Evidence map›Paper›PMID 35084338›Full record

ReviewJMIR mHealth and uHealth2022

Digital Contact Tracing Apps for COVID-19: Development of a Citizen-Centered Evaluation Framework.

Damyanka Tsvyatkova, Jim Buckley, Sarah Beecham, Muslim Chochlov, Ian R O'Keeffe, Abdul Razzaq, Kaavya Rekanar, Ita Richardson, Thomas Welsh, Cristiano Storni and 1 more

Open access · goldAbstract readReview
In one paragraph

Review in JMIR mHealth and uHealth, 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
2.6field-weighted citation impact, top 9% 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. Review
  3. 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

11 authors at 2 institutions in 2 countries.

Damyanka TsvyatkovaLero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland.ORCID 0000-0002-1686-7413
Jim BuckleyLero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland.ORCID 0000-0001-6928-6746
Sarah BeechamLero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland.ORCID 0000-0003-1584-5447
Muslim ChochlovLero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland.ORCID 0000-0002-6580-0311
Ian R O'KeeffeLero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland.ORCID 0000-0001-7329-0617
Abdul RazzaqLero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland.ORCID 0000-0003-4351-1487
Kaavya RekanarLero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland.ORCID 0000-0002-5766-6650
Ita RichardsonLero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland.ORCID 0000-0002-5493-2837
Thomas WelshLero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland.ORCID 0000-0003-3134-5469
Cristiano StorniLero, Science Foundation Ireland Research Centre for Software, University of Limerick, Limerick, Ireland.ORCID 0000-0003-1601-0900
COVIGILANT Group *see Acknowledgments for contributors, .
Science Foundation Ireland · IEKnowledge Centre for Agriculture · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe silent transmission of COVID-19 has led to an exponential growth of fatal infections. With over 4 million deaths worldwide, the need to control and stem transmission has never been more critical. New COVID-19 vaccines offer hope. However, administration timelines, long-term protection, and effectiveness against potential variants are still unknown. In this context, contact tracing and digital contact tracing apps (CTAs) continue to offer a mechanism to help contain transmission, keep people safe, and help kickstart economies. However, CTAs must address a wide range of often conflicting concerns, which make their development/evolution complex. For example, the app must preserve citizens' privacy while gleaning their close contacts and as much epidemiological information as possible.

objectiveIn this study, we derived a compare-and-contrast evaluative framework for CTAs that integrates and expands upon existing works in this domain, with a particular focus on citizen adoption; we call this framework the Citizen-Focused Compare-and-Contrast Evaluation Framework (C

methodsThe framework was derived using an iterative approach. First, we reviewed the literature on CTAs and mobile health app evaluations, from which we derived a preliminary set of attributes and organizing pillars. These attributes and the probing questions that we formulated were iteratively validated, augmented, and refined by applying the provisional framework against a selection of CTAs. Each framework pillar was then subjected to internal cross-team scrutiny, where domain experts cross-checked sufficiency, relevancy, specificity, and nonredundancy of the attributes, and their organization in pillars. The consolidated framework was further validated on the selected CTAs to create a finalized version of C

resultsThe final framework presents seven pillars exploring issues related to CTA design, adoption, and use: (General) Characteristics, Usability, Data Protection, Effectiveness, Transparency, Technical Performance, and Citizen Autonomy. The pillars encompass attributes, subattributes, and a set of illustrative questions (with associated example answers) to support app design, evaluation, and evolution. An online version of the framework has been made available to developers, health authorities, and others interested in assessing CTAs.

conclusionsOur CTA framework provides a holistic compare-and-contrast tool that supports the work of decision-makers in the development and evolution of CTAs for citizens. This framework supports reflection on design decisions to better understand and optimize the design compromises in play when evolving current CTAs for increased public adoption. We intend this framework to serve as a foundation for other researchers to build on and extend as the technology matures and new CTAs become available.

Indexed as

COVID-19Mobile ApplicationsContact TracingCOVID-19 VaccinesHumansPrivacyCOVID-19 Vaccinescontact tracingCOVID-19digital contact tracing appsdigital healthevaluationframeworkhealth appsmHealthmobile health

Identifiers

PMID35084338
PMCPMC8919989
OpenAlexW4206378242

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.