Evidence map›Paper›PMID 38307538›Full record

ArticleBMJ open2024

What might make nurses stay? A protocol for discrete choice experiments to understand NHS nurses' preferences at early-career and late-career stages.

Ourega-Zoé Ejebu, Joanne Turnbull, Iain Atherton, Anne Marie Rafferty, Billy Palmer, Julia Philippou, Jane Prichard, Michelle Jamieson, Lucina Rolewicz, Matthew Williams and 1 more

Abstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Ourega-Zoé EjebuSchool of Health Sciences, University of Southampton, Southampton, UK O.Ejebu@soton.ac.uk.ORCID 0000-0003-0608-5124
Joanne TurnbullSchool of Health Sciences, University of Southampton, Southampton, UK.
Iain AthertonSchool of Nursing, Midwifery and Social Care, Edinburgh Napier University, Edinburgh, UK.
Anne Marie RaffertyFlorence Nightingale Faculty of Nursing, Midwifery and Palliative Care, King's College London, London, UK.
Billy PalmerNuffield Trust, London, UK.
Julia PhilippouFlorence Nightingale Faculty of Nursing, Midwifery and Palliative Care, King's College London, London, UK.
Jane PrichardSchool of Health Sciences, University of Southampton, Southampton, UK.
Michelle JamiesonSchool of Nursing, Midwifery and Social Care, Edinburgh Napier University, Edinburgh, UK.
Lucina RolewiczNuffield Trust, London, UK.
Matthew WilliamsInstitute for Employment Studies, Brighton, UK.
Jane BallSchool of Health Sciences, University of Southampton, Southampton, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionLike many countries, England has a national shortage of registered nurses. Employers strive to retain existing staff, to ease supply pressures. Disproportionate numbers of nurses leave the National Health Services (NHS) both early in their careers, and later, as they near retirement age. Research is needed to understand the job preferences of early-career and late-career nurses working in the NHS, so tailored policies can be developed to better retain these two groups. METHODS AND ANALYSIS: We will collect job preference data for early-career and late-career NHS nurses, respectively using two separate discrete choice experiments (DCEs). Findings from the literature, focus groups, academic experts and stakeholder discussions will be used to identify and select the DCE attributes (ie, job features) and levels. We will generate an orthogonal, fractional factorial design using the experimental software Ngene. The DCEs will be administered through online surveys distributed by the regulator Nursing and Midwifery Council. For each group, we expect to achieve a final sample of 2500 registered NHS nurses working in England. For early-career nurses, eligible participants will be registered nurses who graduated in the preceding 5 years (ie, 2019-2023). Eligible participants for the late-career survey will be registered nurses aged 55 years and above. We will use conditional and mixed logit models to analyse the data. Specifically, study 1 will estimate the job preferences of early-career nurses and the possible trade-offs. Study 2 will estimate the retirement preferences of late-career NHS nurses and the potential trade-offs. ETHICS AND DISSEMINATION: The research protocol was reviewed and approved by the host research organisation Ethics Committees Research Governance (University of Southampton, number 80610) (https://www.southampton.ac.uk/about/governance/regulations-policies/policies/ethics). The results will be disseminated via conference presentations, publications in peer-reviewed journals and annual reports to key stakeholders, the Department of Health and Social Care, and NHS England/Improvement retention leaders. REGISTRATION DETAILS: Registration on OSF http://doi.org/10.17605/OSF.IO/RDN9G.

Indexed as

NursesState MedicineEnglandFocus GroupsHumansResearch DesignHEALTH ECONOMICSNursing CareSTATISTICS & RESEARCH METHODS

Identifiers

PMID38307538
PMCPMC10836387

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.