Journal of Psychology & Psychotherapy

Journal of Psychology & Psychotherapy
Open Access

ISSN: 2161-0487

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Commentary - (2017) Volume 7, Issue 4

Commentary: Universal Screening for Social, Emotional and Behavioral Risk in Schools Using Protective Factors

Julie Q Morrison1* and Jennifer L Rollenhagen2
1University of Cincinnati, College of Education, Criminal Justice, and Human Services, School Psychology Program, USA, E-mail: jennifer@rollenhagen.edu
2Michigan’s Integrated Behavior and Learning Supports Initiative, USA, E-mail: jennifer@rollenhagen.edu
*Corresponding Author: Julie Q Morrison, College of Education, Criminal Justice, and Human Services, School Psychology Program, University of Cincinnati, P.O. Box 210068, Cincinnati, USA, Tel: 45221-0068 Email:

Abstract

Universal screening systems in schools are an essential component of a multi-tiered system of supports (MTSS) framework is a comprehensive service delivery model designed to meet the academic and behavioral needs of students in schools. Universal screening data are used to drive decisions in the interest of reducing risk and promoting positive outcomes for students. This commentary reviews the considerations for selecting screening approaches for assessing social, emotional and behavioral risk within a proactive MTSS framework and advocate for the use of universal screening systems that involve the development of local norms, including local norms for the presence of protective factors. An increasing body of research supports the value of protective factors (e.g. connected with teachers and school, empathy, engagement, pro-social peer groups) as a means of addressing students’ needs proactively through a competency-based lens.

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Keywords: Screening; School mental health; Protective factors

Commentary

A multi-tiered system of supports (MTSS) framework is a comprehensive service delivery model designed to meet the academic and behavioral needs of students in schools [1,2]. The use of data to drive decisions in the interest of reducing risk and promoting positive outcomes is central to an MTSS framework. The core components of an MTSS framework, such as Positive Behavioral Interventions and Supports (PBIS), include: (a) universal screening, (b) data-based decision making and problem solving, (c) continuous progress monitoring, (d) a continuum of evidence-based practices, and (e) a focus on fidelity of implementation [2]. The three tiers of an MTSS framework are based on the three levels of prevention outcomes first established by the United States Public Health Service: primary prevention, secondary prevention and tertiary prevention. In a school-based MTSS framework, the three tiers are conceptualized as: Tier 1 universal support, Tier 2 targeted intervention and Tier 3 intensive, individualized intervention. Taken as a whole, a school-based MTSS framework mirrors the public health surveillance approach endorsed by the Center for Disease Control and Prevention [3], which emphasizes the ongoing, systematic collection and analysis of data for planning, implementing, and evaluating public health practices with a focus on prevention [4]. Within an MTSS framework, a multiple gating screening procedure is established, which involves a stepwise evaluation approach of increasing specificity. Universal screening is employed at the first gate to initially detect students at-risk using broad indicators of social, emotional, and behavioral functioning, followed by a second and third gate that involve increasingly extensive and specialized evaluation to match students to interventions of increasing intensity.

Decades of research provide support for the effectiveness of an MTSS framework in meeting students’ needs [5,6]. Yet the degree to which an MTSS initiative addresses academic and behavioral concerns proactively depends largely on a school’s capacity for timely and responsive data collection to identify concerns, match students to a continuum of increasing intensive evidence-based interventions and monitor progress [7].

This commentary reviews the considerations for selecting screening approaches for assessing social, emotional, and behavioral risk within a proactive MTSS framework and advocate for the use of universal screening systems that involve the development of local norms, including local norms for the presence of protective factors. Currently, there is no one instrument or method that is sufficiently sensitive to serve as the sole universal screener for identifying risk, informing intervention planning and providing for ongoing progress monitoring. Existing approaches to universal screening include a variety of methods, such as teacher ratings, teacher nominations and the use of extant data, such as office discipline referrals. The challenge of designing an efficient universal screening system in schools reflects the complexity of assessing social, emotional and behavioral functioning comprising the multifaceted construct of children’s mental health [8] and to some degree represents a long-standing view that “behavioral assessment” is distinct from “mental health assessment” [9], with the latter somehow less appropriate for use in the schools. Historically, both behavioral assessment and mental health assessment have focused on the presence of within-child deficits relative to a nationally normative sample. The key to bridging the divide between behavioral assessment and mental health assessment will require the use of a comprehensive, yet cost-efficient, screening system that gathers data on at-risk factors and protective factors using a local norm.

