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. Author manuscript; available in PMC: 2019 Jan 29.
Published in final edited form as: Rep Emot Behav Disord Youth. 2017 Spring;17(2):32–38.

Universal Behavioral/Emotional Health Screening in Schools: Overview and Feasibility

E Rebekah Siceloff, W Joshua Bradley, Kate Flory *
PMCID: PMC6350819  NIHMSID: NIHMS982096  PMID: 30705612

Addressing the emotional and behavioral health needs of children and adolescents is a critical public health challenge. As reflected in these four special issues of EBDY, schools are being increasingly used as a system for delivering mental health services for students and their families (Weist et al., 2003; 2014). School-based universal mental health screening provides important information about the emotional and behavioral health of students and school-level functioning and is recognized as an essential component of a multitiered school behavioral health (SBH) framework. Our purpose in this article is twofold. First, we provide an overview of school-based universal mental health screening, including benefits, limitations, and obstacles to implementation. Second, as evidence to support the feasibility of universal mental health screening in schools, we present our implementation experiences in a South Carolina school district serving students in grades K-12.

Mental Health Disorders and Unmet Need in Children and Adolescents

The prevalence of emotional and behavioral health disorders and unmet mental health need among children and adolescents highlight the need for effective interventions. Studies of community samples have generally found that approximately one in five children and adolescents meet criteria for an emotional or behavioral health disorder (Carter et al., 2010). In a national sample, 13.1% of children and adolescents ages 8 to 15 years met criteria for at least one mental health disorder in the previous 12 months (Merikangas et al., 2010a). Assessing a broader array of disorders in a national sample of 13- to 18-year-old adolescents, the prevalence rate was 40.3% for 12-month disorders (Kessler et al., 2012) and 49.5% for lifetime disorders (Merikangas et al., 2010b).

Despite the prevalence of mental health disorders among children and adolescents in the United States, the utilization of services to treat these disorders is broadly lacking (Dvorsky et al., 2014). In national studies, 50% or less of children and adolescents with a mental health disorder had received services in the previous 12 months (Costello et al., 2014; Merikangas et al., 2010a). This low utilization is directly related to numerous barriers that limit service accessibility, including availability of services, lack of transportation, and financial and time costs (Owens et al., 2002). Left untreated, behavioral and emotional concerns are more likely to persist into adulthood and to require more intensive services (Hefiinger et al., 2015; Torio et al., 2015). Therefore, timely identification of concerns and intervention are critical to disrupt this trajectory.

School Behavioral Health

Over the past two decades, the field of SBH has been gaining momentum in the United States and in other countries (Foster et al., 2005; Rowling & Weist, 2004). Studies examining service use patterns have found SBH programs to be the primary source of services for youth with emotional and behavioral health concerns (Angold et al., 2002; Burns et al., 1995; Costello et al., 1996; 2014). However, the type and quality of services provided in schools vary considerably as do the underlying assumptions about what role schools should play in addressing students’ mental health needs. Traditional mental health services in the school setting have largely operated under a refer-test-place model that focuses primarily on the assessment of individual students to determine their eligibility for special education services or referrals for other supports (Dowdy et al., 2010). This service model emphasizes assessment and treatment services for students at the highest levels of risk. Similarly, under the “wait-to-fail” model (Glover & Albers, 2007), students are referred for services in response to emotional or behavioral difficulties that are apparent and have become a cause for concern. Given the reactive nature of these traditional approaches, students with unmet mental health needs may be overlooked or their need for services may not be recognized until after their symptoms have intensified and early intervention services are no longer likely to be beneficial (Dvorsky et al., 2014). Further, because these approaches focus on emotional and behavioral health concerns at the level of the individual student, they are unlikely to have a meaningful impact at the population level.

Universal Mental Health Screening in Schools

SBH programs are most beneficial when appropriately tailored to meet a school’s needs using comprehensive data on the functioning of the entire student body (Dowdy et al., 2010). Therefore, a critical first step in the effective implementation of a multitiered SBH model is to systematically evaluate all students in an identified group (e.g., within a school or district) on behavioral and emotional criteria using a universal screening procedure (Glover & Albers, 2007). A primary objective of this process is to differentiate students based on whether or not their behaviors and characteristics are associated with an elevated risk of having or of developing a mental health disorder (Dvorsky et al., 2014; Glover & Albers, 2007; Lane, Oakes, Ennis et al., 2014; Lane, Oakes, Menzies et al., 2013). Because all students are assessed, fewer students with unmet mental health needs are overlooked. In addition to individual-level data, universal screening provides comprehensive information about school-level functioning that allows a more data-driven approach to the delivery of SBH at all tiers (Humphrey & Wigelsworth, 2016).

