JMIR Form Res. 2023 Jan 24. doi: 10.2196/36608. Online ahead of print.
ABSTRACT
BACKGROUND: Access to data is crucial for decision-making; this fact has become more evident during the pandemic. Data collected using mobile applications can positively influence diagnosis and treatment, the supply chain, and staffing resources of healthcare facilities. Developers and healthcare professionals have worked to create applications that can track a person’s COVID status. For example, these applications can monitor positive COVID test results and vaccination status. Regrettably, people may be concerned about sharing their data with government or private sector organizations developing applications. Understanding user perceptions is essential; without substantial user adoption and the use of mobile tracing apps, the benefits cannot be achieved.
OBJECTIVE: This study aims to assess the factors that positively and negatively affect the use of COVID-tracing apps by examining individuals’ perceptions about sharing data on mobile applications, such as testing regularity, infection, and immunization status.
METHODS: The hypothesized research model was tested using a cross-sectional survey instrument. The survey contained five reflective constructs and four control variables selected after reviewing the literature and interviewing healthcare professionals. A digital copy of the survey was created using Qualtrics. After receiving approval from Institutional Board Review (IRB). Data was collected from 367 participants through Amazon Mechanical Turk (MTurk). The inclusion criteria for participants to complete the anonymized survey included those of any gender who were 18 years and older. We then analyzed the theoretical model using structural equation modeling (SEM).
RESULTS: After analyzing the quality of responses, n=325 participants, 66.46% were male (n=216), and 33.53% were female (n=109). Of the participants in the final dataset, 72.61% were employed. The results of the structural equation modeling showed that perceived vulnerability (β = 0.688, p < .001), Self-efficacy (β = 0.292, p < .001), and an individual’s prior infection with COVID (β = 0.194, p < .05) have statistically significant positive impacts on the intention to use mobile tracing apps. Privacy concerns (β = -0.360, p < .001), risk aversion (β = -0.150, p < .1), and a family members prior infection with COVID (β = – 0.139, p < .05) have statistically significant negative influences on a person’s intention to use mobile tracing apps.
CONCLUSIONS: This study illustrates that various user perceptions affect whether individuals utilize COVID-tracing applications technology. By working collaboratively on legislation and the messaging provided to potential users before releasing an application, developers, healthcare professionals, and policymakers can improve the use of tracking apps. Healthcare professionals need to emphasize disease vulnerability to motivate people to utilize mobile tracing apps which can help reduce the spread of viruses and diseases. In addition, more work is needed at the policy-making level to protect the privacy of users which in return can increase user engagement.
PMID:36735838 | DOI:10.2196/36608
