Evidence map›Paper›PMID 32215217›Full record

ArticleDigital health

Exploring UK doctors' attitudes towards online patient feedback: Thematic analysis of survey data.

Amadea Turk, Joanna Fleming, John Powell, Helen Atherton

Abstract read
In one paragraph

Article in Digital health. 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.

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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

4 authors.

Amadea TurkWarwick Medical School, University of Warwick, UK.ORCID https://orcid.org/0000-0002-5139-0016
Joanna FlemingWarwick Medical School, University of Warwick, UK.
John PowellNuffield Department of Primary Care Health Sciences, University of Oxford, UK.
Helen AthertonWarwick Medical School, University of Warwick, UK.

Funding

Department of Health 14/04/48
6 · The paper itself

Abstract

introductionPatients are increasingly using online platforms to give feedback about their health-care experiences. Online feedback has been proposed as a way to drive transformative change in the health service through informing choice and improving quality. Attitudes held by health-care professionals influence the uptake of new technologies. Understanding these attitudes is essential in exploring the potential of online patient feedback as a standard feedback mechanism. This study explores the content of free-text comments left by doctors responding to a survey with the aim of understanding their attitudes towards online feedback.

methodsA cross-sectional online questionnaire was completed by 1001 UK primary and secondary-care doctors. Doctors were given the opportunity to leave a free-text comment about online patient feedback. Doctors' attitudes towards online patient feedback were identified and explored using thematic analysis. Descriptive statistics and chi-square tests were used to examine demographic differences between those doctors who left a comment and those who did not.

resultsThematic analysis identified five key interrelated themes: anonymity, confidentiality, representativeness, moderation/regulation of online feedback and platform type. The characteristics of those leaving a comment very closely matched those of the entire survey sample.

conclusionAcross the comments, the most prominent finding was a general scepticism and caution towards online feedback, with most of the key themes relating to the perceived limitations and challenges. Further work exploring ways of addressing and verifying online comments without breaching confidentiality could provide valuable information to health systems seeking to drive improvement through patient online feedback.

Indexed as

commentsfeedbackInternetphysicianspolicy

Identifiers

PMID32215217
PMCPMC7065433

What OpenQuestion holds

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LicenceCC BY-NC
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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.