A Meta-Analysis of School Counselor-Led Interventions On

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A META-ANALYSIS OF SCHOOL COUNSELOR-LED INTERVENTIONS ON

SOCIAL-EMOTIONAL SKILLS AND COMPETENCE FOR MIDDLE AND

HIGH SCHOOL STUDENTS

Anna Katharine Owens

A Dissertation Submitted to the Faculty of

The College of Education

In Partial Fulfillment of the Requirements for the Degree of

Doctor of Philosophy

Florida Atlantic University

Boca Raton, FL

December 2018

ACKNOWLEDGEMENTS

I would like to express my sincere gratitude for the individuals that have invested in my educational foundation as a counselor educator. To my chair Dr. Elizabeth Villares, your character radiates what is means to be a mentor. Not only did you encourage me to apply for the doctoral program, but you continued to be my confidant and supporter throughout this process. I thank you for the countless hours and phone calls to make sure

I was on track. You are a true leader in the field of school counseling and I feel fortunate for the knowledge gained. To Dr. Greg Brigman for being a participating committee member, your calm disposition, and willingness to educate future counselors. Dr. Brian

Canfield, thank you for your mentorship in Oxford, NOLA, and through IAMFC. I look forward to continuing my service as a counselor educator. To Dr. Carman Gill for the delivery of simulating lessons throughout the doctoral program and your guidance and support with our Chi Sigma Iota (CSI) chapter. Of course, Dr. Paul Peulso, thank you for your unwavering support and encouragement for students and community outreach projects. It is an honor and a privilege to work with such esteemed professionals in the field of counseling. A special thank you to Darlene Epperson and Mikaela Kursell, the

Department of Counselor Education secretaries, for always working so patiently with me.

Lastly, to the members of CSI Beta Rho Chi, thank you for the humbling experience to serve as the chapter president where I learned invaluable leadership skills. It has been an honor to participate in growth and unity of our chapter and connecting with amazing colleagues and friends along the way.

iv ABSTRACT

This meta-analysis investigated the practical significance of school counselor-led social emotional learning (SEL) interventions on outcomes for students in Grades 6–12.

The sample includes 28 studies involving 3,794 middle and high school students. The treatment group was comprised of a total of 2,032 students, who received interventions led by a certified school counselor. The control/comparison groups were derived from a sample of 1,762 middle and high school students who did not receive the school counselor-led intervention. The meta-analysis included a diverse sample of students, with ethnicity reported as 589 (15.52%) African American, 52 (1.37%) Asian, 1,162

(30.63%) Hispanic, 1,267 (33.39%) Caucasian, 11 (0.28%) Native American, 21 (0.55%)

Pacific Islander, and 177 (4.66%) Multi-racial/Other. Of the studies included in the meta-analysis, the ethnicities of 412 (18.86%) students were not reported. A total of 12 studies were conducted at the middle school level, 10 at the high school level, and 6 studies reported a mixed setting of Grades 6–12. The sample included almost equal representation of 1,883 (49.63%) males and 1,847 (48.68%) females, and the genders of

69 (1.82%) students were not reported.

The overall unweighted Cohen’s d effect size (ES) of the school counselor-led interventions was .312 (95% CI [.173, .452]). The ES for overall cognitive outcomes (d

= 0.380) was slightly larger than for overall effective role functions outcomes (d =0.377) and affective outcomes (d = 0.356). The smallest ES reported for overall variables was for behavioral outcomes (d = 0.228). The largest ES for a specific student outcome

v measure was found for standardized achievement test scores (d = 0.612) (Vernez &

Zimmer, 2007). Moderator analyses were conducted and are explored in the results and discussion. The results address the current gap in school counseling outcome research by broadening future research directions for comprehensive school counseling programs

(CSCP) to incorporate SEL initiatives aimed for middle and high school students.

DEDICATION

In dedication to my family, friends, and mentors throughout my doctoral journey.

Your love and encouragement mean more than you will ever know. To my husband

Brian, thank you for being my rock during one of the most difficult times in my life.

Without question, you always provide unconditional love and support for me to peruse my dreams and passions. You may be Irish, but I am the lucky one. To my family, we will always be the Campbell Kids. To my friends and mentors along the way. Months, even years, may pass but those who leave an impression on you never leave your heart.

A META-ANALYSIS OF SCHOOL COUNSELOR-LED INTERVENTIONS ON

SOCIAL-EMOTIONAL SKILLS AND COMPETENCE FOR MIDDLE AND

HIGH SCHOOL STUDENTS

LIST OF TABLES ...... xii

LIST OF FIGURES ...... xiii

I. INTRODUCTION ...... 1

Significance of the Problem ...... 8

Purpose of the Study ...... 10

Research Questions ...... 11

Definitions...... 11

Limitations of Meta-Analysis ...... 15

Goals of Meta-Analysis ...... 16

Chapter Summary and Dissertation Overview ...... 17

II. LITERATURE REVIEW ...... 19

The Emerging Needs of Twenty-First Century Middle and High School

Students ...... 20

The CASEL framework and Social-Emotional Learning (SEL) ...... 22

Effective SEL Programs for Middle and High Schools ...... 24

Student Success Skills...... 25

Comprehensive School Counseling Programs ...... 27

The Role of the School Counselor ...... 29

viii

Paving the Way for Academic Achievement ...... 32

The Road to College and Career Readiness (CCR) ...... 33

Systematic Review of Literature: Relevant Meta-Analyses ...... 35

School-Based Universal Interventions for SEL Meta-Analysis ...... 35

Promoting Positive Youth Development Meta-Analysis ...... 38

School Counseling Meta-Analysis ...... 40

Student Success Skills Meta-Analysis ...... 43

Meta-Analysis Research Design and Protocol ...... 45

Summary ...... 46

III. METHOD ...... 47

Procedures ...... 47

Defining Research Questions, Variables, and Domain of Interest ...... 48

Research questions...... 48

Variables...... 49

Domain of Interest...... 49

Criteria for Inclusion and Exclusion of Studies for Meta-Analysis ...... 49

Selecting the Effect Sizes to Use ...... 51

Search for and Screen the Studies Using the Inclusion Criteria ...... 52

Conducting and Documenting the Search and Selection Process ...... 54

Coder training...... 54

Data Collection ...... 55

Selection of the Final Set of Studies ...... 55

Coding Procedure for Extract and Code Relevant Data ...... 56

Missing data...... 57

Determining the Effect Size on the Dependent Variables of Interest...... 57

Conduct Reliability Checks on the Coding Procedures...... 58

Grouping Studies Based on Independent or Dependent Variables...... 58

Data Analysis ...... 59

Determine the Mean and Variance of (Independent) Grouped Effect

Sizes...... 59

Fail-safe N and publication bias...... 60

Test for Homogeneity and Exploring Potential Moderator Variables...... 60

Synthesize Findings and Generate Conclusions ...... 61

Benchmarks for Interpreting Effect Sizes ...... 61

Limitations of Meta-Analysis ...... 63

Summary ...... 64

IV. RESULTS ...... 65

Descriptive Statistics ...... 65

Effect Sizes ...... 65

Overall Effects ...... 66

Overall Variable Effect Sizes ...... 66

Affective variable...... 67

Behavioral variable...... 68

Cognitive variable...... 68

Effective role function variable...... 69

Moderator Analyses ...... 70

Grade level...... 71

Intervention delivery type...... 72

Length of treatment...... 73

Treatment protocol...... 74

Summary ...... 75

V. DISCUSSION ...... 76

Impact of School Counselor-Led Interventions ...... 77

Affective variable...... 78

Behavioral variable...... 79

Cognitive variable...... 79

Effective role function variable...... 80

Effect Sizes for Moderating Variables ...... 81

Grade level...... 82

Intervention delivery type...... 83

Length of treatment...... 84

Treatment protocol...... 85

Implications for School Counseling...... 86

Limitations ...... 90

Future Directions ...... 91

Summary ...... 94

REFERENCES ...... 96

LIST OF TABLES

Table 1. Effect Sizes Related to Affective Variable Outcomes ...... 67

Table 2. Effect Sizes Related to Behavioral Variable Outcomes ...... 68

Table 3. Effect Sizes Related to Cognitive Variable Outcomes ...... 69

Table 4. Effect Sizes Related to Effective Role Functions Variable Outcomes ...... 70

Table 5. Effect Sizes Related to Grade Level as a Moderator ...... 72

Table 6. Effect Sizes Related to Intervention Delivery Type as a Moderator ...... 73

Table 7. Effect Sizes Related to Length of Treatment as a Moderator ...... 74

Table 8. Effect Sizes Related to Treatment Protocol ...... 75

xii

LIST OF FIGURES

Figure 1. Calculated ES ...... 52

Figure 2. Flow of studies included and excluded from the meta-analysis ...... 56

Figure 3. Formula for Calculation Effect Size ...... 66

xiii

I. INTRODUCTION

On September 20, 1940, the esteemed Franklin D. Roosevelt stated, “We cannot always build the future for our youth, but we can build the youth for our future” (Address at University of Pennsylvania. September 20, 1940). The development of social- emotional skills and competence throughout middle and high school is critical for student success, yet it remains at the periphery in education (Domitrovich, Syvertsen, & Calin,

2017; Van Velsor, 2009; Weissberg & Cascarino, 2013). Empirically-based studies continue to report the association between well-developed social-emotional competencies

(SEC) and positive student outcomes (Durlak et al., 2015; Durlak, Weissberg, Dymnicki,

Taylor, & Schellinger, 2011 Greenberg et al., 2003). Unfortunately, social-emotional learning (SEL) programs designed for adolescents in middle and high school receive less attention than those developed for younger students (Yeager, 2017). The extent of quality secondary-level, evidence-based research is inadequate when compared to the literature on elementary school settings (Durlak et al., 2011). Furthermore, current research trends not only indicate that the development of SEC for adolescents is important, but the research also highlights the need for creating innovative SEL curriculum to improve positive outcomes for youth (Domitrovich et al., 2017).

Therefore, a more complete description of the critical role that the school counselors play in the delivery of SEL interventions in middle and high school is needed.

The Collaborative for Academic, Social, and Emotional Learning (CASEL) seeks to incorporate evidence-based SEL as an integral part of education. In line with their

mission, CASEL (2015) provides educational guides and emphasizes SEL interventions that must become rooted in educational settings in order to support the positive promotion of outcomes, which ultimately will prevent problem behaviors in students.

Correspondingly, SEL research supports an Adlerian principle that students do not learn in solitude, but rather in collaboration with the encouragement of educators, peers, and families, within the context of schools, homes, and communities (Durlak et al., 2015;

Sperry, 2016). The important mission of SEC is to provide children and adults with a foundation for effectively applying the knowledge, attitudes, and skills necessary for managing emotions, setting and achieving positive goals, empathy to others, establishing positive relationships, and making responsible decisions (CASEL, 2015). Thus, CASEL

(2015) provides the following definition of SEL:

The process through which people acquire and effectively apply the knowledge,

attitudes, and skills necessary to understand and manage emotions, set and

achieve positive goals, feel and show empathy for others, establish and maintain

positive relationships, and make responsible decisions. CASEL has identified

five sets of cognitive, affective, and behavioral competencies: self-awareness,

self-management, social awareness, relationship skills, and responsible decision-

making. (p.5)

Accordingly, defining what embodies SEL would not be complete without the identification of the five interrelated sets of cognitive, affective, and behavioral competencies that can be taught in various ways across different settings: self-awareness, self-management, social awareness, relationship skills, and responsible decision making

(CASEL 2003, 2015; Durlak et. al, 2015). Self-awareness is present when one

recognizes emotions and begins to identify strengths, needs, and values. Self- management involves one’s impulse control, stress management (surrounding discipline), and organizational skills. Social awareness is reflected when one shows respect and empathy for others, as well as appreciates diversity. Relationship skills encourage one to pursue social engagement and relationship building, while also promote cooperation through conflict management processes. Responsible decision making allows one to identify problems while using reflection for personal, moral, and ethical responsibility

(Zins, Weissberg, Wang, & Walberg, 2004). Each skill contributes uniquely to a student’s overall level of SEC. An individual’s own SEC can ultimately facilitate or obstruct their academic achievement, engagement, interactions with others, and overall school success (CASEL, 2015; Domitrovich et al., 2017; Durlak & Weissberg, 2011).

The value of defining SEL correlates with the vision of evidence-based school counseling programs, which are designed to cultivate the fundamental needs that a student requires to achieve academic success (ASCA, 2012; CASEL, 2003; Gysbers, 2004). Furthermore,

SEL interventions are critical for adolescents, as these young students experience rapid developmental growth accompanied by increased social encounters, which can lead to risky behaviors (Bandura, 2006; CASEL, 2015; Vernon, 2009).

As a student begins their journey at the secondary level, they must learn how to navigate major biological, educational, and social role transitions concurrently (Bandura,

2006). This transitional phase in the course of life presents a host of new challenges.

Adolescence is a riveting period of developmental growth that is replete with experiences of personal and social difficulties. Peer relationships continue to be important at this stage of social development (Erikson, 1968; Vernon, 2009). As such, it is critical to

invest in young people’s SEC during adolescence (Domitrovich, et al., 2017). However, there is an alarming lack of research related to responsive service interventions designed to assist with student problems, which often involve individual or group counseling sessions within secondary school settings (Whiston, Tai, Rahardia, & Eder, 2011).

Researchers conclude that middle and high school students require direct assistance to refine college searches, close gaps in college knowledge, and increase preparation for postsecondary readiness (Conley, 2007; Farrington et al., 2012). School counselors are exceptionally trained educators who are equipped to encourage SEL exploration and implement the standards identified in making an impact on student achievement and academic performance (ASCA, 2014).

The following items are characteristic of short- and long-term behavioral outcomes that are imperative for secondary students’ success. Short-term goals include: improved social and emotional skills; healthy view of tasks, others, and self; positive relationships; less conduct issues; and increased academic success (Weissberg, Durlak,

Domitrovich, & Gullotta, 2015). Overtime, researchers have discovered that long-term behavioral outcomes achieve the following: (a) increase high school graduation rates; (b) enhance preparation of students for college-career-readiness; (c) develop strong mental health, along with positive relationships; and (d) reduce criminal behavior, while developing engaged citizens within communities (Durlak et al., 2011; Farrington et al.,

2012; Sklad, Diekstra, Ritter, Ben, & Gravesteijn, 2012). As the evidence is striking, there is currently a rising demand for the development of future SEL programs aimed specifically at the middle and high school levels. Although many effective teachers integrate SEL experiences into their classrooms, they are hesitant to take time away from

academics, which affects student performance outcomes (Van Velsor, 2009). School counselors serve as the first line of defense when identifying and addressing student social-emotional needs within the school setting (ASCA, 2016). Alas, the responsibility lies with educators to capitalize on the full potential of these efforts by designing programs that respond to needs of adolescents, while working in collaboration with all stakeholders (Domitrovich, et al., 2017, Van Velsor, 2009).

Exploring the impact of SEL interventions on student outcomes continues to be at the forefront of education (CASEL, 2015; Dimmitt, Carey & Hatch, 2007). Moreover, school counseling outcome research validates the notion that there is an obligation to practice within the confounds of an evidence-based model (Bridgeland, Webb, &

Hariharan, 2013; Elias, Zins, Graczyk, & Weissberg, 2003). Greenberg, Domitrovich,

Weissberg, and Durlak (2017) view SEL as a public health approach to education with proven benefits, which makes SEL programs an ideal foundation for seeking to improve the general population’s well-being. Weissberg and Cascarino (2013) declare that developing the partnership between academic learning and SEL should be treated as a national priority, wherein schools must urgently spring into action to incorporate SEL as core part of education. Similarly, experts in the field of counseling assert that the scientific community should seek out the support of policy makers in order to provide resources to secondary students, as well as to create research-practice partnerships, which will allow for the expansion of effective universal SEL programs (Achieve, 2013;

Domitrovich et al., 2017). The challenge and responsibility for educational stakeholders is to ensure all students are prepared for postsecondary education and the workforce

(ACT, 2012a). Therefore, school leaders must advocate for the elevation of standards by

setting attainable school improvement goals to inspire students toward a path of becoming college ready, career-driven, and virtuous citizens (ACT 2012b; Dymnicki,

Sambolt, & Kidron, 2013; Weissberg et al., 2015).

The American School Counselor Association (ASCA) provides a framework, known as the ASCA National Model (2012), which encourages the development of a comprehensive school counseling program (CSCP). The ASCA National Model delivers a platform for embedding SEL interventions into the core curriculum program and aligning these programs with the goals of the educational system (Dahir, 2004; Gysbers,

2004). Moreover, the ever-growing body of research literature supports the notion that implementing CSCPs positively affects outcome data (e.g., student achievement, behavior, and college and career readiness) at all grade levels (Carey & Dimmitt, 2012;

Carey & Martin, 2015; Dimmitt et al., 2007; Lapan, 2012). Social-emotional skills and competencies remain primary components in fostering positive social behaviors and academic outcomes (Payton et al., 2008).

Likewise, research on the effectiveness of school‐based universal social, emotional, and behavioral programs has increasingly gained recognition since the turn of the new millennium (Zins, Bloodworth, Weissberg, & Walberg, 2007). A recent meta- analytical review of 75 published SEL outcome studies reported that the interventions had diversity in desired outcomes; yet, an increase in social skills and decrease in antisocial behavior were most often reported, and the authors recommended that researchers expand the spectrum of outcomes under investigation (Sklad et al., 2012).

Subsequently, by focusing exclusively on school counselor-led outcome research for students at the secondary level, school counselors will be recognized as indispensable

resources within school settings, with an ability to teach positive mindsets and behaviors that are necessary for student success (ASCA, 2014).

The call for school counselor accountability and the development of positive student outcomes continues to be reinforced by empirically-proven school counselor-led interventions that enhance academic achievement and SEC for students (ASCA, 2012;

Webb, Brigman, & Campbell, 2005). School counselors are professionals distinctively trained in the fields of counseling and education concurrently (Collins, 2014; Van Velsor,

2009). School counselors’ diverse training empowers them to advocate for adolescents’ overall functioning, social-emotional development, career development, and educational success (Collins, 2014). However, the demand for accountability, collaboration, and leadership is required for systemic change in the schools (Brown & Trusty, 2005; Carey

& Dimmitt, 2006; Van Velsor, 2009).

School counselors foster a link between students’ academic and social competence, which continues to grow (Durlak et. al, 2015; Webb et al., 2005; Villares,

Frain, Brigman, Webb, & Peluso, 2012). Students’ academic achievement remains at the forefront of education and bears national attention (Weissberg & Cascarino, 2013).

According to Lapan, when highly trained, professional school counselors deliver ASCA

National Model CSCPs, students receive quantifiable benefit (2012). Increasingly, school counselors are confronted with the challenge of providing interventions that concretely contribute to increased student achievement (ASCA, 2016; Collins 2014;

Villares et al., 2014). A series of school counseling initiatives and outcome studies consistently report that when research-based, school counselor-led interventions are used to teach critical skills, the results indicate a positive association between improved

academic achievement and social performance of students (ASCA, 2012; Villares et al.,

2012; Webb et al., 2005; White & Kelly, 2010).

The Every Student Succeeds Act (ESSA) of 2015 highlights the importance of academic achievement as a measure of school success. Legally, it is now required for all students in the United States to be taught to high academic standards, which will prepare them to succeed in college and careers. Consequently, educational leaders must place an emphasis on the development of adolescents’ social and emotional growth, while nurturing desirable skills necessary for achieving academic success and college and career readiness (CCR) (ACT, 2012a, ASCA, 2004). Researchers are redefining the relationship between SEL and ambitious academic goals, suggesting that professional development must be integrated into education in order to connect twenty-first century academic competencies to environments that support student learning (Pellegrino &

Hilton, 2012). Thus, this effort will provide students with instruction that promotes SEC, as well as ultimately encourage higher student outcomes on college and career readiness

(CCR) standards (Johnson, & Weiner, 2017). Furthermore, CCR will be improved by integrating SEL competencies, which have been identified by today’s employers and educators as important for success in the workplace and postsecondary settings

(Dymnicki et al., 2013).

