Are Adaptive Interventions Bayesian?

I love the idea of adaptive behavioral interventions. But, I keep hearing about adaptive designs and how they are Bayesian. How can an adaptive behavioral intervention be Bayesian? — Signed, Adaptively Confused, Determined to Continue


Dear AC, DC:

Actually, adaptive behavioral interventions are not Bayesian, but your confusion is understandable, because the same words have been used to refer to different concepts.

Let’s start with the word “adaptive.” This word, which is used in many fields, refers broadly to anything that changes in a principled, systematic way in response to specific circumstances in order to produce a desired outcome. An adaptive intervention is a set of tailoring variables and decision rules whereby an intervention is changed in response to characteristics of the individual program participant or the environment in order to produce a better outcome for each participant (Collins et al., 2004). For example, in an adaptive intervention for treating alcoholism, an individual participant’s alcohol intake may be monitored and reviewed periodically. Here alcohol intake is the tailoring variable. The decision rule might be as follows: if the individual has no more than two drinks per week for six weeks, frequency of clinic visits will be reduced. On the other hand, if the individual has more than two drinks per week, additional clinic visits will be required, plus a pharmaceutical will be added to the treatment regime.

Now let’s discuss the word “design.” In intervention science, the term intervention design refers to the specifics of a behavioral intervention: the factors included in the prevention or treatment approach, such as whether the intervention is delivered in a group or individual setting, or the intensity level of the intervention. In contrast, the term research design refers to how an empirical study is set up. For example, in an experimental research design there is random assignment to conditions; in a longitudinal research design, measures are taken over several different time points.

Confusion may arise when the words “adaptive” and “design” are paired without specifying which sense of the word “design” is meant. In intervention science, an adaptive intervention design is the approach used in a particular adaptive intervention. In methodology, an adaptive research design (Berry et al., 2011) is a Bayesian approach to randomized clinical trials (RCTs), in which the research design may be altered during the course of a clinical trial based on information gathered during the trial. For example, an adaptive clinical trial may be halted before the entire planned sample size is collected if the results are judged to be so clear that additional information would be unlikely to affect decision making. Adaptive intervention designs are not experimental designs, and therefore cannot be Bayesian.

You might think that building or evaluating an adaptive behavioral intervention would require the use of an adaptive experimental design, but this is generally not the case. Investigators who want to build an adaptive intervention—that is, conduct an experiment to decide on the best tailoring variables and/or decision rules—probably want to consider a Sequential Multiple Assignment Randomized Trial (SMART Trial; Murphy et al., 2007). Note that the SMART Trial has been developed especially for building adaptive behavioral interventions, but it is not an adaptive experimental design.

Investigators who have already selected the tailoring variables and decision rules and want to evaluate the adaptive intervention probably want to conduct an RCT. The RCT could potentially involve an adaptive experimental design, but it could also be a standard RCT.

I hope this helps to clear things up! Reading the references listed below may help. And, AC, DC: The next time you hear the term “design,” if you are not sure whether the speaker is talking about intervention design or experimental design, be sure to ask forc larification.


Berry, S. M., Carlin, B. P., Lee, J. J., & Muller, P. (2011). Bayesian adaptive methods for clinical trials. Boca Raton, FL: CRC Press.

Collins, L. M., Murphy, S. A., & Bierman, K. (2004). A conceptual framework for adaptive preventive interventions. Prevention Science, 3, 185-196

Murphy, S. A., Lynch, K. G., McKay, J. R., Oslin, D., & Ten Have, T. (2007). Developing adaptive treatment strategies in substance abuse research. Drug and Alcohol Dependence, 88(2), S24-S30.