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Citing this Article

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Published on 01.06.15 in Vol 17, No 6 (2015): June

This paper is in the following e-collection/theme issue:

Works citing "The Development of Online Doctor Reviews in China: An Analysis of the Largest Online Doctor Review Website in China"

According to Crossref, the following articles are citing this article (DOI 10.2196/jmir.4365):

(note that this is only a small subset of citations)

  1. Schulz PJ, Rothenfluh F. Influence of Health Literacy on Effects of Patient Rating Websites: Survey Study Using a Hypothetical Situation and Fictitious Doctors. Journal of Medical Internet Research 2020;22(4):e14134
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  3. Li Y, Yan X, Song X. Provision of Paid Web-Based Medical Consultation in China: Cross-Sectional Analysis of Data From a Medical Consultation Website. Journal of Medical Internet Research 2019;21(6):e12126
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  4. . How does patient-centered communication improve emotional health? An exploratory study in China. Asian Journal of Communication 2018;28(3):298
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  5. Han X, Qu J, Zhang T. Exploring the impact of review valence, disease risk, and trust on patient choice based on online physician reviews. Telematics and Informatics 2019;45:101276
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  6. . Webcare in healthcare: providers' responses to patients' online reviews. British Journal of Healthcare Management 2019;25(10):1
    CrossRef
  7. Deng Z, Hong Z, Zhang W, Evans R, Chen Y. The Effect of Online Effort and Reputation of Physicians on Patients’ Choice: 3-Wave Data Analysis of China’s Good Doctor Website. Journal of Medical Internet Research 2019;21(3):e10170
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  8. Han X, Li B, Zhang T, Qu J. Factors Associated With the Actual Behavior and Intention of Rating Physicians on Physician Rating Websites: Cross-Sectional Study. Journal of Medical Internet Research 2020;22(6):e14417
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  9. Vu AF, Espinoza GM, Perry JD, Chundury RV. Online Ratings of ASOPRS Surgeons: What Do Your Patients Really Think of You?. Ophthalmic Plastic & Reconstructive Surgery 2017;33(6):466
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  10. . Talk to Your Doctors Online: An Internet-based Intervention in China. Health Communication 2021;36(4):405
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  11. Hao H, Zhang K, Wang W, Gao G. A tale of two countries: International comparison of online doctor reviews between China and the United States. International Journal of Medical Informatics 2017;99:37
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  12. Hu J, Zhang X, Yang Y, Liu Y, Chen X. New doctors ranking system based on VIKOR method. International Transactions in Operational Research 2020;27(2):1236
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  13. Rivas R, Montazeri N, Le NX, Hristidis V. Automatic Classification of Online Doctor Reviews: Evaluation of Text Classifier Algorithms. Journal of Medical Internet Research 2018;20(11):e11141
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  14. . Negative Online Patient Reviews in Headache Medicine. Headache: The Journal of Head and Face Pain 2018;58(9):1435
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  15. Liu JJ, Goldberg HR, Lentz EJ, Matelski JJ, Alam A, Bell CM. Association Between Web-Based Physician Ratings and Physician Disciplinary Convictions: Retrospective Observational Study. Journal of Medical Internet Research 2020;22(5):e16708
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  16. Lin Y, Hong YA, Henson BS, Stevenson RD, Hong S, Lyu T, Liang C. Assessing Patient Experience and Healthcare Quality of Dental Care Using Patient Online Reviews in the United States: Mixed Methods Study. Journal of Medical Internet Research 2020;22(7):e18652
