Effects of an enhanced choice model of skill-based treatment for students with emotional/behavioral disorders.

The enhanced choice model of skill-based treatment (ECM-SBT; Rajaraman et al., 2021) is a package of behavioral treatment procedures with modifications designed to reduce risks associated with extinction of problem behavior. The skill-based treatment component of this package (Hanley et al., 2014) has been investigated thoroughly in clinical settings, though fewer studies have been conducted in public schools. In this investigation, we systematically replicated Rajaraman et al.'s (2021) demonstration of the ECM-SBT with 3 children enrolled in a public special day school for students with emotional and behavioral disorders. Intervention procedures were associated with increases in targeted alternative responses (i.e., communicative response, tolerance response, and cooperation with instructions) and decreased precursor behavior relative to baseline. Severe problem behavior was rare in both assessment and treatment. Participants chose to spend most appointment time participating in ECM-SBT, indicating preference for treatment procedures over alternative contexts (i.e., free access to a break area with preferred activities; regular classroom instruction). These outcomes suggest ECM-SBT has promise for safely teaching alternatives to problem behavior to children with emotional and behavioral disorders in school settings.

A Systematic Review of Direct Assessments to Evaluate Psychotropic Medication Effects for Children With Disabilities.

To evaluate effects of psychotropic medication for children with disabilities, direct assessments may offer a valuable supplement to caregiver reports. Relative to indirect assessment, direct measures of behavior can increase objectivity and sensitivity, and some have potential to isolate distinct behavioral and learning processes. We conducted a systematic, narrative literature review to identify and describe the types and qualities of direct assessment methods that have been used to evaluate effects of non-stimulant psychotropic medication for children with disabilities. We identified 50 studies and 78 direct assessments, which we organized and described using seven assessment categories. Only one study met all three direct assessment quality indicators. We use our descriptive results to highlight research trends and gaps that warrant further study.

Direct Measures of Medication Effects: Exploring the Scientific Utility of Behavior-Analytic Assessments.

The purpose of the current study was to explore the scientific utility of two behavior analytic assessments (i.e., progressive ratio and demand assessments) for psychotropic medication evaluation. For a sample of 23 children with disabilities who were prescribed medication, we conducted a series of generalizability and optimization studies to identify sources of score variance and conditions in which stable estimates of behavior can be obtained. To inform construct validity, we calculated correlations between scores from each assessment and those from a standardized behavior rating scale (Aberrant Behavior Checklist-Second Edition; ABC-2). Results offer initial support for the scientific utility of progressive ratio scores. More research is needed to evaluate sensitivity to change and construct validity of scores from these and other behavior analytic assessments.

A Predictive Multimodal Framework to Alert Caregivers of Problem Behaviors for Children with ASD (PreMAC).

Autism Spectrum Disorder (ASD) impacts 1 in 54 children in the US. Two-thirds of children with ASD display problem behavior. If a caregiver can predict that a child is likely to engage in problem behavior, they may be able to take action to minimize that risk. Although experts in Applied Behavior Analysis can offer caregivers recognition and remediation strategies, there are limitations to the extent to which human prediction of problem behavior is possible without the assistance of technology. In this paper, we propose a machine learning-based predictive framework, PreMAC, that uses multimodal signals from precursors of problem behaviors to alert caregivers of impending problem behavior for children with ASD. A multimodal data capture platform, M2P3, was designed to collect multimodal training data for PreMAC. The development of PreMAC integrated a rapid functional analysis, the interview-informed synthesized contingency analysis (IISCA), for collection of training data. A feasibility study with seven 4 to 15-year-old children with ASD was conducted to investigate the tolerability and feasibility of the M2P3 platform and the accuracy of PreMAC. Results indicate that the M2P3 platform was well tolerated by the children and PreMAC could predict precursors of problem behaviors with high prediction accuracies.