Researching COVID-19 tracing app acceptance: incorporating theory from the technological acceptance model

Abstract

Background The 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. Objective Use 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. Results The 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. Conclusions This 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.

Acceptance of Google Meet during the Spread of Coronavirus by Arab University Students

“…The fear factor was tackled in recent studies by [27] as an external factor that affects students' perception of technology during the pandemic. The fear from COVID-19 is manifested in forms such as threat, anxiety, feeling of uncertainty, the risk for loved ones [19,[28][29][30][31][32]. The feeling of fear among students has affected education and changed the platform of teaching from the physical classes to a virtual class by implementing an online platform [33].…”

Analysis of the factors affecting the adoption and compliance of the NHS COVID-19 mobile application: a national cross-sectional survey in England

“… 27 An extended TAM was used to find that it is likely citizens would download the app regardless of privacy concerns, and the main factor in this decision was determined to be the perceived usefulness of the app. 28 A similar study used a Health Belief Model, and found that perceived benefits of contact tracing apps were the largest factor for users downloading the app, followed by self-efficacy and perceived barriers. 29 Additionally, a report early in the pandemic suggested public trust and confidence, and technical design choices influencing the privacy and security of the system would contribute largely to app adoption.…”

Factors Influencing the Adoption of Contact Tracing Applications: Protocol for a Systematic Review (Preprint)

“…Moreover, in the data security category, a typical example of a facilitator and barrier is "perceived trust" and "privacy concern," respectively. For example, Velicia-Martin et al [14] and Walrave et al [15] found that perceived usefulness (a facilitator) and privacy concern (a barrier), respectively, are associated with contact tracing app adoption. Finally, "%Total" indicates the percentage of the total reviewed articles that found a given factor (facilitator or barrier) to be (1) a significant determinant of contact tracing app adoption in quantitative studies involving correlational, regression, and path analyses and/or (2) a noteworthy theme in qualitative studies based on the thematic analysis of participants' comments.…”

“…For instance, the percentage of study participants (especially nonadopters of contact tracing apps) who are willing to download the app under evaluation may be an indication of how the app may fair in real-life contexts, especially if the facilitators of contact tracing app adoption are prioritized. In addition, we will be looking at the levels of perception of key facilitators (eg, perceived usefulness [14]) and barriers (eg, privacy concern [15]) associated with contact tracing app adoption. For example, in a given study, "Did the participants perceive the contact tracing app described or prototyped as useful, trustworthy, etc?"…”