Significance of the Problem

In a recent Delphi study on future directions for school counselor research, the highest rated questions involved which school counseling interventions impact academic achievement, as well as how these school counseling programs affect student outcomes

(Villares & Dimmitt, 2017). The significance of this problem is highlighted by the gaps

of three critical areas in school counseling outcome research. First, there is a lack of continuous empirical evidence on the associations between school counselors and their vital role within school settings (ASCA, 2014; White & Kelly, 2010). In response, by focusing on counselor-led interventions, this study seeks to expand the existent argument that school counselors are educators who are exceptionally qualified in the delivery of

SEL interventions (Van Velsor, 2009). If experts in the field contend that there is a link between positive student outcomes (e.g., academic achievement, behavior, and CCR) to

CSCPs, without providing strong empirical evidence, then legislators, school administrators, and other various educational stakeholders may dispute the need for school counseling programs at the local, state, and national levels (Whiston, 2002;

Whiston et al., 2011).

Secondly, although there is an overwhelming amount of research which examines effective SEL interventions, the research concerning the school counselor’s role as a key leader in SEL initiatives is unimpressive (Sink, 2005). Weissberg and Cascarino (2013) underscore the importance of identifying empirically-proven SEL interventions which are related to positive school outcomes (e.g., SEC, academic achievement, and CCR). Yet, the implementation of SEL interventions in schools continues to take a backseat in education, even when extensive research demonstrates the benefits on student’s outcomes

(Brown & Trusty, 2005; Domitrovich et al., 2017).

Thirdly, the current meta-analysis study seeks to expand upon the previous outcome research studies in which school counselors delivered interventions to students enrolled in the secondary school setting (i.e., middle or high school). Due to the present gap in school counseling outcome research, this study seeks to broaden future research

directions for SEL programs aimed at middle and high school students. Durlak et al.

(2011) conclude that SEL programs yielded significant positive effects on targeted SEC and attitudes about self, others, and school. However, more than half of all SEL data comes from elementary settings; therefore, future research directions should emphasize the need for SEL programs for middle and high school students. Furthermore, it is evident that there is a dearth of information on SEL outcomes and other factors of great importance at the secondary level (e.g., graduation rates, dropout prevention, and CCR), as the majority of published research on SEL outcomes has been conducted in an elementary setting (Durlak et al., 2015; Dymnicki et al., 2013). Ultimately, this study will focus on the impact of outcome research at the secondary level; thus, it will examine three significant problems in current trends related to school counseling outcome research for secondary students.

Purpose of the Study

The purpose of this research study is to determine the impact of school counselor- led SEL interventions on secondary students. Specifically, the study will evaluate outcome-based research for students at the secondary level, with counselor-led SEL interventions delivered to students in Grades 6-12. Thus, this meta-analysis will address the gap between the amount of school counselor-led SEL outcome research on elementary school settings versus secondary school settings (Durlak et al., 2015).

Academic scholars recognize the challenge that lies ahead for SEL researchers and educators, who must synthesize research from many disciplines and create systemic

SEL programs (Weissberg, et al., 2015). Within the past decade, there have been a multitude of studies that emphasize the importance of school counselor-led SEL

interventions (White & Kelly, 2010; Webb et al., 2005; Urbina, Villares, & Mariani,

2017). This significant information positions school counselors as advocates for the implementation of evidence-based interventions (Brigman, Webb, & Campbell, 2007;

Lapan, Gysbers, & Sun, 1997). Therefore, this meta-analysis is designed to synthesize prior research findings in order to determine the magnitude of SEL school counselor-led interventions specific to secondary students.

Research Questions

1. How effective are school counselor-led, SEL interventions for improving the

social-emotional, academic, and behavior outcomes for students in Grades 6–

12, as compared to the outcomes for students in Grades 6–12 who do not

participate in school counselor-led SEL interventions?

2. How do the program characteristics of school counselor-led, SEL

interventions impact the rate of improvement in social-emotional, academic,

and behavior outcomes for students in Grades 6–12, as compared to outcomes

for students in Grades 6–12 who do not participate in school counselor-led

SEL interventions?

Definitions

1. Social-Emotional Learning (SEL): “The process through which children and

adults acquire and effectively apply the knowledge, attitudes, and skills

necessary to understand and manage emotions, set and achieve positive goals,

feel and show empathy for others, establish and maintain positive

relationships, and make responsible decisions” (CASEL, 2015, p.3).

a. Self-awareness: “The ability to accurately recognize one’s emotions

and thoughts and their influence on behavior. This includes accurately

assessing one’s strengths and limitations and possessing a well-

grounded sense of confidence and optimism” (CASEL, 2015, p. 5). b. Self-management: “The ability to regulate one’s emotions, thoughts,

and behaviors effectively in different situations. This includes

managing stress, controlling impulses, motivating oneself, and setting

and working toward achieving personal and academic goals” (CASEL,

2015, p. 5). c. Social awareness: “The ability to take the perspective of and

empathize with others from diverse backgrounds and cultures, to

understand social and ethical norms for behavior, and to recognize

family, school, and community resources and supports” (CASEL,

2015, p. 5). d. Relationship skills: “The ability to establish and maintain healthy and

rewarding relationships with diverse individuals and groups. This

includes communicating clearly, listening actively, cooperating,

resisting inappropriate social pressure, negotiating conflict

constructively, and seeking and offering help when needed” (CASEL,

2015, p. 6). e. Responsible decision-making: “The ability to make constructive and

respectful choices about personal behavior and social interactions

based on consideration of ethical standards, safety concerns, social

norms, the realistic evaluation of consequences of various actions, and

the well-being of self and others” (CASEL, 2015, p.6).

2. Social-Emotional Competence (SEC) is reflected in the knowledge,

skills, and attitudes that young people need to manage thoughts and

emotions constructively, regulate their actions, nurture a strong sense of

personal and cultural identity, collaborate and resolve interpersonal

conflicts, and cultivate healthy relationships (Domitrovich et al., 2017).

3. The Collaborative for Academic, Social, and Emotional Learning

(CASEL): “A worldwide leader in advancing SEL science, evidence-

based practice, and policy. CASEL believes that effective SEL

programming begins in preschool and continues through high school and

envisions a time when every school in the nation will provide evidence-

based SEL programming to all students at all levels” (CASEL, 2015, p.2).

4. Meta-Analysis Research Design: A quantitative research procedure used

to synthesize empirical studies on a specific topic (Erford, Savin-Murphy,

and Butler, 2010). An attempt to combine numerous replication studies

into one large study (Lipsey & Wilson, 2001).

5. School Counseling Outcome Research: Quantitative research studies on

school counseling interventions that influence student outcomes. These

studies provide valuable information by quantitatively examining the

extent to which school counseling interventions assist students (Whiston et

al., 2011).

6. Comprehensive School Counseling Program: A comprehensive school

counseling program (CSCP) is an integral component of the school’s

academic mission. Comprehensive school counseling programs, driven by

student data and based on standards in academic, career, and

social/emotional development, promote and enhance the learning process

for all students. Thus, comprehensive school counseling programs are

collaborative efforts designed to benefit students, parents, teachers,

administrators, and the overall community (ASCA, 2012; Gysbers, 2004).

7. Adolescence: The process of developing from childhood to adulthood.

Adolescence begins at puberty and ends with independence from adults.

Early adolescence can be described as fifth to seventh grade, and middle

adolescence spans roughly from eighth to 12th grade (Yeager, 2017). For

the purpose of this study, only middle and high school student data will be

considered.

8. Secondary Students: For the present study, secondary students have been

identified as school-aged pre-adolecent and adolescent students in Grades

6–12; both middle and high school students who participated in school

counselor-led interventions were taken into consideration.

9. Certified School Counselors: Certified/licensed educators with a

minimum of a master’s degree in school counseling, making them

distinctively qualified to address all students’ academic, career, and

social/emotional development needs by designing, implementing,

evaluating, and enhancing a comprehensive school counseling program

that promotes and enhances student success (ASCA, 2012; Gysbers,

2004).

10. Academic Achievement: The extent to which a student, teacher, or

institution has achieved their short- or long-term educational goals.

Students will acquire the attitudes, knowledge, and skills that contribute to

effective learning in school and across the life span (ASCA, 2004).

11. College and Career Readiness (CCR): High school students graduate

with the academic knowledge and skills needed to qualify for and succeed

in entry level, credit-bearing postsecondary coursework or job training

(Educational Policy Improvement Center , 2012).

Limitations of Meta-Analysis

Although the strength of the meta-analytic technique for this study lies with the ability to synthesize and systematize research findings on the effectiveness of intervention programs, no meta-analysis is without its limitations (Lipsey, 2003).

Therefore, the researcher notes that the following limitations may be present in the current meta-analysis:

1. This review only included school counselor-led interventions that were

delivered to students in Grades 6–12; therefore, counseling interventions

delivered by graduate students in training, teachers, psychologists, or other

school-based mental health providers were not eligible for this study.

2. This review only covered studies which had been reported in English between

2005 and 2017.

3. This review includes studies from other countries outside of the United States,

which may not adhere to the ASCA National Model and standards when

assessing and evaluating program effectiveness and standards of care (ASCA,

2012).

4. This review is limited to ACA journal publications and unpublished

dissertations.

5. This review may be influenced by the “file drawer problem,” which refers to

bias introduced into the scientific literature, as selective publications tend to

yield positive results but neglect to publish negative or nonconfirmatory

results (Rosenthal, 1979, p. 638). The “file drawer” may consist of

nonpublished studies that arrive at negative or mixed findings (Rosenthal,

1979).

Goals of Meta-Analysis

The pressure continues to rise for middle and high school students to become academically successful at young age. The goal of this meta-analysis is to contribute to school counseling outcome research by illuminating effective SEL interventions delivered by school counselors in secondary school settings. Longitudinal studies demonstrate that increased social and emotional competence is related to heightened academic success and a reduction of risky behaviors (Durlak et al., 2011; Sklad et al.,

2012). Thus, this literature links the importance of SEL to positive outcomes, such as increased academic achievement and college and career readiness (CASEL, 2015). Due to the scope of the current meta-analysis, the results will deliver two unique advantages to the field of school counseling outcome research. First, the outcomes of this study will

only include school counselor-led interventions. Secondly, the researcher will solely investigate SEL interventions implemented at the secondary level (e.g.; middle and high school students). The purpose of this meta-anaylsis is to quantify school counselor-led

SEL interventions, which increase the social/emotional development, academic achievement, and college and career readiness of secondary students in Grades 6–12.

Subsequently, this study will lay the goundwork for future research to expand upon the effectiveness of SEL interventions for middle and high school students.

Chapter Summary and Dissertation Overview

In summary, Chapter I exposed the significant need for school counselor-led interventions and highlighted the impact on student SEL outcomes. As school counselors continue to prove their role in (and connection to) academic achievement, the demand for comprehensive school counseling programs will increase (ASCA, 2012; Gysbers, 2004).

Chapter II will include a review of literature focusing on the evolving needs of twenty- first century students, with an emphasis on the CASEL framework and evidence-based

SEL curricula for middle and high school students. Additionally, the role of the school counselors will be explored, as will the impact of evidence-based interventions.

Furthermore, the chapter will discuss best practices for conducting a meta-analysis research design, and it will provide a systematic review of the relevant meta-analyses on school counseling outcome research and the impact of school counselor-led interventions on SEL. Chapter III will detail the method and protocol required for a meta-analysis by documenting the search and selection process. The chapter will also identify valid studies used for the problem formulation, as well as articulate the specific search strategies and the appropriate inclusion/exclusion criteria. Chapter IV will present the

results significant to the problem, as they relate to the various quantitative school counseling outcome research. Lastly, Chapter V will discuss the impact of school counselor-led SEL interventions, explores the influence of variables and moderators, acknowledges the limitations of the study, highlights future directions, and provides a summary of research.

II. LITERATURE REVIEW

Student SEL and competencies have been persistently tied to positive academic, social, and behavioral outcomes (Durlak et al., 2011; Whiston et al., 2011), yet SEL interventions remain at the periphery in education (Weissberg & Casarino, 2013).

Although there is a basic appreciation of SEL competencies across countries and cultures, they share similar implementation challenges (Elias & Hatzichristou, 2016). A national report on how SEL can empower children and transform schools noted that due to a lack of leadership, there is a scarcity of schools that adopt evidence-based SEL strategies or integrate evidence-based SEL approaches (Bridgeland et al., 2013). According to the survey, K–12 educators identified SEL as the critical piece that was missing in student development as citizens and scholars (Bridgeland et al., 2013).

The call for action in SEL education is ever-present (Carey and Dimmitt, 2012;

Van Velsor, 2009). As educators with training in mental health, school counselors are in a unique position to assume leadership roles and become the voice of change in introducing evidence-based SEL approaches within schools (Sink, 2009; White & Kelly,

2010). Field experts suggest that to achieve this change, the school counselor's role must shift from a traditional focus on responding to individual student needs to a more resolute focus on enhancing the SEL of all students (Sink, 2009; Van Velsor, 2009). However, school administrators report that there are several barriers to implementing SEL strategies into school curriculum, including lack of time, inadequate educator training, and the need for further evidence linking SEL strategies to academic success (Blad, 2017). These

barriers demonstrate that there is an obligation for educational stakeholders to endorse certified school counselors as dynamic leaders in the implementation SEL interventions for students. Hence, the primary focus of the current meta-analysis is to contribute to the literature on the effectiveness of school counselor-led SEL interventions for middle and high school students.

The subsequent chapter will achieve the following: (a) illuminate the emerging needs of twenty-first century students; (b) demonstrate the link between the CASEL framework and Social-Emotional Learning (SEL); (c) review evidence-based SEL curriculum for middle and high school students; (d) explain comprehensive school counseling programs; (e) describe the role of the school counselor and its impact on evidence-based interventions, which enhance student success; (f) define best practices for conducting a meta-analysis research design; and (g) systematically review relevant meta- analyses that focus on school counseling outcome research and the impact of enhancing students’ SEL (CASEL, 2003; Van Velsor, 2009; Whiston et al., 2011).

The Emerging Needs of Twenty-First Century Middle and High School Students

As a child becomes an adolescent, he or she is exposed to a variety of challenging situations, such as peer pressure, risky behavior, and social media (CASEL,

2015; U.S. Department of Education, Office of Academic Improvement [OAL], 2018).

During these periods of growth, it is important for youth to be equipped with the social- emotional tools. Consequently, SEL programming becomes a critical factor in education for students, as it is necessary for students to be successful in and outside of the classroom (CASEL, 2015; Payton et al., 2008). During adolescence, which is a developmental time often characterized as a period of psychosocial turmoil, adolescents

must learn to navigate major biological, educational, and social role transitions concurrently (Bandura, 2006).

Although adolescence can be such a thrilling time in a young person’s life, enjoyment may become inhibited by overwhelming emotions, such as fear, anxiety, anger, and self-doubt. Often, adolescents are not in tune with their social-emotional needs due to the pressure of academics and rapidity of emotional development (Cervone

& Cushman, 2016). As a result, academic scholars understand that positive student outcomes must be defined by more than just standardized test scores (Zins et al., 2004).

These researchers assert that success in school should be measured in a variety of ways.

Furthermore, scholars suggest that effective SEL programs have had a generous influence on overall school success, and positive outcomes are significantly linked with well- organized program implementation (Villares et al., 2012; Weissberg et al., 2015). Zins et al. (2004) provide examples of student success measures such as attitudes (e.g., motivation, responsibility, and attachment); behavior (e.g., engagement, attendance, and study habits); and performance (e.g., grades, subject mastery, and test performance).

These measures all align directly with the SEL foundational framework (CASEL, 2015).

Similarly, Nagaoka et al. (2014) provide a framework for developing young adult success in the twenty-first century and identifies three key factors: agency, an integrated identity, and competencies. The framework also establishes four foundational components: self-regulation, knowledge and skills, mindsets, and values (Nagaoka et al.,

2014). Likewise, Pellegrino and Hilton (2012) recognize that not only is there the need to develop transferable knowledge and skills for the twenty-first century learner, but there is also an obligation to cultivate creative thinkers, inventors, and problem-solvers.

Researchers acknowledge that there is a correlation between effective SEL programs and positive student outcomes, such as academic learning and developmental growth (Durlak et al., 2015). The outcomes will provide educators, policy makers, university trainers, researchers, and practitioners with important guidance and useful tools that can be applied to improve the lives of today’s students and tomorrow’s leaders (Zins et al.,

2004).

A wide audience has been captivated by the intertwined connection between student social-emotional skill competencies and academic achievement (Weissberg &

Cascarino, 2013). As such, there is a critical need to address the social-emotional challenges that interfere with middle and high school students’ connection and performance in school (CASEL, 2015; Yeager, 2017). Behavioral issues, such as discipline, disaffection, lack of commitment, alienation, and dropping out, frequently limit success in school or eventually lead to failure (Zins et al., 2004). This advances the demand for professional school counselors to implement comprehensive guidance curriculum at the middle and high school level (Whiston, 2002; Whiston & Quinby,

2009).

The CASEL framework and Social-Emotional Learning (SEL)

CASEL provides a foundation of SEL principles that directly align with the

ASCA Mindsets and Behaviors for Student Success: K-12 College and Career Readiness

Standards for Every Student (ASCA, 2014), which focuses on promoting the pillars of academic, career, and social/emotional development for all students. Unfortunately, within the education system, the overall lack of development of core SEC has resulted in students that have become less connected to school as they progress from elementary to

middle to high school (Durlak et al., 2011; Weissbeg & Cascarino, 2013). SEL programs for adolescents are attractive, as they reduce problem behaviors, while aiming to assist adolescents in coping with difficult situations (Yeager, 2017). Specifically, CASEL

(2015) has identified five foundational intrapersonal and interpersonal skills: (a) self- awareness; (b) self-management; (c) social awareness; (d) relationship; and (e) responsible decision making. Each of these skill sets contribute to a student’s social- emotional competence. Social-emotional skills can ultimately facilitate or obstruct children's academic achievement, engagement, interactions with others, and overall school success (Durlak et al., 2011). Working toward mastery of SEL competencies is imperative during adolescence, when there is a tremendous period of physical and emotional growth (Bandura, 2006; CASEL, 2015; U.S. Department of Education, Office of Academic Improvement [OAL], 2018).

The University of Chicago Consortium on Chicago School Research (Farrington et al., 2012) distinguishes five categories of non-cognitive factors: academic behaviors, academic perseverance, academic mindsets, learning strategies, and social skills. These non-cognitive factors appear in SEL secondary education literature (Greenberg et al.,

2003; Lemberger, Selig, Bowers, & Rodgers, 2015) and directly align with the research surrounding effective SEL programs. Drawing from SEL vocabulary, the following examples offer a breakdown of the non-cognitive factors recognized by Farrington et al.

(2012): (a) academic behaviors: going to class, doing homework, organizing materials, participating, and studying; (b) academic perseverance: grit, tenacity, delayed gratiﬁcation, self-discipline, and self-control; (c) academic mindsets: described by personal statements of believing in oneself; (d) learning strategies: study skills,

metacognitive strategies, self-regulated learning, and goal-setting; and (e) social skills: interpersonal skills, empathy, cooperation, assertion, and responsibility. Interestingly, these core principles identified by Farrington et al. (2012) are comparable to the social- emotional skills coined as the CASEL Five. According to this body of SEL research, there is considerable overlap between social behaviors, mindsets, and academic behaviors in the non-cognitive factors, all of which positively affect student success in schools

(CASEL, 2015; Farrington et al., 2012; Weissberg & Cascarino, 2013).

Effective SEL Programs for Middle and High Schools

Durlak and Weissberg (2011) recognize that there is a critical need to support school administrators and educators with the choice of selecting carefully evaluated SEL programs that have proven positive effects on a variety of desired student outcomes

(Weissberg, Resnik, Payton, & O'Brien, 2003). In recent years, CASEL’s (2015) Guide for Middle and High School: Effective Social and Emotional Learning Programs has evaluated nine dynamic SEL curriclums specifically designed for secondary students.

