Perceptions of Machine Learning among Therapists Practicing Applied Behavior Analysis: A National Survey.

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Collecting data and logging behaviors of clients who have autism spectrum disorder (ASD) during applied behavior analysis (ABA) therapy sessions can be challenging in real time, especially when the behaviors require a rapid response, like self-injury or aggression. Little information is available about the automation of data collection in ABA therapy, such as through machine learning (ML). Our survey of ABA therapists nationally revealed mixed levels of familiarity with ML and generally neutral responses to statements endorsing the benefits of ML. Higher certification levels and more years of experience with ABA were associated with decreased confidence in ML's ability to accurately identify behaviors during ABA sessions whereas previous familiarity with ML was associated with confidence in ML, comfort with using ML, and trust that ML technology can keep client data secure. Understanding the perceptions of ABA therapists can guide future endeavors to incorporate ML for automated behavior logging into ABA practice.Applied behavior analysis (ABA) therapists perceive some value in utilizing machine learning (ML) in data collection during ABA sessions, but the majority of therapists are not familiar with the concept of ML.In our survey, ABA therapists with greater familiarity with ML were more likely to be comfortable using ML in their practice.Surveyed ABA therapists with higher certification levels and more experience with ABA were less likely to be confident in ML's ability to identify behaviors accurately.Awareness of ABA therapists' perspectives about ML, especially regarding privacy and security, and partnership with computer scientists can further the development of ML technology to augment data collection during ABA therapy.Educating ABA therapists about the potential of ML, especially the potential to reduce the burden of behavior logging while simultaneously intervening for aggressive and self-injurious behaviors, will be necessary for successful implementation of ML in ABA therapy settings.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s40617-024-00936-y.