Five direct behavior rating multi-item scales: Sensitivity to the effects of classroom interventions

Formative behavioral assessment across eight constructs: Dependability of direct behavior ratings and formative behavior rating measures

Due to their promise as a feasible tool for evaluating the effects of school-based interventions, Direct Behavior Ratings (DBR) have received much research attention over the past 2 decades. Although DBR methodology has demonstrated much promise, favorable psychometric characteristics only have been demonstrated for tools measuring a small number of constructs. Likewise, although a variety of methods of DBR have been proposed, most extant studies have focused on the use of single-item methods. The present study examined the dependability of four methods of formative behavioral assessment (i.e., single-item and multi-item ratings administered either daily [DBR] or weekly [formative behavior rating measures or FBRM]) across eight psychological constructs (i.e., interpersonal skills, academic engagement, organizational skills, disruptive behavior, oppositional behavior, interpersonal conflict, anxious depressed, and social withdrawal). School-based professionals (N = 91; i.e., teachers, paraprofessionals, and intervention specialists) each rated one student across all eight constructs after being assigned to one of the four assessment conditions. Dependability estimates varied substantially across methods and constructs (range = 0.75-0.96), although findings of the present study support the use of the broad set of formative assessment tools evaluated.

Assessing Intervention Effects in the Presence of Missing Scores

Due to repeated observations of an outcome behavior in N-of-1 or single-case design (SCD) intervention studies, the occurrence of missing scores is inevitable in such studies. Approximately 21% of SCD articles published in five reputable journals between 2015 and 2019 exhibited evidence of missing scores. Missing rates varied by designs, with the highest rate (24%) found in multiple baseline/probe designs. Missing scores cause difficulties in data analysis. And inappropriate treatments of missing scores lead to consequences that threaten internal validity and weaken generalizability of intervention effects reported in SCD research. In this paper, we comprehensively review nine methods for treating missing SCD data: the available data method, six single imputations, and two model-based methods. The strengths, weaknesses, assumptions, and examples of these methods are summarized. The available data method and three single imputation methods are further demonstrated in assessing an intervention effect at the class and students’ levels. Assessment results are interpreted in terms of effect sizes, statistical significances, and visual analysis of data. Differences in results among the four methods are noted and discussed. The extensive review of problems caused by missing scores and possible treatments should empower researchers and practitioners to account for missing scores effectively and to support evidence-based interventions vigorously. The paper concludes with a discussion of contingencies for implementing the nine methods and practical strategies for managing missing scores in single-case intervention studies.