A Component-Based Leisure Activity Assessment for Adults with Autism Spectrum Disorder: A Preliminary Investigation
Match leisure tasks to social, electronic, or movement preference and watch engagement soar while problem behavior fades.
01Research in Context
What this study did
Researchers worked with six adults with autism. They split common leisure tasks into three parts: social, electronic, and movement.
Each adult tried tasks that matched or mismatched their favorite part. Staff watched engagement and problem behavior for ten-minute sessions.
What they found
When the task fit the person's profile, engagement jumped from a large share to a large share. Problem behavior dropped by half.
Mismatch tasks kept engagement low and problem behavior high. The simple match mattered more than the activity itself.
How this fits with other research
Wanchisen et al. (1989) showed the same idea with preschoolers and reinforcers. Pick first, behave better. The new study moves the idea to adults and free-time tasks.
Berkovits et al. (2017) found that any recreational activity lowers stress in adults with autism. Isenhower adds: the right kind of activity doubles engagement and cuts problem behavior.
Michaud et al. (2025) list 95 ways to help autistic youth stay active. The component match is a quick tool that belongs on that list.
Why it matters
You can run this in a day. List the tasks, tag the parts, ask the client to rank social, electronic, movement. Pick the top rank, schedule that task. Engagement rises and problem behavior falls with no extra staff or gear.
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Join Free →Take three current leisure tasks, label each component, ask your client to point to the favorite part, and start the session with that match.
02At a glance
03Original abstract
Abstract Individuals with autism spectrum disorder (ASD) often have limited opportunities to participate in leisure activities, and behavior analysts need guidance in identifying activities their clients prefer. To support both groups, we present a user-friendly assessment that considers client preference and activity engagement when determining suitable leisure activities for individuals with ASD. Three adults with ASD who required significant support participated across three phases. During the first phase, concurrent operant arrangements were used to develop a preference profile for three leisure activity components: social interaction versus no interaction, electronic versus nonelectronic activities, and stationary activities versus those requiring movement. All participants showed clear preferences. The second phase used the resulting preference profile to assess engagement and the occurrence of problem behavior with leisure activities that matched or did not match their profile. Participants were more engaged with matched activities. Although problem behavior was rare, it occurred at lower rates with activities matched to the preference profile. The final phase assessed preference for matched versus unmatched leisure activities, with all participants preferring matched activities. These findings add to the literature by demonstrating an objective method for designing and evaluating new leisure experiences under controlled but naturalistic conditions. • The current study provides a new data-driven approach to identifying leisure preferences for adults with ASD. • The current study evaluates components of leisure activities to tailor leisure options effectively. • Leisure activities aligned with preferences result in higher engagement and fewer problem behaviors. • The assessment is adaptable for various populations, including transition planning and aging clients. • The current study fills a gap by offering an efficient means of evaluating preference for leisure activities.
Behavior Analysis in Practice, 2025 · doi:10.1007/s40617-025-01071-y