.002 JFS: Jewish Family Services. (2017). Kids S ucce s Program Overview. Denver, CO: N.A. Kelly, C., Kitchener, B. A., & Jorm, A. F. (2010). Youth mental health first aid: A manual for adults assisting young people. Parkville, Vic.: ORYGEN Youth Health Research Centre. Knitzer J. (1982). Unclaimed chil dren: The failure of public responsibility to children and adolescents in need of mental health services. Washington, DC: Children's Defense Fund

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28 Lacey, A., & Cornell, D. G. (2016). School administrator assessments of bullying and state mandated te sting. Journal of School Violence 15 189 212. doi: 10.1080/15388220.2014.971362 LaRusso, M., Romer, D., & Selman, R. (2008). Teachers as builders of respectful school climates: Implications for adolescent drug use norms and depressive symptoms in high school. Journal of Youth & Adolescence, 37, 386 398. doi:10.1007/s10964 007 9212 Malloy, M., Acock, A., DuBois, D. L., Vuchinich, S., Silverthorn, N., Ji, P., & Flay, B. R. and quality of implementation of a social emotional and character development program. Prevention Science, 16(8), 1086 1095. doi:10.1007/s11121 014 0534 7 MDCC : Maria Droste Counseling Center. (2016). Children First: In school therapy that helps children heal, grow, and succeed [Brochure]. Denver, CO: N.A. Markle, R., Splett, J., Maras, M., & Weston, K. (2014) Effective school teams: Benefits, barriers and best practices. In Wiest, N., Lever A., Bradshaw C., & Owens J., Handbook of school mental health Research, training practice and policy (2nd ed., pp 59 73). New York, NY: Springer. McCoy, D. C., Roy, A. L., & Sirkman, G. M. (2013). Neighborho od crime and school climate as predictors of elementary school aca demic quality: A cross lagged panel analysis. American Journal of Community Psychology 52 128 140. McEvoy, A., & Welker, R. (2000). Antisocial behavior, academic failure, and school climate. Journal of Emotional and Behavioral Disorder 8 (3), 130 140. Merikangas, K. R., He, J., Burstein, M., Swanson, S. A., Avenevoli, S., Cui, L., Swendsen, J. (2010). Lifetime Prevalence of Mental Disorders in US Adolescents: Results from t he National Comorbidity Study Adolescent Supplement (NCS A). Journal of the American Academy of Child and Adolescent Psychiatry, 49(10), 980 989. http://doi.org/10.1016/j.jaac.2010.05.017 Mera viglia, M. G., Becker, H., Rosenbluth, B., Sanchez, E., & Robertson, T. (2003). The expect respect project: Creating a positive elementary school climate. Journal of Interpersonal Violence, 18 (11), 1347 1360. doi:10.1177/0886260503257457

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29 Mitchell, M. M., & Bradshaw, C. P. (2013). Examining classroom influences on student perceptions of school climate: The role of classroom management and exclusionary discipline strategies. Journal of School Psychology, 51(5), 599 610. doi:10.1016/j.jsp.2 013.05.005 NASP: The National Association of School Psychologists. (n.d.). Retrieved November 27, 2016, From http://www.nasponline.org/research and policy/current law and policy priorities/ policy priorities/the every student succeeds act/essa implementation resources/ess a mental and behavioral health services for school psychologists NASP: The National Association of School Psychologists. (n.d.). Retrieved May 12, 2017, from https://www.nasponline.org/standards and certification/n asp practice model/nasp practice model implementation guide/section i nasp practice model overview/nasp practice model 10 domains National Census of School Based Health Centers. (n.d.). Retrieved November 27, 2016, from http://www.sbh4all.org/school health care/national census of school based health centers/ NSCC: National School Climate Center. (2016). The 12 dimensions of school climate measured. Retrieved October 13, 2017, from http://www.schoolclimate.org/programs/documents/dimensions_chart_pagebars.pdf Olweus, D., Limber, S., & Mihalic, S. (1999). Blueprints for violence prevention: Bullying prevention program. Boulder, CO: Center for the Study and Prevention of Violence. Owens, J. S., Murphy, C. E., Richerson, L., Girio, E. L., & Himawan, L. K. (2008). Science to practice in underserved communities: The effectiveness of school mental health programming. Journal of Clinical Child & Adolescent Psychology, 37(2), 434 447. doi:10.1080/15374410801955912 Transforming mental health care in America. Final report. (U.S. DHHS Pub. No. SMA 03 3832). Rockville, MD: U.S. Department of Health and Human Services. Powers, J., Wegman, K., Blackman, K., & Swick, D. (2014). Increasing access to mental health services in schools through community engaged research: Results from a one year pilot project. School Social Work Journal, 39(1), 73. Retri eved November 28, 2016.

