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Getting to know my disease better: The influence of linguistic features of patients’ self-disclosure on physicians’ social support in online health consultation

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Abstract

The popularity of online health consultation (OHC) has grown rapidly in recent years and has become a common method for patients to receive affordable healthcare. Despite its widespread use, the impact of patients’ linguistic styles when describing disease symptoms on their continued engagement in consultation remains unclear. Drawing upon social support theory, this study examines the relationship between patients’ linguistic features in self-disclosing disease symptoms and their continued consultation behavior, specifically investigating the role of doctors’ social support. Data was collected from 46,012 patient consultation records on a leading Chinese online health platform. The study’s empirical results demonstrate that the sentence complexity of patients’ self-disclosure has an inverted-U relationship with physicians’ doctors’ social support, while the text length and affective expression of patients’ self-disclosure are positively effective in invoking doctors’ social support in online health consultation. Moreover, the study identifies the moderating influence of patients’ offline visit experience on the above relationships. Finally, for patients with (or without) offline visit experience, doctors’ informational support increases (or decreases) the likelihood of patients’ continued consultation. This study contributes to the creation of long-term doctor-patient relationships in OHCs and the design of platforms through the retention of patients.

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Data Availability

Data are available on reasonable request from the corresponding author.

Notes

  1. https://www.chyxx.com/industry/1106183.html

  2. Note: we search articles with keywords such as “social support,” “informational support,” and “emotional support” in some leading IS journals, including Decision Support Systems, European Journal of Information Systems, Information & Management, Information Systems Journal, Information Systems Research, Journal of the Association for Information Systems, Journal of Management Information Systems, and MIS Quarterly. Some other representative articles from International Journal of Medical Informatics, Journal of Medical Internet Research, Technological Forecasting and Social Change, and Computers in Human Behavior were also included.

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Funding

This work was supported by the National Natural Science Foundation of China (grant numbers 71971008, 72104017), the Beijing Natural Science Foundation (grant number 9222020), and the China Postdoctoral Science Foundation (grant number 2021M690006).

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Authors and Affiliations

  1. School of Economics and Management, Beihang University, Beijing, 100191, China

    Linlin Jing, Wei Shan & Xiaoxiao Shi

  2. Key Laboratory of Complex System Analysis and Management Decision, Ministry of Education, Beijing, 100191, China

    Wei Shan

  3. Faculty of Computer Science, Dalhousie University, Halifax, NS, B3H 4R2, Canada

    Richard David Evans

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  1. Linlin Jing
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  2. Wei Shan
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  3. Richard David Evans
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  4. Xiaoxiao Shi
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Correspondence to Xiaoxiao Shi.

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Jing, L., Shan, W., Evans, R.D. et al. Getting to know my disease better: The influence of linguistic features of patients’ self-disclosure on physicians’ social support in online health consultation. Electron Markets 34, 17 (2024). https://doi.org/10.1007/s12525-024-00700-8

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