ArticleJournal of medical Internet research2019
Predictors of Patients' Intention to Interact With Doctors in Web-Based Health Communities in China: Cross-Sectional Study.
Article in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 14 citations in OpenAlex.
- The Impact of Popular Science Articles by Physicians on Their Performance on Online Medical Platforms.Healthcare (Basel, Switzerland) · 2022Article
- Are Diverse Media Better than a Single Medium? The Relationship between Mixed Media and Perceived Effect from the Perspective of Online Psychological Counseling.International journal of environmental research and public health · 2021Article
- The Impact of Gamification-Induced Users' Feelings on the Continued Use of mHealth Apps: A Structural Equation Model With the Self-Determination Theory Approach.Journal of medical Internet research · 2021Article
- Influences of Medical Crowdfunding Website Design Features on Trust and Intention to Donate: Controlled Laboratory Experiment.Journal of medical Internet research · 2021Article
- Sharing of Verified Information about COVID-19 on Social Network Sites: A Social Exchange Theory Perspective.International journal of environmental research and public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWeb-based health communities provide opportunities for doctors and patients to interact with each other and change the traditional communication mode between doctors and patients. However, little is known about the predictors of patients' intention to interact with doctors in Web-based health communities in China.
objectiveThe purpose of this study was to investigate what are the predictors of patients' intention to interact with doctors in Web-based health communities in China.
methodsOn the basis of two-factor theory and service convenience theory, we propose that the attributes of Web-based health communities including ease of use and perceived synchronicity influence patients' intention to interact through convenience of Web-based health communities, whereas the attributes of physical health facilities such as inaccessibility and discontinuity affect patients' intention to interact through inconvenience of physical health facilities. We employed the survey method to validate our hypothesized relationships. Through developing the measurement instruments, we collected 334 valid answers from Web health community users and utilized partial least square to analyze the data.
resultsEase of use (t
conclusionsThrough including factors from both Web-based health communities and physical health facilities, we can understand patients' intention to interact comprehensively. This study not only contributes to literature of doctor-patient interaction and Web-based health platforms but also provides implications to promote doctor-patient interaction online and offline.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.