Empirically Derived Subclasses of Academic Skill Among Children at Risk for Behavior Problems and Association With Distal Academic Outcomes

Abstract

Students with early indicators of behavior risk have predictable, negative outcomes, and those with co-existing academic problems have significantly more negative outcomes. Identifying academic subclasses of students with behavior risk can inform integrated interventions and school-based problem-solving teams. In addition, identifying academic strengths among a population of children typically only differentiated by severity of maladaptive behaviors may offer insight into academic resiliency. Using a sample of 676 elementary school students identified as behaviorally at risk, latent class analysis of reading and math indicators was conducted. Results indicated a three-class structure was the best fit for these data, with Class 1 (25%) having the least academic risk, Class 2 (37%) as below average reading and math, and Class 3 (38%) with significant academic deficits. Class membership was found to significantly predict end of year statewide assessment performance. While those behaviorally at-risk students with co-occurring academic deficits were very likely to fail the end of year assessments (Class 3; 88%–99% failure rates), those with stronger academic skills (Class 1) were increasingly more likely to pass (47%–56% pass rates). Practical implications, including intervention selection, and future directions are discussed.