Stability and Change of Behavioral and Emotional Screening Scores

Abstract

Universal screening for behavioral and emotional difficulties is integral to the identification of students needing early intervention and prevention efforts. However, unanswered questions regarding the stability of screening scores impede the ability to determine optimal strategies for subsequent screening. This study examined the 2-year stability of behavioral and emotional risk screening scores and investigated whether change could be predicted based on student characteristics or initial risk scores. As part of a district-wide screening effort, 863 middle and high school students completed the Behavioral and Emotional Screening System at two time points. Stability coefficients were moderate, with the majority of students remaining in a similar risk category across time. Gender, race/ethnicity, socioeconomic status, grade, school transition, and special education status were not predictive of movement across time. Initial risk score was predictive of movement from normal to at-risk categorization, with the internalizing domain being the most predictive of change. C 2015 Wiley Periodicals, Inc.

Examining the Long-Term Stability of a Strengths-Based Screener Over 2 Years

“…The school created the additional category to identify students in a multitiered model for early intervention (Naglieri et al, 2010); however, additional research is warranted to validate the Risk category on the DESSA-Mini. Furthermore, the study extended previous long-term stability research (Dever et al, 2015;Dowdy et al, 2014) by including social, emotional, and behavior intervention as a covariate. However, the intervention variable does not account for the variety in identification methods or intervention intensity.…”

“…In comparison, less than 59% of students in our study remained in the same Time 1 category across the five subsequent assessments. Dever et al (2015) examined predictors of movement between categories and found that the initial Time 1 screening score was predictive of movement from normal to at-risk categories while demographic variables were not. The most movement detected in Dever and colleagues' (2015) study was from the Time 1 at-risk to Time 2 normal category (59%).…”

“…Last, entropy indicates classification precision where values near one indicate stronger model fit (Muthén, 2004). In terms of theoretical guidance, we considered strengths-based assessment research (Jimerson, Sharkey, Nyberg, & Furlong, 2004), risk categories on the DESSA-Mini (Naglieri et al, 2010), and past stability screening studies (Dever et al, 2015; Dowdy et al, 2014).…”

“…For example, patterns of stability among longitudinal universal screening data may relate to measures of academic achievement, behavior problems, economic disadvantage, and intervention status. Students with lower screening scores are more likely to receive school-based social, emotional, and behavioral interventions (Lane, Kalberg, Bruhn, Mahoney, & Driscoll, 2008), and there is a need to examine screening stability in relation to participation in interventions (Dever, Dowdy, Raines, & Carnazzo, 2015; Essex et al, 2009). There is also a well-established connection between social-emotional functioning and academic achievement (Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011) and behavior problems (King, Reschly, & Appleton, 2012) that may be reflected in social-emotional stability.…”

Psychometric Properties of the Behavior Assessment System for Children-3 Behavioral and Emotional Screening System Student-Report Form among a Predominantly Latinx Elementary School Sample

“…Previous factor analytic work with the BASC-2 BESS revealed a four-factor structure (personal adjustment [PA], inattention/hyperactivity, internalizing, and school problems), with adequate internal consistency for each of the factors (Dowdy et al, 2011). In addition, stability coefficients ranged from moderate to large across one to four academic years (Dever, Dowdy, Raines, & Carnazzo, 2015; Dowdy et al, 2014).…”