Abstract
Despite the prevalence and negative consequences of depressive disorders among youth, as well as the need for schools to adopt and implement a continuum of mental health services to address depressive disorders, school mental health providers receive very limited guidance in the selection and application of appropriate evidence-based depression prevention and intervention programs for use within a school-based multi-tiered system of support (MTSS). With the goal of supporting school-based mental health providers in the delivery of evidence-based practices targeting depressive symptoms among youth within a MTSS framework, the following study sought to conduct a critical review of the existing school-based prevention and intervention programming for depressive disorders for youth. A systematic, four-stage review was performed from which 119 studies examining 57 unique programs were identified. A review of the studies, including presentation of various participant (e.g., age, grade, ethnicity), study (e.g., control group, randomization), and program (e.g., primary focus, findings, MTSS tier) characteristics, is included. Implementation considerations review and future directions for research are discussed.
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Introduction
Depressive disorders, which are characterized by symptoms including depressed mood, irritability, anhedonia, loss of energy, feelings of guilt, and difficulty concentrating (American Psychiatric Association, 2013), are experienced by a large number of youth (Behavioral Health Statistics and Quality, 2015). Specifically, up to 20% of youth will experience a depressive disorder by the age of 18 and 65% will experience less severe depressive symptoms (Costello, Mustillo, Erkanli, Keeler, & Angold, 2003; Lewinsohn, Hops, Roberts, Seeley, & Andrews, 1993). Starting in adolescence females are diagnosed with depression at a rate of 2 to 1 compared to males (Galambos, Leadbeater, & Barker, 2004), a disparity which persists through adulthood (Hankin & Abramson, 2001). Childhood depression has numerous negative consequences for youth, including increased risk of drug use, poor academic outcomes, negative interpersonal relationships, and physical health problems (Birmaher et al., 1996; Gould et al., 1998; Kessler et al., 2001). Further, childhood depression places youth at a greater risk of future depressive disorders in adulthood (Rohde, Lewinsohn, & Seeley, 1994). Thus, due to their high prevalence and negative impact on youth functioning, prevention of and treatment for childhood depressive disorders is crucial (Kazdin & Weisz, 1998).
School-Based Prevention and Treatment of Depression
Schools have been underscored as the ideal setting to support the delivery of depression prevention (Werner-Seidler, Perry, Calear, Newby, & Christensen, 2017) and intervention services (Stark, Arora, & Funk, 2011). The delivery of school-based mental health (SBMH) interventions often permits increased access to teacher and parents as sources of input and targets of intervention, as well as an opportunity for providers to observe problem behaviors in a naturalistic setting. Further, SBMH services are also believed to reduce typical barriers associated with accessing mental health services (e.g., time, cost; Stephan, Weist, Kataoka, Adelsheim, & Mills, 2007). Several efforts to evaluate the effectiveness of school-based interventions for youth with internalizing symptoms have been undertaken (Stark, Streusand, Arora, & Patel, 2011) and many have stressed the role of SBMH providers (e.g., school psychologists, school social workers) in preventing and addressing depressive symptoms among youth (Herman, Merrell, Reinke, & Tucker, 2004; Lyon, Jacobs, Briggs, Cheng, & Wang, 2014). However, despite the prevalence and negative consequences of depressive disorders, the delivery of school-based interventions for depressive disorders has lagged behind those for others disorders (i.e., externalizing disorders; McIntosh, Ty, & Miller, 2014). Indeed, students with depressive disorders remain under-referred and underrepresented in SBMH services (Bradshaw, Buckley, & Ialongo, 2008; Kauffman, 2001). Accordingly, researchers and policymakers have stressed the need for schools to adopt and implement a continuum of SBMH services to address depressive disorders among youth (Doll & Cummings, 2008; Stark, Arora, & Funk, 2011; Stark, Streusand, Arora, & Patel, 2011).
Multi-tiered Systems of Support and Depression
A multi-tiered system of support (MTSS), a population-based approach to prevention in schools which draws heavily on public health and prevention science models (Weist, Lever, Bradshaw, & Owens, 2014), involves the delivery of evidence-based services along a continuum (Jimerson, Burns, & VanDerHeyden, 2015). Universal, or Tier 1, services are implemented with the goal of preventing mental health concerns which might serve as a barrier to academic achievement Jimerson et al., 2015). Tier 2, or selective, services are delivered with the goal of remediating students at risk for mental health concerns, while Tier 3, or indicated or intensive, services are implemented with the goal of treating youth with the highest level of mental health need (Jimerson et al., 2015).
A long line of research has provided support for the use of the MTSS framework as a model of service delivery in addressing academic (VanDerHeyden, Witt, & Gilbertson, 2007) and behavioral (Bradshaw et al., 2008) concerns among youth in schools. However, only limited guidance in the application of a MTSS framework for addressing internalizing disorders generally (McIntosh et al., 2014), and depression in particular (Herman et al., 2004), has been available. Initial efforts have sought to address this gap by, for instance, describing multi-tiered models of school-based depression prevention that considered both individual and environmental factors associated with the development of depression, included the school environment as a target of intervention, and highlighted observable outcome measures at the individual and systems levels (Herman et al., 2004). Further, there have been additional attempts to identify universal screening measures to identify youth with internalizing concerns (Eklund, Tanner, Stoll, & Anway,2015; Miller et al., 2015; Stormont, Reinke, Newcomer, Marchese, & Lewis, 2015) and examine universal prevention and targeted prevention programs addressing internalizing disorders (Cook et al., 2015; Dart et al., 2015). However, these efforts are in their infancy and additional support is needed to inform the strategic implementation of practices targeting depression within MTSS framework (Kilgus, Reinke, & Jimerson, 2015).
In particular, limited support exists guiding SBMH providers in selecting the appropriate evidence-based depression prevention and intervention programming for use within the context of a school-based MTSS framework. Specifically, although several reviews of depression prevention (Calear & Christensen, 2010; Carnevale, 2013; Werner-Seidler et al., 2017) and intervention programming (Mychailyszyn, Brodman, Read, & Kendall, 2012; Patel, Stark, Metz & Banneyer, 2014) exist, no studies to our knowledge review the full continuum of evidence-based depression services, including universal, selective, and intensive programs, with a particular focus on their potential application within an MTSS framework. Considering recent research highlighting the challenges faced by SBMH providers in selecting and applying depression prevention and intervention programming in schools (Chafouleas, Kilgus, & Wallach, 2010; Warner & Fox, 2012), further clarification of these programs and their application to a MTSS framework is warranted.
Current Study
With the goal of supporting SBMH providers in the delivery of evidence-based practices targeting depression among youth within a MTSS framework, the following review conducted a critical review of the existing school-based prevention and intervention programming for depressive disorders for youth.
Methods
Initial Search
A systematic, four-stage review was performed. The first stage consisted of a comprehensive search of scholarly databases. Two databases, PsycINFO and Education Resources Information Center (ERIC), representing psychology and education were selected. Next, search terms were developed collaboratively by the authors based on their expertise and an informal review of the relevant literature bases to represent the concepts of interest in the study. A total of 12 keywords were used in this systematic review in order to target relevant literature. These included three keywords for the target population (i.e., “adolescent*,” “child*,” and “youth*”), four keywords for internalizing symptoms (i.e., “depress*,” “internalizing,” “mood,” and “suicide*”), four keywords for intervention programming (i.e., “prevention,” “intervention,” “treatment,” and “program,”), and one keyword for setting (i.e., “school*”). The Boolean search modifier “*” was used with certain keywords to identify literature with the same root word and various word endings (e.g., “depress*” would identify articles with the words “depression,” “depressed,” and “depressive”). The Boolean search operators “AND” and “OR” were used in order to conduct a single search with all the relevant keywords.
The keywords were used to search the abstracts, titles, and subject terms of articles within two databases. The search was restricted to articles published within peer-reviewed journals, written in English and published between the years 1990 and 2017. This initial step yielded 4470 results. Authors reviewed titles and abstracts of these articles to determine whether studies were relevant to the keywords described previously. Next, an ancestral search was performed, whereby all articles that were cited by these relevant articles were reviewed for inclusion in the systematic review. Finally, articles that cited these potentially relevant articles were also reviewed for inclusion in the systematic review. As a result of the initial, ancestral, and citation search, 316 articles were identified.
Inclusion Criteria
The next phase of the systematic review consisted of reviewing this initial pool of 316 articles to determine whether they met specific criteria for inclusion. Articles were only included in the review if they (1) described a prevention or intervention study that (2) targeted or discussed depressive symptoms (3) in school-aged youth ages 6–21 in a (4) US school setting.
All 316 articles were reviewed independently by two coders to establish reliability. Scores for each criterion (i.e., “1” or “0”) were compared across two raters using an exact agreement method (Cooper, Heron, & Heward, 2007). That is, an agreement was scored when both raters arrived at the same score for a criterion. Initial agreement across all four criteria was 92.4% for initial search articles and 95.6% for the ancestral and citation search articles. Articles with disagreements between raters were recoded by an author who did not initially code any articles. Any articles that did not meet all four inclusion criteria were dropped from the review. This process reduced the article pool to 119 total articles.
