  We discuss the identifiability of causal estimands for generalizability and
transportability analyses, both under perfect and imperfect adherence to
treatment assignment. We consider a setting where the trial data contain
information on baseline covariates, assignment at baseline, intervention at
baseline (point treatment), and outcomes; and where the data from
non-randomized individuals only contain information on baseline covariates. In
this setting, we review identification results under perfect adherence and
study two examples in which non-adherence severely limits the ability to
transport inferences about the effects of treatment assignment to the target
population. In the first example, trial participation has a direct effect on
treatment receipt and, through treatment receipt, on the outcome (a "trial
engagement effect" via adherence). In the second example, participation in the
trial has unmeasured common causes with treatment receipt. In both examples,
the effect of assignment on the outcome in the target population is not
identifiable. In the first example, however, the effect of joint interventions
to scale-up trial activities that affect adherence and assign treatment is
identifiable. We conclude that generalizability and transportability analyses
should consider trial engagement effects via adherence and selection for
participation on the basis of unmeasured factors that influence adherence.
