ArticleJMIR formative research2021
Predictors to Use Mobile Apps for Monitoring COVID-19 Symptoms and Contact Tracing: Survey Among Dutch Citizens.
Article in JMIR formative research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 3 of them syntheses that pooled it.
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Who cites it
33 citing papers in PubMed, 3 syntheses or guidelines pooled it, 50 citations in OpenAlex.
- Antecedents predicting digital contact tracing acceptance: a systematic review and meta-analysis.BMC medical informatics and decision making · 2023Pooled it
- Factors Influencing the Adoption of Contact Tracing Applications: Systematic Review and Recommendations.Frontiers in digital health · 2022Pooled it
- Facilitators and barriers to engagement with contact tracing during infectious disease outbreaks: A rapid review of the evidence.PloS one · 2020Pooled it
- Discrimination and technology-based disease control.PloS one · 2026Article
- BARRIERS AND FACILITATORS TO PROVIDING COVID-19 CONTACT TRACING INFORMATION AMONG ADULT NIGERIANS.African journal of infectious diseases · 2025Article
- Observational
- Determinants of Citizens' Intention to Participate in Self-Led Contact Tracing: Cross-Sectional Online Questionnaire Study.JMIR public health and surveillance · 2024Article
- Willingness to Use Digital Health Screening and Tracking Tools for Public Health in Sexual Minority Populations in a National Probability Sample: Quantitative Intersectional Analysis.Journal of medical Internet research · 2024Article
- Use of a Health Monitoring System During a US Military Exercise During the COVID-19 Pandemic (April 2021): Participant Characteristics, Demographics and Differences in Participation.Journal of military and veterans' health · 2024Article
- Guide Development for eHealth Interventions Targeting People With a Low Socioeconomic Position: Participatory Design Approach.Journal of medical Internet research · 2023Article
- The epidemiological impact of digital and manual contact tracing on the SARS-CoV-2 epidemic in the Netherlands: Empirical evidence.PLOS digital health · 2023Article
- Citizen involvement in COVID-19 contact tracing with digital tools: a qualitative study to explore citizens' perspectives and needs.BMC public health · 2023Article
- The Adoption of a COVID-19 Contact-Tracing App: Cluster Analysis.JMIR formative research · 2023Article
- The Impact of Individuals' Social Environments on Contact Tracing App Use: Survey Study.JMIR human factors · 2023Article
- Developing and Evaluating a Measure of the Willingness to Use Pandemic-Related mHealth Tools Using National Probability Samples in the United States: Quantitative Psychometric Analyses and Tests of Sociodemographic Group Differences.JMIR formative research · 2023Article
- Self-care for coronavirus disease through electronic health technologies: A scoping review.Health science reports · 2023Article
- Factors Associated With Using the COVID-19 Mobile Contact-Tracing App Among Individuals Diagnosed With SARS-CoV-2 in Amsterdam, the Netherlands: Observational Study.JMIR mHealth and uHealth · 2022Observational
- Fantastic perspectives and where to find them: involving patients and citizens in digital health research.Research involvement and engagement · 2022Article
- Factors impacting the use of the NZ COVID Tracer application in New Zealand".Smart health (Amsterdam, Netherlands) · 2022Review
- Public Perspectives on Exposure Notification Apps: A Patient and Citizen Co-Designed Study.Journal of personalized medicine · 2022Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundeHealth apps have been recognized as a valuable tool to reduce COVID-19's effective reproduction number. The factors that determine the acceptance of COVID-19 apps remain unknown. The exception here is privacy.
objectiveThe aim of this article was to identify antecedents of acceptance of (1) a mobile app for COVID-19 symptom recognition and monitoring and (2) a mobile app for contact tracing, both by means of an online survey among Dutch citizens.
methodsNext to the demographics, the online survey contained questions focusing on perceived health, fear of COVID-19, and intention to use. We used snowball sampling via posts on social media and personal connections. To identify antecedents of the model for acceptance of the 2 mobile apps, we conducted multiple linear regression analyses.
resultsIn total, 238 Dutch adults completed the survey; 59.2% (n=141) of the responders were female and the average age was 45.6 years (SD 17.4 years). For the symptom app, the final model included the predictors age, attitude toward technology, and fear of COVID-19. The model had an r2 of 0.141. The final model for the tracing app included the same predictors and had an r2 of 0.156. The main reason to use both mobile apps was to control the spread of the COVID-19 virus. Concerns about privacy was mentioned as the main reason to not use the mobile apps.
conclusionsAge, attitude toward technology, and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile apps for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile apps to secure acceptance.
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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.