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ArticleTrials2024

Consultations about randomised controlled trials are shorter and less in-depth for socioeconomically disadvantaged patients compared to socioeconomically advantaged patients: qualitative analysis across three trials.

Mariana Popa, Bridget Young, Nikki Rousseau, Mary G Cherry, Isobel Jenkins, Jane Cloke, Andrew Pettitt, Michael D Jenkinson, Saiqa Ahmed, Allan R Pemberton and 1 more

Abstract readComparative Study
In one paragraph

Article in Trials, 2024. 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
–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

3 citing papers in PubMed.

  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.

Mariana PopaDepartment of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK.
Bridget YoungDepartment of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK.
Nikki RousseauSchool of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, UK.
Mary G CherryDepartment of Primary Care and Mental Health, University of Liverpool, Liverpool, UK.
Isobel JenkinsSchool of Medicine, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK.
Jane ClokeNIHR Applied Research Collaboration North West Coast, University of Liverpool, Liverpool, UK.
Andrew PettittDepartment of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, UK.
Michael D JenkinsonInstitute of Systems, Molecular and Integrative Biology, The University of Liverpool, Liverpool, UK.
Saiqa AhmedNIHR Applied Research Collaboration North West Coast, University of Liverpool, Liverpool, UK.
Allan R PembertonNIHR Applied Research Collaboration North West Coast, University of Liverpool, Liverpool, UK.
Frances C SherrattDepartment of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK. sherratt@liverpool.ac.uk.ORCID http://orcid.org/0000-0003-4147-9305

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients from socioeconomically disadvantaged backgrounds are underserved in randomised controlled trials, yet they experience a much greater burden of disease compared with patients from socioeconomically advantaged areas. It is crucial to make trials more inclusive to ensure that treatments and interventions are safe and effective in real-world contexts. Improving how information about trials is verbally communicated is an unexplored strategy to make trials more inclusive. This study examined how trials are communicated verbally, comparing consultations involving patients from the most and least socioeconomically disadvantaged areas.

methodsSecondary qualitative analysis of 55 trial consultation transcripts from 41 patients, sampled from 3 qualitative studies embedded in their respective UK multi-site, cancer-related randomised controlled trials. Patients living in the most and least socioeconomically disadvantaged areas, defined using English Indices of Multiple Deprivation decile scores, were purposively sampled. Analysis was largely thematic and drew on the constant comparison method.

resultsRecruiters communicated clinical uncertainty in a similar way for patients living in different socioeconomic areas. Consultations with disadvantaged patients were, on average, half the duration of those with advantaged patients, and tended to involve recruiters providing less in-depth explanations of trial concepts, used phrasing that softened trial arm risks, and described trial processes (e.g. randomisation) using informal or metaphorical phrasing. Disadvantaged and advantaged patients differed in the concerns they expressed; disadvantaged patients voiced fewer concerns and asked fewer questions but were also less likely to be invited to do so by recruiters.

conclusionInteractions about trials unfolded in different ways between patients living in different socioeconomic areas, likely due to both patient- and recruiter-related factors. We present considerations for recruiters when discussing trials with patients from socioeconomically disadvantaged backgrounds, aimed at enhancing trial communication. Future research should examine disadvantaged patients' and recruiters' experiences of verbal trial communication to inform guidance that addresses the needs and preferences of underserved groups.

Indexed as

Qualitative ResearchRandomized Controlled Trials as TopicSocioeconomic FactorsVulnerable PopulationsAdultAgedCommunicationFemaleHealthcare DisparitiesHealth Knowledge, Attitudes, PracticeHumansMaleMiddle AgedMulticenter Studies as TopicNeoplasmsPatient SelectionCommunicationDisadvantageEquipoiseInclusivityQualitativeRandomisedSocioeconomicTrial

Identifiers

PMID38872208
PMCPMC11177527

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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.