Increasing item engagement and decreasing automatically reinforced problem behavior within a modified competing stimulus assessment

The team ran a modified competing stimulus assessment (CSA) on three kids who hit themselves for automatic reinforcement.

They added two twists: they prompted the child to touch each leisure item and gave a small edible for every 5 s of play.

Sessions happened in a therapy room first, then moved to the classroom to see if the fix stuck.

Prompt plus tiny reward made the kids touch the items 80-100 % of the time instead of 0-20 %.

Self-hitting dropped to near zero in most sessions and stayed low when they faded the prompts.

The same toys that looked useless in a regular CSA became powerful competitors once they added the extra help.

Frank‐Crawford et al. (2026) showed that old-style, rate-based CSA still picks the best toys when results clash with the quick-latency version. Leif keeps the rate format but layers in prompting, so you get the accuracy plus actual engagement.

Ghaemmaghami et al. (2018) shaped complex communication responses bit-by-bit to avoid resurgence. Leif uses the same baby-step idea inside assessment: prompt and then fade so the child does not lose the new play skill when extras disappear.

Sullivan et al. (2020) warned that untreated response forms can pop back up during extinction. By teaching strong toy play early, Leit gives you a front-line buffer that may later lessen resurgence when you start extinction or interruption.

If you test toys for automatically reinforced SIB and the data look flat, do not toss the box. Add a prompt and a quick reinforcer for touching. Run a few more 5-min cycles. You may find a winner that keeps hands busy and cuts injury risk without heavy restraint or punishment. Try it next time the CSA stalls.