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  17. Hong YA, Liang C, Radcliff TA, Wigfall LT, Street RL. What Do Patients Say About Doctors Online? A Systematic Review of Studies on Patient Online Reviews. Journal of Medical Internet Research 2019;21(4):e12521
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  18. Emmert M, Wiener M. What factors determine the intention to use hospital report cards? The perspectives of users and non-users. Patient Education and Counseling 2017;100(7):1394
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  19. Bidmon S, Elshiewy O, Terlutter R, Boztug Y. What Patients Value in Physicians: Analyzing Drivers of Patient Satisfaction Using Physician-Rating Website Data. Journal of Medical Internet Research 2020;22(2):e13830
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  20. Shah AM, Yan X, Shah SAA, Mamirkulova G. Mining patient opinion to evaluate the service quality in healthcare: a deep-learning approach. Journal of Ambient Intelligence and Humanized Computing 2020;11(7):2925
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  21. Chien T, Lin W. Improving Inpatient Surveys: Web-Based Computer Adaptive Testing Accessed via Mobile Phone QR Codes. JMIR Medical Informatics 2016;4(1):e8
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  22. Li J, Liu M, Li X, Liu X, Liu J. Developing Embedded Taxonomy and Mining Patients’ Interests From Web-Based Physician Reviews: Mixed-Methods Approach. Journal of Medical Internet Research 2018;20(8):e254
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  23. Liu J, Zhang W, Jiang X, Zhou Y. Data Mining of the Reviews from Online Private Doctors. Telemedicine and e-Health 2020;26(9):1157
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  24. Pramanik MI, Lau RY, Demirkan H, Azad MAK. Smart health: Big data enabled health paradigm within smart cities. Expert Systems with Applications 2017;87:370
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  25. Ma Z, Wu M. The Psychometric Properties of the Chinese eHealth Literacy Scale (C-eHEALS) in a Chinese Rural Population: Cross-Sectional Validation Study. Journal of Medical Internet Research 2019;21(10):e15720
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  26. Hu G, Han X, Zhou H, Liu Y. Public Perception on Healthcare Services: Evidence from Social Media Platforms in China. International Journal of Environmental Research and Public Health 2019;16(7):1273
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  27. . The Relationship between Face-to-Face and Online Patient-Provider Communication: Examining the Moderating Roles of Patient Trust and Patient Satisfaction. Health Communication 2020;35(3):341
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  28. Schlesinger M, Grob R, Shaller D, Martino SC, Parker AM, Rybowski L, Finucane ML, Cerully JL. A Rigorous Approach to Large-Scale Elicitation and Analysis of Patient Narratives. Medical Care Research and Review 2020;77(5):416
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  29. Li L, Zeng Y, Zhang Z, Fu C. The Impact of Internet Use on Health Outcomes of Rural Adults: Evidence from China. International Journal of Environmental Research and Public Health 2020;17(18):6502
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  30. Shah AM, Yan X, Shah SAA, Shah SJ, Mamirkulova G. Exploring the impact of online information signals in leveraging the economic returns of physicians. Journal of Biomedical Informatics 2019;98:103272
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  31. Wang J, Chiu Y, Yu H, Hsu Y. Understanding a Nonlinear Causal Relationship Between Rewards and Physicians’ Contributions in Online Health Care Communities: Longitudinal Study. Journal of Medical Internet Research 2017;19(12):e427
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  32. . Quantitative Ratings and Narrative Comments on Swiss Physician Rating Websites: Frequency Analysis. Journal of Medical Internet Research 2019;21(7):e13816
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  33. Liu JJ, Matelski JJ, Bell CM. Scope, Breadth, and Differences in Online Physician Ratings Related to Geography, Specialty, and Year: Observational Retrospective Study. Journal of Medical Internet Research 2018;20(3):e76
