ArticleDigital health
Dynamic identity management in online health communities: How illness stage moderates the effects of anonymity - A longitudinal panel data analysis.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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2 authors.
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Abstract
Objective: This study examines how anonymity influences self-disclosure and social feedback across illness stages, and whether these effects vary with disease progression. To theorize these dynamics, we propose a Dynamic Identity Management (DIM) framework to visualize how anonymity shapes self-disclosure and social feedback, and whether these effects vary with disease progression. Methods: We collected posts from the "Cancer" super-topic on Zhihu between January 2018 and January 2024 using Python web crawlers. Through semantic embedding (Sentence-BERT) and clustering (similarity threshold=0.8), we linked anonymous posts to their real-name authors, constructing a six-year longitudinal panel dataset of 1,998 posts from 215 users. User and year fixed-effects models were employed to estimate the causal effects of anonymity on disclosure motivation, emotional expression, information breadth and sensitivity, and social feedback (likes and comments), with illness stage (initial diagnosis, mid-stage, terminal) as a moderator. Results: Anonymity significantly increased intrinsic disclosure motivation ( Conclusion: Anonymity selectively facilitates intrinsic motivation and negative emotional expression but does not increase social feedback or factual information disclosure. Users dynamically manage identity across the illness stage: in high-risk stages (initial diagnosis and terminal), they prioritize emotional release through anonymity, even though this reduces social feedback relative to real-name posting; in the low-risk mid-stage, they use anonymity for intrinsically motivated disclosure without losing social feedback. This pattern supports the DIM framework's proposition: anonymity is not a fixed personal attribute; its effects depend on the illness stage. By specifying this dynamic mechanism, the DIM framework advances understanding of anonymity in OHCs and offers actionable insights for designing stage-sensitive health support systems.
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