Students identified as at-risk are referred for additional assessment or connected with appropriate, evidence-based supports, with the goal of meeting their individual needs through early intervention (Lane et al., 2010). Ideally, universal mental health screening should be implemented as part of a full continuum of SBH programs and services available to students (Weist et al., 2007). However, despite substantial evidence to support the provision of mental health care in schools using an expanded SBH model (Durlak et al., 2011; Wilson & Lipsey, 2007), challenges to implementation (e.g., funding constraints and other limited resources) impede widespread adoption. As we discuss throughout the remaining sections, overcoming these challenges requires the collaborative engagement of families, schools, and other relevant service providers, particularly those in the mental health system.

Implementing Universal Mental Health Screening: Challenges and Considerations

Despite increasing recognition that universal mental health screening is an important means of identifying children and adolescents with emotional and behavioral difficulties, it is estimated that less than 15% of schools currently implement procedures to systematically evaluate students’ mental health needs (Bruhn et al., 2014). This likely refiects the limited availability of resources necessary to support universal screening of students’ mental health needs as well as misconceptions and other issues that reduce the acceptability of implementing these procedures in a school setting (Humphrey & Wigelsworth, 2016; Weist et al., 2007). We review these challenges and considerations in the sections that follow.

Practical Challenges and Measurement Selection.

A central challenge to implementing universal screening in a school setting is the availability of resources necessary to systematically evaluate, identify, and monitor the mental health needs of an entire student population (Dowdy et al., 2010; Weist et al., 2007). Therefore, a number of practical considerations related to implementation should be considered when building capacity for universal screening in schools (Dowdy et al., 2010). Critical to this process is the selection of a screening tool that is contextually and developmentally appropriate, psychometrically sound, and usable (Glover & Albers, 2007). For many schools, this may be challenging due to the limited availability of personnel with adequate training or time to identify psychometrically sound universal screening measures. This is often the result of personnel being constrained to a particular role (e.g., school psychologists only evaluating students, mental health counselors only delivering treatment) and budget limitations (see Glover & Albers, 2007; Splett et al., 2013). In addition, collecting data for hundreds of students in a school or thousands of students across an entire school district requires data infrastructure to efficiently collect and store universal screening data (Glover & Albers, 2007). Electronic data collection and management systems are available that can streamline the data acquisition process and automate scoring screening measures used to identify at-risk students. However, these systems are often costly and may not be economically feasible for many schools. Fortunately, a number of robust mental health screening measures are available that are brief and affordable or free to access, such as the Strengths and Difficul-ties Questionnaire (SDQ; Goodman, 1997), making them well-suited for use in a school setting (Connors et al., 2015).

When choosing a screening instrument, it is important that the objectives for undertaking the screening process are clear so as to ensure that the selected measure not only meets the needs of the school but also has psychometric properties that align with the screening goals (Dvorsky et al., 2014; Humphrey & Wigelsworth, 2016). One issue to consider is the type of behaviors assessed by the instrument. Many universal screening instruments have demonstrated excellent sensitivity in identifying youth with behavior problems, but others have significantly lower sensitivity and specificity for identifying youth with less observable emotional problems or “internalizing” problems such as depression, anxiety, and symptoms of traumatic stress (Cook et al., 2011; Severson et al., 2007). A likely reason for this is that students with behavior problems are more easily identified by teachers completing the screening tool, because these behaviors often result in frequent distractions and other problem behaviors that are easily observed in the classroom. In contrast, students with internalizing problems are often more difficult for teachers to identify, because these children are withdrawn, quiet, and may fit the profile of a successful student (Cook et al., 2011; Gresham & Kern, 2004). Given this measurement limitation, some recently developed universal screening instruments place increased emphasis on the identification of youth with emotional problems, including the Student Risk Screening Scale—Internalizing and Externalizing (SRSS-IE; Lane, Oakes, Carter et al., 2013) and Student Internalizing Behavior Screener (SIBS; Cook et al., 2011). However, additional research is still needed to improve psycho-metric properties of universal screening instruments for identifying students with emotional problems.

Beyond screening students for existing emotional or behavioral health problems, research suggests that universal screeners should also focus on identifying known risk and protective factors associated with mental health disorders (Levine et al., 2005; Severson et al., 2007). Consistent with a public health approach to child and adolescent mental health, universal screening that assesses the presence of risk and protective factors and the presence of mental health difficulties can be used to identify not only students who require treatment, but also those who would benefit from early intervention or targeted preventative services.

Misconceptions, Concerns, and Other Considerations.

In addition to the practical challenges to implementation, universal mental health screening in schools may raise other issues that have the potential to limit stakeholder “buy-in” (Humphrey & Wigelsworth, 2016; Weist et al., 2007). Involving stakeholders, including not only teachers and other school personnel but also families, in implementation planning is essential for building trusting relationships that foster collaboration. These collaborative efforts allow stakeholders to voice concerns and to help resolve issues that might otherwise pose a threat to the social validity of the universal mental health screening process. Social validity refers to the value or social importance attributed to a new method, idea, or product by direct and indirect consumers (Hurley, 2012). The extent to which universal mental health screening is viewed as socially valid is critically relevant to its adoption in school settings (Humphrey & Wigelsworth, 2016).

