Research Paradigm Mismatch: How Patients and Health Care Professionals Seek Health-Related Information Online

Understanding how patients and health care professionals seek and interpret health information online helps to mitigate knowledge gaps at decision points, leading to improved shared decision-making and better health outcomes. The objective of this study was to improve decision-making by identifing themes in how patients, practitioners, and health care researchers seek health information online.

This qualitative focus group study occurred from October 2024 to February 2025. An inductive thematic analysis was used to identify emerging themes directly from the sessions.

A total of 31 participants took part in 7 focus group sessions. Of the participants, 65% were female, 52% self-identified as White, and 62% were between 18 and 34 years. Regarding level of education, 4 participants (13%) had a high school diploma/general educational development degree, although 81% had a bachelor's or graduate-level degree. Four participants (13%) were nonnative English speakers. Three major themes emerged surrounding online sources, social media usage, and trust.

This study revealed critical divergences in online health information-seeking across stakeholder groups. Patients increasingly rely on social media platforms like Reddit and TikTok for peer-driven narratives, whereas practitioners are more inclined to exclusively consult peer-reviewed literature. This divide creates information asymmetry that can undermine shared decision-making when patients are informed by experiential knowledge that practitioners lack or dismiss. All groups began online searches with Google but followed distinct pathways and relied primarily on surface-level credibility markers rather than systematic evaluation. To bridge these divides, the authors recommend integrating patient-sourced information training into medical education, incorporating information-seeking discussions into clinical encounters, and developing resources that bridge experiential and clinical knowledge. Researchers should also accelerate evidence translation through rapid translation mechanisms and partnerships with trusted platforms. As artificial intelligence tools increasingly shape health information access, understanding these evolving patterns remains essential for effective collaborative decision-making and potentially improved health outcomes.