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

ABSTRACT

AIM: Our 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. DESIGN: Cross-sectional. METHODS: Questionnaires 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. RESULTS: Age 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. CONCLUSIONS: This 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. IMPLICATIONS Personalized 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. IMPACT Tackles 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 METHOD: STROBE Statement (for cross-sectional studies). PATIENT OR PUBLIC CONTRIBUTION None.