Developing a Data Note reporting guideline for qualitative health and social care research datasets (the DeNOTE study): A study protocol
- PMID: 40697405
- PMCID: PMC12281645
- DOI: 10.1080/21642850.2025.2532792
Developing a Data Note reporting guideline for qualitative health and social care research datasets (the DeNOTE study): A study protocol
Abstract
Background: Data Note articles describe openly available research datasets. They detail how and why the data were created, with the aim of increasing research transparency and facilitating data reuse. However, existing guidelines and templates for Data Note articles have been designed for quantitative research datasets and are unsuitable for qualitative research datasets. As qualitative health and social care datasets have unique sensitivities, they must be treated and reported differently to quantitative datasets.
Aim: To describe the protocol for developing a novel reporting guideline for Data Note articles describing qualitative health and social care datasets (i.e. the DeNOTE reporting guideline).
Methods: The DeNOTE study includes (i) a rapid scoping exercise of existing documents and expert knowledge to identify and synthesise relevant reporting 'items' or 'statements' for a Data Note article describing qualitative health and social care data, (ii) an online questionnaire with expert participants to rate their agreement with items identified in (i) and to propose new or amended items, (iii) an online workshop with participants to co-develop the reporting items and reach consensus, (iv) eliciting participant feedback on the draft reporting guideline, and (v) finalising the guideline.
Conclusion: Our plans to develop the DeNOTE reporting guideline are registered on the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network. The guideline will support researchers producing Data Note articles describing qualitative health and social care data. We will create a tailored resource to address the needs of qualitative researchers to facilitate transparency and to support data reuse.
Keywords: Qualitative research; data note; open data; open research; reporting guideline.
© 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Conflict of interest statement
No potential conflict of interest was reported by the authors.
References
-
- Allen, L., O’Connell, A., & Kiermer, V. (2019). How can we ensure visibility and diversity in research contributions? How the Contributor Role Taxonomy (CRediT) is helping the shift from authorship to contributorship. Learned Publishing, 32(1), 71–74.
-
- Branney, P. E., Brooks, J., Kilby, L., Newman, K., Norris, E., Pownall, M., et al. , & Whitaker, C. (2023). Three steps to open science for qualitative research in psychology. Social and Personality Psychology Compass, 17(4), e12728.
-
- Braun, V., & Clarke, V. (2025). Reporting guidelines for qualitative research: A values-based approach. Qual Reseach Psychol, 22(2), 399–438.
-
- The British Psychological Society . (2020). Position statement: Open data. [Internet]. Accessed 11 June 2025. Available from: https://cms.bps.org.uk/sites/default/files/2022-06/Open data position statement.pdf.
-
- Campbell, R., Javorka, M., Engleton, J., Fishwick, K., Gregory, K., & Goodman-Williams, R. (2023). Open-Science guidance for qualitative research: An empirically validated approach for de-identifying sensitive narrative data. Advances in Methods and Practices in Psychological Science , 6(4), 1–17.
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