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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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| 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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| author | Mengyuan Peng Kaixuan Zhu Yadi Gu Xuejie Yang Kaixiang Su Dongxiao Gu |
| author_facet | Mengyuan Peng Kaixuan Zhu Yadi Gu Xuejie Yang Kaixiang Su Dongxiao Gu |
| author_sort | Mengyuan Peng |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-fa9f9334259f41c78028ebe0b6c7a847 |
| institution | Kabale University |
| issn | 0718-1876 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Theoretical and Applied Electronic Commerce Research |
| spelling | doaj-art-fa9f9334259f41c78028ebe0b6c7a8472025-08-20T03:27:33ZengMDPI AGJournal of Theoretical and Applied Electronic Commerce Research0718-18762025-03-012025610.3390/jtaer20020056How to Self-Disclose? The Impact of Patients’ Linguistic Features on Doctors’ Service Quality in Online Health CommunitiesMengyuan Peng0Kaixuan Zhu1Yadi Gu2Xuejie Yang3Kaixiang Su4Dongxiao Gu5School of Management, Hefei University of Technology, Hefei 230009, ChinaSchool of Management, Hefei University of Technology, Hefei 230009, ChinaMental Health Education Center, University of Shanghai for Science and Technology, Shanghai 200093, ChinaSchool of Humanity and Law, Hefei University of Technology, Hefei 230009, ChinaSchool of Management, Hefei University of Technology, Hefei 230009, ChinaSchool of Management, Hefei University of Technology, Hefei 230009, ChinaIn 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.https://www.mdpi.com/0718-1876/20/2/56self-disclosurelinguistic featuresservice qualityinformational supportemotional support |
| spellingShingle | Mengyuan Peng Kaixuan Zhu Yadi Gu Xuejie Yang Kaixiang Su Dongxiao Gu How to Self-Disclose? The Impact of Patients’ Linguistic Features on Doctors’ Service Quality in Online Health Communities Journal of Theoretical and Applied Electronic Commerce Research self-disclosure linguistic features service quality informational support emotional support |
| title | How to Self-Disclose? The Impact of Patients’ Linguistic Features on Doctors’ Service Quality in Online Health Communities |
| title_full | How to Self-Disclose? The Impact of Patients’ Linguistic Features on Doctors’ Service Quality in Online Health Communities |
| title_fullStr | How to Self-Disclose? The Impact of Patients’ Linguistic Features on Doctors’ Service Quality in Online Health Communities |
| title_full_unstemmed | How to Self-Disclose? The Impact of Patients’ Linguistic Features on Doctors’ Service Quality in Online Health Communities |
| title_short | How to Self-Disclose? The Impact of Patients’ Linguistic Features on Doctors’ Service Quality in Online Health Communities |
| title_sort | how to self disclose the impact of patients linguistic features on doctors service quality in online health communities |
| topic | self-disclosure linguistic features service quality informational support emotional support |
| url | https://www.mdpi.com/0718-1876/20/2/56 |
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