This guide presents evidence-based SEL programs intended for students at the middle and high school level. The guide provides extensive information on programs, including the following for each: title, recommended setting (middle and/or high school), and specific educational professional (e.g., teacher or school counselor) intended to deliver the interventions to students. Specifically, this guide covers the following nine programs, settings, and professionals: (a) Consistency Management & Cooperative Discipline®

(CMCD®), high school teacher; (b) Expeditionary Learning, middle school teacher; (c)

Facing History and Ourselves, middle/high school teacher; (d) Lions Quest, Skills for

Adolescence, middle/high school teacher; (e) Project Based Learning by Buck Institute

for Education, high school teacher; (f) Reading Apprenticeship, middle/high school teacher; (g) Responding in Peaceful and Postive Ways, middle school teacher; (h)

SecondStep: Student Success Through Prevention for Middle School, middle school teacher; and (i) Student Success Skills (SSS), middle/high school counselor.

The SSS curriculum is a competence-based promotion program that uses teaching practices and free-standing SEL lessons to support SEC (Brigman & Webb, 2016;

CASEL, 2015). Interestingly, out of the nine programs evaluated by CASEL, the SSS intervention is the only school counselor-led SEL intervention, and its effectiveness has been proven through a series of evidence-based outcome research studies (Webb et al.,

2005; Webb, Brigman, Carey, & Villares, 2011, Villares et al., 2012).

Student Success Skills

The SSS program provides outcome research which attests to the effectiveness of a school counselor-led intervention (Villares et al., 2012, Webb & Brigman, 2006; Urbina et al., 2017). The SSS curriculum is delivered in a regular classroom setting and provides five lessons embedded in SEL for students’ growth in: (a) setting goals, monitoring progress, and sharing success; (b) building a caring, supportive, and encouraging environment; (c) practicing memory and cognitive skills; (d) calming anxiety and managing emotions; and (e) developing healthy optimism (Brigman & Webb, 2016;

CASEL, 2015). Additionally, SSS offers a group counseling format for students who need supplementary support outside of the classroom setting (Brigman, Campbell, &

Webb, 2010). Furthermore, esteemed researchers conducted a fully funded, four-year randomized controlled trial of the SSS program, which was supported by a $2.7 million grant from the U.S. Department of Education’s Institute of Education Sciences (IES;

Webb et al., 2011). This research project aimed to improve academic achievement for all students and was implemented by trained school counselors (Webb et al., 2011).

By design, the SSS curriculum is to be delivered by school counselors, and there are numerous evidence-based studies (Brigman & Campbell, 2003; Brigman et al., 2007;

Campbell & Brigman, 2005; León et al., 2011; Urbina et al., 2017; Webb et al., 2005) that reinforce why school counselors are uniquely qualified in the delivery of SEL interventions. Consistent with the research, these studies enforce the value of the SSS program on the impacts of positive academic outcomes for students who participate in both large and small group SSS intervention (Brigman & Campbell, 2003; Brigman et al.,

2007; Campbell & Brigman, 2005; León et al., 2011; Urbina et al., 2017; Webb et al.,

2005, 2011).

The National Panel for Evidence-Based School Counseling Research evaluated three studies that support the efficacy of SSS (Carey, Dimmitt, Hatch, Lapan, & Whiston,

2008; Brigman & Campbell, 2003; Campbell & Brigman, 2005; Webb et al., 2005). The guidelines set forth by the National Panel for Evidence-Based School Counseling

Research aim to improve the field of school counseling by developing responsible and effective research practices (Carey et al., 2008). Additionally, researchers Villares et al.

(2012) conducted a meta-analysis on the impact of SSS on standardized test scores, which focused exclusively on SSS outcome studies that were school counselor-led. The results indicated that student who received the SSS interventions had more improved outcomes than those who did not, reporting overall effect sizes (ES) for math (d = .41), reading (d = .17), and SSS program (d = .29) (Villares et al., 2012). An evaluation of this evidence-based outcome study will demonstrate the need for school counselor-led

interventions and attest as to why school counselors are the most qualified educators in the delivery of SEL interventions.

Researchers evaluated the effects of the SSS program on executive functioning skills, feelings of connectedness, and academic achievement in a predominantly

Hispanic, low-income middle school district in the southwestern United States (Brigman

& Webb, 2016; Lemberger et al., 2015). This research design examined the effects of the

SSS program on a sample of 193 middle school students in this district (Lemberger et al.,

2015). The authors implemented a research design as a two-level cluster randomized trial, with the intervention delivered at the classroom level, and participants were randomly assigned to receive either the intervention or the control condition. The treatment group consisted of seventh grade students from six classrooms who received the SSS intervention. The control group was comprised of seventh grade students from

ﬁve classrooms with the control condition.

The researchers acknowledged that upon completion of data collection, the classrooms not initially assigned to the treatment condition were given the intervention

(Lemberger et al., 2015). The results illuminated the importance of school counselors performing direct therapeutic services in schools. Ultimately, the investigation concluded that the SSS program provided an enriching educational foundation that enhanced students’ executive functioning skills and performance on standardized tests (Lemberger et al., 2015).

Comprehensive School Counseling Programs

Comprehensive school counseling programs (CSCP) have become more prevalent in the professional literature (Gysbers, & Henderson, 2014; McGannon, Carey, &

Dimmitt, 2005; Villares & Dimmitt, 2017). Ultimately, students thrive when an effective counseling curriculum encourages positive development throughout the school year and refines social-emotional competence by increasing decision making, self-awareness, and coping abilities (ASCA, 2012; CASEL, 2015; Lapan, 2012; Vernon, 2009). Thus, CSCP serves the school counseling profession by providing practitioners with the clarity needed to validate their role to critical stakeholders (McGannon et al., 2005; Villares & Dimmitt,

2017). With this in mind, it is imperative for school counselors to implement comprehensive guidance programs. School counselors should be committed to (and engaged in) improving student educational outcomes and unproven practices, as well as refining those practices that show positive results (Sink, 2009).

In addition, the ASCA National Model (2012) established a clear agenda for school counselors to contribute to the academic achievement of the students they serve

(ASCA, 2012; Brown & Trusty, 2005). The ASCA National Model (2012) is used by school counselors to deliver CSCPs driven by student data based on academic, career, and personal/social development standards, which promote and enhance the learning process for all students. The CSCP framework consists of four components: foundation, management, delivery, and accountability (ASCA, 2012). The foundation piece refers to establishing CSCPs that focus on student competencies and outcomes, while also identifying professional competencies (ASCA 2012). Management for a school counselor is essential; therefore, adhering to weekly calendars and creating annual plans for the school year supports effective program implementation and organizational assessments. Beyond orchestrating effective program management, school counselors must also host advisory councils, provide data which measures the effectiveness of

program planning, and create classroom curriculum as well as small-group and individual action plans (ASCA 2012).

The delivery of school counseling services to students, parents, school staff and various educational stakeholders can be broken down into either direct (i.e., classroom curriculum, individual student planning, and/or responsive services) or indirect (i.e., referrals, consultation, and/or collaboration) student services (ASCA, 2012). Lastly, school counselors must demonstrate the effectiveness of the school counseling program in measurable terms. This can be achieved when school counselors show accountability through sharing data regarding the impact of the school counseling program on student achievement, attendance, and behavior (ASCA, 2012; Sink, 2009).

The Role of the School Counselor

School counselors are explicitly trained in education, cultural diversity, and clinical mental health issues (ASCA, 2012; Brown & Trusty, 2005; Dahir & Stone, 2009;

Van Velsor, 2009). This demonstrates how school counselors are essential in education when it comes to identifying barriers to student success; specifically, school counselors bridge the gaps between social emotions learning, academic achievement, and college and career readiness (ACT, 2014; Carey & Dimmitt, 2012). Thus, as the role of the school counselor continues to evolve in relation to SEL, school counselors are the most appropriate educators in schools for delivering SEL competencies (ASCA, 2014; Van

Velsor, 2009). When students are educated and encouraged in the development of SEL standards, they begin to demonstrate a greater understanding of appropriate academic and behavioral competencies, which in turn correlates with academic success and postsecondary readiness (ACT, 2008a; Weissberg & Cascarino, 2013).

As dynamic members of the leadership team within school settings, school counselors foster growth in academic achievement, personal/social development, and

CCR (ASCA, 2016). Furthermore, as professional educators trained in mental health, school counselors can offer insightful perspectives when responding to the challenges that adolescent populations face daily (Whiston, 2002). The ASCA Mindsets and

Behaviors for Student Success: K-12 College and Career Readiness Standards for Every

Student (2014) reinforces the social/emotional domains and standards designed to assist students in managing emotions and employing interpersonal skills. By promoting social and emotional development, school counselors foster a school culture of CCR (ASCA,

2014; Gysbers & Henderson, 2014).

Van Velsor (2009) highlights the leading objective in the school counseling field: to encourage school counselors to renew their commitment to social and emotional development. The author observed that although student personal/social development is at the very heart of school counseling, creating a comprehensive school counseling program can still be problematic even in the best settings (Van Velsor, 2009). School counselors recognize that engaging education must extend beyond just teaching academic skills and should include instruction imbued with both social and emotional competencies

(Brown & Trusty, 2005; Sink, 2009; White & Kelly, 2010). Furthermore, Van Velsor

(2009) assert that there is a need for advocacy for the development of SEL curriculum in our schools. Legitimate SEL programs that are effective require participation from all stakeholders (Weissberg & Cascarino, 2013). As a school counselor, this is not an easy undertaking; nevertheless, SEL programs must collaborate with administration, teachers, parents, student, and community liaisons (Brown & Trusty, 2005; Dahir, & Stone, 2009).

By targeting stakeholders in the initial planning and design of SEL programming, individuals become enthusiastically invested in plan implementation (Van Velsor, 2009).

Ultimately, it is imperative for school counselors to become the agents of change and promote the development of SEL programs within the school system (ASCA, 2016;

McMahon, Mason, & Paisley, 2009; Sink, 2009).

Michelle Obama, the former First Lady, recognized that there is an urgency for students to become college and career ready upon completion of high school, and she spearheaded a call for action through the Reach Higher Initiative. Reporting on the action plan, Hatch and Owen (2014) proclaim that this initiative has opened a conversation regarding the role and current state of school counseling in this country.

The mission is to prepare and inspire every student in the United States to take charge of his or her future by completing education past high school, whether through a professional training program, community college, or four-year college or university

(Hatch & Owen, 2014). During this time, a panel of school counselors convened to foster discussion among experts, practitioners, and policy stakeholders who were working to promote access to higher education (Hatch & Owen, 2014). The panel of contributors created three important memorandums on hot topic issues. Each of these would explore the challenges and opportunities that school counselors encounter in supporting students’ college aspirations. According to Hatch and Owen (2014), the following was the top issue and question proposed by the panel of the Reach Higher Initiative: What challenges and barriers do school counselors face in building adequate social, emotional, academic, and college and career support services for every young person?

This initiative provides great insight for the advancement of the school counseling

profession. The role school counselors assume in SEL can be linked to the foundational skills students will encounter as they prepare for life after high school (ASCA, 2014;

College Board, 2010). The goal of the initiative is for all American students to continue post-secondary education once completing graduation. The tone set by this panel demonstrates that there is an uneven playing field, and the initiative shows that there is a need for school counselors to be implementing CSCPs, as school counselors have been identified as the key players for affecting positive change in SEL competencies and successful student outcomes (Dahir, 2004; ESSA, 2015).

Paving the Way for Academic Achievement

It is well documented that SEL plays a vital role in academic success (CASEL,

2003; Elias et al., 2003). Professional school counselors are essential for maximizing students’ strengths and achievements (Dahir, 2004; Sink, 2009). Furthermore, skilled school counselors align with their school’s educational mission to support the academic achievement of all students (ASCA, 2016). Van Velsor (2009) recognizes that school counselors are significant SEL consultants, yet schools in the United States struggle to improve the academic achievement of their students. The author draws a connection between SEL and academic achievement; however, the approach to enhancing school performance is often dominated by academic instruction (e.g., individual tutoring and/or more classroom instruction) and overlooks learning as a social process (Van Velsor,

2009). Researcher Zins and Elias (2007) attest that SEC and academic achievement are highly related, and they emphasize that coordinated instruction is needed to maximize students’ potential to succeed in school.

Consequently, if the goal of schools is to improve student academic achievement, it makes little sense to neglect the promotion and development of SEL in students (Van

Velsor, 2009). The role of academic behaviors in enhancing CCR and overall school success suggest that standardized achievement tests only identify students who are academically at risk (ACT, 2008a). However, previous academic achievement and cognitive ability surpass all other factors in their influence on student performance (ACT,

2008a).

The Road to College and Career Readiness (CCR)

According to the College Board Advocacy and Policy Center, there are many aspects that are directly linked to a student’s ability to become successful in college and career readiness (2011). The research provides a comprehensive understanding of the complexities that encompass CCR and success, and identifies four central strands: Goals and Expectations, Outcomes and Measures, Pathways and Supports, and Resources and

Structures. By incorporating these four arenas, school counseling curriculum can be directly affiliated with providing the critical component young learners need to be successful (Brown and Trusty, 2005; Gysbers & Henderson, 2014).

The revised version of the ASCA Mindsets and Behaviors for Student Success:

K–12 College and Career Readiness Standards for Every Student (ASCA, 2014) upholds the commitment to developing the knowledge, attitudes, and skills for students to become college and career ready before high school graduation. Dymnicki et al. (2013) affirm that these mindsets and behaviors for students have been identified by today’s employers and educators as important for success in the workplace and postsecondary settings.

Furthermore, Johnson and Weiner (2017) recognize the need for educational leaders to

understand the relationship between social and emotional development and academic goals of students. Thus, by incorporating these keys elements into middle and high school counseling programs, students are empowered to achieve postsecondary success

(ACT, 2008a; CASEL, 2015).

The significance of SEL for students in secondary settings has exploded in recent years (CASEL, 2015; Domitrovich et al., 2017). The Association for Middle Level

Education (2010) promotes the recognition of the unique needs of students aged 10–15, and this organization began the middle school movement which supports creating successful schools for young adolescents. The Forgotten Middle is an executive summary produced by ACT, and the results suggest that middle school is a defining educational point for students’ CCR development (ACT, 2008b). Specifically, regarding the years spent in middle school, a student’s level of academic achievement attained by eighth grade has a larger impact on their CCR than anything that happens academically in high school (ACT, 2008b; Whiston et al., 2011).

At the high school level, SEL competencies are tremendously important, as connections between CCR and dropout prevention become evident (CASEL, 2015).

Although the idea of weaving SEL into the daily fabric of the nation’s high schools seems understandably daunting (Cervone & Cushman, 2016), longitudinal research studies indicate that SEC is associated with a reduction in a variety of problem behaviors

(e.g., aggression, delinquency, substance use, and dropout) (ACT, 2014; Durlak et al.,

2011; Sklad et al., 2012; National Research Council, 2012). The reputation of SEL in high school is growing in light of its association with CCR and dropout prevention

(CASEL, 2015). Unfortunately, research shows that waiting until high school to address

preparation gaps is too late for the majority of students who have fallen behind (ACT,

2012a). In summary, the intention for this current meta-analysis is to examine the impact that school counselor-led interventions have on middle and high school students’ academic learning, social and emotional development, and the trajectory of CCR. By narrowing the focus to SEL interventions that are school-counselor-led, the goal of this meta-analysis is to provide a foundation for future researchers, policy makers, and various invested stakeholders to recognize the inherent value that school counselors provide in secondary school settings.

Systematic Review of Literature: Relevant Meta-Analyses

In an era when defining the effectiveness of school counseling interventions is important (Carey & Martin, 2015; Gysbers, 2004; Sink, 2009), the reputation of evidence‐based practices is critical. Researchers and school counselors in the field must continue to demonstrate their accountability, especially as it is related to positive student outcomes. The subsequent review of literature will illuminate four key meta-analyses which focus on school-based universal interventions and promote positive youth development, school counseling, and SSS interventions. All meta-analyses reviewed were conducted within the last decade with the primary objective of illuminating the connection between school counseling outcome research and SEL interventions.

School-Based Universal Interventions for SEL Meta-Analysis

Durlak et al. (2011) conducted a meta-analysis on school-based universal interventions and the impact of enhancing students’ SEL. With this purpose in mind, the researchers explored 213 studies involving 270,034 students, ranging from kindergarten through Grade 12. This was the first large-scale meta-analysis to focus specifically on

school-based universal interventions. The SEL programs were evaluated by their impact on students’ social and emotional competencies, such as positive social behavior, problem behavior, and academic performance (Durlak et al., 2011; Hattie, Biggs, &

Purdie, 1996). The authors investigated several research themes about school-based interventions for the development of social- emotional skills: (a) Outcomes achieved by interventions that attempt to enhance children's emotional and social skills; (b) SEL interventions promoting positive outcomes and prevent future problems; (c) Programs successfully conducted in the school setting by existing school personnel; and (d)

Variables which moderate the impact of school-based SEL programs (Durlak et al.,

2011). These themes shaped the study, thus providing school counselors with a landscape for evidence-based practices (Durlak et al., 2011).

Like most meta-analyses, Durlak et al. (2011) implemented four key search strategies. First, relevant studies were identified through computer searches. Second, the researchers consulted the reference lists for each identified study and the reviews of psychosocial interventions for youth. Third, manual searches were conducted in 11 journals, which produced relevant studies from the period of January 1, 1970 to

December 31, 2007. Fourth, searches were made of online organizations that promote youth development and SEL (Durlak et al., 2011). Independent and dependent variables were defined as follows. For the independent variable, the SAFE practices intervention format was used. SAFE is an acronym for learning styles and practices that are

Sequenced, Active, Focused, and Explicit. The dependent variables were separated into six student outcomes: (a) social and emotional skills; (b) attitudes toward self and others;

(c) positive social behaviors; (d) conduct problems; (e) emotional distress; and (f) academic performance (Durlak et al., 2011).

By calculating a standardized means difference, Cohen’s d ES, the researchers reported positive values and indicated favorable results for students who received SEL programming when compared to the control group’s performance (Durlak et al., 2011).

Accordingly, the findings for the moderator analyses recommended training practices

(SAFE) at post-outcome, as determined the following outcomes: social-emotional skill performance (d = 0.69); attitudes (d = 0.24); positive social behavior (d = 0.28); conduct problems (d = 0.24); emotional distress (d = 0.28); and academic performance (d = 0.28).

These findings indicate that there were gains across these domains and prove that the implementation of SEL programs leads to positive academic, social, and emotional effects (Durlak et al., 2011).

In an effort to close the disparity in SEL research, Durlak et al. (2011) proposed the following discussion on current findings, limitations, and future research directions.

The authors concluded that SEL programs yielded significant positive effects on targeted social-emotional competencies and attitudes about self, others, and school (2011).

Results from Durlak et al.’s (2011) meta-analysis indicated that after intervention, students developed improved SEL skills, attitudes, and positive social behaviors, and they reported fewer discipline-related issues and lower levels of emotional distress.

Interestingly, when collecting data after initial interventions, the mean follow-up ESs remained signiﬁcant for all outcomes, despite a reduction in the number of studies assessing each outcome. The following were the reported ES results: SEL skills (d =

0.26; n = 8), attitudes (d = 0.11; n = 16), positive social behavior (d = 0.17; n = 12),

conduct problems (d = 0.14; n = 21), emotional distress (d = 0.15; n = 11), and academic performance (d = 0.32; n = 8). All analyses were conducted at post only (Durlak et al.,

2011).

A major limitation of the meta-analysis is that there is a lack of data (across multiple outcomes ranges) with additional follow-up investigations that prove program impact (Durlak et al., 2011). In addition, the authors noted that more than half (56%) of reported program data came from elementary settings; roughly a third (31%) came from middle school settings; and an alarmingly small amount (13%) was derived from the high school level. These findings establish that future research is warranted to spotlight the desperate need for evidence-based outcome studies, especially for students in secondary settings. Hence, the primary objective of this dissertation is to conduct a meta-analysis that is exclusively designed to examine the effects of school counselor-led SEL interventions on middle and high school student outcomes.