The social validity of universal mental health screening in schools is dependent upon the extent to which stakeholders regard the process to be acceptable, to be feasible, and to have utility. Each of these components is important to consider when planning to implement universal screening procedures in a school setting. Acceptability refers to the extent to which stakeholders view universal mental health screening as necessary or socially important. Although well-being and mental health promotion are likely to be broadly considered important, stakeholders should be able to see the value in conducting universal mental health screenings in the school setting as an acceptable means to accomplish these broader objectives. Stakeholders who do not find value in this process may have concerns that diminish the acceptability of universal screening. For example, families may perceive mental health screening as an intrusive over-reach of the government or a violation of their right to privacy. Misconceptions about informed consent and procedural safeguards likely contribute to these concerns. Further, concerns have been raised about possible stigmatization that may occur as a result of the problem-focused approach that is typical in mental health screening and the possible consequences of being identified as at-risk (Williams, 2013).

Utility refers to the extent to which universal screening is useful to stakeholders. It is important that the intended use of universal mental health screening data is clearly articulated and disseminated to stakeholders. Universal screening data provide important baseline information and allow monitoring of both individual and population-level change. However, consideration must be given to the ability to continue monitoring students’ mental health and what response is required of schools and parents to address the needs of students identified as at-risk (e.g., intervention services/pharmaceutical treatment). Ideally, universal mental health screening should be one aspect of a full continuum of programs and services available to address the emotional and behavioral health needs of students in the school setting. Capacity for the expanded model of SBH is often achieved through a collaborative relationship between school- and community-based mental health providers (see Weist, 1997). However, in many schools and districts, infrastructure may not exist to support this model.

Finally, feasibility refers to the extent to which the proposed procedures for implementing universal screenings in schools are satisfactory and are able to be implemented. To increase the likelihood that screening procedures are viewed as feasible for teachers and school personnel, screening measures should be viewed as acceptable and not overly burdensome by the staff completing them (Dowdy et al., 2010; Glover & Albers, 2007). Teachers often serve as the primary or sole informants in universal mental health screening (Dowdy et al., 2010). As such, teachers are often tasked with completing the selected screening measure for all of their students, which can seem like a burdensome addition to their regular responsibilities (Glover & Albers, 2007). Thus, it is important that the length of the screening measure is considered and that the value of school-wide universal screening as an effective means to identify youth with emotional and behavioral health concerns is effectively communicated to teachers and school personnel (Humphrey & Wigelsworth, 2016).

In addition to concerns about the time required to complete the screening measure, teachers may also question whether they are equipped with the knowledge necessary to evaluate their students’ emotional and behavioral health. Although it is widely accepted that multiple informants (e.g., parents and teachers) are important for comprehensive mental health evaluation in children (Huns-ley & Mash, 2007; Sowerby & Tripp, 2009), this is likely inconsistent with the need for universal screening procedures that are minimally intrusive and maximally efficient and cost-effective. Supporting the role of teachers as informants, teacher ratings have been shown to have greater predictive validity than ratings of other informants (e.g., parents)—that is, they are better able to predict a theoretically relevant future state, such as whether a student will meet diagnostic criteria for a mental health disorder (Dowdy et al., 2010). However, teachers may be less accurate in their evaluation of internalizing difficulties than externalizing behaviors (Atzaba-Poria et al., 2004). To assuage teachers’ concerns, it is important to clearly communicate any necessary training required to complete screening measures and to provide teachers with other relevant information to bolster their confidence to complete the measures.

These issues and other aspects of implementation have the potential to infiuence the extent to which stakeholders perceive a universal mental health screener to be feasible. Thus, it is important to understand and address relevant issues to bolster the feasibility of the process. Much of the available research evaluating the feasibility of implementing a universal mental health screening in a school setting is based on small-scale implementation or systematic evaluations conducted within a restricted range of grades (Burke et al., 2012; Chin et al., 2013; Dowdy et al., 2015; Owens et al., 2015). In the sections that follow, we provide an applied example of a universal mental health screening that was implemented across all schools in a school district, representing all students enrolled in grades K-12. We thoroughly describe all steps in the process of implementing the screening because these are important for insuring the acceptability, utility, and feasibility of the screening process.

Applied Example: Overview of Project

Our universal mental health screening took place as part of the ongoing University of South Carolina (USC) Project to Learn about Youth, a study of children’s and adolescents’ mental health, funded by the U.S. Centers for Disease Control and Prevention (CDC) and conducted in collaboration with a school district in central South Carolina. The USC Project to Learn about Youth has three purposes:

  1. To estimate the proportion of children and adolescents in grades K-12 in the school district with emotional or behavioral health concerns, including tic disorders;

  2. To describe rates of current and previous mental health treatment in this population; and

  3. To quantify the misuse of medications prescribed to treat emotional or behavioral health concerns in this population.

An additional objective is to examine change in prevalence rates of emotional or behavioral health concerns, including tic behaviors, over time. To meet this objective, identical data collection procedures were conducted twice over two consecutive academic years, representing two distinct iterations of the project. Data collection began in the fall of each academic year (AY), with the first iteration in AY 2014–2015 and the second iteration in AY 2015–2016. Throughout this report, these iterations of the project are referred to as “Fall 2014” and “Fall 2015,” respectively.

