Evidence map›Paper›PMID 36206241›Full record

ArticlePloS one2022

Capturing the experiences of UK healthcare workers during the COVID-19 pandemic: A structural topic modelling analysis of 7,412 free-text survey responses.

Danielle Lamb, Liam Wright, Hannah Scott, Bethany Croak, Sam Gnanapragasam, Mary Docherty, Neil Greenberg, Matthew Hotopf, Sharon A M Stevelink, Rosalind Raine and 1 more

Abstract read
In one paragraph

Article in PloS one, 2022. 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

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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. Review
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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

11 authors.

Danielle LambUCL, London, United Kingdom.ORCID 0000-0003-1526-9793
Liam WrightUCL, London, United Kingdom.
Hannah ScottKing's College London, London, United Kingdom.
Bethany CroakKing's College London, London, United Kingdom.ORCID 0000-0002-6486-8154
Sam GnanapragasamKing's College London, London, United Kingdom.
Mary DochertySouth London and Maudsley NHS Trust, London, United Kingdom.
Neil GreenbergKing's College London, London, United Kingdom.
Matthew HotopfKing's College London, London, United Kingdom.
Sharon A M StevelinkKing's College London, London, United Kingdom.
Rosalind RaineUCL, London, United Kingdom.
Simon WesselyKing's College London, London, United Kingdom.

Funding

Department of HealthMedical Research Council MR/V034405/1
6 · The paper itself

Abstract

backgroundHealthcare workers (HCWs) have provided vital services during the COVID-19 pandemic, but existing research consists of quantitative surveys (lacking in depth or context) or qualitative interviews (with limited generalisability). Structural Topic Modelling (STM) of large-scale free-text survey data offers a way of capturing the perspectives of a wide range of HCWs in their own words about their experiences of the pandemic.

methodsIn an online survey distributed to all staff at 18 geographically dispersed NHS Trusts, we asked respondents, "Is there anything else you think we should know about your experiences of the COVID-19 pandemic?". We used STM on 7,412 responses to identify topics, and thematic analysis on the resultant topics and text excerpts.

resultsWe identified 33 topics, grouped into two domains, each containing four themes. Our findings emphasise: the deleterious effect of increased workloads, lack of PPE, inconsistent advice/guidance, and lack of autonomy; differing experiences of home working as negative/positive; and the benefits of supportive leadership and peers in ameliorating challenges. Themes varied by demographics and time: discussion of home working decreasing over time, while discussion of workplace challenges increased. Discussion of mental health was lowest between September-November 2020, between the first and second waves of COVID-19 in the UK. DISCUSSION: Our findings represent the most salient experiences of HCWs through the pandemic. STM enabled statistical examination of how the qualitative themes raised differed according to participant characteristics. This relatively underutilised methodology in healthcare research can provide more nuanced, yet generalisable, evidence than that available via surveys or small interview studies, and should be used in future research.

Indexed as

COVID-19Health PersonnelHumansPandemicsSurveys and QuestionnairesUnited Kingdom

Identifiers

PMID36206241
PMCPMC9543686

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.