Evaluation of a latency‐based competing stimulus assessment

Imler et al. (2024) built a new way to pick competing stimuli. They used how fast a person reaches for an item instead of how many times they pick it.

The team ran a single-case test. They timed how long it took to engage with each item when it sat next to a problem item.

The latency method spotted good competing items faster than older count-based ways. One learner needed a small rule tweak, then the tool worked for him too.

Overall, the new check gave clear answers in less time.

Perrin et al. (2018) warned that latency alone can be too touchy when treating severe self-injury. They told clinicians to watch rate as well. Imler’s team shows latency can still save time in the safer context of picking toys, not treating crisis behavior.

Liollio et al. (2020) compared rate and latency for demand tests. They found latency helped most when problem behavior was frequent. Imler extends that idea to preference work, again showing speed gains where behavior is already high.

Kanaman et al. (2022) added social play to preference checks and saw rankings shift. Imler keeps the setting simple but swaps the metric, proving both social context and timing can change what we call "preferred."

You can shave minutes off every stimulus assessment by starting a stopwatch instead of counting ten picks. Shorter tests mean more teaching time and quicker access to items that actually compete with problem behavior. Try the latency format first; if the data wobble, fall back on rate like Perrin suggested.