ArticlePeerJ. Computer science2021
Researching COVID-19 tracing app acceptance: incorporating theory from the technological acceptance model.
Article in PeerJ. Computer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.
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Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- 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
- Understanding continued use of smart learning platforms: psychological wellbeing in an extended TAM-ISCM model.Frontiers in psychology · 2025Article
- Effects of User Experience in Automated Information Processing on Perceived Usefulness of Digital Contact-Tracing Apps: Cross-Sectional Survey Study.JMIR human factors · 2024Article
- Effectiveness and intention to use a COVID-19 self-management app for epidemiological investigation: a web-based survey study.Frontiers in public health · 2024Article
- Review
- A study on the emotional and attitudinal behaviors of social media users under the sudden reopening policy of the Chinese government.Frontiers in public health · 2023Article
- ECAsT: a large dataset for conversational search and an evaluation of metric robustness.PeerJ. Computer science · 2023Article
- Acceptability of the COVID-19 contact-tracing app - Does culture matter?Government information quarterly · 2022Article
- The Effect of Persuasive Design on the Adoption of Exposure Notification Apps: Quantitative Study Based on COVID Alert.JMIR formative research · 2022Article
- Factors Affecting the Perceived Usability of the COVID-19 Contact-Tracing Application "Thai Chana" during the Early COVID-19 Omicron Period.International journal of environmental research and public health · 2022Article
- Joint analysis of the intention to vaccinate and to use contact tracing app during the COVID-19 pandemic.Scientific reports · 2022Article
- The relationship between trust and attitudes towards the COVID-19 digital contact-tracing app in the UK.PloS one · 2022Article
- An ounce of prevention or a pound of cure? Multi-level modelling on the antecedents of mobile-wallet adoption and the moderating role of e-WoM during COVID-19.Frontiers in psychology · 2022Article
- Examining the Prediction of COVID-19 Contact-Tracing App Adoption Using an Integrated Model and Hybrid Approach Analysis.Frontiers in public health · 2022Article
- Article
- The impact of perceived crisis severity on intention to use voluntary proximity tracing applications.International journal of information management · 2021Article
- Public Adoption of and Trust in the NHS COVID-19 Contact Tracing App in the United Kingdom: Quantitative Online Survey Study.Journal of medical Internet research · 2021Article
- Article
- Factors Influencing the Adoption of Contact Tracing Applications: Protocol for a Systematic Review.JMIR research protocols · 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe expansion of the coronavirus pandemic and the extraordinary confinement measures imposed by governments have caused an unprecedented intense and rapid contraction of the global economy. In order to revive the economy, people must be able to move safely, which means that governments must be able to quickly detect positive cases and track their potential contacts. Different alternatives have been suggested for carrying out this tracking process, one of which uses a mobile APP which has already been shown to be an effective method in some countries.
objectiveUse an extended Technology Acceptance Model (TAM) model to investigate whether citizens would be willing to accept and adopt a mobile application that indicates if they have been in contact with people infected with COVID-19. Research Methodology: A survey method was used and the information from 482 of these questionnaires was analyzed using Partial Least Squares-Structural Equation Modelling.
resultsThe results show that the Intention to Use this app would be determined by the Perceived Utility of the app and that any user apprehension about possible loss of privacy would not be a significant handicap. When having to choose between health and privacy, users choose health.
conclusionsThis study shows that the extended TAM model which was used has a high explanatory power. Users believe that the APP is useful (especially users who studied in higher education), that it is easy to use, and that it is not a cause of concern for privacy. The highest acceptance of the app is found in over 35 years old's, which is the group that is most aware of the possibility of being affected by COVID-19. The information is unbelievably valuable for developers and governments as users would be willing to use the APP.
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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.