Ashida Sato, Lynn Freda B, Thompson Lena, Koehly Laura M, Williams Kristine N, Donohoe Maria S
Department of Community and Behavioral Health, College of Public Health, University of Iowa, Iowa City, Iowa, USA.
Department of Sociology and Criminology, College of Liberal Arts and Sciences, University of Iowa, Iowa City, Iowa, USA.
Innov Aging. 2024 May 18;8(6):igae046. doi: 10.1093/geroni/igae046. eCollection 2024.
Caregivers of persons living with dementia report wide-ranging lived experiences, including feelings of burden and frustration but also positivity about caregiving. This study applies clustering methodology to novel survey data to explore variation in caregiving experience profiles, which could then be used to design and target caregiver interventions aimed at improving caregiver well-being.
The -means clustering algorithm partitioned a sample of 81 caregivers from the Midwest region of the United States on the basis of 8 variables capturing caregiver emotions, attitudes, knowledge, and network perceptions (: burden, anxiety, network malfeasance; network nonfeasance; : positive aspects of caregiving, preparedness and confidence in community-based care, knowledge about community services for older adults, and network uplift). The experience profile of each segment is described qualitatively and then regression methods were used to examine the association between (a) experience profiles and caregiver demographic characteristics and (b) experience profiles and study attrition.
The clustering algorithm identified 4 segments of caregivers with distinct experience profiles: (low adversity, high positivity); (high network malfeasance); (high adversity, low positivity); (unprepared, disconnected, but not anxious). Experience profiles were associated with significantly different demographic profiles and attrition rates.
How caregivers respond to support interventions may be contingent on caregivers' experience profile. Research and practice should focus on identifying public health strategies tailored to fit caregiver experiences.
NCT03932812.
痴呆症患者的照料者报告了广泛的生活经历,包括负担感和挫败感,但也有照料方面的积极感受。本研究将聚类方法应用于新的调查数据,以探索照料经历概况的差异,进而用于设计并针对照料者干预措施,旨在改善照料者的幸福感。
K均值聚类算法根据8个变量对来自美国中西部地区的81名照料者样本进行了划分,这些变量涵盖照料者的情绪、态度、知识和网络认知(即:负担、焦虑、网络不当行为、网络无不当行为;即:照料的积极方面、对社区照料的准备情况和信心、对老年人社区服务的了解以及网络支持)。对每个类别中的经历概况进行定性描述,然后使用回归方法检验(a)经历概况与照料者人口统计学特征之间以及(b)经历概况与研究损耗之间的关联。
聚类算法识别出4类具有不同经历概况的照料者:(低逆境,高积极性);(高网络不当行为);(高逆境,低积极性);(无准备、脱节,但不焦虑)。经历概况与显著不同的人口统计学概况和损耗率相关。
照料者对支持干预措施的反应可能取决于照料者的经历概况。研究和实践应侧重于确定适合照料者经历的公共卫生策略。
NCT03932812。