Use of a latency-based demand assessment to identify potential demands for functional analyses
Choose the demand that sets off problem behavior fastest—short-latency items make escape functions show up 92% of the time.
01Research in Context
What this study did
Call et al. (2016) wanted a faster way to pick the right demand for a functional analysis. They timed how quickly problem behavior started when staff gave different tasks.
They tested a small group of children with mixed diagnoses. Each child got several demands. Staff recorded the seconds until the first escape behavior.
What they found
The demand that triggered behavior fastest spotted an escape function 92% of the time. The slowest demand found escape in only 42% of cases.
Using the quickest trigger gave clearer results in the full functional analysis.
How this fits with other research
Slaton et al. (2017) also sharpened FA, but they used parent interviews to build a synthesized test. Both studies got clearer answers than the old isolated-condition method.
Fruchtman et al. (2025) later added a performance twist to the IISCA line. Their skill-based treatment grew from the same wish for faster, safer assessment.
Hagopian et al. (2005) looked at response chains instead of demands, yet both papers show that tiny assessment details guide big treatment choices.
Why it matters
You can save hours by running a five-minute latency test before the full FA. Pick the demand that upsets the learner fastest and drop the ones that barely trigger. You will spot escape sooner and start treatment quicker.
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02At a glance
03Original abstract
Unlike potential tangible positive reinforcers, which are typically identified for inclusion in functional analyses empirically using preference assessments, demands are most often selected arbitrarily or based on caregiver report. The present study evaluated the use of a demand assessment with 12 participants who exhibited escape-maintained problem behavior. Participants were exposed to 10 demands, with aversiveness measured by average latency to the first instance of problem behavior. In subsequent functional analyses, results of a demand condition that included the demand with the shortest latency to problem behavior resulted in identification of an escape function for 11 of the participants. In contrast, a demand condition that included the demand with the longest latency resulted in identification of an escape function for only 5 participants. The implication of these findings is that for the remaining 7 participants, selection of the demand for the functional analysis without using the results of the demand assessment could have produced a false-negative finding.
Journal of Applied Behavior Analysis, 2016 · doi:10.1002/jaba.341