Promoting Positive Youth Development Meta-Analysis

Most recently, Taylor, Oberke, Durlak, and Weissberg (2017) sought to synthesize research by conducting a meta-analysis on the follow-up effects of school- based SEL interventions (Durlak et al., 2011, 2015). The study focused specifically on promoting positive youth development (PYD) intervention through school-based SEL, which enhances young people’s strengths by establishing engaging and supportive contexts (Taylor et al., 2017). The methods detailed descriptions of the literature, inclusion criteria, coding procedures, and analyzed variables (Taylor et al., 2017). The dependent variables were restricted to measures that reported changes in students within seven distinct categories, which assess positive social and emotional assets as well as

positive and negative indicators of well-being (Taylor et al., 2017). The categories are as follows: (a) social and emotional skills; (b) attitudes toward self, others, and school; (c) positive social behavior; (d) academic performance; (e) conduct problems; (f) emotional distress; and (g) substance use. The review aimed to collect post-intervention follow-up assessments at 6 months or more and to identify the specific theory of change within SEL interventions (Taylor et al., 2017).

A total of 82 studies were used in this meta-analysis, and the ES was calculated as

Hedge’s g (Hedges & Olkin, 1985). The data showed outcome measures of social- emotional gains with signiﬁcant positive impacts on the intervention, with participants having stronger SEL skills (n = 36, g = .17, 95% CI [.11, .24]) and improved attitudes (n

= 25, g = .17, 95% CI [.09, .24]) compared with controls (Taylor et al., 2017). In comparison to controls at post, students who participated in the interventions demonstrated signiﬁcantly more favorably on academic performance (n = 8, g = .22, 95%

CI [.07, .36]), emotional distress (n = 38, g = .12, 95% CI [.06, .19]), and drug use (n =

21, g = .12, 95% CI [.04, .19]). Nevertheless, post-intervention mean ESs were not signiﬁcant for either positive social behaviors (n = 28, g = .06, 95% CI [-.01, .13]) or conduct problems (n = 30, g = .07, 95% CI [.00, .14]) (Taylor et al., 2017).

The authors reported five notable findings: (a) there is a durability of impacts from PYD program on students outcomes, which indicated that student who participate in

SEL interventions demonstrated significant positive benefits; (b) SEL interventions produce dual benefits, in terms of affecting both positive and negative indicators of well- being; (c) the SEL approach to PYD was beneﬁcial for all demographic groups; (d) a positive relationship exists between stronger social and emotional assets at post and

higher levels of wellbeing at follow-up; and (e) SEL leads to positive effects on several additional important developmental outcomes (e.g., improving social relationships, increasing high school graduation rates and college attendance, and reducing later negative outcomes) (Taylor et al., 2017).

The authors concluded that by promoting PYD, a broad range of constructive outcomes emerge to improve young people’s self-control, interpersonal skills, problem solving, quality of peer and adult relationships, commitment to schooling, and academic achievement (Durlak et al., 2011, 2015; Sklad et al., 2012; Taylor et al., 2017). In regard to evidence-based SEL practices, a major limitation is the absence of research targeted at secondary settings. Only 11 interventions were cited as being focused on adolescent populations (ages 14–18), and these students did not differ signiﬁcantly at follow-up from either of the other age groups (g = .18, 95% CI = [.05, .31]) (Taylor et al., 2017). Thus, the current meta-analytic review intends to build on recent research trends related to school counselor-led SEL interventions aimed specially at students in secondary school settings.

School Counseling Meta-Analysis

Concentrating on school counseling outcomes, Whiston et al. (2011) evaluated hundreds of studies by developing two large-scale meta-analyses designed to identify gaps in school counseling research. The authors followed the same design method for both analyses by using a five-step procedure to carefully select and regulate studies

(Lipsey, 2003; Whiston & Li, 2011; Whiston et al., 2011). The first step involved noting school counseling interventions that were common within school counseling programs.

Next, the researchers identified studies that had produced quantifiable measures of

outcomes. The third step in the selection process was to confirm that the studies were conducted with either students or parents within a school setting. The fourth phase sought to capture typical school counseling interventions. As the role and responsibilities of a school counselor can fluctuate in different countries, studies conducted outside of the

United States were eliminated. The last criteria in the selection process aimed at evaluating current practices of school counselors. Guidelines provided by Lipsey and

Wilson (2001) were used in the statistical analyses. Each Cohen’s d ES was calculated by subtracting the mean of the control group from the mean of the experimental group and dividing the difference by the standard deviation (Whiston, 2011).

The initial meta-analysis (Meta-analysis 1) was conducted in the traditional sense, by using treatment-control/comparison groups. Accordingly, the period of study was restricted to the timespan between 1980 and 2004 (Whiston et al., 2011). The results were drawn from 118 studies, which consisted of 153 school interventions that examined the effects of school counseling. The authors compared students who received a school counseling intervention with those who did not. Quantifying using Hedges and Olkin’s

(1985) procedure, the authors cited an overall Cohen’s d weighted ES of d = 30 (99% CI

[.25, .34]) (Whiston et al., 2011). School counseling interventions had a significant effect on behavioral outcomes by reducing disciplinary actions (d = .83) and increasing student problem solving skills (d = .96) (Whiston et al., 2011). A limitation of the Whiston et al.

(2011) meta-analysis is that much of the data was collected during the period of 1980–

2004 and before school counselors had a framework for implementing a CSCP (i.e., the

ASCA National Model). This further validates the purpose of the current meta-analysis,

which will encompass a review of the most recent studies between the years of 2005–

2017.

The second meta-analysis (Meta-analysis 2) conducted by Whiston et al. (2011) used standardized gain scores and was based on pretest-posttest measures of outcomes to calculate a Cohen’s d. According to Lipsey and Wilson (2001), this is a necessary procedure due to the ambiguous interpretation of the mean gain ES and treatment-control comparison, which may range in definition and form. In Whiston et al. (2011), the selection of studies and the coding procedures were consistent with the first meta- analysis, with the exception that only studies with a pretest-posttest design were examined. Out of the original 325 qualified studies, a total of 31 studies (involving 51 school counseling interventions) were used in final meta-analysis 2 results (Whiston et al., 2011). Thus, when using an indicator of the relationship between the pretest and posttest, the calculated ES was comprised of 2,015 students, with an average study involving 62.97 student (SD = 59.18). The authors reported that an average unweighted d of .44 for the pretest-posttest and a weighted d of .07 (Whiston et al., 2011).

Although Whiston et al.’s second meta-analysis was more comprehensive than its predecessor, the authors indicated several major limitations. First, the validity of ES depends on the quality of research, and thus, it cannot be addressed statistically. Another limitation surrounds the dearth of studies that address treatment fidelity; the authors cited that only a handful of studies use comprehensive guidance curriculum. The authors also observed an alarming lack of quality of research, noting that 111 studies were eliminated due to insufficient data. Lastly, the researchers explained that the majority of school counseling research is based on specific interventions, rather than on comprehensive

programs. This point echoed an argument previously made by Brown and Trusty (2005), who asserted that there is scarcity of outcome research on the implementation of CSCPs

(Whiston et al., 2011). In response, the current meta-analysis seeks to define school counselor-led interventions to further prove the impact on positive student outcomes.

Student Success Skills Meta-Analysis

The SSS meta-analysis builds upon previous school counseling outcome research by illuminating the effectiveness of delivering a school counselor-led intervention to improve standardized test scores (Villares et al., 2012). The researchers examined the following research question: What is the impact on student academic achievement, as measured by state mandated standardized tests, when participating in a school counselor- led intervention? The SSS meta-analysis contributes to empirical evidence required to link school counselors to the implementation of effective SEL programs, while also strengthening their position as key educational players when increasing students’ academic achievement (Villares et al., 2012).

A total of five SSS studies (Brigman & Campbell, 2003; Brigman et al., 2007;

Campbell & Brigman, 2005; Leon et al., 2011; Webb et al., 2005) were included in the meta-analysis, which involved 5,171 students. The authors provided a summary of participants and overall ES for individual SSS studies, the latter of which was determined by calculating a Cohen’s d ES. Furthermore, the results compared the mean score difference on posttest scores of the FCAT reading and math tests for the treatment and comparison groups. The results from the study reported the overall ESs for the following: SSS intervention (d = .29), with a variance of .0016 (95% CI [.21, .36]); math

(d = .41), with a variance of .0031 (95% CI [.30, .52]); and reading (d =.17), with a

variance of .0030 (95% CI [.06, .27]). Thus, the authors demonstrate that there is statistical significance for SSS intervention in both reading and math (Villares et al.,

2012). Future studies on school counseling research calls for a focus on proximal outcomes, such as cognitive skills, social skills, and self-management skills, rather than standardized test scores (Villares et al., 2012).

The SSS meta-analysis summarized three key implications for practicing school counselors. First, the results prove to educational stakeholders that there is empirical evidence supporting the need for school counseling interventions and the positive impact of student academic success. Secondly, the outcomes of this study demonstrate how an evidence-based curriculum designed for Grades 4–12 can be incorporated into CSCPs.

Finally, when defining the role of the school counselors, an important factor is connecting school counselor-led interventions with improved student achievement. This will help to secure the critical position of school counselors as significant educational leaders in SEL initiatives within classroom settings, schools, and districtwide (Villares et al., 2012; Whiston, 2002). Ultimately, the research findings suggest that there is an unwavering demand for school counselors to remain as essential members of the educational process (Villares & Dimmitt, 2017). However, school counselors must implement evidence-based interventions which prove academic achievement, while addressing the social and college and career needs of every student (ASCA, 2004, 2014;

Villares et al., 2012). The current meta-analysis will not only lend itself to the growing body of literature but will also demonstrate the correlation between the role of the school counselor and academic achievement for all students (ASCA, 2004).

Meta-Analysis Research Design and Protocol

The purpose of this section of the literature review is to summarize the key components of a meta-analysis and the criteria selection process. This systematic review will incorporate recommended protocols set forth by the Campbell Collaboration (2001).

Similarly, researchers Erford et al. (2010) detailed 12 steps for conducting a meta- analysis with counseling outcomes to assist future researchers in the process. By providing future authors with the tools necessary to contribute to the field of counseling outcome and evaluation, counselors may synthesize an array of counseling outcome research. The following is an outline of protocols recommended by Erford et al. (2010):

1. Define the counseling domain of interest and research questions;

2. Establish criteria for inclusion of studies for meta-analysis;

3. Determine the types of ESs to use;

4. Search for and screen the studies using the inclusion criteria;

5. Select the final set of studies;

6. Extract and code relevant data;

7. Determine the ES on the dependent variables of interest;

8. Conduct reliability checks on the coding procedures;

9. Determine whether and how to group studies (ES) based on independent

variables;

10. Determine the mean and variance of grouped ESs;

11. Test for homogeneity and exploring potential moderator variables; and

12. Synthesize findings and generate conclusions.

Erford et al. (2010) shed light on each of these steps of meta-analysis, which lay the foundation for counseling practitioners, educators, and students, who are often confused by the lengthy process and the challenging procedures. Meta-analyses are extremely necessary for counselors, as these research instruments provide practitioners with more accurate parameters for synthesizing incongruent information (Campbell

Collaboration, 2001; Lipsey & Wilson, 2001). Thus, practicing counselors in the field, counselor educators, and students are encouraged to draw upon meta-analytic conclusions when making informed clinical decisions and utilizing best practices (Erford et al., 2010).

Summary

Chapter II provided an overview of the emerging needs of twenty-first century middle and high school students, while presenting the connection between the CASEL framework and SEL. The discussion of how CSCPs align with evidence-based SEL curriculum demonstrates that school counselor-led SEL interventions are effective at improving the social/emotional development, academic achievement, and behavioral outcomes of students in Grades 6–12. The role of the school counselor is explored while highlighting the influences between academic achievement and CCR. Finally, the chapter presented a detailed systematic review of the literature on relevant meta-analyses, which connects school counseling outcomes to SEL interventions for middle and high school students. Chapter III will establish the research design and protocol for conducting the current meta-analysis research, drawing from the model presented by

Erford, et al. (2010).

III. METHOD

Although there is a growing body of literature surrounding SEL interventions

(Durlak et al., 2011, 2015; Taylor et al., 2017), this meta-analysis seeks to identify studies that exclusively pertain to middle and high school students in secondary school settings (Domitrovich et al., 2017; Durlak et al., 2011; Whiston et al., 2011). To conduct a school counseling outcome-based research design, the researcher will investigate previous research studies and analyze relevant literature reviews. Frequently, counseling practitioners, educators, and students are confused by the different outcomes reported in studies, and although it is possible to synthesize study findings, this approach lacks systematic procedures for selection, coding, and interpretation of effects (Erford et al.,

2010). However, by systematically reviewing research and findings on SEL interventions targeted at secondary student populations, the researcher intends to offer guidance on future school counseling practices and the implementation of CSCPs. The following sections will provide a detailed description of the method used in primary research. Due to the controversy surrounding what some regard as the mythological criteria for study selection within metanalyses, it is important to use a more inclusive approach, which will fully represent a specific topic while empirically examining the relationships between the study findings (Lipsey & Wilson, 2001).

Procedures

As counselor educators, there must be a scientifically based way to synthesize disparities in research (Erford et al., 2010). In basic terms, a meta-analysis can be used,

as it is a form of survey research where a coding protocol is created (Lipsey & Wilson.

2001). The following is the list of steps, as recommended by Erford et al. (2010), which will serve as a guideline for the procedures used in the current meta-analysis.

Defining Research Questions, Variables, and Domain of Interest

As with any research study, the problem statement in a meta-analysis must be carefully composed and highly detailed to determine eligibility criteria (Lipsey & Wilson,

2001). A good problem statement will declare that the research is under investigation, and it will clearly define the importance of the independent and dependent variables

(Erford et al., 2010).

Research questions. The current meta-analysis will be guided by the following research questions:

1. How effective are school counselor-led, SEL interventions at improving the

social-emotional, academic, and behavior outcomes for students in Grades 6–

12, as compared to the outcomes for students in Grades 6–12 who do not

participate in school counselor-led SEL interventions?

2. How do the program characteristics of school counselor-led, SEL

interventions impact the improvement rate of social-emotional, academic, and

behavior outcomes for students in Grades 6–12, as compared to outcomes for

students in Grades 6–12 who do not participate in school counselor-led SEL

interventions?

The first question addresses the important influences that will determine which types of studies will be selected for the current meta-analysis. The independent variable is clearly represented as school counselor-led SEL interventions, with the population of

interest identified as middle and high school students (students in Grades 6–12).

Important dependent variables are listed as social/emotional development, academic achievement, and behavior outcomes for students. The second question explores the potential effect of the moderating variables, which can be described as methodological characteristics of research (i.e., program characteristics) and may influence the relationship between the independent and dependent variables (Erford, et al., 2010).

Variables. The independent variable for this meta-analysis study is the school counselor-led interventions. The dependent variables include the previously reported social-emotional, academic achievement, and behavior outcomes for students in Grades

6–12.

Domain of Interest. This meta-analysis seeks to determine the impact of school counselor-led SEL interventions for secondary students. Specifically, this study intends to investigate school counseling outcome research exclusively for middle and high school students, rather than include studies centering on K–12 students in general (Durlak et al.

2015; Yeager, 2017).

Criteria for Inclusion and Exclusion of Studies for Meta-Analysis

The following criteria were used to determine whether a study would be eligible for review in this meta-analysis of school counseling outcome research, which explores the effects of counselor-led SEL interventions for middle and high school students. The population of study for this meta-analysis is limited to the empirical literature on the effect of school counselor-led SEL interventions for secondary students in Grades 6–12.

When creating a well-articulated research statement, the researcher must establish parameters before the literature review can be conducted (Erford et al., 2010; Lipsey &

Wilson, 2001). The intention of this meta-analysis is to review all published and unpublished documents available (Lipsey & Wilson, 2001). Studies were only included for the experimental group if they provided measurable SEL intervention outcomes, which were led by a certified school counselor. For the control group, studies were only included if they demonstrated alternative or no SEL intervention.

The following items encompass the inclusion criteria:

 The study was reported in English, between 2005 and 2017, and engaged in a

comprehensive school counseling program for students in Grades 6–12

(middle and high school setting/secondary students).

 The study assessed intervention effects for one of the following outcome

variables: academic achievement, social/emotional development, and CCR.

 The study reported sufficient information, so that ESs could be calculated at

pre-posttest design, following the end of intervention.

 The study used either of the following research designs: (a) an experimental or

quasi-experimental design, which compared participant groups receiving one

or more school counseling interventions or comprehensive school counseling

program components (i.e., core school counseling curriculum/guidance

curriculum, individual planning, responsive services, and program

management) with one or more control/comparison groups, and that presented

both pretest and posttest measures on the qualifying outcome variable

(social/emotional development); (b) A pre-posttest design or pre-posttest-

posttest design, in which measures of the qualifying outcome variable

(social/emotional development) were taken before and after the intervention

on the same participants. This category includes multiple-group designs (e.g.,

a control/comparison group and two or more treatment groups) involving

different school counseling interventions or comprehensive school counseling

program components (i.e., core school counseling curriculum/guidance

curriculum, individual planning, responsive services, and program

management).

The following items indicate the parameters set forth by the researcher as exclusion criteria for the current meta-analysis:

 The study was not published in English.

 The study was not published between 2005 and 2017.

 The study participant or participants were not in Grades 6–12.

 The study did not assess interventions effects for select outcome variables

(academic achievement, social/emotional development, behavioral, or CCR).

 The study did not involve a quantitative research design.

 The study did not involve a school counseling intervention or comprehensive

school counseling component (core curriculum, individual planning,

responsive services, small group, consultation, and program management).

 The study did not include a pre-posttest design or multiple posttests.

 The study did not include a control or comparison group.

Selecting the Effect Sizes to Use

When conducting a meta-analysis, it is important to identify the type of research findings that will be examined (Erford, et al., 2010). Most psychological journals require the researchers calculate the ES and state whether the result is significant (Brace, Kemp,

& Snelgar, 2016). According Coe (2002), an ES is simply a way of quantifying the size of the difference between two groups (typically, by using the standardized mean difference). It is easy to calculate, readily understood, and can be applied to any measured outcome in education or social science (Coe, 2002). The following is an illustration (Figure 1) of how ES is calculated (Cohen, 1988):

Figure 1.

Calculated ES

Cohen’s d ES = [Mean of experimental group] – [Mean of control group]

Standard Deviation

The ES is particularly valuable for quantifying the effectiveness of an intervention relative to some comparison. For example, if a research study has been conducted to prove that a new counseling technique is more effective than previous evidence-based practices, the researcher must establish how much more effective the intervention is compared to the former. When defining ES, it is useful to quantify the raw difference of means in the same measurable units that are used to calculate the dependent variable

(Brace et al., 2016). The current meta-analysis will be conducting and reporting the

Cohen’s d ES.

Search for and Screen the Studies Using the Inclusion Criteria

For the purposes of this meta-analysis, the researcher used the following databases when searching for school counseling outcome literature that impacts SEL for students in secondary school settings: Academic Search Premier; ERIC; ProQuest

(dissertations and theses); APA publications (in Psych Articles and Psych INFO); the

U.S. Department of Education; What Works Clearinghouse. The following search terms were used when initially collecting relevant literature surrounding school counseling outcome research: (a) school; (b) school counseling; (c) school counselor; (d) school counselor-led interventions; (e) social-emotional learning (SEL) interventions; (f) academic achievement; (g) college and career readiness (CCR); (h) adolescents; (i) youth; (j) secondary students; (k) secondary school setting; (l) middle school students; and (m) high school students.

Manual searches were conducted of all American Counseling Association (ACA) journals including the Adultspan Journal, Counseling and Values, Counseling Outcome

Research and Evaluation, Counselor Education and Supervision, Journal of

Multicultural Counseling and Development, Journal for Social Action in Counseling and

Psychology, Journal for Specialists in Group Work, Journal of Addictions & Offender

Counseling, Journal of Child and Adolescent Counseling, Journal of College Counseling,

Journal of Counseling and Development, Journal of Creativity in Mental Health, Journal of Employment Counseling, Journal of Humanistic Counseling, Journal of Humanistic

Education and Development, Journal of LGBT Issues in Counseling, Journal of Mental

Health Counseling, Measurement and Evaluation in Counseling and Development,

Military and Government Counseling, Professional School Counseling, Rehabilitation

Counseling Bulletin, The Career Development Quarterly, and The Family Journal.

Additionally, the research team manually searched publications in The Practitioner

Scholar, The School Counseling Journal, Journal of College Access, and The

Professional Counselor.