The objectives of the USC Project to Learn about Youth are addressed in two stages of data collection: Stage 1—A districtwide, universal teacher screening of emotional/behavioral concerns, including tic disorders, among students in grades K-12, and Stage 2—A comprehensive evaluation of these health concerns among a subset of screened students. This report describes Stage 1 procedures and results pertinent to feasibility of universal mental health screening.

School District Description

All regular and special education students in grades K-12 in the participating school district were eligible for the Stage 1 universal screening for emotional/behavioral health concerns, including behavioral tics. The district, situated in central South Carolina, includes urban, suburban, and rural areas and subsumes an entire county. According to census data, the racial distribution of county residents under the age of 18 is 30% African American, 67% Caucasian, and 3% other, and the median household income is $38,804. The school district includes 20 schools: 11 elementary, four middle, and three high schools, as well as one vocational school for high school students and one personally tailored, alternative learning center for middle and high school students. According to the South Carolina Department of Education district “report card,” 58% of students in the district were in poverty in 2016. In fall 2014, the first year of our Stage 1 universal screening, the K-12 enrollment of the district was 10,443; in fall 2015, our second year, enrollment was 10,454.

Study Procedures

Building a Relationship With the District.

Before beginning the first Stage 1 universal mental health screening for the USC Project to Learn about Youth, our research team invested a great deal of time and energy in developing a collaborative, working relationship with the participating school district. This entailed meeting with district office personnel, including the public relations coordinator, and principals of all 20 schools in the district. In addition, we presented information about the project to teachers at all 20 schools during in-service trainings at the beginning of AY 2014–2015. Finally, we presented the project to members of the district’s school board, including the superintendent. In each meeting or presentation, we summarized the goals of the project and the potential benefits to participating students and their families (e.g., identification of students in crisis as well as those not previously identified as having a mental health issue, families directed to appropriate services), to the district (e.g., received a report summarizing screener results to be used to better understand the emotional and behavioral health needs of the student population and/or to document need for SBH funding in potential grant applications), and to the field of science. We also allocated time during meetings to address concerns and answer questions. District-level administrators and principals who attended these meetings articulated strong support for the project and felt it would be beneficial to the students and their families as well as to the school district.

Importantly, in each of our meetings with district personnel, we emphasized our desire to work collaboratively with the district by bringing not just a fully planned research project to implement in the district, but by including district personnel feedback and suggestions into each step of the project during the planning process. For example, in developing a website describing the project for teachers and parents, we asked the district school psychologist and public relations coordinator to make suggestions. Similarly, these personnel suggested revisions on drafts of parent mailings about the project and assisted us in preparing press releases and scripts for automated parent informational calls. We also worked with district personnel to develop a procedure for the Stage 1 screening that was believed to be feasible and acceptable to principals and teachers, and we pilot-tested this procedure with a small group of teachers before the project began. This openness, willingness to work together, and acknowledgement of the expertise of school district personnel about their own students and parents likely played a large role in the establishment of a strong working relationship, as well as in the success of our universal screening procedures. In addition, in the rare instances in which a parent has voiced concerns or complaints about our study, or other unforeseen events have occurred, we have had the full support of district personnel in handling these situations.

Consent Process.

To meet the research objectives of the USC Project to Learn about Youth (e.g., to estimate the proportion of youth in grades K-12 in the school district with emotional or behavioral health concerns, including tic disorders), it was crucial to include the majority of the students in the district in each year’s universal screening phase. To accomplish this, in consultation with the district lawyer and other central office personnel, and USC’s Institutional Review Board (IRB), we elected to use a “passive consent” or opt-out procedure for the Stage 1 screening. Passive consent means that consent is assumed unless parents (or legal guardians) opt out of the screening procedure for their child. This is contrasted with active consent, in which parents (or legal guardians) must explicitly give permission (i.e., through a signed consent form or permission slip) for involvement in the screening process. Passive consent typically results in much higher study participation rates and is appropriate when study procedures carry little to no risk for participants. In our case, we believed that having teachers complete a short, online, anonymous (i.e., only school ID numbers were used and no other identifying information was collected) survey on students’ emotional and behavior health in the classroom posed little risk to teachers, students, or families, and thus was appropriate for a passive consent process.

The biggest concern with using passive consent is that when parents do not opt out for their children, it is unclear whether this is because they did not receive information on the study (i.e., either study information never made it to the parent, or the parent did not look at the information provided) or because they processed the information and decided to allow their child to participate.To circumvent this concern, with the district’s help we undertook an extensive campaign to inform parents of the USC Project to Learn about Youth universal screening phase prior to any data collection. This included multiple opportunities for parents to opt out of the screening for their child. All procedures described below were repeated for the second iteration of the project.

