Progressive-ratio schedules and applied behavior analysis.

Poling (2010) wrote a how-to paper, not an experiment. He explained why progressive-ratio schedules belong in every BCBA’s toolbox.

The idea is simple: keep raising the work requirement after each reward. Count the last completed ratio—the breakpoint. That number tells you how much the client wants the item.

The paper gives no new data. Instead, it argues that the breakpoint is an easy, single-number report of reinforcer strength.

Higher breakpoint equals stronger reinforcer. You can now rank toys, snacks, or activities without guessing.

Hackenberg (1995) sketched the first map. He showed that demand curves and work-rate functions predict when a preferred item may flip. Poling (2010) keeps the map but swaps the tool: use one progressive-ratio probe instead of drawing full curves.

Kraijer (2000) tested the map with two learners. He used concurrent schedules and plotted demand curves. The curves matched later progressive-ratio ranks, so both methods agree—Alan just gives a faster route.

Wilson et al. (1973), Tanguay et al. (1982), and Rider et al. (1984) all say the same quiet thing: watch the pause. Whether fixed-interval or fixed-ratio, the post-reinforcement pause carries the message. Alan turns that pause into a single breakpoint score.

You now have a five-minute assessment that yields a number you can drop in a report. Run one probe, note the breakpoint, and you know if the iPad beats the cookie today. No long preference scans, no subjective ratings—just work output. Use it during reassessment to spot satiation or new motivators before they stall therapy.