Rapid determinations of preference in multiple concurrent-chain schedules.
A within-session reversal design can yield reliable preference data faster than traditional baseline methods.
01Research in Context
What this study did
The team ran a multiple concurrent-chain schedule. Think of two vending machines side by side. Each machine shows a brief wait before it drops candy. The wait changes every few minutes inside the same session.
The researchers flipped which machine had the shorter wait several times within one sitting. They watched which machine the subject used more. This let them see a clear choice pattern without waiting days for a baseline.
What they found
Subjects quickly shifted their picks when the shorter wait moved to the other machine. The within-session reversal gave a clean read of what the subject valued in under an hour.
Free versus forced trials also matched: when the subject could choose, the pick rate lined up with the earlier forced samples.
How this fits with other research
LeBlanc et al. (2003) later copied the same setup and saw the same flip toward the richer schedule. Their extra twist showed that how often the subject switched between machines did not predict the final choice.
Leon et al. (2021) pushed the idea further by raising work demands within a single session. They got a different demand curve and saw more problem behavior. This flags a limit: rapid reversals work for simple preference, but steeply climbing cost inside one meeting can give skewed data and stress.
Benvenuti et al. (2024) place the whole method in a big-picture frame. They argue social give-and-take itself runs on concurrent-chain logic. Your client choosing to comply is like picking the terminal link with the better payoff.
Why it matters
You can steal this trick for quick preference checks. Run two short tasks with tiny delays, flip the delay once or twice in the same visit, and watch where the client drifts. You will know the favored option before the coffee cools. Save full baseline days for big treatment decisions.
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02At a glance
03Original abstract
With concurrent chains arranged for a pigeon's key pecks, pecks on two concurrently available initial-link keys (left and right) respectively produce separately operating terminal links (A and B). Preferences for terminal link A over terminal link B are usually calculated as deviations of relative initial-link response rates (left divided by total pecks) from those during baseline conditions, when A equals B. Baseline preferences, however, are often variable and typically are determined indirectly (e.g., with unequal A and B, reversing left-right assignments of A and B over sessions and estimating the baseline from differences between the relative rates generated). Multiple concurrent-chain schedules, with components each consisting of a pair of concurrent chains, speed the determination of preferences by arranging A and B and their reversal within sessions. In two experiments illustrating the feasibility of this procedure, one component operated with circles projected on initial-link keys and the other with pluses; when left and right initial-link pecks respectively produced terminal links A and B in one component, they produced B and A in the other. Even as the baselines fluctuated, preference was observable within sessions as the difference between relative initial-link response rates in the two components. The first experiment demonstrated the rapid development of preferences when terminal links A and B consisted of fixed-interval 15-s and 30-s schedules. The second demonstrated the sensitivity of the procedure to preference for a fixed-interval 30-s schedule operating for pecks on either of two keys (free choice) over its operating for pecks on only a single key (forced choice).
Journal of the experimental analysis of behavior, 1986 · doi:10.1901/jeab.1986.46-211