A component analysis of ABC assessments as demonstrated through function based interventions

Tereshko et al. (2024) asked a simple question. Can ABC data alone tell us what a full functional analysis would say?

They collected ABC sheets, ran a standard FA, then built a treatment from the ABC numbers. Next they checked if the two matched and if the treatment worked.

The antecedent conditional probabilities from the ABC sheets lined up with the FA results. Treatment built from those same numbers reduced problem behavior.

In short, the math you can do on a napkin after recess predicted the lab test and fixed the issue.

Simó-Pinatella et al. (2013) already showed that social antecedents point to most functions. Tereshko gives us the exact numbers to watch.

Call et al. (2024) looked like a contradiction at first. They found only modest agreement between FBA types yet still got good treatment results. The difference is focus. Call compared whole FBAs with and without an FA. Tereshko zoomed in on one slice—antecedent odds—and showed that slice alone can match the FA.

Webb et al. (1999) taught us to plot descriptive data by presumed function. Tereshko turns that plot into a simple probability score you can calculate in Excel.

You can now start intervention sooner. Run a few days of ABC recording, compute the antecedent odds, and you have a data-based guess that stands up to the gold-standard FA. Use the time you save for teaching, not testing.