Extending the concept of social validity: behavior analysis for disease prevention and health promotion.

The authors wrote a think-piece. They asked: what should "social validity" really mean?

They said three things must be true before we scale any program. First, big data must show the problem hurts lots of people. Second, real consumers must actually use the fix. Third, the fix must change behavior at a population level.

They used disease prevention as the example, but the rules apply to any ABA program.

The paper did not test people. It gave a new checklist. Satisfaction alone is not enough.

You need numbers that show (a) the problem matters, (b) people sign up, and (c) society improves.

Szempruch et al. (1993) took the same idea to social-skills classes for kids. They added a fourth demand: show the skills move to the playground with objective probes.

Anderson et al. (2022) built a tool for the job. Thirty-one years later they gave us a textual-analysis script that makes Likert scales you can trust.

Arnold-Saritepe et al. (2026) and D’Agostino et al. (2025) push the idea further. They say add qualitative interviews, especially with marginalized families, so you capture voices that surveys miss. The 1991 paper wanted richer data; these papers show how to collect it.

Nohelty et al. (2023) show the checklist in action. They measured telehealth ABA against all three gates: caregiver uptake, barrier reports, and rated quality of life. Scores were good, but tech and childcare barriers pulled them down—exactly the kind of hard evidence the target paper asked for.

Before you run a large program, open three folders on your computer. Folder 1: epidemiology numbers that prove the problem is big. Folder 2: sign-up sheets and attendance logs that prove consumers stick with you. Folder 3: pre-post graphs that prove behavior changed in the real world. If any folder is empty, scale-up waits. This habit shields you from later complaints and wasted funds.