Exploring patient motivations and preferences for medical data sharing with researchers: a simulation study using the iAgree platform.

Keller, Michelle Sophie; Nguyen, An T; Leder, Chloe; Chen, Yunan; Morse, Brad; Schilling, Lisa M; Hu, Di; SooHoo, Spencer et al. · J Am Med Inform Assoc · 2026

cross_sectional · Level IV

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Abstract

This study explores patient motivations and preferences for sharing medical data with researchers using the iAgree platform. We examine how study characteristics, including data type requested and data-sharing arrangements, influence consent decisions, and assess the role of demographic factors, privacy concerns, and perceived benefits in shaping data-sharing behavior. We conducted a mixed-methods study with 527 US adults (≥18 years) recruited via advisory boards, social media, clinics, and newsletters. Participants completed 3 of 4 simulated studies on iAgree, each varying by data elements requested and data-sharing scope. Participants provided consent and data-sharing decisions and completed a post-simulation survey capturing demographics, data-sharing motivations, privacy concerns, and patient activation. We used logistic regressions to examine associations between demographics, privacy concerns, and patient activation and: (1) consent status and (2) willingness to share particular data elements. Finally, we applied thematic analysis to open-ended responses. Consent status did not significantly vary by data type or study design. However, participants citing altruism, personal benefit, and patient solidarity were more likely to share data. Higher privacy concerns were linked to lower willingness to share family health and mental health information. Participants with higher patient activation were also less likely to share data. Demographic factors were not significantly associated with consent or willingness to share data, countering common assumptions about disparities in sharing preferences. Altruism and perceived benefit drive willingness to share health data, while privacy concerns and patient activation may reduce it, emphasizing the need for patient-centered, transparent consent models.