Conducting and Documenting the Search and Selection Process

The subsequent section describes the required criteria identified in coding for selecting and advancing the studies for analysis. The sample selection process and documentation was conducted by a research team comprised of two school counseling counselor educators and four graduate students. Prior to conducting the search, the research team participated in a training where they were informed of the nature of the study and the three-stage process for searching, evaluating, and coding the data (i.e., round 1, 2, and 3 respectively).

Round 1 consisted of evaluating abstracts that were identified through the databases and manual searches. The authors, titles, citations, and abstracts yielded in

Round 1 were compiled in an Excel spreadsheet. In Round 2, the journal publication and dissertation abstracts were evaluated in the Excel spreadsheet using coding terms (Case;

Phenomenological; Qualitative; Survey; Grounded; Delphi; Parents, School counselor educators; School counselor-in-training; Supervision; Treatment, Experiment; Random;

Interventions; and Mixed Methods) to further identify which full text manuscripts and dissertations would be eliminated or advanced to Round 3. The search field in Excel was used to locate each of the terms and color code the citation, title, or abstract as needed.

This practice narrowed down the data to be examined in the round. The drop-down menu within the Excel spreadsheet was used to select the reason for eliminating a manuscript based on the exclusion criteria. Comments and any corresponding numbers were entered in the appropriate column. Select items were further examined to determine if the inclusion criteria had been met.

Coder training. Round 2 coding training was conducted to ensure procedural

understanding, agreement, and accuracy between coders. Sixty titles, citations, and abstracts were randomly selected from the 10 ACA journals and 20 ProQuest dissertations and added to a spreadsheet for initial coding. At the end of the training, coders independently coded the data and results were compared. Individuals demonstrated accuracy of 85% or above to be certified as Round 2 coders. A minimum of two coders independently reviewed each of the Round 2 citations, titles, abstracts in each spreadsheet. The spreadsheets were forwarded to the lead researcher for data comparison. If conflict between coders arose, a third coder examined the data to reach consensus.

Data Collection

Selection of the Final Set of Studies

The final step in data collection involved reviewing the full-length journal articles and dissertations that advanced to Round 3. Each selected study was reviewed by at least two members of the research team and any differences were resolved through a third- party evaluation of compliance with inclusion criteria (Erford et al., 2010). Each coder read the qualifying articles to determine if the research data presented met inclusion criteria and completed an electronic coding survey form. A flow chart is provided for the inclusion of research for each round (See Figure 2).

Figure 2.

Flow of studies included and excluded from the meta-analysis.

Round 1. Evaluating abstracts that were identified through the databases and manual searches Dissertations (n =538) and Articles (n =49)

Round 2. The dissertation and journal publication abstracts were evaluated in the Excel spreadsheet using coding terms. Dissertations (n =194) and Articles (n =42)

Round 3. The search field in Excel was used to locate each of the terms and color code the citation, title, or abstract as needed. Dissertations (n =35) and Articles (n =23)

Final set of full text manuscripts and dissertations eliminated or advanced to Round 3.

Studies included 28 manuscripts. The studies consisted of dissertations and journal articles of school counselors-led the interventions at the secondary level. (i.e.; middle and high school).

A total number of dissertations (n =18) articles (n =10) and included in the meta-analysis for secondary outcome.

Coding Procedure for Extract and Code Relevant Data

The coding procedure must initially define two parts of the protocol. First, it is necessary to recognize the step that encodes information about study characteristics and 56

then determines how that encoded information relates to the empirical findings (i.e., ES)

(Lipsey & Wilson, 2001). The coding procedures for the current meta-analysis involved a coding protocol that specifies which information is to be extracted from each eligible study (Lipsey & Wilson, 2001). The coding team was comprised of one school counselor educator and two doctoral students from the original research team, as recommended by

Campbell Collaboration (2001). In order to enforce consistent rater reliability, it is required to offer substantial training to coders on the use of coding protocols and the coding manual (Erford et al., 2010). Round 3 data collection consisted of using a

SurveyMonkey questionnaire to indicate if the research material meets all inclusion requirements.

Missing data. Once missing data emerges in a meta-analysis, the researcher may become frustrated (Lipsey & Wilson, 2001). However, in an attempt to offer an explanation, the primary reporter employed efforts to contact the originators of research in order to obtain missing information (Littell, Corcoran, & Pillai, 2008). When data was absent from the current meta-analysis, a member of the coding team emailed the corresponding author of the publication, scheduled a phone meeting, or researched relevant sources (i.e., Internet, instrument manuals, and/or calculated the appropriate ES).

Determining the Effect Size on the Dependent Variables of Interest.

In the current meta-analysis, a Cohen’s d was calculated for the dependent variables of interest. The ES was determined by examining the dependent variables (e.g.; social-emotional, academic, and behavior outcomes) for the meta-analysis. Cohen's d is defined as the difference between two means divided by a standard deviation for the data

(Cohen, 1988). The ES quantifies the size of the difference between two group means

and the correlation between two variables, or it evaluates other output statistics (Erford et al., 2010). Unbiased ESs accounts for the sample size and implies that smaller samples derived from a large population will have greater sampling errors. Thus, ES statistics are converted into unbiased approximations by accounting for sample size (Erford et al.,

2010). Ultimately, the ES calculation reveals the relationship to the proposed research questions.

Conduct Reliability Checks on the Coding Procedures.

Authors Lipsey and Wilson (2001) suggest that a minimum of 20 studies should be used to conduct reliability checks on the coding procedures. In the current meta- analysis, 60 titles, citations, and abstracts were randomly selected from the 10 ACA journals, along with 20 ProQuest dissertations, all of which were added to a spreadsheet for initial coding. The main purpose of the reliability check is to ensure consistency within the coding procedures and to identify any systematic bias from the raters (Erford et al., 2010). Each coder was required to demonstrate an accuracy rate of 85% or above to be certified as a Round 2 coder. At least two coders independently reviewed each of the Round 2 citations, titles, and abstracts. The scope of coder reliability has two dimensions that were considered: the consistency of a single coder from study to study and the consistency between the coders (Lipsey & Wilson, 2001). The spreadsheets were emailed back to the lead researcher for data comparison. If discrepancies between coders arose, a third coder examined the data to reach consensus.

Grouping Studies Based on Independent or Dependent Variables.

To avoid criticism, a meta-analyst must adhere to several guidelines when determining how best to group studies’ ESs based on independent or dependent variables.

First, ESs may be grouped when using the same metric for calculations (e.g.; Cohen’s d,

Hedges g) to avoid inappropriate interpretations. Therefore, it is good practice to combine ESs that have been generated by the same formulas (Erford et al., 2010). To focus on legitimate comparisons, this meta-analysis will only report ESs that measure similar outcomes. Furthermore, in current meta-analysis, school counselor-led SEL interventions is the independent variable, while social-emotional, academic, and behavior implications were identified as outcome measures. Additionally, as independent and dependent patterns emerge in the data, the meta-analyst may notice studies that use two or three similar outcome measures (Erford et al., 2010).

Data Analysis

For the purpose of the current meta-analysis, the researcher utilized the

Comprehensive Meta-Analysis Software (CMA). The CMA software is an indispensable tool utilized for efficient problem solving in meta-analyses (CMA, 2016). This meta- analysis software is considered user friendly and the interface is clear and intuitive. With basic data entry and analysis, research is synthesized and systematically reviewed for finding the ES. The software permits for multiple data entry formats, and the program allows one to create two types of moderator variables, which can then be used in the analysis.

Determine the Mean and Variance of (Independent) Grouped Effect Sizes.

The important part of determining the mean and variance of grouped ESs is to observe the differences in the interpretation. Authors Lipsey and Wilson (2001) affirmed that it is not a wise practice for a meta-analyst to only give attention to mean values without giving appropriate consideration to variances. For example, when as ES

represents a large sample size, it will contain less sample variance than when the ES represents a small sample. Therefore, the larger sample should be weighted more heavily to accurately estimate true ES (Erford et al., 2010).

Fail-safe N and publication bias. Precluding a discussion on research inclusion and exclusion, one must identify the file drawer problem. In 1979, Robert Rosenthal first coined this term, and it refers to the bias introduced into the scientific literature due to selective publication, which chiefly occurs when there is a tendency to publish positive results, but not to publish negative or nonconfirmatory results. The file drawer problem consists of nonpublished studies that arrive at negative or mixed findings (Rosenthal,

1979). When questions remain about the plausibility about biased results due to sampling, additional statistical measures, called fail-safe N (a term also developed by

Rosenthal), can be calculated (Lipsey & Wilson, 2001). The fail-safe N estimates the number of unpublished studies that report null results in order to reduce non-significance

(Erford et al., 2010; Lipsey & Wilson, 2001). More recently, Makel and Plucker (2014) published an article about facts being more important than novelty and focused on replication in the education sciences. The authors discussed how replication of research studies is necessary when conducting a meta-analysis and provided the classic example of when meta-analysis studies are derived from the same meta-analytic pool, but do not serve the same purpose (Makel & Plucker, 2014).

Test for Homogeneity and Exploring Potential Moderator Variables.

The following potential moderators will be explored in the current meta-analysis:

(a) behavioral measures (e.g., executive functioning; discipline; attendance; rating scales and SEL); (b) cognitive measures (e.g., academic grades, GPA, and standardized

achievement test scores); (c) career development measures (e.g., CCR and career inventories); (d) affective measures (e.g., anxiety, test anxiety, depression, locus of control, and SEL); (e) school level (e.g., middle or high school, and mixed Grades 6–12);

(f) length of treatment (e.g., 1–4 weeks, 5–8 weeks, 9–12 weeks, and 13+ weeks), and (g) type of treatment (e.g., classroom, small group, individual, peer tutoring, and combination of types).

Synthesize Findings and Generate Conclusions

The final step entails synthesizing conclusions about the analyzed studies.

Ultimately, ESs have been calculated and tested for homogeneity. If a search for moderator variables is required, this will describe the lack of homogeneity, with the intent of the meta-analyst striving to conform all data collected (Lipsey & Wilson, 2001).

In regard to the mean difference ES, the meta-analyst should follow the rule of thumb when interpreting ESs by using Cohen’s d. The ESs can be interpreted as follows: (d =

0.2) represents a small ES, (d = 0.5) represents a medium ES, and (d = 0.8) represents a large ES (Erford et al., 2010; Lipsey & Wilson, 2001). When synthesizing findings, statistical significance is important, but it can be highly influenced by sample size. Thus, conclusions must be drawn from the effectiveness of interventions and must report the magnitude of ESs (Erford et al., 2010; Sink & Stroh, 2006).

Benchmarks for Interpreting Effect Sizes

The importance of establishing empirical benchmarks to interpret ESs in different contexts has been debated (Hill, Bloom, Black, & Lipsey, 2008). Due to the nature of this meta-analysis, the guidelines set forth by Cohen will be used for reporting results

(1988). The results indicating ES < .20 as small, ES = .50 as medium, and ES > .80 as

large (Cohen, 1988). Noting the limitations of using Cohen’s (1988) benchmarks as rigid standard rather than suggested rule of thumb for small, medium, and large ESs, educational researchers argue such rigid standards disregard the context in which the program or intervention effect is applied (Hill et al., 2008). In addition, researchers attest that when considering the empirical benchmarks for interpreting ES, it is important to consider the context of the study, including the magnitude of an intervention effect, outcomes being measured, and the type of samples evaluated (Hattie et al., 1996; Hill et al., 2008). Consequently, Hill et al. (2008) assert that having just one benchmark for interrupting ESs does not and cannot ﬁt all and argued that it is useful to use multiple benchmarks. For instance, Hattie et al. (1996) research on meta-analyses related to interventions delivered in education settings found the typical ES to be .40 and recommended that other researchers could use that mean ES as a global benchmark.

Similarly, Hill et al. (2008) suggested that researchers could expect the average mean for interventions designed to impact academic achievement in middle school to be .27 and

.24 for high school.

Furthermore, Vernez and Zimmer (2007) conclude that relative to the experience gained so far in education interventions designed to increase student achievement, the interpretations of ESs based on standardized achievement scores should be interpreted differently than suggested by Cohen (1988) for social sciences and recommended a benchmark ranging from .25 = large effect, .15 = medium effect, and .05 to .10 = small effect (Vernez and Zimmer, 2007). Therefore, for the purposes of this meta-analysis, the resulting ESs for the affective, behavioral, cognitive, executive role functioning, and the moderating analyses will be interpreted using Cohen’s ES < .20 as small, ES = .50 as

medium, and ES > .80 as large scale (1988). While the resulting ES for the standardized achievement test score variable will be interpreted using Vernez and Zimmer (2007) benchmarks.

Limitations of Meta-Analysis

Limitations are a normal part of social science research (Flamez, Lenz, Balkin, &

Smith, 2017). No meta-analysis is without limitations; however, the strength of the method for the current study lies with the technique or manner of synthesizing and systematizing research findings pertaining to the effectiveness of intervention programs

(Lipsey, 2003). Ultimately, the researcher acknowledges that the following limitations may be present in the current meta-analysis review: (a) This review only included interventions that were implemented by school counselors and delivered to students in

Grades 6–12; therefore, counseling interventions delivered by graduate students in training, teachers, psychologists, or other school-based mental health providers were not eligible; (b) This review only reported studies written in English between 2005 and 2017;

(c) This review covered studies from other countries outside of the United States, which may not adhere to the ASCA National Model and standards when assessing and evaluating program effectiveness and standards of care (ASCA, 2012); and (d) This review is limited to journal publications and unpublished dissertations. Therefore, the study acknowledges the file drawer problem, which is a potential bias introduced into the scientific literature when selective publications yield positive results but neglect to publish negative or nonconfirmatory results (Rosenthal, 1979, p.638). The file drawer may consist of nonpublished studies that arrive at negative or mixed findings (Rosenthal,

1979).

Summary

The current meta-analysis served to expand upon the existing SEL literature by contributing empirical research regarding the effects of SEL on students in Grades 6–12.

Per the sixth edition of the Publication Manual of the American Psychological

Association (APA, 2010), the policy statement for empirical studies indicates that reports should be of original research, which includes analyses that test hypotheses while presenting novel data that has not previously been reported. Chapter III provided an explanation of the methods and procedures necessary to conduct the meta-analysis. stages of the research process. Chapter IV presents the descriptive statistics, results for overall

ES for affective, behavioral, cognitive, and effective role functions variable outcomes, and results of the ES for moderating variables (APA, 2010).

IV. RESULTS

Descriptive Statistics

The current meta-analysis contains 28 studies involving a total of 3,794 middle and high school students. The treatment group was comprised of a total of 2,032 students, who received interventions led by a certified school counselor. The control/comparison groups were derived from a sample of 1,762 middle and high school students. The meta-analysis included a diverse sample of students, with ethnicity reported as 589 (15.52%) African American, 52 (1.37%) Asian, 1,162 (30.63%)

Hispanic, 1,267 (33.39%) Caucasian, 11 (0.28%) Native American, 21 (0.55%) Pacific

Islander, and 177 (4.66%) Multi-racial/Other. Of the studies included in the meta- analysis, the ethnicities of 412 (18.86%) students were not reported. A total of 12 studies were conducted at the middle school level, 10 at the high school level, and 6 studies reported a mixed setting of Grades 6–12. The sample included almost equal representation of 1,883 (49.63%) males and 1,847 (48.68%) females, and the genders of

69 (1.82%) students were not reported.

Effect Sizes

When conducting a meta-analysis, it is important to identify research findings that have met the inclusion criteria for the identified research questions (Erford, et al., 2010).

The current study used a standardized mean difference effect (Cohen’s d) to determine the magnitude of the findings. The Cohen’s d ES was calculated by using the following formula (See Figure 3).

Figure 3.

Formula for Calculation Effect Size

[Mean of experimental group] – [ Mean of control group] Effect Size = Standard Deviation

Overall Effects

Research question one examined how effective school counselor-led, SEL interventions improve the social-emotional, academic, and behavior outcomes for students in Grades 6–12 when compared to the outcomes for students in Grades 6–12 who do not participate. It is important to note that each study identified for inclusion in the meta-analysis (N = 28) produced an ES with a 95% confidence interval (CI) [Lower

Limit, Upper Limit]. However, to be included in the overall variable or subsequent moderator analyses, the researcher required a minimum of three studies with a similar variable, domain, or sub-domain measure. The overall unweighted Cohen’s d ES of the school counselor-led interventions was .312 (95% CI [.173, .452]). The result of a classic fail-safe N indicated that 206 missing studies with an ES of 0 would be needed to influence the overall ES. The overall ES of .312 is considered small (Cohen’s 1988).

Overall Variable Effect Sizes

Of the studies that met the inclusion criteria, affective, behavioral, cognitive, and effective role function measures were used to examine differences between students who participated in the treatment group, and received a school counselor-led intervention, and students in the control or comparison groups, who did not receive the school counselor- led interventions. Affective measures included anxiety, test anxiety, and social- emotional learning measures, such as self-awareness and self-management. Behavior

measures included attendance, discipline, and rating scales. Cognitive measures were reported as standardized achievement test scores or grade point average. Effective role function measures were used to examine changes in career decision making and career inventory scores.

Affective variable. Table 1 displays the meta-analysis results of the overall analysis for the affective variable, domain, and sub-domain. The results of the anxiety/text anxiety measures (d = 0.469), SEL domain (d = 0.350), self-awareness (d =

0.484), and self-management (d = 0.309) revealed small to close to medium effects

(Cohen, 1988). The result of a classic fail-safe N suggested that 146 missing studies with an ES of 0 would be needed to influence the overall ES. In sum, the resulting overall affective variable ES of 0.356 is considered small (Cohen’s 1988).

Table 1.

Effect Sizes Related to Affective Variable Outcomes

Variable Domain Sub-domain k d 95% CI Z- p- Q- value value value Affective 14 0.356 [0.132, 0.580] 3.119 0.002* 76.642

Anxiety 3 0.469 [-0.202, 1.139] 1.370 0.171 12.524 including test anxiety

SEL 10 0.350 [0.065, 0.634] 2.408 0.016* 64.194

Self- 7 0.484 [-0.084, 1.052] 1.671 0.095 92.586 awareness

Self- 6 0.309 [0.005, 0.175] 4.509 0.000* 5.385 management Notes. k = number of studies; d = Cohen’s standardized mean difference ES; CI = confidence interval; Z = test of the null; p = test of the null is < 0.05; * = statistically significant; Q = test of heterogeneity.

Behavioral variable. As previously mentioned, the behavioral variables included measures for attendance, discipline, and rating scales. Table 2 displays the results of the behavior variables. These findings revealed small effects for attendance (d = 0.232), discipline (d = 0.390), and rating scales (d = 0.166). The result of a classic fail-safe N indicated that 64 missing studies with an ES of 0 would be needed to influence the overall ES. In sum, the resulting overall behavioral variable ES (d = 0.228) is considered small (Cohen, 1988).

Table 2.

Effect Sizes Related to Behavioral Variable Outcomes

Variable Domain k d 95% CI Z-value p-value Q-value

Behavioral 16 0.228 [0.007, 0.069] 2.812 0.005* 38.651

Attendance 8 0.232 [0.009, 0.046] 2.448 0.014* 12.090

Discipline 5 0.390 [-.0183, 0.963] 1.334 0.182 21.974

Rating 7 0.166 [-.069, 0.401] 1.384 0.166 15.868 Scales

Notes. k = number of studies; d = Cohen’s standardized mean difference ES; CI = confidence interval; Z = test of the null; p = test of the null is < 0.05; * = statistically significant; Q = test of heterogeneity.

Cognitive variable. The cognitive variables included measures for students’ academic achievement, as measured by standardized achievement tests and GPA. Table 2 displays the results of the cognitive variables. Table 3 presents the ES results for the cognitive variables. The overall ES for cognitive outcomes is considered small (d =

0.380) and does not contain a zero, indicating the ES is statistically significant at the .05 level. However, when examining the result of the domain of standardized achievement

tests, the finding of (d = 0.612) is considered large when using the recommended Vernez and Zimmer (2007) benchmark for standardized test results.