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30 Richardson, T., Morrissette, M., & Zucker, L. (2012, December). School Based Adolescent Mental Health Programs. Social Work Today, 12(4), 24. Retrieved November 27, 2016, from http://www.socialworktoday.com/archive/111312p24.shtml Richman, J. M., Rosenfeld, L. B., & Bowen, G. L. (1998). Social support for adolescents at risk of school failure. Social Work, 43(4), 309 323. doi:10.1093/sw/43.4.309 Rothwell J. (n.d.). ANCOVA in SPSS. University of Sheffeile. Retrieved October 10, 2017, from https://www.sheffield.ac.uk/polopoly_fs/ 1.531229!/file/MASH_ANCOVA_SPSS.pdf Ruus, V., Veisson, M., Leino well being, coping, academic success, and school climate. Social Behavior & Personality, 35, 919 936. doi:10.2224/sbp.2007.35.7.919 Sheffield, W. (2013). The Community Mental Health Act of 1963 Young Minds Advocacy. Retrieved November 27, 2016, from https://www.ymadvocacy.org/the community mental health act of 1963/ Shochet, I. M., Dadds, M. R., Ham, D., & Montague, R. (2006). School connectedness is an underemphasized parameter in adolescent mental health: Re sults of a community prediction study. Journal of Clinical Child & Adolescent Psychology, 35, 170 179. doi:10.1207/s15374424jccp3502_1 School Based Mental Health Services. (2004). Pediatrics, 113(6), 1839 1845. doi:10.1542/peds.113.6.1839 Schorr L.B. (1997). Common purpose: Strengthening families and neighborhoods to rebuild America. New York: Anchor Books/Doubleday. Thomas, P. A. and Texidor, M. S. (1987), The School Counselor and Holistic Health. Journal of School Health, 57: 461 464. doi:10.111 1/j.1746 1561.1987.tb03194.x Thapa, A., Cohen, J., Guffey, S., & Higgins D'alessandro, A. (2013). A Review of School Climate Research. Review of Educational Research, 83 (3), 357 385. doi:10.3102/0034654313483907

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31 Tolan, P., & Dodge, K. (2005). Children's mental health as a primary care and concern: A system for comprehensive support and service. American Psychologist, 60(6), 601 614. doi:10.1037/0003 066X.60.6.601 Tolan P., Anton B., Culbertson J., Katz S., N elson Le Gall S. Developing psychology's national agenda for children's mental health: APA's response to the surgeon general's action agenda for children's mental health Report of the APA Working Group on Children's Mental Health to the Board of Dire ctors. American Psychological Association; 2001. U.S. Public Health Service. (2000). Report of the Surgeon General's Conference on Children's Mental Health: A national action agenda. U.S. Department of Health and Human Services. U.S. Substance Ab use and Mental Health Administration, Office of Applied Statistics. (2009) Results from the 2008 National Survey on Drug Use and Health: National Findings. Accessed Oct. 14, 2017 from http://www.oas.samhsa.gov/ NSDUH/2k8NSDUH/2k8results.cfm#8.2. Virtanen, M., Kivimaki, M., Luopa, P., Vahtera, J., Elovainio, M., Jokela, J., & health, truancy and health education in Finland. European Journal of Public Health, 19, 554 560.