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  34. Powell J, Atherton H, Williams V, Mazanderani F, Dudhwala F, Woolgar S, Boylan A, Fleming J, Kirkpatrick S, Martin A, van Velthoven M, de Iongh A, Findlay D, Locock L, Ziebland S. Using online patient feedback to improve NHS services: the INQUIRE multimethod study. Health Services and Delivery Research 2019;7(38):1
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  35. Hao H, Zhang K. The Voice of Chinese Health Consumers: A Text Mining Approach to Web-Based Physician Reviews. Journal of Medical Internet Research 2016;18(5):e108
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  36. Jiang S, Street RL. Pathway Linking Internet Health Information Seeking to Better Health: A Moderated Mediation Study. Health Communication 2017;32(8):1024
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  37. . Healthcare at Your Fingertips: The Acceptance and Adoption of Mobile Medical Treatment Services among Chinese Users. International Journal of Environmental Research and Public Health 2020;17(18):6895
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  38. Zhao X, Fan J, Basnyat I, Hu B. Online Health Information Seeking Using “#COVID-19 Patient Seeking Help” on Weibo in Wuhan, China: Descriptive Study. Journal of Medical Internet Research 2020;22(10):e22910
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  39. Zhang S, Wang J, Chiu Y, Hsu Y. Exploring Types of Information Sources Used When Choosing Doctors: Observational Study in an Online Health Care Community. Journal of Medical Internet Research 2020;22(9):e20910
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  40. Yan Y, Yu G, Yan X, Lo Bosco G. Online Doctor Recommendation with Convolutional Neural Network and Sparse Inputs. Computational Intelligence and Neuroscience 2020;2020:1
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  41. Fan G, Deng Z, Ye Q, Wang B. Machine learning-based prediction models for patients no-show in online outpatient appointments. Data Science and Management 2021;2:45
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  42. Chiu Y, Wang J, Yu H, Hsu Y. Consultation Pricing of the Online Health Care Service in China: Hierarchical Linear Regression Approach. Journal of Medical Internet Research 2021;23(7):e29170
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  43. Hu Y, Zhou H, Chen Y, Yao J, Su J. The influence of patient-generated reviews and doctor-patient relationship on online consultations in China. Electronic Commerce Research 2023;23(2):1115
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  44. Lu Y, Wang Q. Doctors’ Preferences in the Selection of Patients in Online Medical Consultations: An Empirical Study with Doctor–Patient Consultation Data. Healthcare 2022;10(8):1435
    CrossRef
  45. Shah AM, Muhammad W, Lee K. Investigating the effect of service feedback and physician popularity on physician demand in the virtual healthcare environment. Information Technology & People 2023;36(3):1356
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  46. Zhuang Y, Zhou J, Liu S, Wang Q, Qian J, Zou X, Peng H, Xue T, Jin Z, Wu C. Yiqi Jianpi Huayu Jiedu Decoction Inhibits Metastasis of Colon Adenocarcinoma by Reversing Hsa-miR-374a-3p/Wnt3/β-Catenin-Mediated Epithelial–Mesenchymal Transition and Cellular Plasticity. Frontiers in Oncology 2022;12
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  47. Li G, Han C, Liu P. Does Internet Use Affect Medical Decisions among Older Adults in China? Evidence from CHARLS. Healthcare 2021;10(1):60
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  48. . Discursive strategies of self-promotion by doctors in online medical consultations in China: an e-commercialised practice. Applied Linguistics Review 2023;14(5):1109
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  49. He Y, Guo X, Wu T, Vogel D. The effect of interactive factors on online health consultation review deviation: An empirical investigation. International Journal of Medical Informatics 2022;163:104781
    CrossRef
  50. Li Z, Tian L, Liu H, Tang S, Chen Q. Factors associated with parental burden among parents of children with food allergies in China: a cross-sectional study. BMJ Open 2022;12(9):e065772