Article Coding
The next stage of the review involved coding to extract information from the 119 articles. Participant characteristics (e.g., age range, grade, ethnicity, socioeconomic status), school characteristics (e.g., type of school, location, school level), and intervention characteristics (e.g., name of program, primary focus of program, content, length and frequency of program sessions, program format) were coded. Information relevant to the particular study was also coded; this included the study interventionist, assessments used to measure depressive symptoms, type of control group, and overall findings (i.e., positive, negative, or mixed). As the goal of the systematic review was to identify and describe existing school-based prevention and intervention programming that addressed depressive symptoms among youth, a narrative description of the study’s characteristics and a summary of the effectiveness findings of each program were provided. A meta-analysis was not chosen to be conducted because of the range of different outcomes measured across the different trials; however, posttest effect sizes are calculated for all studies when sufficient data were available. Finally, MTSS tier was coded. Tier 1 programs were defined as those delivered with the goal of preventing emotional and behavioral, including depressive, disorders. Tier 2 programs were defined as programs delivered to youth at risk of emotional and behavioral, including depressive, disorders. Tier 2 programs were considered to be delivered to youth at risk of emotional and behavioral disorders if defined by as such by the study. Finally, Tier 3 programs were coded as programs delivered to youth identified with emotional and behavioral, including depressive, disorders. While Tier 1 programs were often delivered to entire school or class populations, Tier 2 programs were often delivered in small group contexts, and Tier 3 services were more likely to be delivered individually; format of delivery was not used to determine the tier of the program as this determination is occasionally based on resource availability. When one article included programs across multiple tiers, the article was listed within each relevant tier. Articles were coded based on their primary target for intervention; for instance, if an article noted that the intervention was targeted to at risk youth but, other youth were then considered space permitting, the intervention was nonetheless coded as Tier 2. For all categories, missing data were coded as “Unknown/Missing.”
For reliability purposes, a portion of articles (n = 12; 10%) were coded twice. Inter-rater reliability was calculated using an exact method (Cooper et al., 2007) whereby codes for each variable were compared across raters. An agreement was scored when both raters arrived at the same code. Initial agreement across the 12 articles was 92.31%. Disagreements were discussed between coders until a consensus was reached. The remainder of the articles were coded by one of these two raters.
Results
Participant and Study Characteristics
The 119 studies identified in the current review included a total of 28,594 participants, with a range of 0–5894 (M = 240.3) participants per study. Two studies described the development of programs in detail without providing effectiveness data. One study was listed in two tiers.
Grade
With regard to grade of participants, the majority of studies (65; 54.6%) included students in grades 6–8. High school students (grades 9–12) were included in 51 (42.8%) studies, while elementary school students (grades 1–5) and students in pre-Kindergarten and Kindergarten were included in 35 (29.4%) and 4 (3.4%) of studies, respectively. The grade of participants was inferred for 13 studies in which participants’ age was included; however, four studies (3.4%) did not include sufficient information to determine students’ grades.
Ethnicity
Most studies included White participants (67; 56.3%), African–American participants (65; 54.6%), and/or Hispanic/Latino participants (61; 51.3%). Asian American students were included in 40 studies (33.6%), and Native American participants were included in 23 studies (19.3%). Participants of multi-ethnic identities or other ethnicities were included in 54 (45.4%) of studies. Finally, 21 studies (17.6%) did not provide sufficient information to determine participants’ ethnicity, as many studies reported the percentage of ‘minority’ participants without delineation.
Socioeconomic Status (SES)
Most of the studies (68; 57.1%) did not report sufficient SES data, as many studies did not report SES at all and some reported SES data for only some participants. When SES data were reported, the distribution of studies was as follows: low SES (50; 42%); middle SES (34; 28.5%); and high SES (8; 6.7%).
Type of School
Similarly, 77 studies (64.7%) did not report whether the participating school(s) were public or private. Public schools were included in 37 studies (31.1%), while four studies (3.4%) included private schools and two studies (1.6%) were conducted in charter schools.
Location
Forty-three studies (36.1%) were conducted in urban areas, while 18 studies (15.1%) were in suburban areas and 15 studies (12.6%) were conducted in rural areas. Insufficient data with regard to location were provided in 47 studies (39.5%).
Study Design
Many of the studies included a pre/post design (55; 46.2%) or a pre/post design with follow-up (56; 47.1%). Two studies (1.7%) included data collection before intervention and a follow-up probe without immediate post-intervention data, and four studies (3.4%) included a follow-up probe sometime after intervention without any pre- or immediate post-intervention data. As discussed previously, two studies (1.7%) discussed the development of a program targeting depressive symptoms.
Control Group
With regard to the methods used in the included studies, 49 studies (41.2%) included an active control group, 41 studies (34.5%) included a wait-list control group, and 35 studies (29.4%) did not use a control group.
Tier 1 Programs
Programs identified as Tier 1 were implemented with entire school or class populations with the goal of preventing emotional and behavioral, including depressive, disorders. As such, the following sections include data on a total of 30 studies (25.2%) that discussed Tier 1 programs. Eighteen unique programs were included in these 30 studies. (See Table 1 for a review of Tier 1 studies.)
Primary Focus
Although some Tier 1 studies (8; 26.7% of Tier 1 studies) included programs focused primarily on depressive symptoms, many of the Tier 1 studies focused primarily on other symptoms or disorders while also measuring depressive symptomology. Specifically, seven studies (23.3%) focused primarily on internalizing and/or externalizing behaviors broadly defined, three studies (10%) focused primarily on obesity or weight management, and one study (3.3%) targeted each suicide and social skills and substance use. Four studies each (13.3%) focused primarily on stress or trauma, while nine studies (30%) focused on mental health or social emotional learning generally.
Content
A variety of approaches were used in Tier 1 studies, including CBT (14; 46.7%), social emotional learning (6; 20%), mindfulness (4; 13.3%), social skills training (3; 10%), and behavioral therapy (2; 6.7%). One study (3.3%) used each psychoeducation, family, and interpersonal therapy. Four studies (13.3%) included other content, including teaching school-wide expectations and physical activity.
Frequency
Regarding the frequency with which the programs were implemented, 13 studies (43.3%) included programs delivered weekly, while nine studies (33.3%) included programs implemented more than once per week. Six studies (20%) provided insufficient data on the frequency of implementation.
Format
With regard to the format of Tier 1 program delivery, 21 studies (70%) included class- or school-wide delivery, while seven studies (23.3%) included programs delivered to groups and two studies (6.7%) included programs delivered to families. One study (3.3%) included a program delivered individually.
Interventionist
In Tier 1 programs, the majority of studies (18; 60%) used school staff (e.g., teachers, nurses) as the primary interventionist. Other studies used researchers and/or graduate students (12; 40%), mental health clinicians (4; 13.3%), and community members or other interventionists (6; 20%).
Timing
With regard to when the Tier 1 programs were implemented, 26 out of 30 studies (86.7%) were conducted during school hours, with four studies (13.3%) including an after-school component. One study (3.3%) did not provide sufficient information to determine the timing of implementation.
Measures
Of the studies evaluating the impact of Tier 1 programs, the Children’s Depression Inventory (CDI; Kovacs, 1985) or the Children’s Depression Inventory-Short Version (CDI-S; Kovacs, 2003) were used in seven studies (25%), while the Achenbach System of Empirically Based Assessment (ASEBA; Achenbach & Rescoria, 2001) was utilized in five studies (17.8%). The Beck Youth Inventories (BYI; Beck, Beck, & Jolly, 2001) or Beck Depression Inventory (BDI; Beck, Ward, Mendelson, Mock, & Erbaugh, 1961) was used in three studies (10.7%). Other measures used in Tier 1 studies included the Social Skills Improvement Rating Scales (SSIS-RS; Gresham & Elliott, 2008), the Center for Epidemiologic Studies Depression Scale for Children (CES-DC; Radloff, 1977), and the Reynolds Adolescent Depression Scale (RADS; Reynolds, 1987).
Findings
Study findings were coded similar to Sheridan, Welch, and Orme (1996), as each study was coded as having positive findings (i.e., that significant pre-post differences or differences between groups were found), negative findings (i.e., that the intervention was not effective at reducing depressive symptomology), or mixed findings (i.e., that some main effects or interactions were not significant). With regard to Tier 1 studies, 23 out of 30 (76.7%) yielded positive results. Of the 23 studies that yielded positive results, posttest effect sizes ranged from 0.13 to 2.37. Four studies (13.3%) included mixed results. Specifically, Chaplin and colleagues (2006) found significant intervention effects on secondary variables (e.g., hopelessness and attendance) but not on main effects. Further, the results of Clarke, Hawkins, Murphy, and Sheeber (1993) were different for boys and girls, and the effects were not maintained at follow-up; Connell and Dishion (2017) found significant interaction effects, but no significant main effects; and Gilham and colleagues’ (2007) results differed by school. Three studies (10%) resulted in nonsignificant intervention effects. Hains (1992) and Han, Catron, Weiss, and Marciel (2005) found nonsignificant effects, while Smokowski and colleagues (2016) found that participants’ internalizing scores increased post-intervention.
Tier 2 Interventions
Seventy-one studies (59.6%) were identified as describing Tier 2 interventions, which were delivered with youth identified as at risk of emotional or behavioral, including depressive, disorders. Thirty-six unique programs were included in these 71 studies. (See Table 2 for a review of Tier 2 studies.)
Focus
The majority of Tier 2 interventions primarily focused on depressive disorders (46; 64.8%). Some studies instead focused primarily on trauma (13; 18.3%), suicide (6; 8.4%), anxiety (4; 5.6%), internalizing and/or externalizing behaviors broadly defined (4; 5.6%), stress (3; 4.2%), and mental health broadly defined (3; 4.2%).
Content
Over half of the Tier 2 studies (47; 66.2%) included CBT as a primary component of intervention. Other frequent approaches included mindfulness (5; 7%), interpersonal therapy (2; 2.8%), behavior therapy (2; 2.8%), social skills training (2; 2.8%), and psychoeducation (2; 2.8%). Twenty-five other studies (35.2%) used other intervention approaches, including bibliotherapy, family therapy, positive psychology, and music therapy.
Frequency
The majority of Tier 2 interventions were implemented once per week (43; 60.6%), while other studies included interventions implemented multiple times per week (12; 16.9%). Many studies (16; 22.5%) included insufficient information with regard to frequency, such as specifying the number of total sessions without indicating the number of sessions per week.
Format
The majority of Tier 2 studies included a group intervention format (62; 87.3%). Some studies included individual (28; 39.4%), home/family (12; 16.9%), and class-wide/school-wide components (1; 1.4%).
