Evidence map›Paper›PMID 42011491›Full record

ArticleJournal of research in nursing : JRN2026

A case for qualitatively driven mixed methods in nursing research: a methodological discussion.

Jennifer Hamilton, Simon Cooper, Irene Ngune, Amanda Cole, Richard Bostwick, Debbie Louise Massey

Abstract read
In one paragraph

Article in Journal of research in nursing : JRN, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Jennifer HamiltonSenior Lecturer, School of Nursing and Midwifery, Edith Cowan University, Australia.ORCID https://orcid.org/0000-0003-0026-5298
Simon CooperProfessor, School of Nursing and Midwifery, Edith Cowan University, Australia.ORCID https://orcid.org/0000-0001-5561-3099
Irene NguneAssociate Professor, School of Nursing and Midwifery, Edith Cowan University, Australia.
Amanda ColeSenior Lecturer, School of Nursing and Midwifery, Edith Cowan University, Australia.
Richard BostwickAssociate Professor, School of Nursing, Curtin University, Australia.
Debbie Louise MasseyProfessor, School of Nursing and Midwifery, Edith Cowan University, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mixed methodology continues to grow as a rigorous and respected research design. However, the value of qualitatively driven mixed methods research within nursing is underrepresented. Qualitatively driven mixed methods, where qualitative data dominate meaning-making, have the potential to capture critical experiential elements pertinent to nursing research while supporting empirical rigour. This methodology paper argues for the importance of qualitatively driven mixed methods approaches within nursing research to enable greater understanding of complex phenomenon. Through discussion and case example the role of qualitatively driven mixed methods, including within a sequential explanatory design, are presented. Nurses and midwives are well placed to design and conduct health research, and this paper provides methodological guidance and advances epistemological understanding of qualitatively driven mixed methods within research to improve staff and patient outcomes. For health and social care policy, these methods provide rich contextual data that can inform policy development and evidence-based practice. This methodological discussion piece highlights how qualitatively driven mixed methods enable greater understanding of complex phenomenon and experiential insights.

Indexed as

mental healthmethodsphenomenologyphilosophyresearchresearch design

Identifiers

PMID42011491
PMCPMC13091901

What OpenQuestion holds

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LicenceCC BY
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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.