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  • Title: Between-teacher variance of students' teacher-rated risk for emotional, behavioral, and adaptive functioning.
    Author: Splett JW, Raborn A, Brann K, Smith-Millman MK, Halliday C, Weist MD.
    Journal: J Sch Psychol; 2020 Jun; 80():37-53. PubMed ID: 32540089.
    Abstract:
    As schools increasingly adopt universal social, emotional, and behavioral screening, more research is needed to examine the effects of between-teacher differences due to error and bias on students' teacher-rated screening scores. The current study examined predictors of between-teacher differences in students' teacher-rated risk across one global and three narrow domains of behavioral functioning. Participants included 2450 students (52.1% male, 54.2% White) and 160 teachers (92.1% female, 80.3% White) from four elementary schools in one Southeastern U.S. school district. Teachers rated student behavior on the Behavior Assessment System for Children (Third Edition) Behavioral and Emotional Screening System (BESS)-Teacher Form and completed a survey about their training and perspectives of common behavior problems. Results of multilevel linear regression found between-teacher effects to be greater for internalizing risk scores (intraclass correlation = 0.23) than for externalizing risk scores (intraclass correlation = 0.12) or adaptive behavior scores (intraclass correlation = 0.14). Statistically significant student predictors in most models included student grade, gender, race and/or ethnicity, office discipline referrals, and course grades. We also detected effects of several teacher-level variables in one or more of the models, including teacher gender, teacher ratings of problem severity and concern for hypothetical children displaying behavior problems, and the covariance of random teacher intercept and teacher random slopes for students' office discipline referrals. Although these factors explained some teacher-level variance in students' risk scores, a notable amount of variance between teachers remains unexplained. Future research is needed to fully understand, reduce, and account for differences between teacher ratings due to error and bias.
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