Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Mar 16, 2020
Date Accepted: Aug 6, 2020
Date Submitted to PubMed: Aug 10, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Research On the Influencing Factor Model of Online Continuous Diagnosis-Treatment for Diabetic Patients
ABSTRACT
Background:
Background：The internet has become a major mean for patient to acquire healthcare information and continuous diagnosis and treatment online. However, the web-based healthcare information is usually of mixed quality, this raises the concern about the credibility of online doctor’s advice and markedly affect patients’ choice and decision-making with regard to online diagnosis and treatment behavior. According to trust theory, patient’s trust in their online physicians may potentially have indirect effects on patient’s health-information-seeking and selection of online diagnosis and treatment behavior. Therefore, it is important to identify the influencing factors of continuous online diagnosis and treatment from the perspective of trust.
Objective:
The objective of our study is to investigate the influencing factors of patient’s online continuous diagnosis-treatment behavior based on ELM theory and trust theory in the face of a decline in physiological conditions and the lack of long-term, convenient professional guidance.
Methods:
Methods：Data on diabetic patients in China who used the online health community twice or more from 2018 to June 2019 were collected by developing web crawler. A total of 2,437 valid data were obtained and then analyzed by using correlation factor analysis and regression analysis to validate our research model and hypotheses.
Results:
The analytic results are as the follows. Frist, the timely response rate under central route, reference group under peripheral route, as well as the number of thank-you letters and patient’s rating that measure doctor’s online word of mouth, are all positively related with diabetic patient’s online continuous diagnosis and treatment behavior. Second, doctor’s professional title and hospital’s ranking level have weak effect on diabetic patient’s online continuous diagnosis and treatment behavior, and the effect size of doctor’s professional title is greater than that of hospital’s ranking level.
Conclusions:
From the patient's perspective, of all indicators that measure doctor’s service quality, the effect size of timely response rate is much greater than that of effect satisfaction and attitude satisfaction, playing essential role in influencing patient's online continuous diagnosis and treatment behavior. In addition, the effect size of online word-of-mouth is also greater than that of doctor’s offline reputation. The implications for the improvement of online doctor’s service quality and sustainable development of the platform are as the follows. Doctors online should seek clues of patient’s need and preference for health information from online doctor-patient interactions, and make full use of doctor’s professionalism and service reliability to communicate effectively with patients. Furthermore, the platform should improve the online word-of-mouth mechanism to realize its full potential in trust transmission and motivating, ultimately promoting patient’s information sharing and continuous diagnosis and treatment behavior online.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.