Interaction effects in multielement designs: inevitable, desirable, and ignorable.
Use interaction effects in multielement designs as built-in reversal probes to spot contextual control faster.
01Research in Context
What this study did
Landry et al. (1989) wrote a think-piece about multielement designs. These are the rapid-alternation probes you use to screen treatments in one session.
They asked: what if the jumps between conditions create their own effects? They mapped which ones ruin data and which ones you can actually use.
What they found
The paper says interaction effects are baked in. You can’t delete them, so sort them into two piles.
Bad pile: carry-over that muddies treatment clarity. Good pile: context effects that tell you when and where a skill will appear.
How this fits with other research
Kazdin (2021) updates the same terrain 32 years later and still warns about carry-over, but agrees some interactions speed up detection of contextual control.
Walker et al. (2021) add that you don’t need big groups to trust these patterns—replication across cases gives you generality, not large N.
Soto (2020) takes the idea into animal labs, showing neuroscience can exploit the same quick alternations to link brain events to single-subject behavior.
Why it matters
Stop throwing out multielement data the moment you see order effects. Turn them into a mini-reversal: run A-B-A within the same session to see if the context itself is now controlling the response. That twist can cut your assessment time in half and tell you exactly which environmental triggers to program or avoid during intervention.
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Join Free →After each multielement condition, re-present the first condition as a check—if the behavior flips, you’ve found contextual control.
02At a glance
03Original abstract
A single-subject design often used to compare the effectiveness of two or more independent variables (like treatment programs) is the multielement (alternating treatments or simultaneous treatments) design. Variants of this design approximate the concurrent comparison of the effects of two or more variables (or levels of variables) by programming the variables (or levels) in rapid alternation, typically across or within daily sessions. Properly combined with conventional reversal designs, these designs can also display a variety of interaction effects, some of them worrisome, others highly desirable for the future development of the field. A worrisome model is the possibility that when Treatment B alternates rapidly with Treatment C, the effects of each will not be the same as when each is the only treatment used. A desirable model is the use of the multielement design as a fast-paced component of an otherwise conventional reversal design examining contextual control of some relationship; the possibility that some behavior responds differently to Controlling Variables A and B in Context X than in Context Y. This second possibility opens single-subject designs to the more efficient examination of all interactive effects and is highly desirable, considering the prevalence and importance of interactions in determining the limits and the generality of currently understood behavioral phenomena.
Journal of applied behavior analysis, 1989 · doi:10.1901/jaba.1989.22-57