First, we constructed a detailed website describing the project to parents. The web-site included project funding information, a thorough description of procedures, risks and benefits, biographies of study staff, a copy of the online teacher screener questionnaire, frequently asked questions, and contact information for study staff if parents had concerns or questions or wished to opt out for their child. All other correspondences with parents about the project included the website address.

Second, with the help of the district public relations coordinator, we prepared a press release about the study and the script for an automated phone call to parents that originated from the superintendent’s office.

Third, we sent parents two informational mailings, both of which included a postage-paid opt out postcard parents could complete and return if they did not want their child to participate in the screening phase. The first of these mailings was sent through the USPS to the address the district had on record for the child. The second was sent home with the child from school and addressed to the parents. The press release and automated phone call from the district went out on the day the first letter was mailed and encouraged parents to look for the letters. We allowed parents two to three weeks to return the opt-out postcards before we moved into the data collection phase. It was our hope that the multiple opportunities parents had to receive information about the study would reduce concerns associated with the passive consent process. Opt-out rates are described below in the results section.

Universal Screening.

Once the passive consent procedure was completed, we began collecting screening data from teachers for all children in the district, except for those whose parents opted out of the study. We used an online screener survey, administered through Qualtrics (www.qualtrics.com), composed of items from widely used and validated measures of teacher-reported internalizing and externalizing symptoms among youth in grades K-12. This included the 25-item Strengths and Difficulties Questionnaire (SDQ; Goodman, 1997) and the 28-item BASC-2 Behavioral and Emotional Screening System (BESS; Dowdy et al., 2011; Kamphaus & Reynolds, 2007)). Two additional items were used to assess whether students displayed tics currently or in the past. The 55-item survey took appropriate four to five minutes to complete per child.

One teacher for each student was identified as the survey respondent. For elementary school students, the primary teacher was asked to complete the survey. For middle school students, the first-period teacher was selected to be the survey respondent. Surveys were completed for high school students by their second-block teacher. Prior to beginning data collection, teachers were instructed to use the students’ school ID (not their names) and to keep responses confidential. In recognition of their contribution to the project, teachers received a small monetary incentive valuing $4 for each completed survey.

Results Supporting Feasibility

Of the 10,443 students enrolled at the start of Stage 1 in fall 2014, teachers completed an online screener survey for a total of 7,159 students, yielding an overall screener completion rate of 68.6%. The completion rate was highest among students in elementary and middle school (74.4% and 71.4%, respectively) and lowest among students in high school (56.9%). Students whose parents/caregivers opted out of the study represented approximately 10% of all enrolled students. Excluding these students, the overall screener completion rate was 76.7%.

Of the 10,454 students enrolled at the start of Stage 1 in fall 2015, teachers completed an online screener survey for a total of 7,161 students, yielding an overall screener completion rate of 68.5%. The completion rate was highest among students in elementary and middle school (73.9% and 72.8%, respectively) and lowest among students in high school (56.5%). Students whose parents/caregivers opted out of the study represented approximately 7% of all enrolled students. Excluding these students, the overall screener completion rate was 73.9%.

The survey completion rates observed in fall 2014 and fall 2015 were highly comparable and provide evidence that teachers completed the universal screener for the majority (68.6% and 68.5%, respectively) of students in the district. In both 2014 and 2015, completion rates were highest for elementary (74.4% and 73.9%, respectively) and middle school students (71.4% and 72.8%, respectively) and lowest for high school students (56.9% and 56.5%, respectively). These rates suggests that, across all grade levels, the universal screening process was acceptable to most teachers. Further, the stability of these rates indicates that support for the process remained stable over time.

Comment

This article describes our experiences implementing a universal mental health screening as part of the ongoing University of South Carolina (USC) Project to Learn about Youth, a study of children’s and adolescents’ mental health. Based on our observations during this process and as evidenced by teacher and school personnel feedback and the overall screener completion rate, we were able to successfully implement a district-wide universal mental health screening that was acceptable, feasible, and had utility.

Critical to the success of the mental health screening process was a collaborative approach that was established prior to implementation and that we continue to foster. During planning, we sought out the feedback of school administrators, teachers, and other personnel, and we allowed their input to help guide implementation planning. Having the support and buy-in from these key stakeholders was essential for ensuring the acceptability of the screening procedures and for identifying and addressing obstacles that might otherwise have diminished the feasibility of the universal mental health screening. Further, by engaging stakeholders in the planning, we were able to engage in discourse about the importance of students’ mental health, with regard to both general well-being and academic achievement, and the role of schools in identifying those with unmet mental health needs. This provided a platform for district and school personnel to discuss their experiences and concerns and to consider the benefits of universal mental health screening within an educational setting. These conversations have helped bolster support for the utility of universal mental health screening among district and school personnel, who in turn, enthusiastically endorsed our project.