However, the GPA result (d = 0.284) was considered small when interpreted using

Cohen’s benchmarks. The result of a classic fail-safe N suggested that 283 missing studies with an ES of 0 would be needed to influence the overall ES. In sum, the resulting overall cognitive variable ES (d = 0.380) is considered small (Cohen, 1988).

Table 3.

Effect Sizes Related to Cognitive Variable Outcomes

Variable Domain k d 95% CI Z-value p-value Q-value

Cognitive 15 0.380 [0.191, 0.905] 3.948 0.000* 63.517

Standardized 8 0.612 [0.319, 0.905] 4.093 0.000* 55.670 Achievement Tests

GPA 9 0.284 [ -0.034, 0.603] 1.748 0.080 38.077

Effective role function variable. Finally, studies that examined changes in career decision making and career inventory scores were categorized by the effective role function variable. Table 4 presents the ES results for effective role function. The result of a classic fail-safe N showed that 15 missing studies with an ES of 0 would be needed to influence the overall ES. The resulting overall ES for the effective role function variable (d = 0.377) is considered small (Cohen, 1988).

Table 4.

Effect Sizes Related to Effective Role Functions Variable Outcomes

Variable k d 95% CI Z-value p-value Q-value

Effective Role 4 0.377 [0.081, 0.672] 2.493 0.013* 8.192 Functions

Moderator Analyses

According to Lipsey (2003), methodological moderator variables in meta-analysis may explain differences in treatment effects; however, these variables cannot be assumed to be statistically independent. Moderator analyses aim to separate the ESs by finding the differences between them in order to achieve a true ES. The goal of this portion of the results is to effectively interpret ESs, determine their importance within the context of the research question, and identify patterns of relationships between treatment and subject characteristics related to the intervention effect (Lipsey, 2003).

The second research question responds to investigating the impact of any moderator variables that may be present within the current meta-analysis. Thus, this question examines how program characteristics of school counselor-led, SEL interventions impact the rate of improvement in social-emotional, academic, and behavior outcomes for students in Grades 6–12, when compared to outcomes for students in

Grades 6–12 who do not participate in school counselor-led SEL interventions. The following moderators were explored in the current meta-analysis: (a) affective measures

(e.g., anxiety, test anxiety, depression, locus of control, and SEL); (b) behavioral

measures (e.g., executive functioning, discipline, attendance, rating scales, and SEL); (c) cognitive measures (e.g., academic grades, GPA, and standardized achievement test scores); (d) career development measures (e.g., CCR and career inventories); (e) school level (e.g., middle or high school, and mixed grades from 6–12); (f) intervention delivery type (e.g., manualized and non-manualized) (g) length of treatment (e.g., 1–4 weeks, 5–8 weeks, 9–12 weeks, 13+ weeks); and (h) type of treatment (e.g., classroom, small group, individual, peer tutoring, and combination of types).

Grade level. The first research moderator that was explored included the program setting (i.e., middle, high schools, and Grades 6–12). Specifically, the analysis examined the impact of the program setting and the overall affective, behavioral, cognitive, and effective role functions outcomes. The results of the analysis of all outcomes, as moderated by the program setting, are presented in Table 5. The findings indicate that school counselor-led interventions delivered at the middle school level yielded a larger ES (d = 0.312) than school counselor-led interventions delivered in the high school setting (d = 0.214). Findings at the Grades 6–12 setting were inconclusive, given that there were less than three studies delivered at that level. The result of a classic fail-safe N indicated that 497 missing studies with an ES of 0 would be needed to influence the overall ES. In sum, the resulting overall grade level ES (d = 0.293) is considered small (Cohen, 1988).

Table 5.

Effect Sizes Related to Grade Level as a Moderator

Variable Moderator k d 95% CI Z-value p-value Q-value

All Middle School Only 15 0.371 [0.211, 0.531] 4.539 0.000* 38.447 Outcomes High School Only 10 0.214 [-0.041, 0.470] 1.644 0.100 67.220

Intervention delivery type. The next research moderator examined related to the intervention delivery method (i.e., classroom and small group). Within the 28 studies examined in current meta-analysis, none reported the effect of school counselor-led interventions on individual interventions. Table 6 shows the findings for both classroom

(d = 0.329, small effect) and small group (d = 0.321, small effect) were comparable to each other. The findings are inconclusive for mixed 6–12 school settings, given that there are less than three studies at that level. The result of a classic fail-safe N indicated that 580 missing studies with an ES of 0 would be needed to influence the overall ES. In sum, the resulting overall ES of the intervention delivery type (d = 0.325) is considered small (Cohen, 1988).

Table 6.

Effect Sizes Related to Intervention Delivery Type as a Moderator

Variable Moderator k d 95% CI Z-value p-value Q-value

All Classroom Only 14 0.329 [ 0.163, 0.495] 3.875 0.000* 53.288 Outcomes Small Group Only 12 0.321 [0.108, 0.534] 2.956 0.003* 31.272

Notes. k = number of studies; d+ = Cohen’s d standardized mean difference ES; CI = confidence interval; Z = test of the null; p = test of the null is < 0.05; * = statistically significant; Q = test of heterogeneity.

Length of treatment. Of the 28 studies included in this meta-analysis, the school counselor-led interventions were implemented between one and 13+ weeks. Table 7 presents the ES results for length of treatment. The findings from the moderating analysis showed that interventions that were implemented for 13 or more weeks had a greatest effect (d = 0.564, medium effect) when compared to the results of the interventions delivered from 9–12 weeks (d = 0.407, small effect), and 5–8 weeks (d =

0.369, small effect). Interventions implemented for four weeks or less had almost no effect (d = 0.073). The result of a classic fail-safe N indicated that 587 missing studies with an ES of 0 would be needed to influence the overall ES. In sum, the resulting overall ES for the length of treatment of d = 0.353 is considered small (Cohen, 1988).

Table 7.

Effect Sizes Related to Length of Treatment as a Moderator

Variable Moderator k d 95% CI Z-value p-value Q-value All 1–4 weeks of 8 0.073 [-0.209, 0.355 0.509 0.611* 44.434 Outcomes intervention 5–8 weeks of 11 0.369 [0.270, 0.469] 7.295 0.000 10.979 intervention 9–12 weeks of 6 0.407 [0.129, 0.684] 2.872 0.004 14.497 intervention 13+ weeks of 3 0.564 [0.166, 0.962] 2.779 0.005 3.115 intervention

Treatment protocol. Finally, the researcher conducted an analysis to determine the effect of school counselor-led interventions that were delivered using a manualized treatment protocols versus non-manualized treatments. Table 8 presents the ES results for treatment protocol. Interestingly, only seven studies reported using a manualized treatment; however, the analysis produced a higher ES (d = 0.427, small effect) when compared to the 21 studies that did not follow a manualized treatment protocol (d =

0.275, small effect). The result of a classic fail-safe N indicated that 587 missing studies with an ES of 0 would be needed to influence the overall ES. In sum, the resulting overall ES for the treatment protocol (d = 0.351) is considered small (Cohen, 1988).

Table 8.

Effect Sizes Related to Treatment Protocol

Variable Moderator k d 95% CI Z-value p-value Q-value Treatment Manualized 7 0.427 [0.289, 0.565] 6.061 0.000* 10.324 Protocol Non-manualized 21 0.275 [ 0.091, 0.458] 2.933 0.003* 100.237

Summary

Chapter IV presented the descriptive statistics, results for overall ES for affective, behavioral, cognitive, and effective role functions variable outcomes, and results of the

ES for moderating variables. Chapter V presents a discussion of research findings as it related to the impact of school counseling interventions. The implications of the results are discussed as they relate to the work of school counselors and counselor educators.

Limitations and recommendations for future researcher are also presented.

V. DISCUSSION

The goal of this meta-analysis is to contribute to school counseling outcome research by illuminating effective SEL interventions delivered by school counselors in secondary school settings (Durlak et al., 2011; Sklad et al., 2012). By successfully interpreting ESs, determining their importance within the context of the research questions, and exploring moderator variables, the results can be synthesized into meaningful conclusions to contribute to the field of counseling (Erford et al., 2010). The results of the current meta-analysis deliver two unique contributions to the field of school counseling outcome research. First, the outcomes of this study only included school counselor-led interventions. Secondly, the researcher solely investigated SEL interventions implemented at the secondary level (e.g.; middle and high school students).

Chapter V includes a discussion on the impact of school counselor-led SEL interventions, explores the influence of variables and moderators, acknowledges the limitations of the study, highlights future directions, and provides a summary of research.

A focus on themes generated throughout the meta-analysis will be presented, as well as an explanation for why they are relevant. A total of (K = 28) studies met the criteria. The most frequently reason for excluding a study was due to teachers delivering the interventions rather than school counselors. The findings in this study were interpreted by using the guidelines set forth by Cohen (1988) and the evaluation of ESs is applied in current meta-analysis as 0.80 (large effect), 0.50 (medium effect), and 0.20 (small effect).

Only findings including student achievement scores were interpreted using the

recommended Vernez and Zimmer with 0.25 (large effect), 0.15 (medium effect), and

0.05-0.10 (small effect) benchmarks.

Impact of School Counselor-Led Interventions

Research question 1 explored the effectiveness of school counselor-led, SEL interventions for improving social-emotional, academic, and behavioral outcomes for students in Grades 6–12 as compared to outcomes for students in Grade 6–12 who do not participate in these interventions. This research question identifies important influences that determine the types of studies selected for the current meta-analysis. The independent variable is clearly represented as school counselor-led SEL interventions, with students in middle and high school (Grades 6–12) as the population of interest. The dependent variables are identified as social/emotional development, academic achievement, and behavioral outcomes for students.

The findings of the analysis for the overall impact of school counselor-led SEL interventions revealed that when interventions were delivered by school counselors to participants in the treatment group, the resulting overall unweighted Cohen’s d ES was

0.312, a small effect (Cohen, 1988). When examining the impact of the school counselor-led intervention by the measure used (i.e., affective, behavioral, cognitive, and executive role functions) the students who participated in the intervention experienced an overall positive effective. School counselor-led SEL interventions had the strongest overall significant ES on overall cognitive and effective role function variables, which suggests a positive impact of school counselor-led interventions on student outcomes.

The ES for overall cognitive outcomes (d = 0.380) was slightly larger than for overall effective role functions outcomes (d = 0.377) and affective outcomes (d = 0.356). The

smallest ES reported for overall variables was for behavioral outcomes (d = 0.228), yet the finding was still significant from an educational standpoint. Single greatest ES indicator for a measure was for the impact on standardized achievement test scores (d =

0.612) (Vernez & Zimmer, 2007). This finding illuminates the connection between school counseling interventions and positive student achievement results.

Affective Variable

The overall ESs for affective outcomes was reported (d = 0.356), and it is considered small, when interpreted by Cohen (1988). Under the affective domain lies two subdomains related to the CASEL Five. Self-awareness reported a number of studies

(n = 7) with significantly high ES (d= 0.484) for educational research (Cohen, 1988).

Similarly, self-management quantified several studies (n = 6), which also indicated significant ES (d= 0.309). The researcher investigated outcome research that addresses the five competencies set forth by CASEL; however, an insufficient amount of studies did not meet inclusion criteria to produced significant results for (a) social awareness; (b) relationship; and (c) responsible decision making.

Previously, a meta-analysis on school-based universal interventions and the impact of enhancing students’ SEL reported favorable results for students who received

SEL programming when compared to the control group’s performance (Durlak et al.,

2011). The findings determined the following outcomes: social-emotional skill performance (d = 0.69); attitudes (d = 0.24); positive social behavior (d = 0.28); conduct problems (d = 0.24); emotional distress (d = 0.28); and academic performance (d = 0.28)

(Durlak et al., 2011). Likewise, in the current meta-analysis, findings indicate that there were significant advances across domains, and these findings provide a framework for

school counselor-led SEL programs so that they may lead to positive academic, social, and emotional effects for students (Durlak et al., 2011).

Behavioral Variable

The overall ESs for behavioral outcomes was reported (d = 0.228), and it is considered a small ES, when interpreted by Cohen (1988). From an educational standpoint, the most significant influence under the behavioral domain is discipline results with a total of (n= 5) studies and ES (d= 0.390) which represents a positive impact. These results continue to support the notion that school counselors are the most appropriate educators in schools to deliver SEL competencies (ASCA, 2014; Van Velsor,

2009). Whiston et al. (2011) focused on school counseling outcomes by evaluating hundreds of studies, using two large-scale meta-analyses designed to identify gaps in school counseling research and found an overall Cohen’s d weighted ES (d= .30) that compared students who received a school counseling intervention with those who did not.

School counseling interventions were significantly effective on behavioral outcomes, as they reduced disciplinary actions (d = .83) and increased student problem solving skills (d

= .96) (Whiston et al., 2011). In regard to the current meta-analysis, studies focused on reducing disciplinary actions and specifically measuring problem solving skills did not meet the inclusion criteria and therefore could not be compared.

Cognitive Variable

The overall largest ES reported for cognitive outcomes (d = 0.380), with a total of

15. The results demonstrate the domains of standardized achievement tests, with a significantly large effect (k = 8, d = 0.612) when interpreted by the Vernez and Zimmer rubric (2007). In comparison, by examining the effectiveness of delivering school

counselor-led interventions to improve standardized test scores, the SSS meta-analysis conducted by Villares et al. (2012) is most similar to the current meta-analysis. The results from the study reported an overall ES of SSS intervention (d = .29) with a variance of .0016 (95% CI [.21, .36]); overall math ES (d = .41) with a variance of .0031

(95% CI [.30, .52]); and overall reading ES (d =.17) with a variance of .0030 (95% CI

[.06, .27]). Thus, these findings demonstrate statistical significance for SSS intervention in both reading and math (Villares et al., 2012). The researchers noted that future studies on school counseling research should focus on proximal outcomes, such as cognitive skills, social skills, and self-management skills rather than standardized test scores

(Villares et al., 2012). As such, the current meta-analysis results indicate a small ES (d =

0.312) when school counselors deliver, and students receive interventions designed to improve cognitive outcomes. School counseling outcome research continues to demonstrate counselors closing the academic gap for students by providing better access to postsecondary options.

Effective Role Function Variable

The resulting overall ES (d = 0.377) is considered small, when interpreted by

Cohen (1988). The outcome variable included changes in career decision making and career inventory scores. According to ASCA Mindsets and Behaviors for Student

Success: K-12 College and Career Readiness Standards for Every Student (2014) there is an emphasis on the importance of school counselor’s role in career development for students. These standards guide school counseling programs to help students (a) understand the connection between school and the world of work and (b) plan for and

make a successful transition from school to postsecondary education and/or the world of work and from job to job across the life span (ASCA, 2014).

By promoting social and emotional development, school counselors foster the growth of knowledge, attitudes, and skills necessary for students to become CCR before high school graduation (ASCA, 2014; Gysbers & Henderson, 2014). Yet, school counselors must devote adequate time in this area to create postsecondary options resulting in less time in college, better decision-making skills and career satisfaction

ASCA, 2014). When adhering to Cohen’s guidelines, the results are similar to previous research in that school counseling interventions have a positive effect on students

(Cohen, 1988; Whiston et al., 2011).

Whiston et al. (2011) suggested that students who received school counseling interventions scored nearly one third of a standard deviation higher on various outcomes than students who did not receive school counseling interventions. The overall average weighted ES for school counseling interventions is (d = 0.30) (Whiston et al., 2011).

Including the results of current meta-analysis, these findings address the question of evaluating the impact of school counselor-led SEL interventions on the social-emotional, academic, and behavioral outcomes of students in Grades 6–12, compared to those for students who do not participate in these interventions. To summarize, in this meta- analysis the overall unweighted Cohen’s d effect size (ES) of the school counselor-led interventions was .321 (95% CI [.173, .452]). The ES for overall cognitive outcomes (d

measure was found for standardized achievement test scores (d = 0.612) (Vernez &

Zimmer, 2007).

Effect Sizes for Moderating Variables

Research question 2 examines the program characteristics of school counselor- led, SEL interventions and how they impact the rate of improvement in social-emotional, academic, and behavior outcomes for students in Grades 6–12, as compared to outcomes students in Grades 6–12 who do not participate in school counselor-led SEL interventions. This research focus evaluates the effect of moderating variables as methodological characteristics of research, including program setting related to: (a) grade level (i.e., middle school, high school, and Grades 6–12); (b) the intervention delivery method (i.e., classroom and small group); (c) the length of treatment (i.e., number of weeks); and (d) treatment protocol (i.e., manualized and non-manualized) and its influence on the relationship between the independent and dependent variables (Erford et al., 2010). The moderator analyses posed interesting findings and demonstrated the results of school counselor-led interventions on positive student outcomes.

Grade level. The first research moderator that was explored included the program setting (i.e., middle school, high school, and grades 6–12). The findings indicate that school counselor-led interventions delivered at the middle school level yielded higher ES (d = 0.371) when compared to the impact of school counselor-led interventions delivered in the high school setting (d = 0.214). When comparing the ESs of the grade level setting (i.e., middle or high school setting), interventions delivered at the middle school level yielded a larger effect than at the high school level. The results reported by Whiston et al. (2011) indicated a need for additional school-based inventions

targeted at middle and high school levels. Similarly, the current meta-analysis concludes future studies should focus on student outcomes at the secondary school level. As the role of the school counselor at the middle and high school level are identified, ASCA’s use-of-time assessment determines the amount of time spent towards direct services at these levels and recommends 80 percent or more of the school counselor’s time to direct and indirect services with students (ASCA, 2012).

Intervention delivery type. The next research moderator examined ESs related to the intervention delivery method (i.e., classroom and small group). The results conclude that both classroom (k = 14, d = 0.329) and small group (k = 12, d = 0.321) school counselor-led interventions had small effect and had an adequate numbers of studies (Cohen, 1988). Findings were inconclusive for mixed 6–12 school settings, given that there are less than three studies at that level. The results revealed that classroom (d =

0.329) and small group (d = 0.321) school counselor-led interventions are comparable with medium effect (Cohen, 1988). The intervention delivery type (classroom and small group treatment settings) were compared for all outcomes. Each treatment setting reported significant results and posed similar ESs and the number of studies included in the analysis was comparable (Cohen, 1988). Of the 28 studies examined in current meta- analysis, none reported the effect of school counselor-led interventions on individual interventions.

ASCA recommends school counselors should spend approximately 80 percent or more in direct student services such as classroom and in small groups (ASCA, 2012).

Overall, the results support school counselors spending more time in the classroom and

small group setting. Ultimately, school counselors who are trying to advocate for more direct service time with students must continue to demonstrate their effectiveness.

Length of treatment. The findings evaluated studies (K = 28) of interventions with a span between one and 13+ weeks in length. The results reported length and span for all outcomes, with 13 + weeks of school counselor-led interventions generating the highest ES (k = 3, d = 0.564), as compared to a moderator of 1–4 weeks of school counselor-led intervention, which showed the smallest ES (k = 8, d = 0.073).

Additionally, it was revealed that any treatment length of less than 4 weeks was considered to be non-significant. Interestingly, 5-8 weeks of interventions (k = 11, d =

0.369) and 9-12 weeks of interventions had similar effects (k = 6, d = 0.407). Given these findings, school counselors should consider implementing school counselor-led interventions for a minimum of 5 weeks. Planning classroom interventions followed by small group interventions, as part of a CSCP program, provides students a means of extending their learning and skill practice. For example, SSS classroom followed by SSS small group will ultimately benefit the well-being of the whole student (Brigman et al.,

2007). Thus, these findings suggest the critical need for more access to CSCP and to advocate for school counselors to be in the classrooms.

Most recently, Taylor et al. (2017) synthesized research by conducting a meta- analysis on follow-up effects of school-based SEL interventions (Durlak et al., 2011,

Durlak et al., 2015). Postintervention mean ESs were not signiﬁcant for either positive social behaviors (k = 28, g = .06, 95% CI [-.01, .13]) or conduct problems (k = 30, g =

.07, 95% CI [.00, .14]) (Taylor et al., 2017). Notably, when comparing the meta-analysis conducted by Taylor et al. (2017) to the current meta-analysis, the results conclude

overall ESs for outcome variables are significant when led by a school counselor (Cohen,

1988). Although Taylor et al. (2017) did not assess interventions led by school counselors, the results indicate similarities in variable outcomes. The current study evaluated the ES related to length of treatment as a moderator, as well as the overall ES outcomes.

