Dataset Information

Mobile health technology as a solution to self-control problems: The behavioral impact of COVID-19 contact tracing apps in Japan.

ABSTRACT:

Rationale

Mobile technology has been widely utilized as an effective healthcare tool during the COVID-19 pandemic. Notably, over 50 countries have released contact-tracing apps to trace and contain infection chains. While earlier studies have examined obstacles to app uptake and usage, whether and how this uptake affects users' behavioral patterns is not well understood. This is crucial because uptake can theoretically increase or decrease behavior that carries infection risks.

Objective

The goal of this study is to evaluate the impact of app uptake on the time spent out of home in Japan. It tests four potential underlying mechanisms that drive the uptake effect: compliance with stay-at-home requirements, learning about infection risk, reminders, and commitment device.

Method

We use unique nationwide survey data collected from 4,379 individuals aged between 20 and 69 in December 2020 and February 2021 in Japan. Japan has features suitable for this exercise. The Japanese government released a contact tracing app in June 2020, which sends a warning message to users who have been in close contact with an infected person. We conduct a difference-in-differences estimation strategy combined with the entropy balancing method.

Results

App uptake reduces the time spent out of home. Sensitivity analysis shows that it cannot be explained by unobserved confounders. Importantly, the impact is large even among users who have not received a warning message from the app, and even larger for those with poor self-control ability. Furthermore, individuals' self-control ability is negatively associated with the uptake decision, supporting our hypothesis that the apps serve as a commitment device.

Conclusions

It may be beneficial to encourage citizens to uptake contact tracing apps and other forms of commitment devices. This study also contributes to the literature on mobile health (mHealth) by demonstrating its efficacy as a commitment device.

SUBMITTER: Shoji M

PROVIDER: S-EPMC9192110 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Publications

Mobile health technology as a solution to self-control problems: The behavioral impact of COVID-19 contact tracing apps in Japan.

Shoji Masahiro M Cato Susumu S Ito Asei A Iida Takashi T Ishida Kenji K Katsumata Hiroto H McElwain Kenneth Mori KM

Social science & medicine (1982) 20220613

<h4>Rationale</h4>Mobile technology has been widely utilized as an effective healthcare tool during the COVID-19 pandemic. Notably, over 50 countries have released contact-tracing apps to trace and contain infection chains. While earlier studies have examined obstacles to app uptake and usage, whether and how this uptake affects users' behavioral patterns is not well understood. This is crucial because uptake can theoretically increase or decrease behavior that carries infection risks.<h4>Object ...[more]

PMID: 35716553

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Project description:BackgroundMany countries across the globe have released their own COVID-19 contact tracing apps. This has resulted in the proliferation of several apps that used a variety of technologies. With the absence of a standardized approach used by the authorities, policy makers, and developers, many of these apps were unique. Therefore, they varied by function and the underlying technology used for contact tracing and infection reporting.ObjectiveThe goal of this study was to analyze most of the COVID-19 contact tracing apps in use today. Beyond investigating the privacy features, design, and implications of these apps, this research examined the underlying technologies used in contact tracing apps. It also attempted to provide some insights into their level of penetration and to gauge their public reception. This research also investigated the data collection, reporting, retention, and destruction procedures used by each of the apps under review.MethodsThis research study evaluated 13 apps corresponding to 10 countries based on the underlying technology used. The inclusion criteria ensured that most COVID-19-declared epicenters (ie, countries) were included in the sample, such as Italy. The evaluated apps also included countries that did relatively well in controlling the outbreak of COVID-19, such as Singapore. Informational and unofficial contact tracing apps were excluded from this study. A total of 30,000 reviews corresponding to the 13 apps were scraped from app store webpages and analyzed.ResultsThis study identified seven distinct technologies used by COVID-19 tracing apps and 13 distinct apps. The United States was reported to have released the most contact tracing apps, followed by Italy. Bluetooth was the most frequently used underlying technology, employed by seven apps, whereas three apps used GPS. The Norwegian, Singaporean, Georgian, and New Zealand apps were among those that collected the most personal information from users, whereas some apps, such as the Swiss app and the Italian (Immuni) app, did not collect any user information. The observed minimum amount of time implemented for most of the apps with regard to data destruction was 14 days, while the Georgian app retained records for 3 years. No significant battery drainage issue was reported for most of the apps. Interestingly, only about 2% of the reviewers expressed concerns about their privacy across all apps. The number and frequency of technical issues reported on the Apple App Store were significantly more than those reported on Google Play; the highest was with the New Zealand app, with 27% of the reviewers reporting technical difficulties (ie, 10% out of 27% scraped reviews reported that the app did not work). The Norwegian, Swiss, and US (PathCheck) apps had the least reported technical issues, sitting at just below 10%. In terms of usability, many apps, such as those from Singapore, Australia, and Switzerland, did not provide the users with an option to sign out from their apps.ConclusionsThis article highlighted the fact that COVID-19 contact tracing apps are still facing many obstacles toward their widespread and public acceptance. The main challenges are related to the technical, usability, and privacy issues or to the requirements reported by some users.

