Review of strategies to investigate low sample return rates in remote tobacco trials: A call to action for more user-centered design research

Abstract

Remote collection of biomarkers of tobacco use in clinical trials poses significant challenges. A recent meta-analysis and scoping review of the smoking cessation literature indicated that sample return rates are low and that new methods are needed to investigate the underlying causes of these low rates. In this paper we conducted a narrative review and heuristic analysis of the different human factors approaches reported to evaluate and/or improve sample return rates among 31 smoking cessation studies recently identified in the literature. We created a heuristic metric (with scores from 0 to 4) to evaluate the level of elaboration or complexity of the user-centered design strategy reported by researchers. Our review of the literature identified five types of challenges typically encountered by researchers (in that order): usability and procedural, technical (device related), sample contamination (e.g., polytobacco), psychosocial factors (e.g., digital divide), and motivational factors. Our review of strategies indicated that 35% of the studies employed user-centered design methods with the remaining studies relying on informal methods. Among the studies that employed user-centered design methods, only 6% reached a level of 3 in our user-centered design heuristic metric. None of the studies reached the highest level of complexity (i.e., 4). This review examined these findings in the context of the larger literature, discussed the need to address the role of health equity factors more directly, and concluded with a call to action to increase the application and reporting of user-centered design strategies in biomarkers research.