Jusheng Liu, Mei Song, Chaoran Li, Shanshan Guo, Jingti Han
{"title":"患者交流的特点对在线健康社区中医生反馈的影响：一项观察性横断面研究","authors":"Jusheng Liu, Mei Song, Chaoran Li, Shanshan Guo, Jingti Han","doi":"10.1080/10410236.2023.2300901","DOIUrl":null,"url":null,"abstract":"<p><p>With the rapid development of e-health and telemedicine, previous studies have explored the relationship between physician-patient communication and patient satisfaction; however, there is a paucity of research on the influence of the characteristics of patient communication on the characteristics of physician feedback. Based on the communication accommodation theory, as well as the computer-mediated communication theory and media richness theory, this study aimed to explore how characteristics of patient communication influence characteristics of physician feedback in online health communities. We employed a crawler software to download the communication data between 1652 physicians and 105,325 patients from the Good Doctor platform, the biggest online health community in China. We built an empirical model using this data and employed a multilevel model to test our hypotheses using Stata and Python software. The results indicate that the amount of patients' rendered information positively influences the physicians' text (<i>α</i> = 0.123, <i>t</i> = 33.147, <i>P</i> < .001) and voice feedback (<i>β</i> = 0.201, <i>t</i> = 40.011, <i>P</i> < .001). Patients' hope for help signals and the provision of their electronic health records weaken the effect of the amount of patients' rendered information on physicians' text feedback (<i>α </i>= -0.040, <i>t </i>= -24.857, <i>P</i> < .001; <i>α </i>= -0.048, <i>t </i>= -15.784, <i>P</i> < .001), whereas, it strengthened the effect of the amount of patients' rendered information on physicians' voice feedback (<i>β</i> = 0.033, <i>t</i> = 14.789, <i>P</i> < .001; <i>β</i> = 0.017, <i>t</i> = 4.208, <i>P</i> < .001). Moreover, the occurrence of high-privacy diseases strengthened the effect of the amount of patients' presented information on physicians' text and voice feedback (<i>α</i> = 0.023, <i>t</i> = 4.870, <i>P</i> < .001; <i>β</i> = 0.028, <i>t</i> = 4.282, <i>P</i> < .001). This research contributes to the development of computer-mediated communication theories and sheds light on service delivery in the online health community.</p>","PeriodicalId":12889,"journal":{"name":"Health Communication","volume":" ","pages":"3009-3031"},"PeriodicalIF":3.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Effect of Characteristics of Patient Communication on Physician Feedback in Online Health Communities: An Observational Cross-Sectional Study.\",\"authors\":\"Jusheng Liu, Mei Song, Chaoran Li, Shanshan Guo, Jingti Han\",\"doi\":\"10.1080/10410236.2023.2300901\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>With the rapid development of e-health and telemedicine, previous studies have explored the relationship between physician-patient communication and patient satisfaction; however, there is a paucity of research on the influence of the characteristics of patient communication on the characteristics of physician feedback. Based on the communication accommodation theory, as well as the computer-mediated communication theory and media richness theory, this study aimed to explore how characteristics of patient communication influence characteristics of physician feedback in online health communities. We employed a crawler software to download the communication data between 1652 physicians and 105,325 patients from the Good Doctor platform, the biggest online health community in China. We built an empirical model using this data and employed a multilevel model to test our hypotheses using Stata and Python software. The results indicate that the amount of patients' rendered information positively influences the physicians' text (<i>α</i> = 0.123, <i>t</i> = 33.147, <i>P</i> < .001) and voice feedback (<i>β</i> = 0.201, <i>t</i> = 40.011, <i>P</i> < .001). Patients' hope for help signals and the provision of their electronic health records weaken the effect of the amount of patients' rendered information on physicians' text feedback (<i>α </i>= -0.040, <i>t </i>= -24.857, <i>P</i> < .001; <i>α </i>= -0.048, <i>t </i>= -15.784, <i>P</i> < .001), whereas, it strengthened the effect of the amount of patients' rendered information on physicians' voice feedback (<i>β</i> = 0.033, <i>t</i> = 14.789, <i>P</i> < .001; <i>β</i> = 0.017, <i>t</i> = 4.208, <i>P</i> < .001). Moreover, the occurrence of high-privacy diseases strengthened the effect of the amount of patients' presented information on physicians' text and voice feedback (<i>α</i> = 0.023, <i>t</i> = 4.870, <i>P</i> < .001; <i>β</i> = 0.028, <i>t</i> = 4.282, <i>P</i> < .001). 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The Effect of Characteristics of Patient Communication on Physician Feedback in Online Health Communities: An Observational Cross-Sectional Study.
With the rapid development of e-health and telemedicine, previous studies have explored the relationship between physician-patient communication and patient satisfaction; however, there is a paucity of research on the influence of the characteristics of patient communication on the characteristics of physician feedback. Based on the communication accommodation theory, as well as the computer-mediated communication theory and media richness theory, this study aimed to explore how characteristics of patient communication influence characteristics of physician feedback in online health communities. We employed a crawler software to download the communication data between 1652 physicians and 105,325 patients from the Good Doctor platform, the biggest online health community in China. We built an empirical model using this data and employed a multilevel model to test our hypotheses using Stata and Python software. The results indicate that the amount of patients' rendered information positively influences the physicians' text (α = 0.123, t = 33.147, P < .001) and voice feedback (β = 0.201, t = 40.011, P < .001). Patients' hope for help signals and the provision of their electronic health records weaken the effect of the amount of patients' rendered information on physicians' text feedback (α = -0.040, t = -24.857, P < .001; α = -0.048, t = -15.784, P < .001), whereas, it strengthened the effect of the amount of patients' rendered information on physicians' voice feedback (β = 0.033, t = 14.789, P < .001; β = 0.017, t = 4.208, P < .001). Moreover, the occurrence of high-privacy diseases strengthened the effect of the amount of patients' presented information on physicians' text and voice feedback (α = 0.023, t = 4.870, P < .001; β = 0.028, t = 4.282, P < .001). This research contributes to the development of computer-mediated communication theories and sheds light on service delivery in the online health community.
期刊介绍：
As an outlet for scholarly intercourse between medical and social sciences, this noteworthy journal seeks to improve practical communication between caregivers and patients and between institutions and the public. Outstanding editorial board members and contributors from both medical and social science arenas collaborate to meet the challenges inherent in this goal. Although most inclusions are data-based, the journal also publishes pedagogical, methodological, theoretical, and applied articles using both quantitative or qualitative methods.
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