Non-Compliance and Instrumental Variables in Behavioural Medicine: a Commentary on van Dongen et al.

The paper by van Dongen et al. [1] in this issue is to be commended on many levels. It contributes substantially to the blood donor recruitment and mere-measurement literatures and highlights the importance of replication. Importantly, it opens up the debate on the causes and consequences of non-compliance in randomised controlled trials (RCTs) in behav-ioural medicine. Non-compliance introduces non-random selection bias to RCTs and has implications for causality, generalizability and policy [2–5]. Therefore, reducing bias caused by non-compliance either methodologically or statistically is important. Methodological solutions to this bias are less likely to be used than statistical ones, due, in part, to the lack of coherent frameworks to understand non-compliance. Indeed, as van Don-gen et al. [1] highlight, non-compliance is complex, arising from person characteristics (e.g. attitudes to trials and conscientious-ness), intervention idiosyncrasies or person/intervention interactions [6]. A first step in a methodological solution would be to identify psychological (traits, attitudes, beliefs) and demographic characteristics that differentiate compliant from non-compliant behaviour in treatment and control arms of trials. A framework developed by Angrist and colleagues offers a useful starting point [2–4]. This model identifies four groups [2–4]. The first group comply with the intervention protocol regardless of their assignment to the treatment or control arms: these are called compliers. The second group comply only if allocated to the treatment but not the control arm: called always-takers or may also be termed treatment only compliers. The third group comply if allocated to the control but not the treatment arm: the never-takers or control only compliers. The final group—defiers —do not comply with whichever arm they are allocated. Using these groups, non-compliance could be studied at a general or trial-specific level. At a general level, these four groups could be identified with respect to stable preferences to comply or not with treatment or control arm protocols across a variety of RCTs. Any stable psychological and demographic differences across these groups could be fed into compliance enhancing designs. For a specific RCT, it would be possible to explore how different intervention protocols influence who are likely to be treatment-only and control-only compliers and this information used to enhance compliance in both treatment and control arms. For example, in general, financially incentivized questionnaires (treatment arm) increase compliance relative to non-incentivized questionnaires (control arm) [7]. However, for blood donors, financially incentivized questionnaires may be either counter-productive [8] or helpful [9–13] for compliance. Identifying if incentivizing …