Interventionist
Tier 2 interventions were frequently implemented by researchers and/or graduate students (34; 47.9%), mental health clinicians (32; 45.1%), and school staff (23; 32.4%). Other interventionists (e.g., peers, paid external staff) were included in nine studies (12.7%).
Timing
Over half of studies (44; 62%) included interventions implemented during school hours, while 20 studies (28.2%) were implemented after school or at home. Fourteen studies (19.7%) did not provide sufficient information with regard to the location of implementation.
Measures
The CDI (Kovacs, 1985) and CDI-S (Kovacs, 2003) were most often used as an outcome measure for Tier 2 interventions (24; 33.8%), followed by the CES-D (Radloff, 1977) (11; 15.5%), the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS; Puig-Antich & Chambers, 1983) (9; 12.7%), the BDI or BYI-D (Beck et al., 1961) (8; 11.3%), the Mood and Feelings Questionnaire (MFQ; Angold, Costello, Pickles, & Winder, 1987) (7; 9.9%) and the RADS (Reynolds, 1987) (4; 5.6%). Other measures included the ASEBA (Achenbach & Rescoria, 2001), the Patient Health Questionnaire (Kroenke, Spitzer, & Williams, 2003), and the Child Depression Rating Scale-Revised (CDRS-R; Mayes, Bernstein, Haley, Kennard, & Emslie, 2010).
Findings
Fifty-five out of 71 (77.5%) Tier 2 studies yielded positive results. Of the 55 studies that yielded positive results, posttest effect sizes ranged from 0.10 to 2.24. Four studies (7%) had nonsignificant results and 11 studies (15.5%) were mixed. Studies without positive findings included music therapy (i.e., DeLucia-Waack & Gellman, 2007), bibliotherapy (i.e., Müller, Rohde, Gau, & Stice, 2015), and positive psychology (i.e., Roth, Suldo, & Ferron, 2017) as the primary approach. Some of the studies with mixed results demonstrated positive effects immediately post-intervention that were not maintained at follow-up (e.g., Gillham et al., 2012; Ruffolo & Fischer, 2009). As discussed previously, one of the studies (Stark et al., 1990) discussed the development of a Tier 2 program.
Tier 3 Interventions
Tier 3 interventions, those implemented with youth identified with emotional or behavioral, including depressive, disorders, were included in 19 studies (16% of total studies). Eleven unique programs were included in these 19 studies. (See Table 3 for a review of Tier 3 studies.)
Focus
Depressive disorders were the primary focus of 15 Tier 3 studies (78.9%), followed by anxiety disorders (8; 42.1%), and Conduct Disorder/ADHD/ODD (3; 15.8%). The remaining studies focused primarily either on trauma (1; 5.3%) and mental health broadly defined (1; 5.3%).
Content
Most of the Tier 3 studies included CBT as a major intervention component (8; 42.1%). Other approaches included interpersonal therapy (6; 31.6%), social skills training (5; 26.3%), behavioral therapy (3; 15.8%), and social emotional learning (1; 5.3%).
Frequency
Many Tier 3 interventions were implemented weekly (10; 52.6%), while one was implemented multiple times per week (5.3%). Eight of the Tier 3 studies (42.1%) did not include sufficient data with regard to frequency.
Format
Individual components were used in 12 Tier 3 studies (63.1%). Group components were used in 13 studies (68.4%) and three studies (15.8%) included family components. One of the Tier 3 studies used class-wide components.
Interventionist
A majority of the Tier 3 studies employed mental health clinicians to implement interventions (13; 68.4%). Researchers and/or graduate students implemented interventions in eight studies (42.1%), followed by staff (2; 10.5%).
Timing
The majority of Tier 3 studies (15; 78.9%) were implemented during school hours, while two studies (10.5%) included after-school components. Four studies (21.1%) did not provide sufficient information to determine the timing of intervention implementation.
Measures
Within Tier 3 studies, the CDI (Kovacs, 1985) or the CDI-S (Kovacs, 2003), as well as the CES-D (Radloff, 1977) were the most common measure used (5 each; 26.3%). Following this were several diagnostic interviews including the Hamilton Depression Rating Scale (Hamilton, 1960) (4; 21.1%) and the K-SADS (Puig-Antich & Chambers, 1983) (4; 21.1%). Other measures used included the BYI (Beck et al., 2001) or the BDI (Beck, et al., 1961) (3; 15.8%), the Diagnostic Interview Schedule for Children (DISC; Shaffer et al., 1996) (3; 15.8%), and the CDRS-R (Mayes et al., 2010) (2; 10.5%). Several measures, including the MFQ short version (Angold et al., 1995), and the RADS (Reynolds, 1987), were each used once in Tier 3 studies (5.3%).
Findings
The majority of Tier 3 studies (15; 78.9%) yielded positive results. Of the 15 studies that yielded positive results, posttest effect sizes ranged from 0.14 to 1.49. One study (Chu et al., 2016) found nonsignificant results. Also, one study (Young, Mufson, & Gallop, 2010) found immediate positive results that were not maintained at follow-up, while another study (Ehrenreich-May & Bilek, 2012) presented the preliminary results of an open trial. As noted above, one of the studies (Stark, Arora, & Funk, 2011; Stark, Streusand, Arora, & Patel, 2011) discussed the development of a Tier 3 program.
Discussion
The MTSS framework is an increasingly popular service delivery model for addressing the academic, behavioral, and mental health needs of students in schools; however, guidance in the application of the MTSS framework for addressing youth depression in schools has remained limited. The purpose of this study was to identify and review school-based interventions for depressive symptoms in an attempt to provide researchers and practitioners with a collection of programs that might be considered when developing a MTSS framework to address the mental health needs of students in schools. One-hundred and nineteen (n = 119) studies were identified, and the interventions investigated therein were categorized as either a Tier 1, Tier 2, or Tier 3 strategy to align with the three tiers of service typically provided within an MTSS framework. Overall, there appear to be a large number of interventions that yielded positive results as implemented within schools which may be suitable to address the depressive symptoms of students within an MTSS framework. However, there are some issues that must be discussed to put the current findings within the appropriate context and identify areas in need of further study.
First categorizing interventions into one of the three tiers of service delivery proved challenging. Typically, MTSS frameworks structure services along a continuum of student need and intervention intensity whereby the students exhibiting the most severe difficulties are provided with the most intense interventions (Eagle, Dowd-Eagle, Snyder, & Holtzman, 2015). Similarly, intervention intensity often covaries with the resources required to implement the intervention. Thus, there are numerous variables that characterize interventions at any tier of service and we were faced with the challenge of selecting a primary characteristic by which to make categorical decisions. Although intensity and resource requirement are important, we opted to categorize interventions on the severity of participants’ symptoms as treatment decisions within a MTSS are typically made based on student outcomes; however, further complicating this decision was the disconnect between clinical assessment, diagnosis, and treatment of depression and service delivery within a MTSS.
MTSS frameworks are intended to provide services to students prior to special education service delivery and students at any tier are unlikely to have been identified as a student with an emotional disturbance, the Individuals with Disabilities Education Act (IDEA, 2004) classification covering symptoms of depression. This disconnect became apparent when trying to categorize strategies as Tier 2 and Tier 3. Ultimately, we decided to define Tier 2 strategies as those interventions targeting students at risk of emotional or behavioral, including depressive, disorders and Tier 3 strategies as those interventions targeting students with clinical diagnoses of emotional or behavioral, including depressive, disorders; however, in practice, Tier 3 services are likely to be provided to students with no corresponding special education classification. Future research should further investigate what distinction is most appropriate when considering Tier 2 and Tier 3 strategies to address students’ mental health.
Effectiveness
Within a MTSS, it is critical that practitioners have a variety of effective strategies at their disposal at each tier of service. As the outcomes of all studies included in this review were categorized as either positive, mixed, or negative, and the magnitude of the effects (i.e., effect sizes) was reviewed, it was possible to gauge the effectiveness of programs at each tier of service. In general, most of the programs investigated at each tier were identified as effective. Of the programs classified as Tier 1, 76.7% were identified as effective, with effect sizes ranging from small (0.13) to very large (2.37). Of the programs classified as Tier 2, 77.5% were identified as effective, with effect sizes ranging from small (0.10) to very large (2.24). Finally, of the programs classified as Tier 3, 78.9% were classified as effective, with effect sizes ranging from small (0.14) to large (1.49). Thus, all three tiers contained effective options for the prevention and treatment of depression in schools. It should be noted that the fewest number of interventions were classified as Tier 3, suggesting there is a relative lack of available intervention options at this tier of service compared to Tier 1 and Tier 2; however, this finding may be an artifact of our classification process, which required Tier 3 interventions to target youth with diagnoses in a school setting. It is possible that Tier 2 interventions may also be effective at Tier 3, but more research is needed to determine the most appropriate distinction between the two.
Participant and Setting Concerns
Although we identified a number of potentially effective interventions in this review, several issues were also identified related to the participants and settings across studies. First, the large majority of participants included in these studies were in middle and high school students, which was not unexpected given the data suggesting that the prevalence of mood disorders increases over the lifespan and is least common in early childhood (Merikangas et al., 2010). Nonetheless, MTSS frameworks emphasize prevention and, as such, efforts to prevent depressive symptoms would likely be best served in the early grades. A meta-analysis conducted by Stice and colleagues (2009) identified age as a predictor of effectiveness in prevention programs for depression in youth. They found that participants below the median age of 13.5 were conferred negligible benefits, while older participants demonstrated moderate response to intervention and hypothesized that the difference was due to the complexity of intervention components (Stice, Shaw, Bohon, Marti, & Rohde, 2009). Issues related to age and intervention effectiveness must be addressed for younger students to benefit, whether that involves modifying complex concepts used in CBT to make them more suitable, and thus more effective, for young children or investigating alternative modalities that require less complex concepts (e.g., behavior analysis; Kanter, Busch, Weeks, & Landes, 2008).
