Evidence map›Paper›PMID 37716982›Full record

ArticleBMC public health2023

Citizen involvement in COVID-19 contact tracing with digital tools: a qualitative study to explore citizens' perspectives and needs.

A van der Meer, Y B Helms, R Baron, R Crutzen, A Timen, M E E Kretzschmar, M L Stein, N Hamdiui

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In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

8 authors.

A van der MeerNational Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands. akke.van.der.meer@rivm.nl.
Y B HelmsNational Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
R BaronNational Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
R CrutzenDepartment of Health Promotion, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands.
A TimenNational Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
M E E KretzschmarJulius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht University, Utrecht, The Netherlands.
M L SteinNational Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.
N HamdiuiNational Coordination Centre for Communicable Disease Control, Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundContact tracing (CT) is a key strategy when dealing with outbreaks of infectious diseases such as COVID-19. The scale of the COVID-19 pandemic has often left public health professionals (PHPs), who are responsible for the execution of CT, unable to keep up with the rapid and largescale spread of the virus. To enhance or support its execution, and potentially lower the workload for PHPs, citizens may be more actively involved in CT-tasks that are commonly executed by PHPs (referred to as 'self-led CT'). There is limited insight into citizens' perspectives on and needs for self-led CT for COVID-19. This study aims to explore the perspectives and needs of Dutch citizens on taking more responsibilities in the execution of CT for COVID-19, potentially through the use of digital tools.

methodsAn exploratory qualitative study was performed, in which online semi-structured interviews were conducted. Questions were based on the Reasoned Action Approach and Health Belief Model. Interviews were audio-recorded and transcribed verbatim. A thematic analysis was conducted to identify citizens' perspectives and needs to participate in self-led CT.

resultsWe conducted 27 interviews with Dutch citizens. Seven main themes were identified from the interviews: 1) 'Citizens' perspectives on self-led CT are influenced by prior experiences with regular CT', 2) 'Citizens' felt responsibilities and the perceived responsibilities of the PHS in CT shape their perspectives on self-led CT', 3) 'Anticipated impacts of self-led CT on the CT-process', 4) 'Citizens' attitude towards the application of self-led CT depends on their own perceived skills and the willingness and skills of others', 5) 'Shame and social stigma may hamper participation in self-led CT', 6) 'Concerns about privacy and data security: a barrier for self-led CT', and 7) 'Citizens' perspectives and anticipated needs for the implementation and application of self-led CT in practice'.

conclusionsMost interviewees hold a positive attitude towards self-led CT and using digital tools for this purpose. However, their intention for self-led CT may depend on various factors, such as prior experiences with regular CT, and their perceived self-efficacy to participate. Perspectives and needs of citizens should be considered for the future implementation of self-led CT in practice.

Indexed as

Contact TracingCOVID-19Disease OutbreaksEmotionsHumansPandemicsCitizen involvementContact tracingCOVID-19Digital toolsInfectious diseasesPublic health

Identifiers

PMID37716982
PMCPMC10504771

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.