Causal models accounted for research participation effects when estimating effects in a behavioral intervention trial

OBJECTIVE: Participants in intervention studies are asked to take part in activities linked to the conduct of research, including signing consent forms and being assessed. If participants are affected by such activities through mechanisms by which the intervention is intended to work, then there is confounding. We examine how to account for research participation effects analytically. STUDY DESIGN AND SETTING: Data from a trial of a brief alcohol intervention among Swedish university students is used to show how a proposed causal model can account for assessment effects. RESULTS: The proposed model can account for research participation effects as long as researchers are willing to use existing data to make assumptions about causal influences, for instance on the magnitude of assessment effects. The model can incorporate several research processes which may introduce bias. CONCLUSIONS: As our knowledge grows about research participation effects, we may move away from asking if participants are affected by study design, toward rather asking by how much they are affected, by which activities and in which circumstances. The analytic perspective adopted here avoids assuming there are no research participation effects.