背景:先前在夜班工人中进行的干预研究主要集中在单一干预措施上,并没有发现有效性的确凿证据。有人认为,包括个人和环境组成部分的全面干预方法很重要。深入了解对夜班工作人员实施干预措施的影响因素和有效性对于区分理论和计划失败很重要。
目的:为了评估PerfectFit@Night干预改善睡眠的效果和实施,医疗保健夜班工作人员的疲劳和恢复,使用RE-AIM框架,评估覆盖范围,有效性,收养,实施和维护干预措施。
方法:前瞻性研究前后设计,在干预前和干预后三个月和六个月进行两次测量。
方法:荷兰一所大学医院的12个不同科室。
方法:医护人员夜班(n=210)。
方法:PerfectFit@Night包括环境(提供睡床和健康食品,和讲习班健康名册)和个人元素(电子学习和睡眠辅导),并分阶段实施了三个月。问卷调查,使用了日志和采访数据。干预对睡眠的影响,使用混合效应模型评估疲劳和恢复,和实施范围因素,收养,实施和维护进行了评估。
结果:夜班相关失眠(-11%-分,95%CI:-19%,-三个月时4%),干预后,恢复需求(β:-2.45,95%CI:-4.86,-0.03,六个月)和疲劳(OR:0.46,95%CI:0.25,0.86,六个月)显着降低。主观睡眠质量和睡眠时间没有变化。为每个干预要素确定了实施的障碍和促进者(例如,饮食偏好),组织(例如,工作职责)和工作场所级别(例如,电源午睡床的位置),而对于干预本身(例如,电子学习中的有用信息)。尽管满意度很高,并且首选延续,在日常生活中嵌入干预是有限的.未来执行的促进者包括对干预措施持积极态度,关于干预要素的明确指导方针,任命夜班工人为大使,以及在工作要求和干预要素方面的适当条件。
结论:多方面的PerfectFit@Night干预减少了失眠,疲劳和需要恢复在夜间工作人员的医疗保健。改善PerfectFit@Night实施的最重要的促进者存在于组织层面(例如,文化中的积极态度和合适的工作要求)。将效果和实施评估相结合对于确定阻碍或增强干预效果的障碍和促进因素至关重要。
背景:该研究于2021年1月17日在荷兰试验登记册中注册(试验编号NL9224)。
BACKGROUND: Previous intervention studies among night workers mainly focused on single interventions and found inconclusive evidence for effectiveness. A comprehensive intervention approach that includes individual and environmental components has been argued as important. Gaining insight into contributing factors for the implementation of interventions for night workers and effectiveness is important to distinguish between theory and programme failure.
OBJECTIVE: To evaluate the effects and implementation of the PerfectFit@Night intervention to improve sleep, fatigue and recovery of night workers in healthcare, using the RE-AIM framework, which assesses reach, effectiveness, adoption, implementation and maintenance of interventions.
METHODS: A prospective pre-post
study design, with two measurements before and three and six months after the intervention.
METHODS: Twelve different departments of a university hospital in the Netherlands.
METHODS: Healthcare workers working night shifts (n = 210).
METHODS: PerfectFit@Night consisted of environmental (provision of a powernap bed and healthy food, and workshop healthy rostering) and individual elements (e-learning and sleep coaching) and was implemented for three months in a phased manner. Questionnaires, logbooks and interview data were used. Effects of the intervention on sleep, fatigue and recovery were evaluated with mixed-effects models, and implementation factors of reach, adoption, implementation and maintenance were evaluated.
RESULTS: Night shift-related insomnia (-11 %-points, 95 % CI: -19 %, -4 % at three months), need for recovery (β: -2.45, 95 % CI: -4.86, -0.03 at six months) and fatigue (OR: 0.46, 95 % CI: 0.25, 0.86 at six months) decreased significantly after the intervention. No changes were found for subjective sleep quality and sleep duration. Barriers and facilitators for implementation were identified for each intervention element at individual (e.g., dietary preferences), organisational (e.g., responsibilities at work) and workplace levels (e.g., location of power nap bed), and for the intervention itself (e.g., useful information in e-learning). Although satisfaction was high and continuation was preferred, embedding of the intervention in the daily routine was limited. Facilitators for future implementation include a positive attitude towards the intervention, clear guidelines regarding intervention elements, appointment of night workers as ambassadors, and suitable conditions in terms of work demands and for the intervention elements.
CONCLUSIONS: The multi-faceted PerfectFit@Night intervention reduced insomnia, fatigue and need for recovery in night workers in healthcare. The most important facilitators to improve the implementation of PerfectFit@Night exist at the organisational level (e.g., positive attitude within the culture and suitable work demands). Combining effect and implementation evaluation is crucial to identify barriers and facilitators that hamper or enhance intervention effects.
BACKGROUND: The
study was registered in the Netherlands
Trial Register on 17 January 2021 (
trial number NL9224).