Fujimoto Kanako, Utsumi Momoe, Suzuki Ayako, Harada Nahoko
Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.
Graduate School of Health and Nursing Sciences, Kyoto Prefectural University of Medicine, Kyoto, Japan.
Nurs Health Sci. 2025 Jun;27(2):e70125. doi: 10.1111/nhs.70125.
Understanding the determinants influencing healthcare workers' (HCWs) behaviors is essential for promoting infection prevention and control (IPC) in Japanese nursing homes (NHs). This scoping review aimed to map IPC determinants in Japanese NHs using two behavior change frameworks and to identify research gaps. We conducted a scoping review using three databases, following the Joanna Briggs Institute methodology. Reviewers independently screened reports, assessed eligibility, and extracted IPC behavior determinants. Extracted data were mapped and thematically analyzed using the Theoretical Domains Framework (TDF) and the Capability, Opportunity, and Motivation-Behavior model. Of 1778 records identified, 22 reports published between 2006 and 2021 met the inclusion criteria. We codified 70 determinants and generated 15 themes. Most reports addressed barriers related to limited IPC knowledge, skills, resources, and systems. Facilitators were mainly codified within motivation-related TDF domains, where an underexplored research gap was identified. Further research focusing on IPC motivation and a deeper understanding of NH contexts is important for developing context-appropriate IPC promotion strategies. A participatory approach involving NH residents and HCWs may be helpful in future research.
了解影响医护人员(HCWs)行为的决定因素对于促进日本养老院(NHs)的感染预防与控制(IPC)至关重要。本综述旨在使用两个行为改变框架梳理日本养老院中的IPC决定因素,并找出研究空白。我们按照乔安娜·布里格斯研究所的方法,使用三个数据库进行了综述。评审人员独立筛选报告、评估合格性并提取IPC行为决定因素。使用理论领域框架(TDF)和能力、机会与动机-行为模型对提取的数据进行梳理和主题分析。在确定的1778条记录中,2006年至2021年间发表的22份报告符合纳入标准。我们编纂了70个决定因素并生成了15个主题。大多数报告讨论了与IPC知识、技能、资源和系统有限相关的障碍。促进因素主要编纂在与动机相关的TDF领域内,其中发现了一个未充分探索的研究空白。聚焦于IPC动机以及对养老院环境更深入理解的进一步研究,对于制定适合具体环境的IPC促进策略很重要。涉及养老院居民和医护人员的参与式方法可能对未来研究有所帮助。