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ABSTRACTDetermining the precise number of therapy hours a patient needs is a critical clinical decision. Too few hours can reduce overall progress and likely keeps the individual in treatment longer than necessary. Too many hours can cause the individual to spend unnecessary time and money they could have spent on other activities that increase their happiness and well‐being. Too many hours also can reduce the hours the provider has available to see other clients further exacerbating access issues prominent in mental health today. Despite its importance, little research exists to show how specific patient profiles and intake assessments can lead to replicable and precise therapeutic recommendations. In this study, we show how patient clustering algorithms can be combined with predictive modeling to create a data‐driven, algorithmic system that generates dose‐response curves relating hours per week of therapy to patient progress, while considering the patient's unique profile. Specifically, we used 48 variables spanning hours and characteristics of therapy, treatment goal characteristics, and patient characteristics to predict goals mastered for 39,475 individuals with ASD receiving applied behavior analysis (ABA) services from 833 service providers. Unsupervised machine learning identified 18 distinct patient clusters. Across clusters, top performing regression models predicted patient progress for all patients with r2 = 0.97 and MAE = 0.003 and with r2 for individual clusters ranging between 0.95 and 0.99 (∼0.20–0.24 points higher than past research) and MAE ranging between < 0.001 and 0.25. Once designed, the resulting patient‐specific dose‐response curves can be used to identify the optimal hours of week that maximizes progress while reducing unnecessary time in treatment. Though designed specifically for predicting ABA hours for individuals with ASD, the current method offers an adaptable data‐driven, algorithmic approach to determine the hours of therapy that optimize patient progress.

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Abstract Functional communication training (FCT) is a widely used behavioral intervention for reducing challenging behavior for students with disabilities. As more students with disabilities are being served in educational settings, it is essential to understand and evaluate the evidence base of FCT in educational contexts. A clear synthesis of how FCT has been applied, by whom, under what conditions, and with what outcomes is needed to evaluate its evidence base and inform translational practice. This mega-review aggregated six systematic reviews and meta-analyses of FCT implemented in educational settings, following PRISMA guidelines. Data were extracted at the review level on participant characteristics (e.g., age, gender, race, disability), functional behavior assessment (FBA) methods and identified functions of behavior, interventionist roles, procedural components of FCT, methodological quality, and outcomes (behavioral change, communication, social validity), as well as documented recommendations. Findings revealed consistent positive effects of FCT on challenging behavior reduction, with variability in reported moderators (e.g., setting, communication modality, and implementer). Notable gaps included limited demographic reporting, overrepresentation of male participants, and variability in review rigor. Implications of this mega-review include the need for greater transparency in methodological reporting, inclusion of culturally responsive and demographically disaggregated data, and appropriate individualized modification of FBA and FCT implementation by natural change agents in educational settings to support generalization, maintenance, and equity.

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ABSTRACT The American Heart Association recently implemented a new requirement, which requires instructors to implement the use of a feedback device during CPR classes. A previous study evaluated using a feedback device and a stringent mastery criterion while training adults to perform hands‐only CPR on adult manikins. Approximately 5000 infants and children experience out‐of‐hospital cardiac arrest, and the most frequent cause is respiratory emergencies such as drowning, choking, sudden infant death syndrome, or heart abnormalities. The present study aimed to replicate and extend this previous work by equipping caregivers with the skills to performing infant CPR. Before training, all participants scored below the mastery criterion. After behavioral skills training was complete, all participants met the mastery criterion in the absence of feedback. The findings are discussed in light of previous research, and areas for future researchers to explore are provided.

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