ArticleFrontiers in public health2022
Examining the Prediction of COVID-19 Contact-Tracing App Adoption Using an Integrated Model and Hybrid Approach Analysis.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 14 citations in OpenAlex.
- Determinants of Health Care Technology Adoption Using an Integrated Unified Theory of Acceptance and Use of Technology and Task Technology Fit Model: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Antecedents predicting digital contact tracing acceptance: a systematic review and meta-analysis.BMC medical informatics and decision making · 2023Pooled it
- The role of behavioral nudges in sustaining public health engagement through the "Tawakkalna" app: insights from healthcare professionals.Frontiers in public health · 2026Article
- Understanding the role of cybersecurity in the internet of things within the health sector: an empirical study.Frontiers in public health · 2026Article
- A matter of child monitoring: a multistage analysis examining factors influencing parent use behavior of parental control apps.Frontiers in psychology · 2026Article
- Cybersecurity governance in the healthcare sector during digital transformation: an integrated model and hybrid analytical approach.Frontiers in public health · 2025Article
- Exploring the factors that influence academic performance in Jordanian higher education institutions.Heliyon · 2024Article
- Nurses' continuance intention to use electronic health record systems: The antecedent role of personality and organisation support.PloS one · 2024Article
- The Use of a Technology Acceptance Model (TAM) to Predict Patients' Usage of a Personal Health Record System: The Role of Security, Privacy, and Usability.International journal of environmental research and public health · 2023Article
- Editorial: Epidemiological considerations in COVID-19 forecasting.Frontiers in epidemiology · 2022Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COVID-19 contact-tracing applications (CTAs) offer enormous potential to mitigate the surge of positive coronavirus cases, thus helping stakeholders to monitor high-risk areas. The Kingdom of Saudi Arabia (KSA) is among the countries that have developed a CTA known as the Tawakkalna application, to manage the spread of COVID-19. Thus, this study aimed to examine and predict the factors affecting the adoption of Tawakkalna CTA. An integrated model which comprises the technology acceptance model (TAM), privacy calculus theory (PCT), and task-technology fit (TTF) model was hypothesized. The model is used to understand better behavioral intention toward using the Tawakkalna mobile CTA. This study performed structural equation modeling (SEM) analysis as well as artificial neural network (ANN) analysis to validate the model, using survey data from 309 users of CTAs in the Kingdom of Saudi Arabia. The findings revealed that perceived ease of use and usefulness has positively and significantly impacted the behavioral intention of Tawakkalna mobile CTA. Similarly, task features and mobility positively and significantly influence task-technology fit, and significantly affect the behavioral intention of the CTA. However, the privacy risk, social concerns, and perceived benefits of social interaction are not significant factors. The findings provide adequate knowledge of the relative impact of key predictors of the behavioral intention of the Tawakkalna contact-tracing 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.