  Dynamic treatment regimes (DTRs) are sequences of decision rules that
recommend treatments based on patients' time-varying clinical conditions. The
sequential multiple assignment randomized trial (SMART) is an experimental
design that can provide high-quality evidence for constructing optimal DTRs. In
a conventional SMART, participants are randomized to available treatments at
multiple stages with balanced randomization probabilities. Despite its relative
simplicity of implementation and desirable performance in comparing embedded
DTRs, the conventional SMART faces inevitable ethical issues including
assigning many participants to the empirically inferior treatment or the
treatment they dislike, which might slow down the recruitment procedure and
lead to higher attrition rates, ultimately leading to poor internal and
external validities of the trial results. In this context, we propose a SMART
under the Experiment-as-Market framework (SMART-EXAM), a novel SMART design
that holds the potential to improve participants' welfare by incorporating
their preferences and predicted treatment effects into the randomization
procedure. We describe the steps of conducting a SMART-EXAM and evaluate its
performance compared to the conventional SMART. The results indicate that the
SMART-EXAM can improve the welfare of the participants enrolled in the trial,
while also achieving a desirable ability to construct an optimal DTR when the
experimental parameters are suitably specified. We finally illustrate the
practical potential of the SMART-EXAM design using data from a SMART for
children with attention-deficit/hyperactivity disorder (ADHD).
