ArticleJournal of medical Internet research2023
Investigating Individuals' Preferences in Determining the Functions of Smartphone Apps for Fighting Pandemics: Best-Worst Scaling Survey Study.
Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The trial behind it
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Who cites it
5 citing papers in PubMed, 1 citations in OpenAlex.
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- Predictive Modeling of Localized Mobile App to Improve Snakebite Management in Ghana.PLoS neglected tropical diseases · 2026Article
- Developing Attributes and Levels for a Discrete Choice Experiment on Internet Hospital Service Preferences Among Chinese Patients with Chronic Diseases: A Mixed-Methods Study.Patient preference and adherence · 2026Article
- U-shaped association between social media usage frequency and suggestibility by internet health information in Chinese online population with pre-diabetes and diabetes: a cross-sectional study.BMC public health · 2025Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSmartphone apps have been beneficial in controlling and preventing the COVID-19 pandemic. However, there is a gap in research surrounding the importance of smartphone app functions from a user's perspective. Although the insights and opinions of different stakeholders, such as policymakers and medical professionals, can influence the success of a public health policy, any strategy will face difficulty in achieving the expected effect if it is not based on a method that users can accept.
objectiveThis study aimed to assess the importance of a hypothetical smartphone app's functions for managing health during a pandemic based on the perspective of user preferences.
methodsA cross-sectional and web-based survey using the best-worst scaling (BWS) method was used to investigate the general population's preferences for important smartphone app functions. Participants were recruited from a professional surveying company's web-based surveying panel. The attributes of the BWS questionnaire were developed based on a robust process, including literature review, interviews, and expert discussion. A balanced incomplete block design was used to construct the choice task to ensure the effectiveness of the research design. Count analysis, conditional logit model analysis, and mixed logit analysis were used to estimate preference heterogeneity among respondents.
resultsThe responses of 2153 participants were eligible for analysis. Nearly 55% (1192/2153) were female, and the mean age was 31.4 years. Most participants (1765/2153, 81.9%) had completed tertiary or higher education, and approximately 70% (1523/2153) were urban residents. The 3 most vital functions according to their selection were "surveillance and monitoring of infected cases," "quick self-screening," and "early detection of infected cases." The mixed logit regression model identified significant heterogeneity in preferences among respondents, and stratified analysis showed that some heterogeneities varied in respondents by demographics and COVID-19-related characteristics. Participants who preferred to use the app were more likely to assign a high weight to the preventive functions than those who did not prefer to use it. Conversely, participants who showed lower willingness to use the app tended to indicate a higher preference for supportive functions than those who preferred to use it.
conclusionsThis study ranks the importance of smartphone app features that provide health care services during a pandemic based on the general population's preferences in China. It provides empirical evidence for decision-makers to develop eHealth policies and strategies that address future public health crises from a person-centered care perspective. Continued use of apps and smart investment in digital health can help improve health outcomes and reduce the burden of disease on individuals and communities.
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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.