Multi-Informant Universal Screening: Evaluating Student-Teacher Rating Discrepancies, Student Characteristics and Academic Outcomes

School settings can facilitate proactive identification for mental health challenges, yet current identification practices may over- and under-identify certain populations. Multi-informant universal screening practices may offer an important advancement for addressing youth needs. This study evaluated multi-informant universal screening practices through (a) student-teacher rating discrepancies, (b) the relationship between student characteristics and teacher-student rating discrepancies and (c) the relationship between teacher-student discrepancies and student academic outcomes. The study utilized multilevel regression modeling to examine 1,235 teacher-student dyads from three middle schools. Variables examined were scores from the Social, Academic, and Emotional Behavior Risk Screener, student demographics, and academic achievement test scores and office discipline referrals. Results indicated medium to strong correlations between teacher-student ratings, four statistically significant student demographic variables that predicted teacher-student rating discrepancies, and that teacher-student rating discrepancies significantly predicted academic performance. Discussion of the findings, limitations, and implications for practice is also included.Impact StatementThis study found that teacher and student universal screening ratings were moderately to strongly correlated, and that four student demographic variables predicted those differences. Rating discrepancies also significantly predicted academic performance. Practitioners can use these results to consider multiple raters when conducting universal screening in their school.