A second issue revolves around the lack of reporting related to seemingly important participant and setting characteristics. Many studies did not report participant SES, the location or type (i.e., public or private) of school, or the ethnicity of the participants. From a clinical perspective, culturally adapted interventions have been shown to be beneficial for clients’ mental health (Griner & Smith, 2006). Logically, mental health interventions in schools should also be adapted to address students’ cultural differences. Sue, Zane, Hall, and Berger (2009) identified the method of intervention delivery and intervention content as important factors that should be adapted to a client’s culture. Similarly, SES has been linked to a variety of mental health outcomes in children (Bradley & Corwyn, 2002) yet was not often reported in included studies. Without data to support the use of these strategies across a range of student characteristics, it is difficult to determine which interventions may be beneficial for which students. Thus, it is important that researchers collect and report data related to participant characteristics, culture, and socioeconomic status when evaluating interventions for depressive symptoms in order to identify effective strategies. Relatedly, it is critical that the ethnicity of participants be fully reported instead of being combined into categories (e.g., “minorities”) given the evidence that individuals from different ethnicities experience different rates of depression (e.g., Sen, 2004).
Implementation Concerns
A discussion of two issues related to implementation of these interventions is warranted. First, although this review sought to identify interventions that could be implemented within the context of a school-based MTSS, the majority of the studies were not couched in this context. Instead, many of the studies simply evaluated the effects of a traditional intervention within a school setting but not within the MTSS service delivery model. As a result, it is unclear how such a framework would function if a particular Tier 1, Tier 2, or Tier 3 intervention were selected and implemented within a MTSS service delivery model. As noted in the review, many of the studies used standardized rating scales as outcome measure. Unfortunately, these rating scales are often lengthy and would make poor progress monitoring assessments, a staple in MTSS frameworks (Eagle et al., 2015). Additionally, decision rules and criteria to move students between tiers of service were also missing from the evaluations. Thus, despite identifying potentially effective interventions, establishing a MTSS for depressive symptoms does not seem as simple as selecting an intervention from each tier. Questions related to the appropriate use of progress monitoring assessments and the application of decision rules and criteria to move students between tiers will need to be answered prior to the integration of such interventions within the MTSS service delivery model.
A second implementation concerns involve the individuals responsible for implementing these interventions. Fortunately, a majority of the Tier 1 studies used school staff members to implement the intervention. This is consistent with Tier 1 interventions in other domains of functioning and highlights the feasibility of these strategies. On the other hand, the Tier 2 and Tier 3 intervention studies almost exclusively used mental health professionals and researchers to implement interventions. One exception was the study by Kam and colleagues (2004), which investigated the use of the PATHS curriculum as a class-wide intervention in special education classrooms. Teachers were trained to implement the curriculum by researchers, providing an example of a Tier 3 strategy that required less involvement from the researchers than typical Tier 2 and Tier 3 strategies. A reliance on clinicians and researchers may be problematic at Tier 2 as up to 15% of students (e.g., 75 students in a school building of 500) may require services. Many schools may not sufficient funds to staff SBMH providers. Moreover, many SBMH providers currently do not have the necessary training to implement such evidence-based programs with fidelity. In such cases, there may not be anyone present at the school who has the requisite training and expertise to implement the Tier 2 or Tier 3 strategy. Thus, in order for a school-based MTSS for depressive symptoms to be viable, it will need to emphasize interventions that do not require highly specialized training, particularly at the Tier 1 and Tier 2 levels.
Implications
Several implications are relevant for practitioners and researchers in light of our findings. First, those wishing to implement a MTSS to address students’ depressive symptoms may use this review as a starting place to guide their selection of interventions. As noted above, implementing a service delivery model based upon a MTSS framework is not as simple as selecting an intervention from each tier and putting it into place; however, the interventions identified here should be considered within the larger planning process.
As mentioned earlier, there are several empirical questions that must be addressed before widespread implementation of a MTSS for depressive symptoms is encouraged. Researchers should work to identify which interventions are maximally effective at each tier and for which students and schools. Doing so would require an evaluation of these interventions within the context of a MTSS framework using, for instance, progress monitoring assessments of depression instead of traditional standardized rating scales. Interventions that are deemed effective in this context may then be suitable for use within an MTSS system. Researchers should also work to develop transition criteria between tiers as well as identifying a progress monitoring assessment that can be administered repeatedly. Currently, we lack sufficient empirical guidance on how to make data-based decisions when addressing depression within a MTSS compared to an outcome like oral reading fluency (e.g., Van Norman & Christ, 2016).
Limitations
There are two limitations of this study to address in order to place the results in the appropriate context. First, the review only dated back until 1990. This date was selected because nearly all of the child research related to internalizing disorder prevention and treatment has been conducted over the past 30 years. Additionally, this cut-off is consistent with other reviews of the SBMH literature (e.g., Carnevale, 2013; Von der Embse, Kilgus, Segool, & Putwain, 2013). Nevertheless, it is possible that we missed older studies that were otherwise appropriate for inclusion in this review. Future research could expand the search for school-based interventions for depression in order to encompass the full breadth of extant literature. A second limitation involved our decision to conduct a systematic review instead of a meta-analysis. Although recent meta-analyses have demonstrated these types of interventions to be effective (e.g., Mychailyszyn et al., 2012), we chose to use a less formal approach to synthesizing their effectiveness. Clearly, as with any empirical synthesis, the findings of our review are skewed in a favorable direction due to publication bias (Rothstein, Sutton, & Borenstein, 2006). The primary purpose of the review was simply to categorize extant interventions based on their appropriateness for use within a MTSS. Furthermore, the content of the interventions at each tier was disparate. For example, Tier 2 interventions included components involving bibliotherapy, family therapy, positive psychology, music therapy, behavioral therapy, and mindfulness. Attempting to quantify the effectiveness of these as Tier 2 strategies would have provided little insight into which particular strategy was most effective. Thus, we chose not to conduct a meta-analysis. However, future research should more fully explore the effectiveness of such interventions, particularly within the context of a MTSS.
Conclusion
In sum, although there appears to be no shortage of school-based interventions for depressive symptoms in students, there are a number of implementation and population issues that have yet to be addressed before these services can be delivered within an MTSS framework. This review should be viewed as a starting place for research and practitioners to continue exploration of a MTSS to meet the mental health needs of students in schools. What might be needed most is an experimental evaluation of a three-tiered service delivery model to address depressive symptoms in students. Furthering our field’s knowledge in this area is critical if students are to receive adequate mental health services in schools.
References
*References marked with an asterisk indicate studies included in the systematic review.
Achenbach, T. M., & Rescoria, L. A. (2001). Manual for the ASEBA school-age forms & profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth and Families.
*Allison, A. C., & Ferreira, R. J. (2017). Implementing cognitive behavioral intervention for trauma in schools (CBITS) with Latino youth. Child and Adolescent Social Work Journal, 34(2), 181–189.
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.
Angold, A., Costello, E. J., Messer, S. C., Pickles, A., Winder, F., & Silver, D. (1995). The development of a short questionnaire for use in epidemiological studies of depression in children and adolescents. International Journal of Methods in Psychiatric Research, 5, 237–249.
Angold, A., Costello, E. J., Pickles, A., & Winder, F. (1987). The development of a questionnaire for use in epidemiological studies of depression in children and adolescents. London: Medical Research Council Child Psychiatry Unit.
Beck, J. S., Beck, A. T., & Jolly, J. B. (2001). Beck Youth Inventories. San Antonio, TX: Psychological Corporation.
Beck, A. T., Ward, C. H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychiatry, 4, 561–571.
Behavioral Health Statistics and Quality. (2015). Behavioral health trends in the United States: Results from the 2014 National Survey on Drug Use and Health (HHS Publication No. SMA 15-4927, NSDUH Series H-50). Retrieved February 1, 2019 from http://www.samhsa.gov/data.
*Benas, J. S., McCarthy, A. E., Haimm, C. A., Huang, M., Gallop, R., & Young, J. F. (2016). The depression prevention initiative: Impact on adolescent internalizing and externalizing symptoms in a randomized trial. Journal of Clinical Child and Adolescent Psychology. https://doi.org/10.1080/15374416.2016.1197839.
Birmaher, B., Ryan, N. D., Williamson, D. E., Brent, D. A., Kaufman, J., Dahl, R. E., et al. (1996). Childhood and adolescent depression: A review of the past 10 years. Part I. Journal of the American Academy of Child & Adolescent Psychiatry, 35(11), 1427–1439.
*Bluth, K., Campo, R. A., Pruteanu-Malinici, S., Mullarkey, M., & Broderick, P. C. (2016). A school-based mindfulness pilot study for ethnically diverse at-risk adolescents. Mindfulness, 7(1), 90–104.
Bradley, R. H., & Corwyn, R. F. (2002). Socioeconomic status and child development. Annual Review of Psychology, 53, 371–399.
Bradshaw, C. P., Buckley, J. A., & Ialongo, N. S. (2008). School-based service utilization among urban children with early onset educational and mental health problems: The squeaky wheel phenomenon. School Psychology Quarterly, 23(2), 169–186.
*Brière, F. N., Rohde, P., Shaw, H., & Stice, E. (2014). Moderators of two indicated cognitive-behavioral depression prevention approaches for adolescents in a school-based effectiveness trial. Behaviour Research and Therapy, 53, 55–62.
*Britton, W. B., Lepp, N. E., Niles, H. F., Rocha, T., Fisher, N. E., & Gold, J. S. (2014). A randomized controlled pilot trial of classroom-based mindfulness meditation compared to an active control condition in sixth-grade children. Journal of School Psychology, 52(3), 263–278.
*Brown, E. J., McQuaid, J., Farina, L., Ali, R., & Winnick-Gelles, A. (2006). Matching interventions to children’s mental health needs: Feasibility and acceptability of a pilot school-based trauma intervention program. Education and Treatment of Children, 29(2), 257–286.
*Cabiya, J. J., Padilla-Cotto, L., González, K., Sanchez-Cestero, J., Martínez-Taboas, A., & Sayers, S. (2008). Effectiveness of a cognitive-behavioral intervention for Puerto Rican children. Interamerican Journal of Psychology, 42(2), 195–202.
