Text Analysis and Optimization of Privacy Policy of Health Information Platform from the Perspective of Dual Perception

Corresponding author: qianaibing, 280989@njucm.edu.cn

DOI: 10.12201/bmr.202509.00004

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  Abstract: Purpose/Significance: From the dual perspectives of perceived ease of use and perceived usefulness, this study systematically analyzes the textual characteristics of privacy policies of health information platforms to enhance the transparency and user-friendliness of policy design, providing theoretical and practical foundations for policy optimization. Method/Process: The privacy policy texts of 17 mainstream health information platforms were selected, and a perceived ease of use index system was constructed based on the TAM model. The LDA topic model was used to identify policy themes. Results/Conclusions: The current privacy policies of health information platforms generally suffer from poor comprehensibility, heavy reading burdens, and complex access paths. Overall, they remain centered around the interests of the platform, lacking consideration for users cognitive abilities. Privacy design concepts such as default protection should be introduced to enhance the recognizability and readability of policies, promoting a transformation of privacy policies from compliance-focused to a multi-dimensional approach centered on user understanding and trust, achieving a balance of usability, accessibility, and user orientation.

  Key words: Health Information Platforms; Privacy Policies; Text Analysis; LDA Model

  Submit time: 1 September 2025

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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