What makes people install a COVID-19 contact-tracing app? Understanding the influence of app design and individual difference on contact-tracing app adoption intention

Li, Tianshi; Cobb, Camille; Yang, Jackie; Baviskar, Sagar; Agarwal, Yuvraj; Li, Beibei; Bauer, Lujo; Hong, Jason I.

doi:10.1016/j.pmcj.2021.101439

Cited by 75 publications

(116 citation statements)

References 39 publications

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“…One of the key factors in the acceptance of contact-tracing via smartphone apps is privacy concerns ( Li et al., 2021 ). People generally strive to protect their private life from any attempts at interference.…”

Section: Contact-tracing Apps: Public Acceptancementioning

confidence: 99%

“…Another line of research suggests that risk perception of COVID-19 is associated with the adoption of preventive behaviors against the disease ( Dryhurst et al., 2020 ). Particularly relevant in this context is that COVID-19 risk perception correlates positively with the intention to use contact-tracing apps ( Li et al., 2021 ). Risk perception of extreme events like COVID-19 has cognitive, emotional, and social dimensions.…”

Section: Contact-tracing Apps: Public Acceptancementioning

confidence: 99%

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I use a COVID-19 contact-tracing app. Do you? Regulatory focus and the intention to engage with contact-tracing technology

Ross

2021

International Journal of Information Management Data Insights

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Based on regulatory focus theory, it is proposed that there is a relationship between the intention to use COVID-19 contact-tracing apps and goal-directed motivation. Two studies tested this proposal. Study 1 examined the relationship between participants’ chronic regulatory focus and the intention to use contact-tracing apps. Apps usage intention was positively associated with prevention focus. A mediation analysis showed that the relationship between prevention focus and apps usage intention was mediated by privacy and information security concerns. The stronger the prevention focus, the weaker the concerns, thus, the stronger the intention to use contact-tracing apps. Study 2 used priming to have participants adopt either a momentary promotion or prevention focus, after which they were asked about their intention to use contact-tracing apps. A situationally induced regulatory focus influenced the intention to use contact-tracing apps. A moderation analysis showed that age moderated the relationship between regulatory focus and apps usage intention.

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Section: Contact-tracing Apps: Public Acceptancementioning

confidence: 99%

Section: Contact-tracing Apps: Public Acceptancementioning

confidence: 99%

I use a COVID-19 contact-tracing app. Do you? Regulatory focus and the intention to engage with contact-tracing technology

Ross

2021

International Journal of Information Management Data Insights

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“…First, generalization will be limited to the adult population living or working in the canton of Geneva. Second, adoption and utilization of the @choum tool might suffer from a participation bias, as attitudes toward digital COVID-19 public health tools such as contact tracing apps vary among sociodemographic groups [ 64 , 65 ]. However, we developed and implemented several strategies to foster participation across sociodemographic groups and ensure user retention.…”

Section: Discussionmentioning

confidence: 99%

Detection of Spatiotemporal Clusters of COVID-19–Associated Symptoms and Prevention Using a Participatory Surveillance App: Protocol for the @choum Study

Ridder¹,

Loizeau²,

Sandoval³

et al. 2021

JMIR Res Protoc

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Background The early detection of clusters of infectious diseases such as the SARS-CoV-2–related COVID-19 disease can promote timely testing recommendation compliance and help to prevent disease outbreaks. Prior research revealed the potential of COVID-19 participatory syndromic surveillance systems to complement traditional surveillance systems. However, most existing systems did not integrate geographic information at a local scale, which could improve the management of the SARS-CoV-2 pandemic. Objective The aim of this study is to detect active and emerging spatiotemporal clusters of COVID-19–associated symptoms, and to examine (a posteriori) the association between the clusters’ characteristics and sociodemographic and environmental determinants. Methods This report presents the methodology and development of the @choum (English: “achoo”) study, evaluating an epidemiological digital surveillance tool to detect and prevent clusters of individuals (target sample size, N=5000), aged 18 years or above, with COVID-19–associated symptoms living and/or working in the canton of Geneva, Switzerland. The tool is a 5-minute survey integrated into a free and secure mobile app (CoronApp-HUG). Participants are enrolled through a comprehensive communication campaign conducted throughout the 12-month data collection phase. Participants register to the tool by providing electronic informed consent and nonsensitive information (gender, age, geographically masked addresses). Symptomatic participants can then report COVID-19–associated symptoms at their onset (eg, symptoms type, test date) by tapping on the @choum button. Those who have not yet been tested are offered the possibility to be informed on their cluster status (information returned by daily automated clustering analysis). At each participation step, participants are redirected to the official COVID-19 recommendations websites. Geospatial clustering analyses are performed using the modified space-time density-based spatial clustering of applications with noise (MST-DBSCAN) algorithm. Results The study began on September 1, 2020, and will be completed on February 28, 2022. Multiple tests performed at various time points throughout the 5-month preparation phase have helped to improve the tool’s user experience and the accuracy of the clustering analyses. A 1-month pilot study performed among 38 pharmacists working in 7 Geneva-based pharmacies confirmed the proper functioning of the tool. Since the tool’s launch to the entire population of Geneva on February 11, 2021, data are being collected and clusters are being carefully monitored. The primary study outcomes are expected to be published in mid-2022. Conclusions The @choum study evaluates an innovative participatory epidemiological digital surveillance tool to detect and prevent clusters of COVID-19–associated symptoms. @choum collects precise geographic information while protecting the user’s privacy by using geomasking methods. By providing an evidence base to inform citizens and local authorities on areas potentially facing a high COVID-19 burden, the tool supports the targeted allocation of public health resources and promotes testing. International Registered Report Identifier (IRRID) DERR1-10.2196/30444

