How to Self-Disclose? The Impact of Patients’ Linguistic Features on Doctors’ Service Quality in Online Health Communities

In online medical consultations, patients convey their medical condition through self-disclosure, and the linguistic features of this disclosure, as signals, may significantly impact doctors’ diagnostic behavior and service quality. Based on signaling theory, this paper collects consultation data fr...

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Bibliographic Details
Main Authors: Mengyuan Peng, Kaixuan Zhu, Yadi Gu, Xuejie Yang, Kaixiang Su, Dongxiao Gu
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Journal of Theoretical and Applied Electronic Commerce Research
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Online Access:https://www.mdpi.com/0718-1876/20/2/56
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Summary:In online medical consultations, patients convey their medical condition through self-disclosure, and the linguistic features of this disclosure, as signals, may significantly impact doctors’ diagnostic behavior and service quality. Based on signaling theory, this paper collects consultation data from a large online medical platform in China, employs text mining and classification techniques to extract relevant variables, and applies econometric models to empirically examine the effect of patients’ self-disclosure linguistic features on the quality of online medical services. The results indicate that the completeness and readability of patients’ self-disclosure have a significant positive impact on the quality of doctors’ services, while the expertise and positive sentiment of the disclosure have a significant negative effect. From the perspective of signaling theory, this study reveals the mechanism through which patients’ self-disclosure linguistic features influence doctors’ online consultation behavior, providing an important theoretical foundation for promoting online doctor–patient interaction and enhancing patient well-being.
ISSN:0718-1876