Importantly, buy-in from the school district was critical for earning the trust and support of the families it serves. The school district conveyed support for the project by sending out a press release, initiating automated calls, and countersigning letters that were sent to families with information about the mental health screening. It is likely that families were more willing to support the universal mental health screening knowing that the school district was involved in implementation planning and had vetted and approved the screening instrument and procedures. Further, the school district helped support an extensive campaign to inform parents of these procedures and that included multiple opportunities for parents to opt out of the process.

The success of our universal mental health screening notwithstanding, there are a number of important caveats. First, our screening procedures were implemented in a school district with research funding support from the CDC. This funding allowed the formation of a research team at the University of South Carolina, composed of the principal investigator, paid staff, and undergraduate and graduate student volunteers. This team took the lead in all aspects of planning and implementation of screening procedures, including coordinating meetings with district and school personnel, selecting acceptable screening instruments, establishing and providing technology support for an online data collection system, and maintaining and managing screening data. In the absence of the funding to support the formation of a university-affiliated research team, district and school personnel would be responsible for this process. This raises important issues regarding the ability of schools to access the resources necessary to implement and maintain universal mental health screening procedures.

Despite efforts to advance universal mental health screening in schools and the broader SBH agenda, a lack of funding for necessary resources along with other obstacles (e.g., stigmatization of mental health disorders) have impeded the systematic adoption of evidence-based practices in schools (Bruhn et al., 2014; Humphrey & Wigelsworth, 2016). Overcoming these obstacles will require the attention and collaborative engagement of stakeholders across various contexts who are committed to promoting the mental health of children and adolescents by advocating for meaningful SBH policies and practices. Such advocacy should represent not only mental health professionals, school personnel, researchers, and families, but also members of the broader community, legislators, and policymakers. Further, data are needed that demonstrate the need for policies that support universal mental health screening as well SBH programs to address the mental health needs of students. Universal mental health screening in the school setting is an important tool for gathering these data; however, the issues that are prompting the need for policy change are the same issues that make it difficult to implement these screening procedures. Therefore, funding for studies such as we describe in this article plays an important role in achieving greater advocacy for meaningful SBH policy change by providing a means to gather universal screening data.

Studies of community samples have generally found that approximately one in five children and adolescents meet criteria for an emotional or behavioral health disorder.

Students with internalizing problems are often more difficult for teachers to identify, because these children are withdrawn, quiet, and may fit the profile of a successful student.

It is important that the length of the screening measure is considered and that the value of school-wide universal screening as an effective means to identify youth with emotional and behavioral health concerns is effectively communicated to teachers and school personnel.

In each of our meetings with district personnel, we emphasized our desire to work collaboratively with the district by bringing not just a fully planned research project to implement in the district, but by including district personnel feedback and suggestions into each step of the project during the planning process.

This openness, willingness to work together, and acknowledgement of the expertise of school district personnel about their own students and parents likely played a large role in the establishment of a strong working relationship, as well as in the success of our universal screening procedures.

The school district conveyed support for the project by sending out a press release, initiating automated calls, and countersigning letters that were sent to families with information about the mental health screening.