Treatment protocol. The moderator for ESs related to treatment protocol focused on manualized versus non-manualized interventions, and both categories were compared. The manualized treatment protocol yielded a significantly higher ES (d =

0.427) when compared to the studies that did not use a specific treatment manual for interventions. In fact, manualized treatment protocols overwhelmingly surpassed non- manualized programs in regard to impact on student outcomes, nearly doubling the effect

(d = 0.275). Thus, this finding reinforces the notion that manualized school counselor-led evidence-based interventions yield the highest positive outcomes for students. The finding underscores the need for school counselor educators to develop and conduct research to determine the effectiveness of school counselor-led interventions. Similarly, school counseling practitioners should identify curricula appropriate to address the needs of the students and implement the intervention as designed to achieve maximum impact.

Regardless, evidence-based counseling programs are available for school counselors to delivering them without training or to deliver the program as designed and following the manual. School counseling evidenced-based programs attest to positive impact on student outcomes (Brigman et al., 2007; Villares et al., 2012). Whiston et al. recommended future researchers to articulate curriculum guides or treatment manuals for school counseling interventions (2011). Results from current meta-analysis are

consistent with Whiston et al. (2001) which provides an example of a systematic researched program; SSS and the effectiveness on positive student outcomes (Brigman et al., 2010; Villares et al., 2012).

Overall, the results indicate that there is a significance when school counselors are implementing SEL interventions for middle and high school students. The magnitudes of the overall effects (d= 0.312) were meaningful for the variable outcomes (i.e.; affective, behavioral, cognitive, and executive functioning roles) and moderator analyses (i.e.; school level, intervention delivery type, length of treatment, and treatment protocol)

(Cohen, 1988). Notably, the most significant issue to be observed in the current meta- analysis is the scarcity of school counselor-led SEL outcome-based research. This is a clear indication that it is necessary to conduct additional outcome-based research studies in order to address the gaps in the existing research.

Implications for School Counseling

The results of the current meta-analysis produced several implications for the field of school counseling. Foremost, the results continue to build upon and support the premise that SEL interventions led by certified school counselors are linked to positive student outcomes. Thus, it is the responsibility of school counselors and educators to ensure that students are equipped with the vital skills required for success in and out of school. Although SEL interventions remain at the periphery of the field of education

(Weissberg & Casarino, 2013), the results conclude that student SEL and competencies are linked to positive academic, social, and behavioral outcomes (Durlak et al., 2011;

Whiston et al., 2011).

After interpreting ESs in this study, the findings support the viewpoint that school counselor educators, school counselors, and school counselors-in-training should be the leaders in implementing the delivery of SEL interventions in schools. The ASCA

National Model recommends that school counselors spend 80% of their time delivering direct services to students in the form of a CSCP (2012). This is not an easy undertaking for school counselors; however, by participating in evidence-based research that directly aligns with the ASCA Mindsets and Behaviors for Student Success: K-12 College and

Career Readiness Standards for Every Student (ASCA, 2014), counseling programs can prove their effectiveness through outcomes that promote academic, career, and social/emotional development for all students.

The role of the school counselor needs to be clearly defined in order for CSCPs to be widely received by educational stakeholders. School counselors continue to be a driving force in positive student outcomes and are an essential player in education when it comes to identifying barriers to student success. Thus, as the role of the school counselor continues to evolve in relation to SEL, school counselors are the most appropriate educators in schools for developing SEL competencies (ASCA, 2014; Van

Velsor, 2009). However, further research may be warranted by administrative teams and school districts alike in order to allocate appropriate funding for such programs.

Additionally, by synthesizing data aimed at examining evidence-based outcomes, scholars will continue to bridge the gap in research on the effects of school counselor-led interventions on social-emotional skills and competencies for students. The results from this meta-analysis intend to guide counseling education programs and school districts alike in effectively implementing CSCP into their curriculum for students. Specifically,

classroom (d = 0.329) and small group (d = 0.321) interventions produced the highest

ESs. No individual counseling interventions were reported in the current study.

Interestingly, individual counseling (with regards to scheduling and CCR) frequently takes place at the high school level (ACT, 2012a; ASCA, 2014).

Furthermore, the ASCA Mindsets and Behaviors for Student Success: K-12

College and Career Readiness Standards for Every Student (2014) endorses the growth of knowledge, attitudes, and skills necessary for students to become college and career ready before high school graduation. By promoting social and emotional development, school counselors foster a school culture of CCR (ASCA, 2014; Gysbers & Henderson,

2014). Researchers Dymnicki et al. (2013) affirm that these mindsets and behaviors for students are identified by workforce employers as important for success in the postsecondary settings. Moreover, there is a pressing need for educational leaders to recognize the relationship between social and emotional development and academic goals of students (Johnson & Weiner, 2017). When school counselors are able to incorporate these keys elements into middle and high school counseling programs, students are empowered to achieve postsecondary success (ACT, 2008a; CASEL, 2015).

One of the most tremendous outcomes discovered was the significance of the effect on standardized achievement scores. For instance, a significant ES (d = 0.612) was reported for students who participated in the school counselor-led intervention when compared to their peers who did not participate in the school counselor-led intervention.

In fact, the impact of the standardized achievement score ES was the greatest among all overall and moderating variables, which provides a clear indication of the effectiveness of school counselors and their ability to close the achievement gap. Thus, this finding

will attest to the notion that school counselors possess the ability to help close the achievement gap for middle and high school students. In addition, this meta-analysis resulted in positive ESs for social emotional skills and competence (i.e., self-awareness and self-management) with students at the secondary level (CASEL, 2015; Carey &

Dimmitt, 2012). Nevertheless, the question remains as to how to make changes school district wide. School counselors must continue to work with administrators, school districts, and policy makers to demonstrate their effectiveness on positive student outcomes. Thus, this discourse will bridge the gaps between school counselor-led SEL interventions and the impact on academic achievement and CCR (ACT, 2014; Carey &

Dimmitt, 2012). Furthermore, in alignment with ASCA’s recommendation for the student-to-school counselor ratio (250:1), the results of this meta-analysis demonstrate that school counselors are statistically significant educators, who have the capacity to develop SEL competencies (ASCA, 2014; Van Velsor, 2009). However, often, school counselors are faced with unmanageable caseloads which make it difficult to serve students to full capacity. As such, the current meta-analysis produced data intended to contribute to school counselor literature pertaining to the effectiveness of school counselors on SEL interventions. Thus, this study pushes forward the advocacy agenda and supports the position that more state and federal funding is required to hire, train, and equip school counselors in schools.

Correspondingly, the alarming lack of research on SEL interventions implemented by school counselors has been a perpetual issue in educational research.

This study included an expansive and exhausted search of the literature however the limited number of studies found supports the notion that there continues to be a dearth of

quality outcome research. Nevertheless, it behooves counselor educators and practitioners to develop advocacy efforts in the field of school counseling. By providing research findings and implications, this study serves as a reinforcement for CSCP, and ultimately advocates for growth in the profession of school counseling, while continuing to define and defend the important role of the school counselor.

Limitations

Limitations are a normal part of social science research (Flamez et al., 2017). The following acknowledges the limitations existing in current meta-analysis, plausible explanations for variations of outcomes, and reasons why the limitation is present. First, only interventions that were implemented by school counselors and delivered to students in Grades 6–12 were included. Although this limitation was intentional, restricting the scope of school counseling interventions to middle and high school students is a constraint. When conducting any form of research, collecting a diverse sample population can be difficult (Lipsey & Wilson, 2001; Flamez et al., 2017). As previously discussed, numerous studies (k = 412, 18.86%) failed to report the ethnicities of their sample. It is critical for counseling researchers to attempt to account for all relevant data when reporting program design and protocols (Erford et al., 2010; Lipsey, 2003). In the current meta-analysis, every effort was made to gather missing data and to reach out to authors for supplementary explanations; however, the majority of authors did not respond to the requests for additional information. Furthermore, the number of studies was less than desirable (i.e., N = 28), which lends credence to the notion that more evidence-based research must take precedence to yield comprehensive outcomes. Throughout this meta- analytic process, a large portion of the excluded studies involved SEL intervention;

however, these studies did not utilize the school counselor in the delivery. Therefore, expanding the inclusion criteria to include both teachers and school counselors could have generated additional studies.

In a quest to only include relevant and up-to-date outcome research, each study must have been reported in English between 2005 and 2017. Previous meta-analyses casted a wider net of time; however, this study focused on a twelve-year span to coincide with the release of the ASCA National Model, which calls for the use of evidence-based interventions as part of CSCPs (ASCA, 2012). In addition, the accumulated research exclusively evaluated student outcomes; other possibilities could include outcomes related to district policies, administrative input, teacher perspective, and parental concerns. Nevertheless, the interventions varied from each study, which accounts for the need of moderator analyses. Finally, the inclusion criteria for this study was restricted to counseling journal publications and published/unpublished dissertations due to the nature of the research questions investigated. Despite these shortcomings, the focus on school counselor-led SEL interventions for middle and high school students is imperative and provides support for the school counselor’s role in positive student outcomes.

Future Directions

The findings from this meta-analysis suggest that additional research is undeniably required for the field of school counseling. Specifically, there is a need for research designs aligning with the ASCA National Model (2012). When school counselors implement the ASCA National Model (2012) to deliver CSCPs, as well as collect student data demonstrating gains in academic, career, and personal/social development standards, the argument for further developing the school counseling

profession is strengthened. Likewise, future research agendas should focus on how the

CSCP framework incorporates four components of the ASCA National Model: (a) foundation; (b) management; (c) delivery; and (d) accountability (ASCA, 2012). To achieve maximum program effectiveness, ASCA (2012) advocates for a school counselor-to-student ratio of 1:250. In addition, the National Model indicates that school counselors should focus their skills and energy toward dedicating 80 percent or more of their time and direct and indirect services to students (ASCA, 2012). It is easy to imagine the potential for positive student outcomes that would ensue if policy makers, school districts, and administrators allowed for school counselors to focus on delivering effective programs. School counselors must implement evidence-based interventions in order to remain an essential component of the educational process (Villares et al., 2012).

Another important recommendation pertains to advocacy for the profession of school counseling and the unique training of counselors as experts in implementing programs that focus on students’ social-emotional well-being. For this meta-analysis, the bulk of research that did not meet inclusion criteria was due in part to the school counselor-led component. By and large, when SEL initiatives are delivered by teachers, it takes away from the academic content and subject areas that they have been trained to teach (Bridgeland et al., 2013). Future researchers must demonstrate that school counselors are vital members of the educational team, thus promoting the skills of leadership, advocacy, and collaboration in order to create systemic change, as appropriate

(ASCA, 2012).

Furthermore, future research directions should place an emphasis on how manualized intervention protocols produce positive outcomes on students’ affective,

behavioral, cognitive, and effective role functioning outcomes. By developing research agendas that focus specifically on the school counselor’s role in the delivery of evidence- based SEL interventions, the results will bring light to the positive correlation between

SEL intervention and student outcomes. In addition, researchers need to address the hurdles encountered in regard to district policies that may prevent outcome research studies that prove more difficult to conduct.

Although this meta-analysis has significance, the low number of quality studies is alarming. This begs the question—are researchers receiving adequate training in counselor education programs to conduct this outcome based-research? Questions emerge in regard to the rigor of studies, as well as the issue of whether school counselors are motivated to become good stewards of research by participating in outcome research studies. Additionally, future researchers may want to examine the pressure that school counselor educators are faced with in earning promotion and tenure professionally. As pressure to secure tenure grows, counselor educators may avoid conducting more challenging studies due to the level of difficulty and time constraints. Moreover, an investigation is warranted on funding issues for large scale educational research designs.

Thus, creating motive for the support of policy makers in SEL outcome research conducted in schools and should be further explored.

Finally, counselor educators must not only adequately prepare graduate students to become effective school counselors but must encourage graduate students to advocate for the profession. Thus, this instruction will prompt broader involvement among practicing school counselors and will instill within recent graduates a shared commitment to conducting research (Whiston, 2002). From a school counselor practitioner standpoint,

if there is participation at the school level, then school counselors will be in a better position to advocate for their time in the classroom and small groups.

Summary

This meta-analysis attempted to respond to several important issues in the field of school counseling. The presence of three reoccurring themes throughout the collection of research were as follows. The first theme puts a spotlight on the critical need for outcome research in school counseling, with research specifically aimed at the SEL needs of twenty-first century secondary student. The second theme promotes the notion that evidence-based SEL interventions (with proven positive outcomes) should be further targeted toward middle and high school students. And finally, the third theme recognizes the evolving role of school counselors across the United States and links their efforts to improved student outcomes.

The purpose of this meta-analysis was to investigate two questions of interest specific to the field of school counseling. The first question explored the effectiveness of school counselor-led, SEL interventions in improving the social-emotional, academic, and behavioral outcomes of students in Grades 6–12, as compared to outcomes for students in Grades 6–12 who do not participate in these interventions. This question addressed important influences, which determined the sample of studies to be included in the current meta-analysis. The second question examined the impact of school counselor-led, SEL intervention program characteristics on the social-emotional, academic, and behavioral outcomes for students in Grades 6–12, as compared to outcomes for students in Grades 6–12 who do not participate. This question explored the potential effect of moderating variables described as methodological characteristics of

research (i.e., program characteristics, type of measure, level, and length), as well as the influence of the relationship between the independent and dependent variables.

Overall, there is much less research on school counselor-led interventions for middle and high school students than is available at the elementary level (Whiston et al.,

2011). After conducting a comprehensive meta-analysis, the conclusions demonstrate that there is an insufficient amount of outcome-based research connecting school counselors to positive student outcomes. However, this meta-analysis illuminated additional benefits for schools, school counselors, students, and counselor educators. By examining studies that met the inclusion criteria, affective, behavioral, cognitive, and effective role function measures observed differences between students who participated in the treatment group, and received the school counselor-led intervention, and students in the control or comparison groups, who did not receive the school counselor-led interventions. In conclusion, the current meta-analysis examined 28 outcome-based studies specific to school counseling interventions at the secondary level, and yielded effects that were significant (Cohen, 1988) and important to the field of school counseling research.

REFERENCES

“References marked with an askerisk indicates studies included in meta-anaylsis.” (APA

Publication Manual, 5th ed., section 4.05, p. 222).

Achieve (2013, February). Implementing the Common Core State Standards: The role of

the school counselor. Retrieved from

http://www.achieve.org/files/RevisedCounselorActionBrief_Final_Feb.pdf

ACT. (2008a). Enhancing college and career readiness and success: The role of

academic behaviors. Retrieved from

http://www.act.org/engage/pdf/ENGAGE_Issue_Brief.pdf

ACT. (2008b). The forgotten middle: Ensuring that all students are on target for college

and career readiness before high school. Retrieved from

https://www.act.org/research/policymakers/pdf/ForgottenMiddle.pdf

ACT. (2012a). Catching up to college and career readiness. Retrieved from

http://www.act.org/research/policymakers/pdf/CatchingUpToCCR.pdf

ACT. (2012b). Rising to the challenge of college and career readiness: A framework for

effective practices. Retrieved from

http://www.act.org/research/policymakers/pdf/RisingToChallenge.pdf

ACT. (2014). Broadening the definition of college and career readiness: A holistic

approach. Retrieved from http://www.act.org/research/

researchers/reports/pdf/ACT_RR2014-5.pdf

American Psychological Association (2010). Publication manual of the American

Psychological Association (6th ed.). Washington, DC: Author.

American School Counselor Association (2004). ASCA national standards for

students. Alexandria, VA: Author.

American School Counselor Association (2012). The ASCA National Model: A

framework for school counseling programs (3rd ed.). Alexandria, VA: Author.

American School Counselor Association (2014). ASCA mindsets and behaviors for

student success: K-12 college- and career-readiness standards for every student.

Alexandria, VA: Author.

American School Counselor Association. (2016). ASCA ethical standards for school

counselors. Retrieved from

https://www.schoolcounselor.org/asca/media/asca/Ethics/EthicalStandards2016.p

Association for Middle Level Education. (2010). This we believe: Keys to educating

young adolescents. Westerville, Ohio: Author.

*Austin, D.D.M. (2011). Effect of a counseling intervention program on tenth grade

students’ attendance, discipline referrals, and academic achievement. Walden

University. ProQuest Dissertations Publishing, 2013. 3552680.

Bandura, A. (2006). Adolescent development from an agentic perspective. In F. Pajares

& T. Urdan (Eds.), Self-efficacy beliefs of adolescents (pp. 307–337). Charlotte,

*Bennett, M. (2008). Take a stand against bullying: Evaluation of the efficacy of a school

wide program for middle school Students. Retrieved from ProQuest Dissertations

& Theses Global.

Blad, E. (2017). Social-emotional learning; ‘Ready to lead: A national principal

survey on how social and emotional learning can prepare children and transforms

school’. Education Week (14).

*Blackburn, S.S. (2007). Social constructivist counseling groups as a means to affect

school performance and behaviors in middle school student reading below grade

level. St. Louis, Missouri. School of the University of Missouri.

*Bowers, H., Lemberger, M. E., Jones, M.H., & Rogers, J. E. (2015). The influence of

repeated exposure to the Student Success Skills program on middle school

students' feelings of connectedness, behavioral and metacognitive skills, and

reading achievement. Journal for Specialists in Group Work, 40(4), 344-364.

Brace, N., Kemp, R. & Snelgar, R. (2016). IBM SPSS for psychologist and everybody

else (6th Edition) New York, NY: Psychology Press.

Bridgeland, J., Bruce, M., & Hariharan, A. (2013). The missing piece: A national survey

on how social and emotional learning can empower children and transform

schools. Washington, DC: Civic Enterprises.

Brigman, G. & Campbell, C. (2003). Helping students improve academic achievement

and school success behavior. Professional School Counseling, 7, 91-98.

Brigman, G., Campbell, C, & Webb, L. (2010). Student Success Skills: Group

Counseling Manual (3rd ed.). Boca Raton, FL: Atlantic Education

Consultant

Brigman, G., & Webb, L. (2016). Student Success Skills: Classroom manual. Boca

Raton, FL: Atlantic Education Consultants.

Brigman, G., Webb, L., & Campbell, C. (2007). Building skills for school success:

Improving the academic and social competence of students. Professional School

Counseling, 10(3), 279–288. doi:10.1080/01933920701227257

*Brougham, L., & Kashubeck-West, S. (2017). Impact of a growth mindset intervention

on academic performance of students at two urban high schools. Professional

School Counseling, (1), doi:10.1177/2156759X18764934

Brown, D., & Trusty, J. (2005). School counselors, comprehensive school counseling

programs and academic achievement: Are school counselors promising more than

they can deliver? Professional School Counseling, 9, 1-8.

Campbell, C., & Brigman, G. (2005). Closing the achievement gap: A structured

approach to group counseling. Journal for Specialists in Group Work, 30, 67-82.

Campbell Collaboration. (2001). Campbell systematic reviews: Guidelines for the

preparation of review protocols. Retrieved from

http://www.campbellcollaboration.org/artman2/uploads/1/C2_Protocols_guideline

s.pdf

Carey, J. C., & Dimmitt, C. (2006). Resources for school counselors and counselor

educators: The Center for School Counseling Outcome Research.

Professional School Counseling, 9, 416-420.

Carey, J., & Dimmitt, C. (2012). School counseling and student outcomes: Summary of

six statewide studies. Professional School Counseling, 16(2), 146-153. doi:

10.5330/PSC.n.2012-16.146

Carey, J. C., Dimmitt, C., Hatch, T. A., Lapan, R. T., & Whiston, S. A. (2008). Report of

the national panel for evidence-based school counseling: Outcome research

coding protocol and evaluation of Student Success Skills and Second Step.

Professional School Counseling, 11(3), 197–206. doi:10.5330/PSC.n.2010-11.197

Carey, J. C., & Martin, I. (2015). A review of the major school counseling policy studies

in the United States: 2000-2014. Amherst, MA: The Ronald H. Fredrickson

Center for School Counseling Outcome Research and Evaluation.