Calear, A. L., & Christensen, H. (2010). Systematic review of school-based prevention and early intervention programs for depression. Journal of adolescence, 33(3), 429–438.
*Cardemil, E. V., Reivich, K. J., Beevers, C. G., Seligman, M. E., & James, J. (2007). The prevention of depressive symptoms in low-income, minority children: Two-year follow-up. Behaviour Research and Therapy, 45(2), 313–327.
*Cardemil, E. V., Reivich, K. J., & Seligman, M. E. (2002). The prevention of depressive symptoms in low-income minority middle school students. Prevention & Treatment, 5(1), 8a.
Carnevale, T. D. (2013). Universal adolescent depression prevention programs: A review. The Journal of School Nursing, 29(3), 181–195.
*Carter, J. S., Karczewski, S., DeCator, D. D., & Hollowell, A. M. (2017). Ethnic differences in impact of physical activity program on psychological symptoms in youth. Journal of Physical Activity and Health, 14(4), 283–289.
Chafouleas, S. M., Kilgus, S. P., & Wallach, N. (2010). Ethical dilemmas in school-based behavioral screening. Assessment for Effective Intervention, 35(4), 245–252.
*Chaplin, T. M., Gillham, J. E., Reivich, K., Elkon, A. G., Samuels, B., Freres, D. R., et al. (2006). Depression prevention for early adolescent girls: A pilot study of all girls versus co-ed groups. The Journal of Early Adolescence, 26(1), 110–126.
*Cheney, D. A., Stage, S. A., Hawken, L. S., Lynass, L., Mielenz, C., & Waugh, M. (2009). A 2-year outcome study of the check, connect, and expect intervention for students at risk for severe behavior problems. Journal of Emotional and Behavioral Disorders, 17(4), 226–243.
*Chu, B. C., Colognori, D., Weissman, A. S., & Bannon, K. (2009). An initial description and pilot of group behavioral activation therapy for anxious and depressed youth. Cognitive and Behavioral Practice, 16(4), 408–419.
*Chu, B. C., Crocco, S. T., Esseling, P., Areizaga, M. J., Lindner, A. M., & Skriner, L. C. (2016). Transdiagnostic group behavioral activation and exposure therapy for youth anxiety and depression: Initial randomized controlled trial. Behaviour Research and Therapy, 76, 65–75.
*Chu, B. C., Hoffman, L., Johns, A., Reyes-Portillo, J., & Hansford, A. (2015). Transdiagnostic behavior therapy for bullying-related anxiety and depression: Initial development and pilot study. Cognitive and Behavioral Practice, 22(4), 415–429.
*Clarke, G. N., Hawkins, W., Murphy, M., & Sheeber, L. B. (1993). School-based primary prevention of depressive symptomatology in adolescents: Findings from two studies. Journal of Adolescent Research, 8(2), 183–204.
*Clarke, G. N., Hawkins, W., Murphy, M., Sheeber, L. B., Lewinsohn, P. M., & Seeley, J. R. (1995). Targeted prevention of unipolar depressive disorder in an at-risk sample of high school adolescents: A randomized trial of a group cognitive intervention. Journal of the American Academy of Child and Adolescent Psychiatry, 34(3), 312–321.
*Connell, A. M., & Dishion, T. J. (2008). Reducing depression among at-risk early adolescents: Three-year effects of a family-centered intervention embedded within schools. Journal of Family Psychology, 22(3), 574–585.
*Connell, A. M., & Dishion, T. J. (2017). Long-term effects of the family check-up in public secondary school on diagnosed major depressive disorder in adulthood. Journal of Youth and Adolescence, 46(3), 570–581.
*Cook, C. R., Xie, S. R., Earl, R. K., Lyon, A. R., Dart, E., & Zhang, Y. (2015). Evaluation of the courage and confidence mentor program as a tier 2 intervention for middle school students with identified internalizing problems. School Mental Health, 7(2), 132–146.
Cooper, J. O., Heron, T. E., & Heward, W. L. (2007). Applied behavior analysis. Upper Saddle River, NJ: Pearson.
Costello, E. J., Mustillo, S., Erkanli, A., Keeler, G., & Angold, A. (2003). Prevalence and development of psychiatric disorders in childhood and adolescence. Archives of General Psychiatry, 60(8), 837–844.
*Crisp, H. L., Gudmundsen, G. R., & Shirk, S. R. (2006). Transporting evidence-based therapy for adolescent depression to the school setting. Education and Treatment of Children, 29(2), 287–309.
*Cutuli, J. J., Chaplin, T. M., Gillham, J. E., Reivich, K. J., & Seligman, M. E. (2006). Preventing co-occurring depression symptoms in adolescents with conduct problems. Annals of the New York Academy of Sciences, 1094(1), 282–286.
*Cutuli, J. J., Gillham, J. E., Chaplin, T. M., Reivich, K. J., Seligman, M. E., Gallop, R. J., et al. (2013). Preventing adolescents’ externalizing and internalizing symptoms: Effects of the Penn Resiliency Program. The International Journal of Emotional Education, 5(2), 67–79.
Dart, E. H., Furlow, C. M., Collins, T. A., Brewer, E., Gresham, F. M., & Chenier, K. H. (2015). Peer-mediated check-in/check-out for students at-risk for internalizing disorders. School Psychology Quarterly, 30(2), 229–243.
*DeLucia-Waack, J. L., & Gellman, R. A. (2007). The efficacy of using music in children of divorce groups: Impact on anxiety, depression, and irrational beliefs about divorce. Group Dynamics: Theory, Research, and Practice, 11(4), 272–282.
*DeRosier, M. E., & Marcus, S. R. (2005). Building friendships and combating bullying: Effectiveness of SS GRIN at one-year follow-up. Journal of Clinical Child and Adolescent Psychology, 34(1), 140–150.
*DiPerna, J. C., Lei, P., Bellinger, J., & Cheng, W. (2015). Efficacy of the Social Skills Improvement System Classwide Intervention Program (SSIS-CIP) primary version. School Psychology Quarterly, 30(1), 123–141.
Doll, B., & Cummings, J. A. (Eds.). (2008). Transforming school mental health services: Population-based approaches to promoting the competency and wellness of children. Thousand Oaks, CA: Sage and National Association of School Psychologists.
*Duong, M. T., Cruz, R. A., King, K. M., Violette, H. D., & McCarty, C. A. (2016a). Twelve-month outcomes of a randomized trial of the positive thoughts and action program for depression among early adolescents. Prevention Science, 17(3), 295–305.
*Duong, M. T., Kelly, B. M., Haaland, W. L., Matsumiya, B., Huey, S. J., & McCarty, C. A. (2016b). Mediators and moderators of a school-based cognitive-behavioral depression prevention program. Cognitive Therapy and Research, 40(5), 705–716.
Eagle, J. W., Dowd-Eagle, S. E., Snyder, A., & Holtzman, E. G. (2015). Implementing a multi-tiered system of support (MTSS): Collaboration between school psychologists and administrators to promote systems-level change. Journal of Educational and Psychological Consultation, 25(2–3), 160–177.
*Eggert, L. L., Thompson, E. A., Herting, J. R., & Nicholas, L. J. (1995). Reducing suicide potential among high-risk youth: Tests of a school-based prevention program. Suicide and Life-Threatening Behavior, 25(2), 276–296.
*Eggert, L. L., Thompson, E. A., Randell, B. P., & Pike, K. C. (2002). Preliminary effects of brief school-based prevention approaches for reducing youth suicide-risk behaviors, depression, and drug involvement. Journal of Child and Adolescent Psychiatric Nursing, 15(2), 48–64.
*Ehrenreich-May, J., & Bilek, E. L. (2012). The development of a transdiagnostic, cognitive behavioral group intervention for childhood anxiety disorders and co-occurring depression symptoms. Cognitive and Behavioral Practice, 19(1), 41–55.
*Eiraldi, R., Power, T. J., Schwartz, B. S., Keiffer, J. N., McCurdy, B. L., Mathen, M., et al. (2016). Examining effectiveness of group cognitive-behavioral therapy for externalizing and internalizing disorders in urban schools. Behavior Modification, 40(4), 611–639.
Eklund, K., Tanner, N., Stoll, K., & Anway, L. (2015). Identifying emotional and behavioral risk among gifted and nongifted children: A multi-gate, multi-informant approach. School Psychology Quarterly, 30(2), 197–211.
*Ellis, B. H., Miller, A. B., Abdi, S., Barrett, C., Blood, E. A., & Betancourt, T. S. (2013). Multi-tier mental health program for refugee youth. Journal of Consulting and Clinical Psychology, 81(1), 129–140.
*Frank, J. L., Bose, B., & Schrobenhauser-Clonan, A. (2014). Effectiveness of a school-based yoga program on adolescent mental health, stress coping strategies, and attitudes toward violence: Findings from a high-risk sample. Journal of Applied School Psychology, 30(1), 29–49.
*Freres, D. R., Gillham, J. E., Reivich, K., & Shatté, A. J. (2002). Preventing depressive symptoms in middle school students: The Penn Resiliency Program. International Journal of Emergency Mental Health, 4(1), 31–40.
*Fung, J., Guo, S., Jin, J., Bear, L., & Lau, A. (2016). A pilot randomized trial evaluating a school-based mindfulness intervention for ethnic minority youth. Mindfulness, 7(4), 819–828.
Galambos, N., Leadbeater, B., & Barker, E. (2004). Gender differences in and risk factors for depression in adolescence: A 4-year longitudinal study. International Journal of Behavioral Development, 28(1), 16–25.
*Garcia, C., Pintor, J. K., & Lindgren, S. (2010). Feasibility and acceptability of a school-based coping intervention for Latina adolescents. The Journal of School Nursing, 26(1), 42–52.
