Unravelling the ideal roster: A cross‐sectional study of nurse shift preferences using multivariate analysis

Author:

Wynendaele Herlinde1ORCID,Peeters Ellen2ORCID,Gemmel Paul3,Myny Dries1,Trybou Jeroen1

Affiliation:

1. Department of Public Health and Primary Care Ghent University Ghent Belgium

2. TIAS School for Business and Society Utrecht The Netherlands

3. Department of Marketing, Innovation and Organization & Department of Public Health and Primary Care Ghent University Ghent Belgium

Abstract

AbstractAimOur study aims to explore nurses' shift preferences in relation to their personal characteristics and examine how these preferences align with the rosters imposed in Belgian healthcare settings. Additionally, the study seeks to identify patterns in shift preferences across different days of the week and investigate the existence of distinct groups of nurses with similar preferences, further examining the link between these groups and their personal characteristics.DesignCross‐sectional.MethodsQuestionnaires were distributed to 778 nurses across 11 general hospitals in Belgium, collecting data on demographics, chronotype, shift preferences, and roster alignment. Statistical analyses included logistic regression, principal component analysis, and k‐means clustering.ResultsAge and chronotype significantly influence nurses' shift preferences. Preferences were consistent across the days within the week. The study revealed two groups of preferences: ‘early birds’ (preferring morning/day shifts) and ‘night owls’ (preferring evening/night shifts). Night owls were often neutral or evening‐type chronotypes and had a higher alignment between imposed and ideal rosters.ConclusionsThis study reinforces the importance of considering individual differences in nurses' shift preferences, linked to age and chronotype, and advocates for the adoption of flexible, personalized rostering systems.ImplicationsPersonalized scheduling has the potential to improve workforce management, suggesting that healthcare administrators should consider individual preferences in rostering to mitigate the challenges of nurse understaffing.ImpactTackles the pressing problem of nurse understaffing. Proposes that tailored rosters based on individual preferences could improve work conditions for nurses. Relevant to policymakers aiming to enhance nursing workforce management.Reporting methodSTROBE Statement (for cross‐sectional studies).Patient or public contributionNone.

Publisher

Wiley

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