Department of Healthcare Delivery Research and Evaluation, Westat, Inc., Rockville, Maryland.
J Gerontol B Psychol Sci Soc Sci. 2020 Nov 13;75(10):2181-2192. doi: 10.1093/geronb/gbz165.
This study investigates the relationship of caregiver demographics, caregiving intensity, caregiver support use, and aspects of the caregiving situation to a self-reported measure of unmet need among U.S. informal caregivers of older adults living at home with various conditions.
Response data from 1,558 caregiver participants interviewed by telephone during the December 2016 baseline period of the Outcome Evaluation of the National Family Caregiver Support Program were used. Caregivers who responded "Definitely No" to the question "Are you receiving all the help you need?" were classified as reporting unmet need. Logistic regression was used to find significant factors associated with unmet need among the full sample and among caregivers tiered by three levels of burden.
Unmet need was reported by 22% of the caregivers. In a fully adjusted model, unmet need was predicted by higher levels of caregiving intensity, non-White race of the caregiver, and the caregiver not feeling appreciated by their care recipient. Other predictors associated with unmet need were no use of caregiver educational services, fewer respite hours, not living in a rural area, and caregiver having an education past high school.
Caregivers who do not feel appreciated by their care recipient and non-White caregivers should be identified as potential targets for intervention to address unmet need, especially if they are also reporting higher levels of caregiver burden. Understanding the factors associated with self-reported unmet need can assist caregiver support programs in measuring and addressing the needs of informal caregivers to support their continued caregiving.
本研究调查了美国老年居家照护者的照顾者人口统计学特征、照顾强度、照顾者支持使用情况以及照顾情况各方面与自我报告的未满足需求之间的关系，这些照顾者照顾的对象患有各种疾病。
使用了在 2016 年 12 月全国家庭照顾者支持计划结果评估的基线期间通过电话采访的 1558 名照顾者参与者的应答数据。对“你是否得到了你所需要的所有帮助？”这个问题回答“肯定没有”的照顾者被归类为报告存在未满足需求。使用逻辑回归来寻找全样本以及根据三个负担水平分层的照顾者中与未满足需求相关的显著因素。
22%的照顾者报告存在未满足需求。在完全调整的模型中，较高的照顾强度、照顾者的非白人种族以及照顾者感觉自己没有得到照顾对象的感激与未满足需求相关。与未满足需求相关的其他预测因素包括不使用照顾者教育服务、较少的缓解时间、不住在农村地区以及照顾者的教育程度超过高中。
如果那些没有得到照顾对象感激的照顾者和非白人照顾者同时也报告了更高水平的照顾者负担，那么他们应该被确定为干预以解决未满足需求的潜在目标。了解与自我报告的未满足需求相关的因素可以帮助照顾者支持计划衡量和满足非正式照顾者的需求，以支持他们继续照顾。