References

  1. Angold A, Erkanli A, Farmer EM, Fairbank JA, Burns BJ, Keeler G, & Costello EJ (2002). Psychiatric disorder, impairment, and service use in rural African American and white youth. Archives of general psychiatry, 59(10), 893–901. [DOI] [PubMed] [Google Scholar]
  2. Atzaba-Poria N, Pike A, & Barrett M (2004). Internalising and externalising problems in middle childhood: A study of Indian (ethnic minority) and English (ethnic majority) children living in Britain. International Journal of Behavioral Development, 28(5), 449–460. [Google Scholar]
  3. Bruhn AL, Woods-Groves S, & Huddle S (2014). A preliminary investigation of emotional and behavioral screening practices in K–12 schools. Education and Treatment of Children, 37(4), 611–634. [Google Scholar]
  4. Burke MD, Davis JL, Lee YH, Hagan-Burke S, Kwok OM, & Sugai G (2012). Universal screening for behavioral risk in elementary schools using SWPBS expectations. Journal of Emotional and Behavioral Disorders, 20(1), 38–54. [Google Scholar]
  5. Burns BJ, Costello EJ, Angold A, Tweed D, Stangl D, Farmer E, & Erkanli A (1995). Children’s mental health service use across service sectors. Health Affairs, 14(3), 147–159. [DOI] [PubMed] [Google Scholar]
  6. Carter AS, Wagmiller RJ, Gray SA, McCarthy KJ, Horwitz SM, & Briggs-Gowan MJ (2010). Prevalence of DSM-IV disorder in a representative, healthy birth cohort at school entry: Sociodemo-graphic risks and social adaptation. Journal of the American Academy of Child & Adolescent Psychiatry, 49(7), 686–698. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Chin JK, Dowdy E, & Quirk MP (2013). Universal Screening in Middle School Examining the Behavioral and Emotional Screening System. Journal of Psychoeducational Assessment, 31(1), 53–60. [Google Scholar]
  8. Connors EH, Arora P, Curtis L, & Stephan SH (2015). Evidence-based assessment in school mental health. Cognitive and Behavioral Practice, 22(1), 60–73. [Google Scholar]
  9. Cook CR, Rasetshwane KB, Truelson E, Grant S, Dart EH, Collins TA, & Sprague J (2011). Development and validation of the Student Internalizing Behavior Screener: Examination of reliability, validity, and classification accuracy. Assessment for Effective Intervention, 36(2), 71–79. [Google Scholar]
  10. Costello EJ, Angold A, Burns BJ, Stangl DK, Tweed DL, Erkanli A, & Worthman CM (1996). The Great Smoky Mountains Study of Youth: Goals, design, methods, and the prevalence of DSM-III-R disorders. Archives of general psychiatry, 53(12), 1129–1136. [DOI] [PubMed] [Google Scholar]
  11. Costello EJ, He JP, Sampson NA, Kessler RC, & Merikangas KR (2014). Services for adolescents with psychiatric disorders: 12-month data from the National Comorbidity Survey–Adolescent. Psychiatric Services, 65(3), 359–366. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Dowdy E, Furlong M, Raines TC, Bovery B, Kauffman B, Kamphaus RW, Dever BV, Price M, & Murdock J (2015). Enhancing school-based mental health services with a preventive and promotive approach to universal screening for complete mental health. Journal of Educational and Psychological Consultation, 25(2–3), 178–197. [Google Scholar]
  13. Dowdy E, Ritchey K, & Kamphaus RW (2010). School-based screening: A population-based approach to inform and monitor children’s mental health needs. School Mental Health, 2(4), 166–176. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Dowdy E, Twyford JM, Chin JK, DiStefano CA, Kamphaus RW, & Mays KL (2011). Factor structure of the BASC–2 Behavioral and Emotional Screening System Student Form. Psychological Assessment, 23(2), 379–387. [DOI] [PubMed] [Google Scholar]
  15. Durlak JA, Weissberg RP, Dymnicki AB, Taylor RD, & Schellinger KB (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] [PubMed] [Google Scholar]
  16. Dvorsky MR, Girio-Herrera E, & Owens JS (2014). School-based screening for mental health in early childhood In Handbook of School Mental Health (pp. 297–310). New York: Springer. [Google Scholar]
  17. Foster S, Rollefson M, Doksum T, Noonan D, Robinson G, & Teich J (2005). School Mental Health Services in the United States, 2002–2003 . Washington, DC: U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration. [Google Scholar]
  18. Glover TA, & Albers CA (2007). Considerations for evaluating universal screening assessments. Journal of School Psychology, 45(2), 117–135. [Google Scholar]
  19. Goodman R (1997). The Strengths and Difficulties Questionnaire: A research note. Journal of Child Psychology and Psychiatry, 38(5), 581–586. [DOI] [PubMed] [Google Scholar]
  20. Gresham FM, & Kern L (2004). Internalizing behavior problems in children and adolescents In Rutherford R, Quinn M, & Mathur S (Eds.). Handbook of Research in Behavior Disorders (pp. 262–281). New York: Guilford. [Google Scholar]
  21. Hefiinger CA, Shaw V, Higa-McMillan C, Lunn L, & Brannan AM (2015). Patterns of Child Mental Health Service Delivery in a Public System: Rural Children and the Role of Rural Residence. Journal of Behavioral Health Services & Research, 42(3), 292–309. [DOI] [PubMed] [Google Scholar]
  22. Humphrey N, & Wigelsworth M (2016). Making the case for universal school-based mental health screening. Emotional and Behavioural Difficulties, 21(1), 22–42. [Google Scholar]
  23. Hunsley J, & Mash EJ (2007). Evidence-based assessment. Annual Review of Clinical Psychology, 3, 29–51. [DOI] [PubMed] [Google Scholar]
  24. Hurley JJ (2012). Social validity assessment in social competence interventions for preschool children: A review. Topics in Early Childhood Special Education, 32(3), 164–174. [Google Scholar]
