Exposure Detection Applications Acceptance

The Case of Covid-19

Datos Bibliográficos

ID15475303
AutoresAdi Alsyouf (0000-0002-4672-8991, King Abdulaziz University, autor de correspondencia), Abdalwali Lutfi (0000-0002-3928-7497, University of Business and Technology, autor de correspondencia), Mohammad Al‐Bsheish (0000-0003-2698-8101, Batterjee Medical College), Mu’taman Jarrar (0000-0001-7748-2069, King Fahd Hospital of the University), Khalid Al‐Mugheed (0000-0001-9727-7804, Near East University), Khalid Al-Mugheed (0000-0002-8437-977X, Near East University), Mohammed Amin Almaiah (0000-0002-0246-4365, King Faisal University), Fahad Nasser Alhazmi (0000-0002-0271-7166, King Abdulaziz University), Ra’ed Masa’deh (0000-0002-9070-3732, University of Jordan), Rami J Anshasi (0000-0001-5122-2875, Jordan University of Science and Technology), Abdallah Ashour (0000-0002-3027-3160, Philadelphia University)
Año2022
Volumen19
Número12
Páginas7307-7307
Fecha de publicación2022-06-14
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaInternational Journal of Environmental Research and Public Health (JOURNAL)
Identificadores de la revistaISSN: 1661-7827 • E-ISSN: 1660-4601
EditorialMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph19127307
PMID35742560
OpenAlexW4282918163
IdiomaEN
Citas recibidas7
Referencias citadas127

The pandemic's context is rife with numerous dangerous threats and high fear levels, influencing human decision-making. Such characteristics are identified by investigating the acceptance of exposure detection apps from the technology acceptance model (TAM) perspective. This study purposed a model to investigate protection technology acceptance, specifically exposure detection apps in the context of COVID-19. Quantitative study approach and a cross-section design targeted 586 participants from Saudi Arabia. As the study model is complex, the study hypotheses were analysed using the structural equation modelling-partial least squares (SEM-PLS3) approach. The findings support the entire model hypothesis except the link between social media awareness and exposure detection apps' intention. Mediation of COVID-19 anxiety and influence was confirmed as well. The current paper contributes to the technologies acceptance domain by developing a context-driven model comprising the major pandemic characteristics that lead to various patterns of technology acceptance. This study also fills the literature gap regarding mediating effects of social influence and COVID-19 anxiety in the relationship between trust in government and exposure detection apps implementation, and between COVID-19 anxiety and exposure detection apps implementation, respectively. The results may assist government agencies, health policymakers, and health organisations in the wide world and specifically Saudi Arabia, in their attempts to contain the COVID-19 pandemic spread

2019-20 coronavirus outbreak · Betacoronavirus · Coronavirus disease 2019 (COVID-19 · Coronavirus Infections · Infectious disease (medical specialty · Outbreak · Pathology · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Computer Science · COVID-19 Digital Contact Tracing · Human Mobility and Location-Based Analysis · IoT and Edge/Fog Computing · Medicine · Virology