ArticleJournal of medical Internet research2014
What explains usage of mobile physician-rating apps? Results from a web-based questionnaire.
Article in Journal of medical Internet research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical- and cost-effectiveness of telemedicine in type 2 diabetes mellitus: a systematic review and meta-analysis.Medicine · 2014Pooled it
- Consumers' Preferences for Purchasing mHealth Apps: Discrete Choice Experiment.JMIR mHealth and uHealth · 2023Article
- STYLCONNECT Study: An Assessment of Automatic Data Collection Devices by People Living with Diabetes and Using an Insulin Pen.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2023Article
- The Impact of Social Influence on the Intention to Use Physician Rating Websites: Moderated Mediation Analysis Using a Mixed Methods Approach.Journal of medical Internet research · 2022Article
- Factors Associated with the Patient/Client Use of Report Cards, Physician Rating Websites, Social Media, and Google for Hospital and Physician Selection: A Nationwide Survey.Healthcare (Basel, Switzerland) · 2022Article
- Nexus of Ethical Leadership, Career Satisfaction, Job Embeddedness, and Work Engagement in Hospitality Industry: A Sequential Mediation Assessment.Frontiers in psychology · 2022Article
- Developing Future-Ready University Graduates: Nurturing Wellbeing and Life Skills as Well as Academic Talent.Frontiers in psychology · 2022Article
- Predicting the Intention to Pursue Certified Professional Accountancy Qualification Among the Accounting Students.Frontiers in psychology · 2022Article
- Awareness of and interaction with physician rating websites: A cross-sectional study in Austria.PloS one · 2022Article
- Moderating Role of Initiative on the Relationship Between Intrinsic Motivation, and Self-Efficacy on Entrepreneurial Intention.Frontiers in psychology · 2022Article
- The addiction behavior of short-form video app TikTok: The information quality and system quality perspective.Frontiers in psychology · 2022Article
- Validity Evidence Based on Relations to Other Variables of the eHealth Literacy Questionnaire (eHLQ): Bayesian Approach to Test for Known-Groups Validity.Journal of medical Internet research · 2021Article
- Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study.JMIR mHealth and uHealth · 2021Article
- What Patients Value in Physicians: Analyzing Drivers of Patient Satisfaction Using Physician-Rating Website Data.Journal of medical Internet research · 2020Article
- Servant Leadership, Innovative Capacity and Performance in Third Sector Entities.Frontiers in psychology · 2020Article
- The Predictors of Consumer Behavior in Relation to Organic Food in the Context of Food Safety Incidents: Advancing Hyper Attention Theory Within an Stimulus-Organism-Response Model.Frontiers in psychology · 2019Article
- Public Awareness, Usage, and Predictors for the Use of Doctor Rating Websites: Cross-Sectional Study in England.Journal of medical Internet research · 2018Article
- Systematic Review of Data Mining Applications in Patient-Centered Mobile-Based Information Systems.Healthcare informatics research · 2017Article
- Exploring Patients' Views Toward Giving Web-Based Feedback and Ratings to General Practitioners in England: A Qualitative Descriptive Study.Journal of medical Internet research · 2016Article
- What Predicts Patients' Willingness to Undergo Online Treatment and Pay for Online Treatment? Results from a Web-Based Survey to Investigate the Changing Patient-Physician Relationship.Journal of medical Internet research · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundConsumers are increasingly accessing health-related information via mobile devices. Recently, several apps to rate and locate physicians have been released in the United States and Germany. However, knowledge about what kinds of variables explain usage of mobile physician-rating apps is still lacking.
objectiveThis study analyzes factors influencing the adoption of and willingness to pay for mobile physician-rating apps. A structural equation model was developed based on the Technology Acceptance Model and the literature on health-related information searches and usage of mobile apps. Relationships in the model were analyzed for moderating effects of physician-rating website (PRW) usage.
methodsA total of 1006 randomly selected German patients who had visited a general practitioner at least once in the 3 months before the beginning of the survey were randomly selected and surveyed. A total of 958 usable questionnaires were analyzed by partial least squares path modeling and moderator analyses.
resultsThe suggested model yielded a high model fit. We found that perceived ease of use (PEOU) of the Internet to gain health-related information, the sociodemographic variables age and gender, and the psychographic variables digital literacy, feelings about the Internet and other Web-based applications in general, patients' value of health-related knowledgeability, as well as the information-seeking behavior variables regarding the amount of daily private Internet use for health-related information, frequency of using apps for health-related information in the past, and attitude toward PRWs significantly affected the adoption of mobile physician-rating apps. The sociodemographic variable age, but not gender, and the psychographic variables feelings about the Internet and other Web-based applications in general and patients' value of health-related knowledgeability, but not digital literacy, were significant predictors of willingness to pay. Frequency of using apps for health-related information in the past and attitude toward PRWs, but not the amount of daily Internet use for health-related information, were significant predictors of willingness to pay. The perceived usefulness of the Internet to gain health-related information and the amount of daily Internet use in general did not have any significant effect on both of the endogenous variables. The moderation analysis with the group comparisons for users and nonusers of PRWs revealed that the attitude toward PRWs had significantly more impact on the adoption and willingness to pay for mobile physician-rating apps in the nonuser group.
conclusionsImportant variables that contribute to the adoption of a mobile physician-rating app and the willingness to pay for it were identified. The results of this study are important for researchers because they can provide important insights about the variables that influence the acceptance of apps that allow for ratings of physicians. They are also useful for creators of mobile physician-rating apps because they can help tailor mobile physician-rating apps to the consumers' characteristics and needs.
Indexed as
Identifiers
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.