Wynendaele Herlinde, Peeters Ellen, Gemmel Paul, Myny Dries, Trybou Jeroen
Department of Public Health and Primary Care, Ghent University, Ghent, Belgium.
TIAS School for Business and Society, Utrecht, The Netherlands.
J Adv Nurs. 2025 Apr;81(4):1829-1844. doi: 10.1111/jan.16373. Epub 2024 Aug 8.
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.
Cross-sectional.
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.
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.
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.
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.
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.
STROBE Statement (for cross-sectional studies).
None.
我们的研究旨在探讨护士的轮班偏好与其个人特征之间的关系,并研究这些偏好如何与比利时医疗环境中规定的排班表相匹配。此外,该研究还试图找出一周中不同日期轮班偏好的模式,调查是否存在偏好相似的不同护士群体,并进一步研究这些群体与其个人特征之间的联系。
横断面研究。
对比利时11家综合医院的778名护士进行问卷调查,收集有关人口统计学、生物钟类型、轮班偏好和排班匹配情况的数据。统计分析包括逻辑回归、主成分分析和k均值聚类。
年龄和生物钟类型显著影响护士的轮班偏好。一周内各天的偏好是一致的。该研究揭示了两种偏好类型:“早起者”(偏好早班/日班)和“夜猫子”(偏好晚班/夜班)。夜猫子通常是中性或晚上型生物钟类型,并且规定排班表与理想排班表之间的匹配度更高。
本研究强化了考虑与年龄和生物钟类型相关的护士轮班偏好个体差异的重要性,并主张采用灵活的、个性化的排班系统。
个性化排班有可能改善劳动力管理,这表明医疗保健管理人员在排班时应考虑个人偏好,以缓解护士人员不足的挑战。
解决护士人员不足这一紧迫问题。提出基于个人偏好的定制排班表可以改善护士的工作条件。与旨在加强护士劳动力管理的政策制定者相关。
STROBE声明(用于横断面研究)。
无。