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“…In general, the literature on public health and disaster research also supports the roles of community in encouraging protective behavior [14,57]. However, the association between prosociality and uptake of COVID-19 contact tracing apps is largely unexplored, with the exception of 2 studies that have examined the role of prosocial personality traits and attitudes [7,58]; attachment to the community is less well understood. This is problematic because, unlike personality traits, feelings of attachment may easily change over time in response to changes in one's living conditions [59].…”

Section: Xsl • Fomentioning

confidence: 99%

Prosociality and the Uptake of COVID-19 Contact Tracing Apps: Survey Analysis of Intergenerational Differences in Japan

Shoji¹,

Ito²,

Cato³

et al. 2021

JMIR Mhealth Uhealth

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Background: To control the COVID-19 pandemic, it is essential to trace and contain infection chains; for this reason, policymakers have endorsed the usage of contact tracing apps. To date, over 50 countries have released such apps officially or semiofficially, but those that rely on citizens' voluntary uptake suffer from low adoption rates, reducing their effectiveness. Early studies suggest that the low uptake is driven by citizens' concerns about security and privacy, as well as low perceptions of infection risk and benefits from the usage. However, these do not explore important generational differences in uptake decision or the association between individuals' prosociality and uptake. Objective:The objective of our study was to examine the role of individuals' prosociality and other factors discussed in the literature, such as perceived risk and trust in government, in encouraging the usage of contact tracing apps in Japan. We paid particular attention to generational differences. Methods: A web-based survey was conducted in Japan 6 months after the release of a government-sponsored contact tracing app. Participants were recruited from individuals aged between 20 and 69 years. Exploratory factor analyses were conducted to measure prosociality, risk perception, and trust in government. Logistic regression was used to examine the association between these factors and uptake.Results: There was a total of 7084 respondents, and observations from 5402 respondents were used for analysis, of which 791 respondents (14.6%) had ever used the app. Two factors of prosociality were retained: agreeableness and attachment to the community. Full-sample analysis demonstrated app uptake was determined by agreeableness, attachment to the community, concern about health risks, concern about social risks, and trust in the national government; however, important differences existed. The uptake decision of respondents aged between 20 and 39 years was attributed to their attachment to the community (odds ratio [OR] 1.28, 95% CI 1.11-1.48). Agreeable personality (OR 1.18, 95% CI 1.02-1.35), concern about social risk (OR 1.17, 95% CI 1.02-1.35), and trust in national government (OR 1.16, 95% CI 1.05-1.28) were key determinants for those aged between 40 and 59 years. For those aged over 60 years, concerns about health risks determined the uptake decision (OR 1.49, 95% CI 1.24-1.80). Conclusions:Policymakers should implement different interventions for each generation to increase the adoption rate of contact tracing apps. It may be effective to inform older adults about the health benefits of the apps. For middle-age adults, it is important to mitigate concerns about security and privacy issues, and for younger generations, it is necessary to boost their attachment to their community by utilizing social media and other web-based network tools.

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What makes people install a COVID-19 contact-tracing app? Understanding the influence of app design and individual difference on contact-tracing app adoption intention

Cited by 75 publications

References 39 publications

I use a COVID-19 contact-tracing app. Do you? Regulatory focus and the intention to engage with contact-tracing technology

I use a COVID-19 contact-tracing app. Do you? Regulatory focus and the intention to engage with contact-tracing technology

Detection of Spatiotemporal Clusters of COVID-19–Associated Symptoms and Prevention Using a Participatory Surveillance App: Protocol for the @choum Study

Prosociality and the Uptake of COVID-19 Contact Tracing Apps: Survey Analysis of Intergenerational Differences in Japan

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