    CrossRef
  51. Hsu Y, Duan R, Chiu Y, Wang J. Understanding the Inequality of Web Traffic and Engagement in Online Healthcare Communities. Frontiers in Public Health 2022;10
    CrossRef
  52. Guetz B, Bidmon S, Dür M. Awareness of and interaction with physician rating websites: A cross-sectional study in Austria. PLOS ONE 2022;17(12):e0278510
    CrossRef
  53. Fan J, Geng H, Liu X, Wang J. The Effects of Online Text Comments on Patients’ Choices: The Mediating Roles of Comment Sentiment and Comment Content. Frontiers in Psychology 2022;13
    CrossRef
  54. Chen X, Wang H, Li X. Doctor recommendation under probabilistic linguistic environment considering patient’s risk preference. Annals of Operations Research 2022;
    CrossRef
  55. Liu J, Gao L. Research on the Characteristics and Usefulness of User Reviews of Online Mental Health Consultation Services: A Content Analysis. Healthcare 2021;9(9):1111
    CrossRef
  56. Fan W, Zhou Q, Qiu L, Kumar S. Should Doctors Open Online Consultation Services? An Empirical Investigation of Their Impact on Offline Appointments. Information Systems Research 2023;34(2):629
    CrossRef
  57. Hussain A, Hakeem-ur-Rehman , Muhammad Usman Awan . Analyzing physicians ratings and reviews landscape of a developing country (Pakistan). Journal of Public Value and Administrative Insight 2021;4(2):153
    CrossRef
  58. Huang Y, Xu D, Tsuei SH, Fu H, Yip W. Understanding Impacts of Online Dual Practice on Health System Performance: A Qualitative Study in China. Health Systems & Reform 2023;9(1)
    CrossRef
  59. Li C, Li S, Yang J, Wang J, Lv Y. Topic evolution and sentiment comparison of user reviews on an online medical platform in response to COVID-19: taking review data of Haodf.com as an example. Frontiers in Public Health 2023;11
    CrossRef
  60. Dong W, Liu Y, Zhu Z, Cao X. The Impact of Ambivalent Attitudes on the Helpfulness of Web-Based Reviews: Secondary Analysis of Data From a Large Physician Review Website. Journal of Medical Internet Research 2023;25:e38306
    CrossRef
  61. Zhu Y, Wang X, You X, Zhao H, Guo Y, Cao W, Xin M, Li J. Cut-off value of the eHEALS score as a measure of eHealth skills among rural residents in Gansu, China. DIGITAL HEALTH 2023;9
    CrossRef
  62. Fan G, Deng Z, Liu LC. Understanding the antecedents of patients’ missed appointments: the perspective of attribution theory. Data Science and Management 2023;6(4):247
    CrossRef
  63. Anastasio AT, Baumann AN, Curtis DP, Rogers H, Hogge C, Ryan SF, Walley KC, Adams SB. An examination of negative one-star patient reviews for foot and ankle orthopedic surgery: A retrospective analysis. Foot and Ankle Surgery 2024;30(3):252
    CrossRef
  64. Gu H, Cai Y, Sun K, Zhao T. Equity and spatial accessibility of healthcare resources in online health community network. Frontiers in Physics 2024;11
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  65. Kalabikhina I, Moshkin V, Kolotusha A, Kashin M, Klimenko G, Kazbekova Z. Advancing Semantic Classification: A Comprehensive Examination of Machine Learning Techniques in Analyzing Russian-Language Patient Reviews. Mathematics 2024;12(4):566
    CrossRef
  66. Chen L, Rai A, Chen W, Guo X. Signaling Effects Under Dynamic Capacity in Online Matching Platforms: Evidence from Online Health Consultation Communities. Information Systems Research 2024;
    CrossRef

According to Crossref, the following books are citing this article (DOI 10.2196/jmir.4365):

  1. Song X, Song S, Chen S, Zhao Y, Zhu Q. Human Aspects of IT for the Aged Population. Design for the Elderly and Technology Acceptance. 2019. Chapter 24:332
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  2. Rizvi SQA, Wang G, Chen J. Security, Privacy, and Anonymity in Computation, Communication, and Storage. 2018. Chapter 7:84
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  3. . Advances in Advertising Research X. 2019. Chapter 2:15
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  4. . The Digital Pill: What Everyone Should Know about the Future of Our Healthcare System. 2021. :183
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