Evidence map›Paper›PMID 34313601›Full record

ArticleJMIR mHealth and uHealth2021

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

Masahiro Shoji, Asei Ito, Susumu Cato, Takashi Iida, Kenji Ishida, Hiroto Katsumata, Kenneth Mori McElwain

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
7.9field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 31 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Masahiro Shoji *Institute of Social Science, University of Tokyo, Tokyo, Japan.ORCID 0000-0002-1299-9320
Asei Ito *Institute of Social Science, University of Tokyo, Tokyo, Japan.ORCID 0000-0003-1304-8583
Susumu Cato *Institute of Social Science, University of Tokyo, Tokyo, Japan.ORCID 0000-0002-4244-7199
Takashi Iida *Institute of Social Science, University of Tokyo, Tokyo, Japan.ORCID 0000-0002-1835-8065
Kenji Ishida *Institute of Social Science, University of Tokyo, Tokyo, Japan.ORCID 0000-0002-1801-6540
Hiroto Katsumata *Graduate School of Arts and Sciences, University of Tokyo, Tokyo, Japan.ORCID 0000-0001-5901-8844
Kenneth Mori McElwain *Institute of Social Science, University of Tokyo, Tokyo, Japan.ORCID 0000-0002-9982-4784
Tokyo University of the Arts · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

COVID-19Mobile ApplicationsAdultAgedContact TracingHumansJapanMiddle AgedPandemicsSARS-CoV-2Surveys and QuestionnairesYoung Adultcontact tracingcontact tracing appCOVID-19health policymHealthpandemicplace attachmentplace identity

Identifiers

PMID34313601
PMCPMC8396313
OpenAlexW3186300414

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.