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32 Appendix Table I ANCOVA table for reading proficiency percentage (Read) when controlling for confounding variables Dependent Variable dF F p value Partial Eta Squared Group Read 1, 61 .142 .708 .003 Population Read 1, 61 .386 .537 .008 Other Ethnicity Read 1, 61 1.052 .310 .020 Black Read 1, 61 .979 .327 .019 Hispanic Read 1, 61 .988 .325 .019 White Read 1, 61 .943 .336 .018 Free and Reduced Lunch Read 1, 61 .463 .499 .009 English Language Learners Read 1,61 1.331 .254 .025 Special Education Read 1, 61 3.180 .081 .059 a. R Squared = .503 (Adjusted R Squared = .415) Table II ANCOVA table for math proficiency percentage when controlling for confounding variables Dependent Variable dF F p value Partial Eta Squared Group Math 1, 61 .260 .612 .005 Population Math 1, 61 .247 .621 .005 Other Ethnicity Math 1, 61 1.126 .294 .022 Black Math 1, 61 1.057 .309 .020 Hispanic Math 1, 61 1.062 .308 .020 White Math 1, 61 1.012 .319 .019 Free and Reduced Lunch Math 1, 61 .598 .443 .012 English Language Learners Math 1,61 .728 .398 .014

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33 Special Education Math 1, 61 2.720 .105 .051 a. R Squared = .465 (Adjusted R Squared = .370) Table III ANCOVA table for total discipline incidents (Total) when controlling for confounding variables. Dependent Variable dF F p value Partial Eta Squared Group Total 1, 61 1.290 .261 .025 Population Total 1, 61 .015 .902 .000 Other Ethnicity Total 1, 61 .385 .538 .008 Black Total 1, 61 .353 .555 .007 Hispanic Total 1, 61 .369 .546 .007 White Total 1, 61 .388 .536 .008 Free and Reduced Lunch Total 1, 61 1.528 .222 .030 English Language Learners Total 1,61 .353 .555 .007 Special Education Total 1, 61 .173 .679 .003 a. R Squared = .153 (Adjusted R Squared = .001) Table IV ANCOVA table for out of school suspension (OSS) when controlling for confounding variables Dependent Variable dF F p value Partial Eta Squared Group OSS 1, 61 .158 .693 .003 Population OSS 1, 61 .635 .429 .013 Other Ethnicity OSS 1, 61 2.926 .093 .056 Black OSS 1, 61 2.952 .092 .057 Hispanic OSS 1, 61 3.016 .089 .058 White OSS 1, 61 3.042 .087 .058 Free and Reduced Lunch OSS 1, 61 .935 .338 .019 English Language OSS 1,61 1.780 .188 .035

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34 Learners Special Education OSS 1, 61 .015 .902 .000 a. R Squared = .235 (Adjusted R Squared = .095) Table V ANCOVA table for in school suspension (ISS) when controlling for confounding variables Dependent Variable dF F p value Partial Eta Squared Group ISS 1, 61 1.545 .220 .031 Population ISS 1, 61 .033 .856 .001 Other Ethnicity ISS 1, 61 .864 .357 .017 Black ISS 1, 61 .891 .350 .018 Hispanic ISS 1, 61 .907 .346 .018 White ISS 1, 61 .890 .350 .018 Free and Reduced Lunch ISS 1, 61 .051 .822 .001 English Language Learners ISS 1,61 .203 .655 .004 Special Education ISS 1, 61 .090 .765 .002 a. R Squared = .171 (Adjusted R Squared = .019) Table VI ANCOVA table for attendance percentage (Attend) when controlling confounding variables Dependent Variable dF F p value Partial Eta Squared Group Attend 1, 61 1.047 .311 .020 Population Attend 1, 61 .000 .997 .000 Other Ethnicity Attend 1, 61 .776 .382 .015 Black Attend 1, 61 .713 .402 .014 Hispanic Attend 1, 61 .726 .398 .014 White Attend 1, 61 .703 .406 .014 Free and Reduced Lunch Attend 1, 61 .106 .746 .002 English Language Learners Attend 1,61 .485 .489 .009

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35 Special Education Attend 1, 61 .270 .606 .005 a. R Squared = .229 (Adjusted R Squared = .093) Table VII ANCOVA table for truancy rate (Truancy) when controlling for confounding variables Dependent Variable dF F p value Partial Eta Squared Group Truancy 1, 61 .081 .777 .002 Population Truancy 1, 61 .692 .409 .013 Other Ethnicity Truancy 1, 61 .628 .432 .012 Black Truancy 1, 61 .611 .438 .012 Hispanic Truancy 1, 61 .612 .438 .012 White Truancy 1, 61 .586 .447 .011 Free and Reduced Lunch Truancy 1, 61 .650 .424 .013 English Language Learners Truancy 1,61 .451 .505 .009 Special Education Truancy 1, 61 .791 .378 .015 a. R Squared = .200 (Adjusted R Squared = .058)