*Garcia, C., Pintor, J. K., Vazquez, G., & Alvarez-Zumarraga, E. (2013). Project Wings, a coping intervention for Latina adolescents: A pilot study. Western Journal of Nursing Research, 35(4), 434–458.
*Gillham, J. E., Reivich, K. J., Brunwasser, S. M., Freres, D. R., Chajon, N. D., Kash-MacDonald, V. M., et al. (2012). Evaluation of a group cognitive-behavioral depression prevention program for young adolescents: A randomized effectiveness trial. Journal of Clinical Child & Adolescent Psychology, 41(5), 621–639.
*Gillham, J. E., Reivich, K. J., Freres, D. R., Chaplin, T. M., Shatté, A. J., Samuels, B., et al. (2007). School-based prevention of depressive symptoms: A randomized controlled study of the effectiveness and specificity of the Penn Resiliency Program. Journal of Consulting and Clinical Psychology, 75(1), 9–19.
*Gillham, J. E., Reivich, K. J., Freres, D. R., Lascher, M., Litzinger, S., Shatté, A., et al. (2006). School-based prevention of depression and anxiety symptoms in early adolescence: A pilot of a parent intervention component. School Psychology Quarterly, 21(3), 323–348.
*Gillham, J. E., Reivich, K. J., Jaycox, L. H., & Seligman, M. E. (1995). Prevention of depressive symptoms in schoolchildren: Two-year follow-up. Psychological Science, 6(6), 343–351.
*Goldman, E. E., Bauer, D., Newman, D. L., Kalka, E., Lochman, J. E., Silverman, W. K., et al. (2015). A school-based post-Katrina therapeutic intervention. Administration and Policy in Mental Health and Mental Health Services Research, 42(3), 363–372.
*Goodkind, J. R., LaNoue, M. D., & Milford, J. (2010). Adaptation and implementation of cognitive behavioral intervention for trauma in schools with American Indian youth. Journal of Clinical Child & Adolescent Psychology, 39(6), 858–872.
Gould, M. S., King, R., Greenwald, S., Fisher, P., Schwab-Stone, M., Kramer, R., et al. (1998). Psychopathology associated with suicidal ideation and attempts among children and adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 37(9), 915–923.
*Graham, R. A., Osofsky, J. D., Osofsky, H. J., & Hansel, T. C. (2017). School based post disaster mental health services: Decreased trauma symptoms in youth with multiple traumas. Advances in School Mental Health Promotion, 10(3), 161–175.
Gresham, F., & Elliott, S. N. (2008). Social skills improvement system rating scales. Minneapolis, MN: Pearson Assessments.
Griner, D., & Smith, T. B. (2006). Culturally adapted mental health intervention: A meta-analytic review. Psychotherapy: Theory, Research, Practice, Training, 43, 531–548.
*Gudiño, O. G., Leonard, S., & Cloitre, M. (2016). STAIR-A for girls: A pilot study of a skills-based group for traumatized youth in an urban school setting. Journal of Child & Adolescent Trauma, 9(1), 67–79.
*Gunlicks-Stoessel, M., Mufson, L., Jekal, A., & Turner, J. B. (2010). The impact of perceived interpersonal functioning on treatment for adolescent depression: IPT-A versus treatment as usual in school-based health clinics. Journal of Consulting and Clinical Psychology, 78(2), 260–267.
*Hains, A. A. (1992). Comparison of cognitive-behavioral stress management techniques with adolescent boys. Journal of Counseling & Development, 70(5), 600–605.
*Hains, A. A. (1994). The effectiveness of a school-based, cognitive-behavioral stress management program with adolescents reporting high and low levels of emotional arousal. The School Counselor, 42(2), 114–125.
*Hains, A. A., & Ellmann, S. W. (1994). Stress inoculation training as a preventative intervention for high school youths. Journal of Cognitive Psychotherapy, 8(3), 219–232.
Hamilton, M. (1960). A rating scale for depression. Journal of Neurology, Neurosurgery and Psychiatry, 23(1), 56–62.
*Han, S. S., Catron, T., Weiss, B., & Marciel, K. K. (2005). A teacher-consultation approach to social skills training for pre-kindergarten children: Treatment model and short-term outcome effects. Journal of Abnormal Child Psychology, 33(6), 681–693.
Hankin, B. L., & Abramson, L. Y. (2001). Development of gender differences in depression: An elaborated cognitive vulnerability–transactional stress theory. Psychological Bulletin, 127(6), 773–796.
*Hansel, T. C., Osofsky, H. J., Osofsky, J. D., Costa, R. N., Kronenberg, M. E., & Selby, M. L. (2010). Attention to process and clinical outcomes of implementing a rural school-based trauma treatment program. Journal of Traumatic Stress, 23(6), 708–715.
*Hendricks, C. B., Robinson, B., Bradley, L. J., & Davis, K. (1999). Using music techniques to treat adolescent depression. The Journal of Humanistic Counseling, 38(1), 39–46.
Herman, K. C., Merrell, K. W., Reinke, W. M., & Tucker, C. M. (2004). The role of school psychology in preventing depression. Psychology in the Schools, 41(7), 763–775.
*Hooven, C., Herting, J. R., & Snedker, K. A. (2010). Long-term outcomes for the promoting CARE suicide prevention program. American Journal of Health Behavior, 34(6), 721–736.
*Horowitz, J. L., Garber, J., Ciesla, J. A., Young, J. F., & Mufson, L. (2007). Prevention of depressive symptoms in adolescents: A randomized trial of cognitive-behavioral and interpersonal prevention programs. Journal of Consulting and Clinical Psychology, 75(5), 693–706.
*Hoying, J., & Melnyk, B. M. (2016). COPE: A pilot study with urban-dwelling minority sixth-grade youth to improve physical activity and mental health outcomes. The Journal of School Nursing, 32(5), 347–356.
*Hoying, J., Melnyk, B. M., & Arcoleo, K. (2016). Effects of the COPE cognitive behavioral skills building TEEN program on the healthy lifestyle behaviors and mental health of Appalachian early adolescents. Journal of Pediatric Health Care, 30(1), 65–72.
*Hunter, K. K., Chenier, J. S., & Gresham, F. M. (2014). Evaluation of check in/check out for students with internalizing behavior problems. Journal of Emotional and Behavioral Disorders, 22(3), 135–148.
*Jaycox, L. H., Reivich, K. J., Gillham, J., & Seligman, M. E. (1994). Prevention of depressive symptoms in school children. Behaviour Research and Therapy, 32(8), 801–816.
Jimerson, S. R., Burns, M. K., & VanDerHeyden, A. M. (Eds.). (2015). Handbook of response to intervention: The science and practice of multi-tiered systems of support. New York: Springer.
*Jones, S. M., Brown, J. L., & Aber, J. L. (2011). Two-year impacts of a universal school-based social-emotional and literacy intervention: An experiment in translational developmental research. Child Development, 82(2), 533–554.
*Jones, S. M., Brown, J. L., Hoglund, W. L., & Aber, J. L. (2010). A school-randomized clinical trial of an integrated social–emotional learning and literacy intervention: Impacts after 1 school year. Journal of Consulting and Clinical Psychology, 78(6), 829–842.
*Kahn, J. S., Kehle, T. J., Jenson, W. R., & Clark, E. (1990). Comparison of cognitive-behavioral, relaxation, and self-modeling interventions for depression among middle-school students. School Psychology Review, 19(2), 196–211.
*Kam, C. M., Greenberg, M. T., & Kusché, C. A. (2004). Sustained effects of the PATHS curriculum on the social and psychological adjustment of children in special education. Journal of Emotional and Behavioral Disorders, 12(2), 66–78.
Kanter, J. W., Busch, A. M., Weeks, C. E., & Landes, S. J. (2008). The nature of clinical depression: Symptoms, syndromes, and behavior analysis. The Behavior Analyst, 31(1), 1–21.
*Kataoka, S. H., Stein, B. D., Jaycox, L. H., Wong, M., Escudero, P., Tu, W., et al. (2003). A school-based mental health program for traumatized Latino immigrant children. Journal of the American Academy of Child and Adolescent Psychiatry, 42(3), 311–318.
Kauffman, J. M. (2001). Characteristics of emotional and behavioral disorders in children and youth (7th ed.). Upper Saddle River, NJ: Prentice Hall.
Kazdin, A. E., & Weisz, J. R. (1998). Identifying and developing empirically supported child and adolescent treatments. Journal of Consulting and Clinical Psychology, 66(1), 19–36.
Kessler, R. C., Berglund, P. A., Bruce, M. L., Koch, J. R., Laska, E. M., Leaf, P. J., et al. (2001). The prevalence and correlates of untreated serious mental illness. Health Services Research, 36(6 Pt 1), 987.
Kilgus, S. P., Reinke, W. M., & Jimerson, S. R. (2015). Understanding mental health intervention and assessment within a multi-tiered framework: Contemporary science, practice, and policy. School Psychology Quarterly, 30(2), 159–165.
Kovacs, M. (1985). The Children’s Depression Inventory (CDI). Psychopharmacology Bulletin, 21, 995–998.
Kovacs, M. (2003). Children’s Depression Inventory (CDI): Technical manual update. North Tonawanda, NY: Multi-Health Systems.
*Kramer, T. J., Caldarella, P., Young, K. R., Fischer, L., & Warren, J. S. (2014). Implementing Strong Kids school-wide to reduce internalizing behaviors and increase prosocial behaviors. Education and Treatment of Children, 37(4), 659–680.
Kroenke, K., Spitzer, R., & Williams, J. B. W. (2003). The Patient Health Questionnaire-2: Validity of a two-item depression screener. Medical Care, 41(11), 1284–1292. Retrieved February 1, 2019 from http://www.jstor.org/stable/3768417.
*La Greca, A. M., Ehrenreich-May, J., Mufson, L., & Chan, S. (2016). Preventing adolescent social anxiety and depression and reducing peer victimization: Intervention development and open trial. Child & Youth Care Forum, 45(6), 905–926.