Considerations for selecting a universal screening system

Guidance for the selection of screening instruments for assessing social, emotional, and behavioral risk comes from Severson et al. [10], who recommend careful consideration of the following characteristics: (a) cost efficient, (b) able to accurately identify a high proportion of students requiring support (sensitivity), (c) able to accurately identify students not requiring support (specificity), (d) capable to identifying students early, (e) able to provide information useful for guiding interventions, and (f) usable by various raters. The appropriateness of the tool in relation to the student population, the service delivery context, and its intended purpose is an additional consideration advanced by Glover and Albers. In their examination of five instruments and methods shown to have technical adequacy as a universal screening, Miller et al. [11] found that risk identification varied by screening approach, with large percentage of students identified inconsistently depending on the measure used. In this study, the Direct Behavior Rating – Single Item Scales (DBR-SIS: http://www.directbehaviorrating.org), Social Skills Improvement System – Performance Screening Guide (SSiS; [12]), and the Behavior and Emotional Screening System – Teacher Form (BESS; [13]) resulted in larger proportions of students identified at-risk that did the use of office discipline referrals and school nomination methods. Given that the screening results differed by the approach used, Miller et al. [11] recommended that the universal screening system selected should be linked to the assessment aims within an MTSS framework.

Among the many considerations for selecting a universal screening system, the issue of fairness has not received adequate attention. Fairness, according to the Standards for Educational and Psychological Testing, has four possible meanings (American Educational Research Association, American Psychological Association and National Council on Measurement in Education [14]). Most relevant to universal screening, a screening instrument is fair to the degree that all students have a comparable opportunity to learn or perform the targeted indicators (e.g. social skills) assessed by the instrument. Fairness is a critically important consideration, particularly when universal screening is conducted for a student population that is culturally diverse and/or economically disadvantaged. The use of a local norm can help ensure the contextual fit or appropriateness of the tool in relation to the student population so that it is a fair assessment for all students.

Developing local norms for universal screening

A local norm is a description of a population’s performance on a set of tasks, developed to represent students from a particular school or school system [15]. As such, local norms provide direct measures of a student’s performance in a given instructional context relative to peers within that same ecology. The rationale for developing local norms relies on the recognition that students interact within a unique, contextuallyspecific ecology and this context provides an opportunity to make normative comparisons that are unique and contextually sensitive [16]. As such, locally-normed assessments address many of the criticisms of traditional norm-referenced assessments, namely that they are culturally and ethnically biased and function primarily to identify, classify and sort students. Whereas, nationally-normed assessment measures frequently result in the overrepresentation of culturally, ethnically and linguistically diverse students attaining “at-risk” status, local norms reflect what is relevant for success within the local context [17].

Creating local norms with the student risk screening scale – internalizing and externalizing

The Student Risk Screening Scale – Internalizing and Externalizing (SRSS-IE; [18]) is a universal screening tool in which the classroom teacher provides a rating for each student on seven behavioral descriptors (original to the Student Risk Screening Scale developed by Drummond [19]) and five additional internalizing behavioral descriptors added in 2012. The SRSS-IE is formatted as a matrix. The first column of the matrix is used to list students’ names. Seven externalizing behavioral descriptors appear across the top of the rating form: (a) steal; (b) lie, cheat, sneak; (c) behavior problem; (d) peer rejection; (e) low academic achievement, (f) negative attitude; and (g) aggressive behavior. The elementary grade level version includes five internalizing behavioral descriptors: (a) emotionally flat; (b) shy; withdrawn; (c) sad; depressed; (d) anxious; and (e) lonely. The secondary grade level version includes six internalizing behavior descriptors, with peer rejection included as an internalizing behavior accompanying the five internalizing behavioral descriptors used at the elementary grade level. The classroom teacher rates each student on all items based on the behaviors they have observed. Every student is assigned a rating, ranging from 0=“Never” to 3=“Frequently,” for each of the descriptors. The ratings are summed for each student to yield an Externalizing total score ranging from 0-21 and an Internalizing total score ranging from 0-15 (elementary) or 0-18 (secondary). The total scores for each scale, Externalizing and Internalizing, are then used to identify students’ risk level using research-derived cut scores. The total score for the SRSS-IE Externalizing scale and the total score for the SRSS-IE Internalizing scale are used to determine whether a student is at risk and in need of additional supports. Individual SRSS-IE descriptor items should not be used to group students into interventions.

When used as part of a universal behavioral screening system, the SRSS-IE is administered three times a year, creating a local norm for each classroom, the grade level, and the school as a whole. Research supports the use of the SRSS-IE as a reliable and valid tool for universal screening at the elementary school level [18,20], middle school level [21], high school level [22], in early childhood settings [23] and for use with English Language Learners [24].

