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Dynamic treatment regimes (DTRs) are sequences of decision rules thatrecommend treatments based on patients' time-varying clinical conditions. Thesequential multiple assignment randomized trial (SMART) is an experimentaldesign that can provide high-quality evidence for constructing optimal DTRs. Ina conventional SMART, participants are randomized to available treatments atmultiple stages with balanced randomization probabilities. Despite its relativesimplicity of implementation and desirable performance in comparing embeddedDTRs, the conventional SMART faces inevitable ethical issues includingassigning many participants to the empirically inferior treatment or thetreatment they dislike, which might slow down the recruitment procedure andlead to higher attrition rates, ultimately leading to poor internal andexternal validities of the trial results. In this context, we propose a SMARTunder the Experiment-as-Market framework (SMART-EXAM), a novel SMART designthat holds the potential to improve participants' welfare by incorporatingtheir preferences and predicted treatment effects into the randomizationprocedure. We describe the steps of conducting a SMART-EXAM and evaluate itsperformance compared to the conventional SMART. The results indicate that theSMART-EXAM can improve the welfare of the participants enrolled in the trial,while also achieving a desirable ability to construct an optimal DTR when theexperimental parameters are suitably specified. We finally illustrate thepractical potential of the SMART-EXAM design using data from a SMART forchildren with attention-deficit/hyperactivity disorder (ADHD).

Incorporating Participants' Welfare into Sequential Multiple Assignment Randomized Trials