Project description:BackgroundTo 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.ObjectiveThe 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.MethodsA 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.ResultsThere 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).ConclusionsPolicymakers 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.

Project description:BackgroundIn the context of the COVID-19 pandemic, there is much discussion about contact tracing apps, their use to contain the spread of the virus as well as the ethical, legal, and social aspects of their development, implementation, acceptance, and use. In these discussions, authors frequently mention "solidarity" when making key points in arguments. At the same time, authors rarely specify how they understand "solidarity". This lack of specification about how they understand "solidarity" can lead to misunderstandings in discussions.ObjectiveTo prevent such misunderstandings, it is important to specify how one understands "solidarity" when mentioning it in the discussions on contact tracing apps. Therefore, the aim of this paper is to elaborate how "solidarity" is understood in the context of contact tracing apps, i.e., how different authors understand "solidarity" when using it in discussions about these apps.MethodsIn order to find out how different authors understand "solidarity" when discussing contact tracing apps, I conduct a literature review. I collect papers from several databases, inductively work out central differences and similarities between the different uses of "solidarity", and use them to code and analyze relevant passages.ResultsIn the final sample, five different understandings of "solidarity" in the context of contact tracing apps can be identified. These understandings differ in how different authors (1) imagine the basic concept of solidarity, i.e., what "solidarity" refers to, (2) how they temporally relate solidarity to contact tracing apps, and (3) how they perceive the causal interactions between solidarity and contact tracing apps, i.e., the different ways in which solidarity and contact tracing apps influence each other.ConclusionsThe five understandings of "solidarity" in the context of contact tracing apps presented here can serve as guidance for how "solidarity" can be understood in discussions-thus contributing to a better mutual understanding and preventing communicative misunderstandings.

Project description:BackgroundTo combat the global COVID-19 pandemic, contact tracing apps have been discussed as digital health solutions to track infection chains and provide appropriate information. However, observational studies point to low acceptance in most countries, and few studies have yet examined theory-based predictors of app use in the general population to guide health communication efforts.ObjectiveThis study utilizes established health behavior change and technology acceptance models to predict adoption intentions and frequency of current app use.MethodsWe conducted a cross-sectional online survey between May and July 2020 in a German convenience sample (N=349; mean age 35.62 years; n=226, 65.3% female). To inspect the incremental validity of model constructs as well as additional variables (privacy concerns, personalization), hierarchical regression models were applied, controlling for covariates.ResultsThe theory of planned behavior and the unified theory of acceptance and use of technology predicted adoption intentions (R2=56%-63%) and frequency of current app use (R2=33%-37%). A combined model only marginally increased the predictive value by about 5%, but lower privacy concerns and higher threat appraisals (ie, anticipatory anxiety) significantly predicted app use when included as additional variables. Moreover, the impact of perceived usefulness was positive for adoption intentions but negative for frequency of current app use.ConclusionsThis study identified several theory-based predictors of contact tracing app use. However, few constructs, such as social norms, have a consistent positive effect across models and outcomes. Further research is required to replicate these observations, and to examine the interconnectedness of these constructs and their impact throughout the pandemic. Nevertheless, the findings suggest that promulgating affirmative social norms and positive emotional effects of app use, as well as addressing health concerns, might be promising strategies to foster adoption intentions and app use in the general population.

Dataset Information

Mobile health technology as a solution to self-control problems: The behavioral impact of COVID-19 contact tracing apps in Japan.

Rationale

Objective

Method

Results

Conclusions

Publications

Mobile health technology as a solution to self-control problems: The behavioral impact of COVID-19 contact tracing apps in Japan.

Similar Datasets

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