An Evaluation of Assistive Technology in Determining Job-Specific Preference for Adults With Autism and Intellectual Disabilities

Walsh et al. (2020) built a tablet app that shows short video clips of real job tasks. Adults with autism and intellectual disability tapped the clips they liked best.

The team then placed each adult in two jobs: one the app said they loved, and one the app said they disliked. They measured how fast and accurately the adults worked in each job.

Every adult worked faster and made fewer errors in the high-preference job. This happened even when the liked job did not match their skill level.

Skill match did not predict success; preference did.

Lattimore et al. (2002) did the same idea with paper cards instead of tablets. Their adults also picked preferred tasks, showing the concept holds across tools.

LaRue et al. (2020) looked at skill-match instead of preference-match. They found better work when jobs fit assessed skills. The two studies seem to clash, but LaRue’s group did not have adults with ID. Preference may matter more when both autism and ID are present.

Rosenberg (1986) first used a computer to let non-speaking clients choose liked stimuli. Walsh’s tablet app extends that old microswitch method into the vocational world.

If you support adults with ASD and ID, run a quick video preference check before job placement. A five-minute tablet tour can save weeks of poor fit and prompt-heavy teaching. Let the client’s likes, not your guess of their skills, pick the first worksite.