Content analysis reveals significant accuracy differences across web-based gynecological cancer resources, indicating that source attribution strongly predicts online information quality.
Chinese internet users increasingly seek health information online, yet little research has examined the quality of gynecological cancer resources specifically. This exploratory study analyzed 78 websites from Baidu search results to assess their information quality and communicative features. Three website categories emerged: encyclopedic health content (n = 32), expert-guided health content (n = 37), and self-media health content (n = 9). While most quality dimensions showed comparable performance across types, accuracy differed significantly (p = .026), with encyclopedia and expert-guided content outperforming self-media platforms. Source attribution proved the strongest predictor of overall quality. These preliminary findings provide practical guidance for librarians and health educators directing consumers to credible gynecological cancer information.
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Huang et al. (2026) studied this question.
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