The SRSS-IE features many of the characteristics valued in a universal screening system. The SRSS-IE has adequate overall classification accuracy, accurately identifying students requiring support (sensitivity) and students not requiring support specificity). The SRSS-IE provides for the early identification of student need and yields information useful for planning interventions. In addition, the SRSS-IE can be used by a variety of raters and does not require specialized training for its use. Finally, the SRSS-IE is cost efficient, as it is available at no cost and teachers can complete ratings for students on a given class roster in less than 20 min.

Building local norms using protective factors

Protective factors are conditions or attributes of students and families that mitigate risk and promote healthy development and well-being [25]. An increasing body of research supports the value of protective factors (e.g., connected with teachers and school, empathy, engagement, pro-social peer groups) as a means of addressing students’ needs proactively through a competency-based lens [26-31]. By identifying students who lack core protective factors relative to others in their school setting, behavioral supports and interventions can be designed and implemented proactively to mitigate risk before externalizing and/ or internalizing behaviors emerge.

The Student Protective Factors Screening Scale (SPF-7; [32]) employs the same matrix system used by the SRSS-IE. Unlike the SRSSIE, however, which gathers a teacher’s ratings on risk factors, the SPF- 7 involves teacher ratings of individual students on seven protective factors. The seven behavioral descriptors include: (a) demonstrates competence, is optimistic and has a sense of purpose; (b) has effective social skills, relates well to others, has good friendship skills; (c) shows respect and concern for others, empathy; (d) identifies with a prosocial peer group; (e) engaged and motivated to do well in school; (f) connected with teachers and school; and (g) family is supportive and invested in student’s school success. Initial research supports the use of the SPF-7 as a reliable and valid measure at the elementary school level [32]. Further research is needed to examine the technical adequacy and overall classification accuracy (i.e., sensitivity and specificity) of the SPF-7 at various grade levels (i.e., early childhood, middle school and high school) and among culturally and linguistically diverse student populations. If supported by future research, the SPF-7 could serve as cost-effective screening tool that represented one component of a universal screening system that also included a focus on at-risk indicators.

By focusing on protective factors at the first gate of a multiple gating screening procedure, students who are vulnerable to developing externalizing and/or internalizing behaviors that have not yet manifest themselves may be identified and provided support before at-risk indicators emerge. This might be particularly useful in an early childhood setting where identifying students who lack protective factors may enable a more proactive approach to meeting their needs before the classroom time outs, phone calls home, and office discipline referrals begin to accumulate. Similarly, English Language Learners or students with disabilities who struggle to feel included and connected to the teacher, the school and a pro-social peer group could be identified for additional support before they are drawn down a path of increasing disenfranchisement.

Information garnered from the SPF-7 could be used to identify the need for both selected (secondary prevention) and universal (primary prevention) interventions. In all cases, further assessment is needed as part of a multiple gating screening procedure to identify individual areas of need in order to match students to appropriate interventions.

A final benefit of focusing on protective factors to build local norms for universal screening relates to long-standing concerns about the use of mental health assessment screening in schools, where assessments focus on the presence of within-child deficits relative to a nationally normative sample. A criticism of one such mental health screening system, the Teenscreen, was that too many students were identified as atrisk for mental health concerns, overwhelming the resources available for intervention and consequently making school districts liable for meeting the needs of students identified (Anderson-Butcher, personal communication April 21, 2005 cited in Morrison, [32]). Anti-screening groups, such as the Church of Scientology and Concerned Women for America, traditionally have contended that the use of universal screening for mental health concerns usurp parental authority, enable pharmaceutical companies to market their products to school children, and promotes labeling children as mentally ill [33].

Conclusion

School psychologists rely on the use of universal screening systems that are valid, reliable, and fair for the purposes of assessing social, emotional, and behavioral risk within a multiple gating MTSS framework. To date, there is no one instrument or method that is sufficiently sensitive to serve in isolation as a universal screener for identifying risk, informing intervention planning, and providing for ongoing progress monitoring. In this commentary, we review the considerations for selecting screening approaches and advocate for the use of tools that involve the development of local norms. Using local norms to gather data on protective factors, rather than exclusively focusing on at-risk factors, has several benefits of interest to school psychologists, including the ability to cast a wider net to identify students who lack protective factors before they manifest social, emotional, and behavioral concerns. The focus on protective factors may also circumvent criticisms of mental health assessments in schools that focus on the presence of at-risk indicators relative to a national norm. The use of the SPF-7 to assess protective factors, coupled with the SRSS-IE, may provide school psychologists with a comprehensive, costeffective universal screening system that accounts for the local school context to identify students for further assessment in a manner that is valid, reliable and fair.

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Citation: Morrison JQ, Rollenhagen JL (2017) Commentary: Universal Screening for Social, Emotional and Behavioral Risk in Schools Using Protective Factors. Family Therapy. J Psychol Psychother 7: 314.

Copyright: © 2017 Morrison JQ, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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