Evidence map›Paper›PMID 35329008›Full record

ArticleInternational journal of environmental research and public health2022

High Acceptance of COVID-19 Tracing Technologies in Taiwan: A Nationally Representative Survey Analysis.

Paul M Garrett, Yu-Wen Wang, Joshua P White, Yoshihsa Kashima, Simon Dennis, Cheng-Ta Yang

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
3.2field-weighted citation impact, top 7% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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

6 authors at 3 institutions in 2 countries.

Paul M GarrettSchool of Psychological Sciences, University of Melbourne, Melbourne 3010, Australia.ORCID 0000-0002-8200-8377
Yu-Wen WangDepartment of Psychology, National Cheng Kung University, Tainan 701, Taiwan.
Joshua P WhiteSchool of Psychological Sciences, University of Melbourne, Melbourne 3010, Australia.ORCID 0000-0003-3129-5473
Yoshihsa KashimaSchool of Psychological Sciences, University of Melbourne, Melbourne 3010, Australia.
Simon DennisSchool of Psychological Sciences, University of Melbourne, Melbourne 3010, Australia.
Cheng-Ta YangDepartment of Psychology, National Cheng Kung University, Tainan 701, Taiwan.ORCID 0000-0002-6561-763X
The University of Melbourne · AUNational Cheng Kung University · TWTaipei Medical University · TW

Funding

Ministry of Science and Technology of the People's Republic of China MOST 108-2321-B-006-022-MY2Ministry of Science and Technology of the People's Republic of China MOST 110-2321-B-006-004
6 · The paper itself

Abstract

Taiwan has been a world leader in controlling the spread of SARS-CoV-2 during the COVID-19 pandemic. Recently, the Taiwan Government launched its COVID-19 tracing app, 'Taiwan Social Distancing App'; however, the effectiveness of this tracing app depends on its acceptance and uptake among the general population. We measured the acceptance of three hypothetical tracing technologies (telecommunication network tracing, a government app, and the Apple and Google Bluetooth exposure notification system) in four nationally representative Taiwanese samples. Using Bayesian methods, we found a high acceptance of all three tracking technologies, with acceptance increasing with the inclusion of additional privacy measures. Modeling revealed that acceptance increased with the perceived technology benefits, trust in the providers' intent, data security and privacy measures, the level of ongoing control, and one's level of education. Acceptance decreased with data sensitivity perceptions and a perceived low policy compliance by others among the general public. We consider the policy implications of these results for Taiwan during the COVID-19 pandemic and in the future.

Indexed as

COVID-19Bayes TheoremHumansPandemicsSARS-CoV-2TaiwanTechnologycontact tracingCOVID-19health policyprivacyprivacy calculuspublic healthSARS-CoV-2Taiwantracking technologies

Identifiers

PMID35329008
PMCPMC8954552
OpenAlexW4220692183

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.