Evidence map›Paper›PMID 39758428›Full record

ArticleCochrane evidence synthesis and methods2024

Using visual methods to further enhance qualitative evidence synthesis.

Mayara Silveira Bianchim, Emma F France, Jane Noyes

Abstract read
In one paragraph

Article in Cochrane evidence synthesis and methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Mayara Silveira BianchimSchool of Medical and Health Sciences Bangor University Bangor UK.ORCID https://orcid.org/0000-0003-3082-7984
Emma F FranceCentre for Healthcare and Community Research, Faculty of Health Sciences and Sport University of Stirling Stirling UK.ORCID 0000-0003-0876-7030
Jane NoyesSchool of Medical and Health Sciences Bangor University Bangor UK.ORCID 0000-0003-4238-5984

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The use of visual methods in qualitative evidence synthesis (QES) adds a valuable dimension to the synthesis process by enhancing understanding and knowledge generation. Visual methods are currently underused and underreported in QES. Methods: This is the first study to describe accessible visual methods that support various stages of QES and to show the application of visual methods to a Cochrane QES of 43 studies using meta-ethnography and systematic review methods. This study also addresses the involvement of stakeholders including the public, practical considerations of equity, diversity, inclusion, and reflexivity in the selection and application of visual methods. Results: In a novel approach, the review authors utilized a combination of remote and in-person visual methods to initiate and develop their synthesis, involving stakeholders throughout the process. The review authors used methods including paper labels, cartoons, infographics, virtual whiteboards, and diagrams. The rigorous use of visual methods in the QES facilitated data visualization, remote analysis meetings, interpretation of extensive data, and meaningful patient and public involvement. Conclusion: QES authors are encouraged to consider the use of visual methods, particularly when involving the public in the synthesis process. When selecting visual methods, authors should consider how they align with the study's objectives, suit the stage of synthesis, might enhance analysis, their available resources, and the team's technical skills.

Indexed as

meta‐ethnographyQESqualitative evidence synthesisvisual methods

Identifiers

PMID39758428
PMCPMC11698405

What OpenQuestion holds

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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.