Cervone, B.; & Cushman. K. (2016). Belonging and becoming: the power of social and

emotional learning in high schools. Harvard Education Press, 2015

*Christian, D. D. (2013). Adventure based counseling: Exploring the impact of ABC on

adaptive functioning in high school males. University of North Texas.

Coe, Robert, (2002). It's the effect size, stupid. What effect size is and why it is

important. British Educational Research Association, School of Education,

University of Durham. Retrieved from

https://www.leeds.ac.uk/educol/documents/00002182.htm

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.).

Hillsdale, N J: Erlbaum.

Collaborative for Academic, Social, and Emotional Learning. (2003). Safe and

sound: An educational leader's guide to evidence-based social and

emotional learning (SEL) programs. Chicago, IL: Author.

Collaborative for Academic, Social, and Emotional Learning. (2015). CASEL guide:

Effective social and emotional learning programs—middle and high school

edition. Chicago, IL: Author. Retrieved from http://www.casel.org/middle-and-

high-school-edition-casel-guide/

100

College Board. (2010). Eight components of college and career readiness counseling.

Retrieved from http:// secure-

media.collegeboard.org/digitalServices/pdf/nosca/11b_4416_8_Components_WE

B_111107.pdf

College Board Advocacy & Policy Center (2011). The college completion report 2011

progress report. New York, NY: Author.

Collins, T. P. (2014). Addressing mental health needs in our schools: Supporting the role

of school counselors. The Professional Counselor, 4(5), 413.

*Connell, M. (2014) Modifying academic performance using online grade book

review during solution-focused brief therapy. Retrieved from ProQuest

Dissertations & Theses Global.

Conley, D. (2007). Toward a more comprehensive conception of college readiness.

Eugene OR: Educational Policy Improvement Center.

*Conyers. R.E.D. (2005). The effects of group counseling compared with individual

counseling in the reduction of at-risk behaviors using grade point average,

discipline referrals, and attendance among sixth grade black males. Retrieved

from ProQuest Dissertations & Theses Global. UMI Number: 3361383

Dahir, C. A. (2004). Supporting a nation of learners: The role of school counseling in

educational reform. Journal of Counseling & Development, 82, 344-353.

Dahir, C. A., & Stone, C. B. (2009). School counselor accountability: The path to social

justice and systemic change. Journal of Counseling & Development, 87, 12–20.

doi:10.1002/j.1556-6678.2009. tb00544.x

101

Dimmitt, C., Carey J., & Hatch T. (2007). Evidence-based school counseling: Making a

difference with data-driven practices. Thousand Oaks, CA: Corwin Press.

Domitrovich, C.E., Syvertsen, A. K. & Calin, S. S. (2017). Promoting social and

emotional learning in the middle and high school years. Edna Bennett Pierce

Prevention Research Center, Pennsylvania State University.

Durlak, J. A., Domitrovich, C. E., Weissberg, R. P., Gullotta, T. P., Darling Hammond,

L., Shriver, T. P, Goldman, D. (Eds.). (2015). Handbook of social and emotional

learning: Research and practice (1st ed.). New York, NY: The Guilford Press.

Durlak, J. A., & Weissberg, R. P. (2011). Promoting social and emotional development

is an essential part of students' education. Human Development, 54(1), 1-3.

doi:10.1159/000324337

Durlak, J. A., Weissberg, R. P., Dymnicki, A. B., Taylor, R. D., & Schellinger, K.

B. (2011). The impact of enhancing students’ social and emotional learning: A

meta‐ analysis of school‐ based universal interventions. Child Development,

82(1), 405-432. doi:10.1111/j.1467-8624. 2010.01564.x

Dymnicki, A., Sambolt, M., & Kidron, Y. (2013). Improving college and career

readiness by incorporating social and emotional learning. Washington DC:

American Institutes for Research College & Career Readiness and Success

Center.

Educational Policy Improvement Center (2012). A complete definition of college and

career readiness. Retrieved from ERIC database. (ED537876)

Elias, M. J., & Hatzichristou, C. (2016). Special issue: SEL training, intervention and

research worldwide. International Journal of Emotional Education, 8(2), 1.

102

Elias, M. J., Zins, J. E., Graczyk, P. A., & Weissberg, R. P. (2003). Implementation,

sustainability, and scaling up of social-emotional and academic innovations in

public schools. School Psychology Review, 32(3).

Erford, B., Savin-Murphy, J., & Butler, C., (2010). Conducting a meta-analysis of

counseling outcome research: Twelve steps and practical procedures. Counseling

Outcome Research and Evaluation, 1(1) 19- 43.

Erikson, E. (1968). Identity: Youth and crisis. New York: W.W. Norton.

Every Student Succeeds Act. , Pub. L. No. 114-95, 114 Stat. 1177 (2015- 2016).

*Falco, L.D. (2008). “Skill-Builders”: Enhancing middle school students’ self-efficacy

and adaptive learning strategies in mathematics. The University of Arizona.

Retrieved from ProQuest Dissertations & Theses Global. UMI Number: 3303631

*Falco, L.D., Hugh, C., & Sheri, B. (2008). Skill-Builders: Improving middle school

students' self-beliefs for learning mathematics. Professional School Counseling,

(4), 229

Farrington, C. A., Roderick, M., Allensworth, E., Nagaoka, J., Keyes, T. S., Johnson, D.

W., & Beechum, N. O. (2012). Teaching adolescents to become learners. The

role of noncognitive factors in shaping school performance: A critical literature

review. Chicago: University of Chicago Consortium on Chicago School Research.

Flamez, B., Lenz, S.A., Balkin, R.S., & Smith, R.L., (2017). A counselors guide to the

dissertation process. Where to start & how to finish. Alexandria, VA: American

Counseling Association.

103

*Froeschle, J.G., Smith, R.L., & Ricard, R., (2007). The efficacy of a systematic

substance abuse program for adolescent females. Professional School Counseling,

(5), 498.

*Freiden, J. (2005). GAME: A clinical intervention to reduce adolescent violence in

schools. Memphis, Tennessee. The University of Memphis.

Greenberg, M. T., Domitrovich, C. E., Weissberg, R. R., & Durlak, J. A. (2017). Social

and emotional learning as a public health approach to education. Future of

Children, 27(1), 13-32.

Greenberg, M. T., Weissberg, R. P., O'Brien, M. U., Zins, J. E., Fredericks, L., Resnik,

H., & Elias, M. J. (2003). Enhancing school-based prevention and youth

development through coordinated social, emotional, and academic learning.

American Psychologist, 58(6-7), 466-474. doi:10.1037/0003066X.58.6-7.466

Gysbers, N. C. (2004). Comprehensive guidance and counseling programs: The evolution

of accountability. Professional School Counseling, 8, 1-14

Gysbers, N. C., & Henderson, P. (2014). Developing and managing your school guidance

and counseling program. Hoboken, NJ: Wiley.

Hatch, T. & Owen, L. (2014). White House college opportunity agenda: Strengthening

the school counseling profession through the First Lady’s reach higher initiative.

Retrieved from http://www.rcoe.us/leadership-institute/files/2014/09/Equity-

Conference-RCOE-9-25-14-Final.pdf

Hattie, J., Biggs, J., & Purdie, N. (1996). Effects of learning skills interventions on

student learning: A meta-analysis. Review of Educational Research, 66(2), 99-

136. doi:10.2307/1170605

104

Hedges, L.V., & Olkin, I. (1985). Statistical methods for meta-analysis. Orlando, FL:

Academic Press.

Hill, C. J., Bloom, H. S., Black, A. R., & Lipsey, M. W. (2008). Empirical benchmarks

for interpreting effect sizes in research. Child Development Perspectives, 2(3),

172-177.

*Hunter, M. (2005). The effects of a peer tutoring and group counseling program on

academic achievement and behavior of at-risk junior high males. Auburn,

Alabama. Auburn University.

Johnson, H. & Weiner, R. (2017). This time, with feeling: Integrating social and

emotional development and college- and career-readiness standards. New York:

Aspen Institute.

Lapan, R. (2012). Comprehensive school counseling programs: In some schools for

some students but not in all schools for all students. Professional School

Counseling,16(2), 84-88.

Lapan, R. T., Gysbers, N. C., & Sun, Y. (1997). The impact of more fully

implemented guidance programs on the school experiences of high school

students: A statewide evaluation study. Journal of Counseling and Development,

75, 292-302.

*Lemberger, M. E., Selig, J. P., Bowers, H., & Rogers, J. E. (2015). Effects of the

Student Success Skills program on executive functioning skills, feelings of

connectedness, and academic achievement in a predominantly Hispanic, low‐

income middle school district. Journal of Counseling & Development, 93(1), 25-

37. doi:10.1002/j.1556-6676. 2015.00178.x

105

León, A., Villares, E., Brigman, G., Webb, L., & Peluso, P. (2011). Closing the

achievement gap of Latina/o students: A school counseling response. Counseling

Outcome Research and Evaluation, 2, 73–86. doi:10.1177/215013781140073

Lipsey, M. W. (2003). Those confounded moderators in meta-analysis: Good, bad, and

ugly. Annals of the American Academy of Political and Social Science, 587, 69-

81.

Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. Thousand Oaks,

Calif.: Sage Publications, c2001.

Littell, J. H., Corcoran J., & Pillai, V. (2008). Systematic reviews and meta-analysis.

New York: Oxford.

*Loos, L.A. (2008). Career education: Addressing career indecision and career

decision in middle school students. Capella University. Retrieved from ProQuest

Dissertations & Theses Global. UMI Number: 3324725

*Macey, A. (2011). Effects of a group counseling career intervention on the hopefulness

and future orientation of at-risk middle school students. Retrieved from ProQuest

Dissertations & Theses Global.

Makel, M. C., & Plucker, J. A. (2014). Facts are more important than novelty:

Replication in the education sciences. Educational Researcher, 43(6), 304-316.

doi:10.3102/0013189X14545513

*Martinez, R.R. (2015). Effects of a school guidance curriculum on postsecondary

education going literacy, postsecondary education going access aspirations, and

career and college readiness self efficacy. Retrieved from ProQuest Dissertations

& Theses Global.

106

McGannon, W., Carey, J., & Dimmitt, C. (2005). The current status of school

counseling outcome research. Center School Counseling Research Monograph, 2,

1–30.

*Mclaughlin, L.P. (2009). The effect of cognitive behavioral therapy and cognitive

behavioral therapy plus media on the reduction of bullying and victimization and

the increase of empathy and bystander response in a bullying prevention program

for urban sixth-grade students. The University of Toledo. Retrieved from

ProQuest Dissertations & Theses Global. UMI Number: 3364312

McMahon, G., Mason E. C. M., and Paisley, P.O., (2009). School counselor

educators as educational leaders promoting systemic change. Professional School

Counseling, (2), 116.

Nagaoka, J., Farrington, C. A., Ehrlich, S. B., Johnson, D. W., Dickson, S., Heath, R., &

Mayo, A. (2014). A framework for developing young adult success in the 21st

century. Chicago: University of Chicago Consortium on Chicago School

Research.

National Research Council. (2012). Education for life and work: Developing transferable

knowledge and skills in the 21st century. Committee on Defining Deeper Learning

and 21st Century Skills, J. W. Pellegrino & M. L. Hilton (Eds). Board on Testing

and Assessment and Board on Science Education, Division of Behavioral and

Social Sciences and Education. Washington, DC: The National Academies Press.

*Nota, L., Santilli, S., & Soresi, S. (2016). A life-design-based online career

intervention for early adolescents: Description and initial analysis. Career

Development Quarterly, 64(1), 4-19. doi:10.1002/cdq.12037

107

Payton, J., Weissberg, R. P., Durlak, J. A., Dymnick, A. B., Taylor, R. D., Schellinger, K.

B., & Pachan, M. (2008). The positive impact of social and emotional learning for

kindergarten to eighth-grade students: Findings from three scientific reviews.

Chicago, IL: Collaborative for Academic, Social, and Emotional Learning.

Pellegrino, J.W., & Hilton, M. L. (2012). Education for life and work: Developing

transferable knowledge and skills in the 21st century. Washington, DC: The

National Academies Press.

*Poyton,T.A., Carlson, M.W., Hopper, J.A., & Carey, J. C., (2006). Evaluation of an

innovative approach to improving middle school students' academic achievement.

Professional School Counseling, (3), 190.

*Reeder, S.D. (2011). Choice Theory: An investigation of the treatment effects of a

Choice Theory protocol on students identified as having a behavioral or

emotional disability on measures of anxiety, depression, locus of control and self

esteem. University of North Carolina at Charlotte. Retrieved from ProQuest

Dissertations & Theses Global. UMI Number: 3457935

*Renda, M. R., & Brigman, G. D. (2014). The effect of a student achievement curriculum

on grade 9 completion rate and student engagement. Florida Atlantic University.

*Ricard, R. J., Lerma, E., & Heard, C. C. (2013). Piloting a Dialectical Behavioral

Therapy (DBT) infused skills group in a disciplinary alternative education

program (DAEP). Journal for Specialists In Group Work, 38(4), 285-306.

doi:10.1080/01933922.2013.834402

Rosenthal, R. (1979). The file drawer problem and tolerance for null results.

Psychological Bulletin, 86, 638–641. doi:10.1037//0033– 2909.86.3.638

108

Roosevelt, Franklin D. (September 20, 1940.) Address at University of Pennsylvania.

*Shen, Y. (2007). Developmental model using gestalt-play versus cognitive-verbal

group with Chinese adolescents: effects on strengths and adjustment

enhancement. Journal For Specialists In Group Work, 32(3), 285-305.

Sink, C. A. (2009). School counselors as accountability leaders: Another call for action.

Professional School Counseling, 13, 68–74.

Sink, C. A., & Stroh, H. R. (2006). Practical significance: The use of effect sizes in

school counseling research. Professional School Counseling, (5), 401.

Sklad, M., Diekstra, R., Ritter, M. D., Ben, J., & Gravesteijn, C. (2012). Effectiveness of

school‐ based universal social, emotional, and behavioral programs: Do they

enhance students’ development in the area of skill, behavior, and adjustment?

Psychology in the Schools, 49(9), 892-909. doi:10.1002/pits.21641

Sperry, L. (2016). Mental health and mental disorders: An encyclopedia of conditions,

treatments, and well-being [3 Volumes]. Santa Barbara, California: Greenwood.

Taylor, R. D., Oberle, E., Durlak, J. A., & Weissberg, R. P. (2017). Promoting positive

youth development through school-based social and emotional learning

interventions: A meta-analysis of follow-up effects. Child Development, (4),

1156. doi:10.1111/cdev.12864

*Urbina, I. (2011). Effects of student participation in the cultural Spanish translation of

the Student Success Skills program on high school student achievement. Boca

Raton, Fla.: Florida Atlantic University

Urbina, I., Villares, E., & Mariani, M. (2017). Examining the efficacy of the Spanish

cultural translation of the Student Success Skills program to improve academic

109

achievement. Journal of Humanistic Counseling, (2). 127.

doi:10.1002/johc.12048.

U.S. Department of Education. (2018). Office of Academic Improvement. High school

graduation initiative also known as school dropout prevention program.

Retrieved from https://www2.ed.gov/programs/dropout/index.html

Van Velsor, P. (2009). School counselors as social-emotional learning consultants:

Where do we begin? Professional School Counseling, 13(1), 50-58.

doi:10.5330/PSC.n.2010-13.50

Vernez, G., & Zimmer, R. (2007). Interpreting the effects of Title 1 supplemental

educational services. Retrieved September 13, 2018, from

https://www2.ed.gov/rschstat/eval/choice/.../achievementanalysis-sizes.pdf

Vernon, A. (2009). Counseling children and adolescents (4th ed.). Colorado: Love

Publishing Company.

Villares, E., Colvin, K., Carey, J., Webb, L., Brigman, G., & Harrington, K. (2014). The

convergent and divergent validity of the Student Engagement in School Success

Skills Survey. The Professional Counselor, 4, 541–553. doi:10.15241/ev.4.5.541

Villares, E., & Dimmitt, C. (2017). Updating the school counseling research agenda: A

Delphi study. Counselor Education and Supervision, (3), 177.

doi:10.1002/ceas.12071

Villares, E., Frain, M., Brigman, G., Webb, L., & Peluso, P. (2012). The impact of

Student Success Skills on standardized test scores: A meta-analysis. Counseling

Outcome Research and Evaluation, 3(3), 1–16. doi:10.1177/2150137811434041

110

Webb, L., & Brigman, G. (2006). Student Success Skills: Tools and strategies for

improved academic and social outcomes. Professional School Counseling, 10,

112–120. doi:10.5330/prsc.10.2.9612807w81q8v374

Webb, L. D., Brigman, G. A., & Campbell, C. (2005). Linking school counselors and

student success: A replication of the Student Success Skills approach targeting the

academic and social competence of students. Professional School Counseling, 8,

407-413.

Webb, L., Brigman, G., Carey, J., & Villares, E. (2011). A randomized controlled trial of

Student Success Skills: A program to improve academic achievement for all

students (Education Research Grant 84.305A). Institute of Education Sciences,

U.S. Department of Education. Unpublished.

*Weinstein, J. (2013). The effect of the Student Success Skills small group counseling

Interventions of factors associated with dropout potential in high school. Boca

Raton, Fl. Florida Atlantic University.

Weissberg, R. P. & Cascarino, J. (2013). Academic learning + social-emotional learning

= national priority. Phi Delta Kappan, 95(2): 8-13.

Weissberg, R. P., Durlak, J. A., Domitrovich, C. E., & Gullotta, T. P. (2015). Social and

emotional learning: Past, present, and future. In J. A. Durlak, C. E. Domitrovich,

R. P. Weissberg, & T. P. Gullotta (Eds.), Handbook of social and emotional

learning: Research and practice (pp. 3–19). New York, NY: Guilford.

Weissberg, R. P., Resnik, H., Payton, J., & O'Brien, M. U. (2003). Evaluating social and

emotional learning programs. Alexandria: Association for Supervision and

Curriculum Development.

111

White, S. W., & Kelly, F. D. (2010). The school counselor’s role in school dropout

prevention. Journal of Counseling & Development,88, 227–235.

doi:10.1002/j.1556-6678.2010.tb00014.x

Whiston, S. C. (2002). Response to the past, present, and future of school counseling:

Raising some issues. Professional School Counseling, 5(3), 148-155.

Whiston, S. C., & Li, P. (2011). Meta-analysis: a systematic method for synthesizing

counseling research. Journal of Counseling and Development, (3), 273.

Whiston, S. C., & Quinby, R. F. (2009). Review of school counseling outcome research.

Psychology in The Schools, 46(3), 267-272.

Whiston, S. C., Tai, W. L., Rahardja, D., & Eder, K. (2011). School counseling outcome:

A meta-analytic examination of interventions. Journal of Counseling and

Development, 89(1), 37-55. Retrieved from

http://link.galegroup.com.ezproxy.fau.edu/apps/doc/A248092369/ITOF?u=gale15

691&sid=ITOF&xid=8d6c8854

*Winters, K. C., Fahnhorst, T., Botzet, A., Lee, S., & Lalone, B. (2012). Regular article:

Brief intervention for drug-abusing adolescents in a school setting: Outcomes and

mediating factors. Journal of Substance Abuse Treatment, 42279-288.

doi:10.1016/j.jsat.2011.08.005

*Wisinger, S. (2010). The effects of two anxiety reducing interventions for algebra I

test scores for a samples of rural high school students. Retrieved from ProQuest

Dissertations & Theses Global.

Yeager, D. S. (2017). Social and emotional learning programs for adolescents. Future of

Children, 27(1), 73-94.

112

Zins, J. E., Bloodworth, M. R., Weissberg, R. P., & Walberg, H. J. (2007). The scientific

base linking social and emotional learning to school success. Journal of

Educational and Psychological Consultation, 17(2), 191-210.

doi:10.1080/10474410701413145

Zins, J. E., & Elias, M. J. (2007). Social and emotional learning: Promoting the

development of all students. Journal of Educational and Psychological

Consultation, 17(2), 233-255. doi:10.1080/10474410701413152

Zins, J. E., Weissberg, R. P., Wang, M. C., & Walberg, H. J. (2004). Building academic

success on school social and emotional learning: What does the research say?

New York: Teachers College Press.

113