*Lamb, J. M., Puskar, K. R., Sereika, S. M., & Corcoran, M. (1998). School-based intervention to promote coping in rural teens. MCN: The American Journal of Maternal/Child Nursing, 23(4), 187–194.
*Lane, K. L., Wehby, J. H., Robertson, E. J., & Rogers, L. A. (2007). How do different types of high school students respond to schoolwide positive behavior support programs? Characteristics and responsiveness of teacher-identified students. Journal of Emotional and Behavioral Disorders, 15(1), 3–20.
*Langley, A. K., Gonzalez, A., Sugar, C. A., Solis, D., & Jaycox, L. (2015). Bounce back: Effectiveness of an elementary school-based intervention for multicultural children exposed to traumatic events. Journal of Consulting and Clinical Psychology, 83(5), 853–865.
*Last, C. G., Hansen, C., & Franco, N. (1998). Cognitive-behavioral treatment of school phobia. Journal of the American Academy of Child and Adolescent Psychiatry, 37(4), 404–411.
*Le, T. N., & Gobert, J. M. (2015). Translating and implementing a mindfulness-based youth suicide prevention intervention in a Native American community. Journal of Child and Family Studies, 24(1), 12–23.
Lewinsohn, P. M., Hops, H., Roberts, R. E., Seeley, J. R., & Andrews, J. A. (1993). Adolescent psychopathology: I. Prevalence and incidence of depression and other DSM-III—R disorders in high school students. Journal of Abnormal Psychology, 102(1), 133–144.
*Lewis, K. M., DuBois, D. L., Bavarian, N., Acock, A., Silverthorn, N., Day, J., et al. (2013). Effects of positive action on the emotional health of urban youth: A cluster-randomized trial. Journal of Adolescent Health, 53(6), 706–711.
*Listug-Lunde, L., Vogeltanz-Holm, N., & Collins, J. (2013). A cognitive-behavioral treatment for depression in rural American Indian middle school students. American Indian and Alaska Native Mental Health Research, 20(1), 16–34.
Lyon, M. E., Jacobs, S., Briggs, L., Cheng, Y. I., & Wang, J. (2014). A longitudinal, randomized, controlled trial of advance care planning for teens with cancer: Anxiety, depression, quality of life, advance directives, spirituality. Journal of Adolescent Health, 54(6), 710–717.
*Marchant, M. R., Solano, B. R., Fisher, A. K., Caldarella, P., Young, K. R., & Renshaw, T. L. (2007). Modifying socially withdrawn behavior: A playground intervention for students with internalizing behaviors. Psychology in the Schools, 44(8), 779–794.
Mayes, T. L., Bernstein, I. H., Haley, C. L., Kennard, B. D., & Emslie, G. J. (2010). Psychometric properties of the Children’s Depression Rating Scale-Revised in adolescents. Journal of Child and Adolescent psychopharmacology, 20(6), 513–516.
*McCarty, C. A., Violette, H. D., Duong, M. T., Cruz, R. A., & McCauley, E. (2013). A randomized trial of the positive thoughts and action program for depression among early adolescents. Journal of Clinical Child & Adolescent Psychology, 42(4), 554–563.
*McCarty, C. A., Violette, H. D., & McCauley, E. (2010). Feasibility of the positive thoughts and actions prevention program for middle schoolers at risk for depression. Depression Research and Treatment, 2011, 241386.
McIntosh, K., Ty, S. V., & Miller, L. D. (2014). Effects of school-wide positive behavioral interventions and supports on internalizing problems: Current evidence and future directions. Journal of Positive Behavior Interventions, 16(4), 209–218.
*McNaughton, D. B., Cowell, J. M., & Fogg, L. (2015). Efficacy of a Latino mother–child communication intervention in elementary schools. The Journal of School Nursing, 31(2), 126–134.
*Melnyk, B. M., Jacobson, D., Kelly, S. A., Belyea, M. J., Shaibi, G. Q., Small, L., et al. (2015). Twelve-month effects of the COPE healthy lifestyles TEEN program on overweight and depressive symptoms in high school adolescents. Journal of School Health, 85(12), 861–870.
*Melnyk, B. M., Kelly, S., & Lusk, P. (2014). Outcomes and feasibility of a manualized cognitive-behavioral skills building intervention: Group COPE for depressed and anxious adolescents in school settings. Journal of Child and Adolescent Psychiatric Nursing, 27(1), 3–13.
*Mendelson, T., Tandon, S. D., O’Brennan, L., Leaf, P. J., & Ialongo, N. S. (2015). Brief report: Moving prevention into schools: The impact of a trauma-informed school-based intervention. Journal of Adolescence, 43, 142–147.
Merikangas, K. R., He, J. P., Burstein, M., Swanson, S. A., Avenevoli, S., Cui, L., et al. (2010). Lifetime prevalence of mental disorders in US adolescents: results from the National Comorbidity Survey Replication-Adolescent Supplement (NCS-A). Journal of the American Academy of Child and Adolescent Psychiatry, 49(10), 980–989.
*Michael, K. D., George, M. W., Splett, J. W., Jameson, J. P., Sale, R., Bode, A. A., et al. (2016). Preliminary outcomes of a multi-site, school-based modular intervention for adolescents experiencing mood difficulties. Journal of Child and Family Studies, 25(6), 1903–1915.
Miller, F. G., Cohen, D., Chafouleas, S. M., Riley-Tillman, T. C., Welsh, M. E., & Fabiano, G. A. (2015). A comparison of measures to screen for social, emotional, and behavioral risk. School Psychology Quarterly, 30(2), 184–196.
*Miller, D. N., & Cole, C. L. (1998). Effects of social skills training on an adolescent with comorbid conduct disorder and depression. Child & Family Behavior Therapy, 20(1), 35–53.
*Miu, A. S., & Yeager, D. S. (2015). Preventing symptoms of depression by teaching adolescents that people can change: Effects of a brief incremental theory of personality intervention at 9-month follow-up. Clinical Psychological Science, 3(5), 726–743.
*Morsette, A., Swaney, G., Stolle, D., Schuldberg, D., van den Pol, R., & Young, M. (2009). Cognitive behavioral intervention for trauma in schools (CBITS): School-based treatment on a rural American Indian reservation. Journal of Behavior Therapy and Experimental Psychiatry, 40(1), 169–178.
*Morsette, A., van den Pol, R., Schuldberg, D., Swaney, G., & Stolle, D. (2012). Cognitive behavioral treatment for trauma symptoms in American Indian youth: Preliminary findings and issues in evidence-based practice and reservation culture. Advances in School Mental Health Promotion, 5(1), 51–62.
*Mufson, L., Dorta, K. P., Wickramaratne, P., Nomura, Y., Olfson, M., & Weissman, M. M. (2004). A randomized effectiveness trial of interpersonal psychotherapy for depressed adolescents. Archives of General Psychiatry, 61(6), 577–584.
*Müller, S., Rohde, P., Gau, J. M., & Stice, E. (2015). Moderators of the effects of indicated group and bibliotherapy cognitive behavioral depression prevention programs on adolescents’ depressive symptoms and depressive disorder onset. Behaviour Research and Therapy, 75, 1–10.
Mychailyszyn, M. P., Brodman, D. M., Read, K. L., & Kendall, P. C. (2012). Cognitive-behavioral school-based interventions for anxious and depressed youth: A meta-analysis of outcomes. Clinical Psychology: Science and Practice, 19(2), 129–153.
*Noël, L. T., Rost, K., & Gromer, J. (2013). Depression prevention among rural preadolescent girls: A randomized controlled trial. School Social Work Journal, 38(1), 1–18.
Patel, P. G., Stark, K. D., Metz, K. L., & Banneyer, K. N. (2014). School-based interventions for depression. In M. S. Weist, N. A. Lever, C. P. Bradshaw, & J. S. Owens (Eds.), Handbook of school mental health (pp. 369–385). New York: Springer.
*Pössel, P., Martin, N. C., Garber, J., & Hautzinger, M. (2013). A randomized controlled trial of a cognitive-behavioral program for the prevention of depression in adolescents compared with nonspecific and no-intervention control conditions. Journal of Counseling Psychology, 60(3), 432–438.
Puig-Antich, J., & Chambers, W. J. (1983). Schedule for affective disorders and schizophrenia for school-age children (6–18 years). Pittsburgh: Western Psychiatric Institute.
*Puskar, K., Sereika, S., & Tusaie-Mumford, K. (2003). Effect of the Teaching Kids to Cope (TKC©) program on outcomes of depression and coping among rural adolescents. Journal of Child and Adolescent Psychiatric Nursing, 16(2), 71–80.
Radloff, L. S. (1977). The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401.
*Randell, B. P., Eggert, L. L., & Pike, K. C. (2001). Immediate post intervention effects of two brief youth suicide prevention interventions. Suicide and Life-Threatening Behavior, 31(1), 41–61.
Reynolds, W. M. (1987). Reynolds Adolescent Depression Scale (RADS). Odessa, FL: Psychological Assessment Resources.
Rohde, P., Lewinsohn, P. M., & Seeley, J. R. (1994). Are adolescents changed by an episode of major depression? Journal of the American Academy of Child and Adolescent Psychiatry, 33(9), 1289–1298.
*Rohde, P., Stice, E., & Gau, J. M. (2012). Effects of three depression prevention interventions on risk for depressive disorder onset in the context of depression risk factors. Prevention Science, 13(6), 584–593.
*Rohde, P., Stice, E., Shaw, H., & Brière, F. N. (2014). Indicated cognitive behavioral group depression prevention compared to bibliotherapy and brochure control: Acute effects of an effectiveness trial with adolescents. Journal of Consulting and Clinical Psychology, 82(1), 65–74.
*Rohde, P., Stice, E., Shaw, H., & Gau, J. M. (2015). Effectiveness trial of an indicated cognitive-behavioral group adolescent depression prevention program versus bibliotherapy and brochure control at 1-and 2-year follow-up. Journal of Consulting and Clinical Psychology, 83(4), 736–747.
