White coats in the news feed: the effects of content features on physicians' engagement behaviors in online academic medical communities

Purpose Online academic medical communities (OAMCs) have become central channels for physicians to exchange medical knowledge. Yet a substantial share of physician-generated medical content on these platforms fails to elicit meaningful peer engagement, constraining the dissemination of medical knowledge. Given that the intrinsic features of content in OAMCs are likely key drivers of peer engagement, understanding what makes content appealing is essential. However, the relationship remains unclear. This study aims to address this gap by examining how distinct content features influence different forms of peer engagement in OAMCs. Design/methodology/approach Leveraging data from a leading Chinese OAMC, we operationalize six content features (complexity, subjectivity, professionalism, completeness, informativeness, multimodal information presentation) via natural language processing and examine their effects on physicians' collecting and interacting behaviors and the moderating role of disease severity. Findings Peer physicians prioritize information-rich content for collecting, while favoring discussion-oriented content for interacting. Multimodal, comprehensive content is welcomed, whereas overly sophisticated, highly specialized content is less effective. Disease severity moderates these relationships, with physicians exhibiting greater selectivity in collecting but more interactive under high-severity conditions. Originality/value This study is among the first to uncover the impact of content features on physicians' engagement behaviors while considering disease severity as the moderating variable. By incorporating natural language processing techniques, it extends the information adoption model to online physician platforms and offers actionable guidance for optimizing physician online engagement.