Evidence map›Paper›PMID 34841372›Full record

ArticlePublic health in practice (Oxford, England)2021

Survey on usage and concerns of a COVID-19 contact tracing application in Japan.

Masaki Machida, Itaru Nakamura, Reiko Saito, Tomoki Nakaya, Tomoya Hanibuchi, Tomoko Takamiya, Yuko Odagiri, Noritoshi Fukushima, Hiroyuki Kikuchi, Shiho Amagasa and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Public health in practice (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
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

13 authors.

Masaki MachidaDepartment of Preventive Medicine and Public Health, Tokyo Medical University, 6-1-1 Shinjuku, Shinjuku-ku, Tokyo, 160-8402, Japan.
Itaru NakamuraDepartment of Infection Prevention and Control, Tokyo Medical University Hospital, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan.
Reiko SaitoDivision of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, 1-757, Asahimachi-dori, Niigata, Niigata, 951-8510, Japan.
Tomoki NakayaGraduate School of Environmental Studies, Tohoku University, Aoba, 468-1, Aramaki, Aoba-ku, Sendai, Miyagi, 980-0845, Japan.
Tomoya HanibuchiGraduate School of Environmental Studies, Tohoku University, Aoba, 468-1, Aramaki, Aoba-ku, Sendai, Miyagi, 980-0845, Japan.
Tomoko TakamiyaDepartment of Preventive Medicine and Public Health, Tokyo Medical University, 6-1-1 Shinjuku, Shinjuku-ku, Tokyo, 160-8402, Japan.
Yuko OdagiriDepartment of Preventive Medicine and Public Health, Tokyo Medical University, 6-1-1 Shinjuku, Shinjuku-ku, Tokyo, 160-8402, Japan.
Noritoshi FukushimaDepartment of Preventive Medicine and Public Health, Tokyo Medical University, 6-1-1 Shinjuku, Shinjuku-ku, Tokyo, 160-8402, Japan.
Hiroyuki KikuchiDepartment of Preventive Medicine and Public Health, Tokyo Medical University, 6-1-1 Shinjuku, Shinjuku-ku, Tokyo, 160-8402, Japan.
Shiho AmagasaDepartment of Preventive Medicine and Public Health, Tokyo Medical University, 6-1-1 Shinjuku, Shinjuku-ku, Tokyo, 160-8402, Japan.
Takako KojimaDepartment of International Medical Communications, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan.
Hidehiro WatanabeDepartment of Infection Prevention and Control, Tokyo Medical University Hospital, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan.
Shigeru InoueDepartment of Preventive Medicine and Public Health, Tokyo Medical University, 6-1-1 Shinjuku, Shinjuku-ku, Tokyo, 160-8402, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesWe aimed to identify the concerns, current implementation status and correct usage, and factors inhibiting implementation and correct use of a COVID-19 contact tracing application among the ordinary citizens in Japan. STUDY

designThis was a cross-sectional study based on an internet survey completed by 2013 participants who were selected among registrants of an Internet research company between September 8 and 13, 2020.

methodsParticipants completed an online survey that included thoughts and concerns about the application, status of use, and questions about whether the application was being used correctly. We performed multiple logistic regression analysis to clarify the association between the use of the app and sociodemographic factors and user concerns.

resultsOf the 2013 respondents, 429 (21.3%) participants reported using this application, but only 60.8% of them used it correctly. The percentage of those having some concerns about the application ranged from 45.9% to 75.5%, with the highest percentage being 'doubts about effectiveness of apps for preventing spread of infection'. Multiple logistic regression analysis revealed, the main concerns inhibiting application use were insufficient knowledge of how to use it, privacy concerns, doubts about the effectiveness of the app, and concerns about battery consumption and communication costs. Additionally, the prevalence of the application was lower for lower-income individuals.

conclusionsThe findings suggest that income may create inequalities in the efficacy and effectiveness of COVID-19 contact tracing applications. Awareness activity strategies to dispel such concerns and support low-income individuals may be needed.

Indexed as

Contact tracing applicationCOVID-19PandemicPersonal protective measuresPublic health

Identifiers

PMID34841372
PMCPMC8608395

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.