*Roth, R. A., Suldo, S. M., & Ferron, J. M. (2017). Improving middle school students’ subjective well-being: Efficacy of a multicomponent positive psychology intervention targeting small groups of youth. School Psychology Review, 46(1), 21–41.
Rothstein, H. R., Sutton, A. J., & Borenstein, M. (Eds.). (2006). Publication bias in meta-analysis: Prevention, assessment and adjustments. Hoboken, NJ: Wiley.
*Ruffolo, M. C., & Fischer, D. (2009). Using an evidence-based CBT group intervention model for adolescents with depressive symptoms: Lessons learned from a school-based adaptation. Child and Family Social Work, 14(2), 189–197.
*Salloum, A., & Overstreet, S. (2012). Grief and trauma intervention for children after disaster: Exploring coping skills versus trauma narration. Behaviour Research and Therapy, 50(3), 169–179.
*Santiago, C. D., Kataoka, S. H., Hu-Cordova, M., Alvarado-Goldberg, K., Maher, L. M., & Escudero, P. (2015). Preliminary evaluation of a family treatment component to augment a school-based intervention serving low-income families. Journal of Emotional and Behavioral Disorders, 23(1), 28–39.
*Seifer, R., Gouley, K., Miller, A. L., & Zakriski, A. (2004). Implementation of the PATHS curriculum in an urban elementary school. Early Education & Development, 15(4), 471–486.
Sen, B. (2004). Adolescent propensity for depressed mood and help seeking: Race and gender differences. The Journal of Mental Health Policy and Economics, 7(3), 133–145.
Shaffer, D., Fisher, P., Dulcan, M., Davies, M., Piacentini, J., Schwab-Stone, M., et al. (1996). The NIMH Diagnostic Interview Schedule for Children (DISC-2): Description, acceptability, prevalences and performance in the MECA study. Journal of the American Academy of Child and Adolescent Psychiatry, 35, 865–877.
Sheridan, S. M., Welch, M., & Orme, S. F. (1996). Is consultation effective? A review of outcome research. Remedial and Special Education, 17(6), 341–354.
*Shirk, S. R., Kaplinski, H., & Gudmundsen, G. (2009). School-based cognitive-behavioral therapy for adolescent depression: A benchmarking study. Journal of Emotional and Behavioral Disorders, 17(2), 106–117.
*Sibinga, E. M., Webb, L., Ghazarian, S. R., & Ellen, J. M. (2016). School-based mindfulness instruction: An RCT. Pediatrics, 137(1), 1–8.
*Smokowski, P. R., Guo, S., Wu, Q., Evans, C. B., Cotter, K. L., & Bacallao, M. (2016). Evaluating dosage effects for the positive action program: How implementation impacts internalizing symptoms, aggression, school hassles, and self-esteem. American Journal of Orthopsychiatry, 86(3), 310–322.
*Stark, K. D., Arora, P., & Funk, C. L. (2011a). Training school psychologists to conduct evidence-based treatments for depression. Psychology in the Schools, 48(3), 272–282.
*Stark, K. D., Brookman, C. S., & Frazier, R. (1990). A comprehensive school-based treatment program for depressed children. School Psychology Quarterly, 5(2), 111–140.
Stark, K. D., Streusand, W., Arora, P., & Patel, P. (2011b). Treatment of childhood depression: The ACTION treatment program. In P. C. Kendall (Ed.), Child and adolescent therapy: Cognitive behavioral procedures (4th ed.). New York, NY: Guilford Press.
*Stein, B. D., Jaycox, L. H., Kataoka, S. H., Wong, M., Tu, W., Elliott, M. N., et al. (2003). A mental health intervention for schoolchildren exposed to violence: A randomized controlled trial. JAMA, 290(5), 603–611.
Stephan, S. H., Weist, M., Kataoka, S., Adelsheim, S., & Mills, C. (2007). Transformation of children’s mental health services: The role of school mental health. Psychiatric Services, 58(10), 1330–1338.
*Stice, E., Burton, E., Bearman, S. K., & Rohde, P. (2007). Randomized trial of a brief depression prevention program: An elusive search for a psychosocial placebo control condition. Behaviour Research and Therapy, 45(5), 863–876.
*Stice, E., Rohde, P., Gau, J. M., & Wade, E. (2010). Efficacy trial of a brief cognitive-behavioral depression prevention program for high-risk adolescents: Effects at 1-and 2-year follow-up. Journal of Consulting and Clinical Psychology, 78(6), 856–867.
*Stice, E., Rohde, P., Seeley, J. R., & Gau, J. M. (2008). Brief cognitive-behavioral depression prevention program for high-risk adolescents outperforms two alternative interventions: A randomized efficacy trial. Journal of Consulting and Clinical Psychology, 76(4), 595–606.
*Stice, E., Rohde, P., Seeley, J. R., & Gau, J. M. (2010). Testing mediators of intervention effects in randomized controlled trials: An evaluation of three depression prevention programs. Journal of Consulting and Clinical Psychology, 78(2), 273–280.
Stice, E., Shaw, H., Bohon, C., Marti, C. N., & Rohde, P. (2009). A meta-analytic review of depression prevention programs for children and adolescents: Factors that predict magnitude of intervention effects. Journal of Consulting and Clinical Psychology, 77(3), 486.
Stormont, M., Reinke, W. M., Newcomer, L., Marchese, D., & Lewis, C. (2015). Coaching teachers’ use of social behavior interventions to improve children’s outcomes: A review of the literature. Journal of Positive Behavior Interventions, 17(2), 69–82.
Sue, S., Zane, N., Nagayama Hall, G. C., & Berger, L. K. (2009). The case for cultural competency in psychotherapeutic interventions. Annual Review of Psychology, 60, 525–548.
*Thompson, E. A., Eggert, L. L., & Herting, J. R. (2000). Mediating effects of an indicated prevention program for reducing youth depression and suicide risk behaviors. Suicide and Life-Threatening Behavior, 30(3), 252–271.
*Thompson, E. A., Eggert, L. L., Randell, B. P., & Pike, K. C. (2001). Evaluation of indicated suicide risk prevention approaches for potential high school dropouts. American Journal of Public Health, 91(5), 742–752.
*Trudeau, L., Spoth, R., Randall, G. K., Mason, W. A., & Shin, C. (2012). Internalizing symptoms: Effects of a preventive intervention on developmental pathways from early adolescence to young adulthood. Journal of Youth and Adolescence, 41(6), 788–801.
Van Norman, E. R., & Christ, T. J. (2016). Curriculum-based measurement of reading: Accuracy of recommendations from three-point decision rules. School Psychology Review, 45, 296–309.
VanDerHeyden, A. M., Witt, J. C., & Gilbertson, D. (2007). A multi-year evaluation of the effects of a response to intervention (RTI) model on identification of children for special education. Journal of School Psychology, 45(2), 225–256.
Von der Embse, N. P., Kilgus, S. P., Segool, N., & Putwain, D. (2013). Identification and validation of a brief test anxiety screening tool. International Journal of School & Educational Psychology, 1(4), 246–258.
Warner, C. M., & Fox, J. K. (2012). Advances and challenges in school-based intervention for anxious and depressed youth: Identifying and addressing issues of sustainability. School mental health, 4(4), 193–196.
*Weiss, B., Harris, V., Catron, T., & Han, S. S. (2003). Efficacy of the RECAP intervention program for children with concurrent internalizing and externalizing problems. Journal of Consulting and Clinical Psychology, 71(2), 364–374.
Weist, M. D., Lever, N. A., Bradshaw, C. P., & Owens, J. (2014). Further advancing the field of school mental health. In M. Weist, N. Lever, C. Bradshaw, & J. Owens (Eds.), Handbook of school mental health. issues in clinical child psychology (pp. 1–14). Boston, MA: Springer.
*Weisz, J. R., Thurber, C. A., Sweeney, L., Proffitt, V. D., & LeGagnoux, G. L. (1997). Brief treatment of mild-to-moderate child depression using primary and secondary control enhancement training. Journal of Consulting and Clinical Psychology, 65(4), 703–707.
Werner-Seidler, A., Perry, Y., Calear, A. L., Newby, J. M., & Christensen, H. (2017). School-based depression and anxiety prevention programs for young people: A systematic review and meta-analysis. Clinical Psychology Review, 51, 30–47.
*Young, J. F., Benas, J. S., Schueler, C. M., Gallop, R., Gillham, J. E., & Mufson, L. (2016). A randomized depression prevention trial comparing interpersonal psychotherapy—Adolescent skills training to group counseling in schools. Prevention Science, 17(3), 314–324.
*Young, J. F., Makover, H. B., Cohen, J. R., Mufson, L., Gallop, R., & Benas, J. S. (2012). Interpersonal psychotherapy-adolescent skills training: Anxiety outcomes and impact of comorbidity. Journal of Clinical Child & Adolescent Psychology, 41(5), 640–653.
*Young, J. F., Mufson, L., & Davies, M. (2006). Impact of comorbid anxiety in an effectiveness study of interpersonal psychotherapy for depressed adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 45(8), 904–912.
*Young, J. F., Mufson, L., & Gallop, R. (2010). Preventing depression: A randomized trial of interpersonal psychotherapy-adolescent skills training. Depression and Anxiety, 27(5), 426–433.
*Zubernis, L. S., Cassidy, K. W., Gillham, J. E., Reivich, K. J., & Jaycox, L. H. (1999). Prevention of depressive symptoms in preadolescent children of divorce. Journal of Divorce & Remarriage, 30(1–2), 11–36.
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Arora, P.G., Collins, T.A., Dart, E.H. et al. Multi-tiered Systems of Support for School-Based Mental Health: A Systematic Review of Depression Interventions. School Mental Health 11, 240–264 (2019). https://doi.org/10.1007/s12310-019-09314-4
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DOI: https://doi.org/10.1007/s12310-019-09314-4