Future development of eHealth programs (automated web-based health interventions) will be furthered ifprogram design can be based on knowledge of eHealth’s working mechanisms. A promising and pragmaticmethod for exploring potential working mechanisms is qualitative interview studies, in which eHealthworking mechanisms can be explored through the perspective of the program user. Qualitative interviewstudies are promising because they are suited for exploring what is yet unknown, building new knowledgeand constructing theory. They are also pragmatic, because the development of eHealth programs oftenentails user interviews for applied purposes (e.g. getting feedback for program improvement or identifyingbarriers for implementation). By capitalizing on these existing (applied) user interviews to also pursue (basic)research questions of how such programs work, the knowledge base of eHealth’s working mechanisms cangrow quickly. To be useful, such interview studies need to be of sufficient quality, which entails that theinterviews should generate enough data of sufficient quality relevant to the research question (i.e. “richdata”). However, getting rich interview data on eHealth working mechanisms can be surprisingly challenging,as several of the authors have experienced. Moreover, when encountering difficulties as we did, there arefew places to turn to: there are currently no guidelines for conducting such interview studies in a way thatensure their quality. In this paper, we build on our experience as well as the qualitative literature to addressthis need, by describing five challenges that may arise in such interviews and presenting methodologicaltools to counteract each challenge. We hope the ideas we offer will spark methodological reflections andprovide some options for researchers interested in using qualitative interview studies to explore eHealth’sworking mechanisms.
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