  25. Kamphaus RW, & Reynolds CR (2007). BASC-2 Behavioral and Emotional Screening System Manual. Circle Pines, MN: Pearson. [Google Scholar]
  26. Kessler RC, Avenevoli S, Costello EJ, Georgia-des K, Green JG, Gruber MJ, ... Petukhova M (2012). Prevalence, persistence, and sociodemographic correlates of DSM-IV disorders in the National Comorbidity Survey Replication Adolescent Supplement. Archives of General Psychiatry, 69(4), 372–380. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Lane KL, Oakes WP, Carter EW, Lambert WE, & Jenkins AB (2013). Initial evidence for the reliability and validity of the Student Risk Screening Scale for internalizing and externalizing behaviors at the middle school level. Assessment for Effective Intervention, 39(1), 24–38. [Google Scholar]
  28. Lane KL, Oakes WP, Ennis RP, & Hirsch SE (2014). Identifying students for secondary and tertiary prevention efforts: How do we determine which students have tier 2 and tier 3 needs? Preventing School Failure : Alternative Education for Children and Youth, 58, 171–182. [Google Scholar]
  29. Lane KL, Oakes W, & Menzies H (2010). Systematic screenings to prevent the development of learning and behavior problems: Considerations for practitioners, researchers, and policy makers. Journal of Disability Policy Studies, 21(3), 160–172. [Google Scholar]
  30. Lane KL, Oakes WP, Menzies HM, Oyer J, & Jenkins A (2013). Working within the context of three-tiered models of prevention: Using schoolwide data to identify high school students for targeted supports. Journal of Applied School Psychology, 29(2), 203–229. [Google Scholar]
  31. Levine M, Perkins DD, & Perkins DV (Eds.). (2005). Prevention. Principles of Community Psychology: Perspectives and Applications (3rd ed., pp. 271–325). New York: Oxford University Press. [Google Scholar]
  32. Merikangas KR, He JP, Brody D, Fisher PW, Bourdon K, & Koretz DS (2010. a). Prevalence and treatment of mental disorders among US children in the 2001–2004 NHANES. Pediatrics, 125(1), 75–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Merikangas KR, He JP, Burstein M, Swanson SA, Avenevoli S, Cui L, Benjet C, Georgiades K, & Swendsen J (2010b). Lifetime prevalence of mental disorders in U.S. adolescents: Results from the National Comorbidity Survey Replication–Adolescent Supplement (NCS-A). Journal of the American Academy of Child & Adolescent Psychiatry, 49(10), 980–989. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Owens PL, Hoagwood K, Horwitz SM, Leaf PJ, Poduska JM, Kellam SG, & Ialongo NS (2002). Barriers to children’s mental health services. Journal of the American Academy of Child & Adolescent Psychiatry, 41(6), 731–738. [DOI] [PubMed] [Google Scholar]
  35. Owens JS, Storer J, Holdaway AS, Serrano VJ, Watabe Y, Himawan LK, ... & Andrews N (2015). Screening for social, emotional, and behavioral problems at kindergarten entry: Utility and incremental validity of parent report. School Psychology Review, 44(1), 21–40. [Google Scholar]
  36. Pierce CD, Nordness PD, Epstein MH, & Cullinan D (2016). Applied examples of screening students at risk of emotional and behavioral disabilities. Intervention in School and Clinic, 52(1), 6–11. [Google Scholar]
  37. Rowling L, & Weist M (2004). Promoting the growth, improvement and sustainability of school mental health programs worldwide. International Journal of Mental Health Promotion, 6(2), 3–11. [Google Scholar]
  38. Severson HH, Walker HM, Hope-Doolittle J, Kratochwill TR, & Gresham FM (2007). Proactive, early screening to detect behaviorally at-risk students: Issues, approaches, emerging innovations, and professional practices. Journal of School Psychology, 45(2), 193–223. [Google Scholar]
  39. Sowerby P, & Tripp G (2009). Evidence-based assessment of attention-deficit/hyperactivity disorder (ADHD) In Matson JL et al. (Eds.). Assessing Childhood Psychopathology and Developmental Disabilities (pp. 209–239). New York: Springer. [Google Scholar]
  40. Splett JW, Fowler J, Weist MD, McDaniel H, & Dvorsky M (2013). The critical role of school psychology in the school mental health movement. Psychology in the Schools, 50(3), 245–258. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Torio CM, Encinosa W, Berdahl T, McCormick MC, & Simpson LA (2015). Annual report on health care for children and youth in the United States: National estimates of cost, utilization and expenditures for children with mental health conditions. Academic Pediatrics, 15(1), 19–35. [DOI] [PubMed] [Google Scholar]
  42. Weist MD (1997). Expanded school mental health services In Ollendick TH & R.J. (Eds.). Advances in Clinical Child Psychology (pp. 319–352): New York: Plenum. [Google Scholar]
  43. Weist MD, Evans SW, & Lever NA (Eds.) (2003). Handbook of School Mental Health: Advancing Practice and Research. New York: Springer. [Google Scholar]
  44. Weist MD, Lever NA, Bradshaw CP, & Owens JS (Eds.). (2013). Handbook of School Mental Health: Research, Training, Practice, and Policy. New York: Springer. [Google Scholar]
  45. Weist MD, Rubin M, Moore E, Adelsheim S, & Wrobel G (2007). Mental health screening in schools. Journal of School Health, 77(2), 53–58. [DOI] [PubMed] [Google Scholar]
  46. Wilson SJ, & Lipsey MW (2007). School-based interventions for aggressive and disruptive behavior: Update of a meta-analysis. American Journal of Preventive Medicine, 33(2), S130–S143. [DOI] [PMC free article] [PubMed] [Google Scholar]

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