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. 2023 Feb 6:6:10.
doi: 10.12688/hrbopenres.13667.1. eCollection 2023.

Qualitative data sharing practices in clinical trials in the UK and Ireland: towards the production of good practice guidance

Affiliations

Qualitative data sharing practices in clinical trials in the UK and Ireland: towards the production of good practice guidance

Megan McCarthy et al. HRB Open Res. .

Abstract

Background: Data sharing enables researchers to conduct novel research with previously collected datasets, thus maximising scientific findings and cost effectiveness, and reducing research waste. The value of sharing, even de-identified, quantitative data from clinical trials is well recognised with a moderated access approach recommended. While substantial challenges to sharing quantitative data remain, there are additional challenges for sharing qualitative data in trials. Incorporating the necessary information about how qualitative data will be shared into already complex trial recruitment and consent processes proves challenging. The aim of this study was to explore whether and how trial teams share qualitative data collected as part of the design, conduct, analysis, or delivery of clinical trials. Methods: Phase 1 involved semi-structured, in-depth qualitative interviews and focus groups with key trial stakeholder groups including trial managers and clinical trialists (n=3), qualitative researchers in trials (n=9), members of research funding bodies (n=2) and trial participants (n=1). Data were analysed using thematic analysis. In Phase 2, we conducted a content analysis of 16 participant information leaflets (PIL) and consent forms (CF) for trials that collected qualitative data. Results: Three key themes were identified from our Phase 1 findings: ' Understanding and experiences of the potential benefits of sharing qualitative data from trials', 'Concerns about qualitative data sharing', and ' Future guidance and funding'. In phase 2, the PILs and CFs received revealed that the benefits of data sharing for participants were only explained in two of the study documents. Conclusions: The value of sharing qualitative data was acknowledged, but there are many uncertainties as to how, when, and where to share this data. In addition, there were ethical concerns in relation to the consent process required for qualitative data sharing in trials. This study provides insight into the existing practice of qualitative data sharing in trials.

Keywords: data sharing; focus groups; qualitative; trials.

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Conflict of interest statement

No competing interests were disclosed.

References

    1. Aitken M, de St Jorre J, Pagliari C, et al. : Public responses to the sharing and linkage of health data for research purposes: a systematic review and thematic synthesis of qualitative studies. BMC Med Ethics. 2016;17(1):73. 10.1186/s12910-016-0153-x - DOI - PMC - PubMed
    1. Al Dandan HB, Rose G, McClurg D, et al. : Management strategies for lower urinary tract symptoms (LUTS) among people with multiple sclerosis (MS): a qualitative study of the perspectives of people with MS and healthcare professionals [version 1; peer review: 2 approved]. HRB Open Res. 2019;2:31. 10.12688/hrbopenres.12960.1 - DOI - PMC - PubMed
    1. Alexander SM, Jones K, Bennett NJ, et al. : Qualitative data sharing and synthesis for sustainability science. Nat Sustain. 2020;3(2):81–8. 10.1038/s41893-019-0434-8 - DOI
    1. Antes AL, Walsh HA, Strait M, et al. : Examining Data Repository Guidelines for Qualitative Data Sharing. J Empir Res Hum Res Ethics. 2018;13(1):61–73. 10.1177/1556264617744121 - DOI - PMC - PubMed
    1. Bates DW, Saria S, Ohno-Machado L, et al. : Big data in health care: using analytics to identify and manage high-risk and high-cost patients. Health Aff (Millwood). 2014;33(7):1123–1131. 10.1377/hlthaff.2014.0041 - DOI - PubMed

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