Measuring Caregiver Networks of Older Adults with Alzheimer's Disease

本提案的总体目标是使用社交网络测量方法（Network Canvas） 获取与阿尔茨海默病患者相关的家庭照顾者的扩展定义 和相关痴呆症（AD/ADRD），特别关注积极/消极关系方面。这 所提出的方法将推进残疾人-护理人员二元研究，以包括测量现实世界 残疾人护理者网络。在阿尔茨海默病（PWD）患者中， 个人如何定义“家庭”照顾者的人口异质性。大多数研究集中在 有一个单一主要照顾者的成年人-残疾人二人组。这种二分体方法可能不代表 现实生活中，因为多个家庭成员和朋友支持照顾残疾人。多个护理人员可能 也有不同的观念的义务，期望的照顾，和积极/消极方面的照顾。我们 先前的研究已经表明看护者之间的交互可以是积极的（例如，团队合作 说服PWD接受帮助）或负面（例如，造成情绪困扰的冲突）。都缺乏 研究如何在网络层面上测量这些人际互动。以减轻 这些关系测量的差距，我们的团队已经建立了一个免费的，开源的，NIH资助的软件 这是一个专为研究人员设计的名为Network Canvas的软件，它可以识别和映射社交网络数据。我们的目标是： 目标1。使用Network Canvass测量和绘制PWD照顾者的社会网络 方法，研究人口异质性的个人如何定义“家庭”照顾者。 目标2.测量照顾者和残疾人积极幸福感的网络预测因素。我们将进行 200个PWD护理者网络（最多1000人）的大型多中心（IL、IN、HI）研究-使用雪球 招聘，以确定/采访网络成员-和网络画布方法。 招募将通过跨学科的社区合作伙伴，医生办公室，和正在进行的NIH- 资助的队列-代表农村/城市，种族/种族多样化，LGBTQ群体。我们预计 PWD-护理者网络的多层：1.）与看护者一起接受同意的PWD（轻度、中度AD）， 2.）的情况。仅照顾者（患有严重痴呆症/无法同意的PWD），3.）仅限同意的PWD，不 照顾者（un-befriended）。混合方法访谈将检查详细的以患者为中心的结果 措施，人际交往（积极/消极），以及网络对个人的影响。 通过这项研究，我们计划有1。）更好地了解如何衡量护理人员 网络，2.）确定照顾者网络的哪些方面最能预测对 照顾者和残疾人的心理和身体健康，以及3.）使网络运行 测量方法，以了解将与其他人共享的护理人员系统 研究人员为残疾人研究社区提供更大的利益。

The overall goal of this proposal is to use a social network measurement methodology (Network Canvas) to capture expanded definitions of family caregivers related to people living with Alzheimer’s disease and related dementias (AD/ADRD), with special focus on positive/negative relationship aspects. This proposed methodology will advance PWD-caregiver dyad research to encompass measuring real-world PWD-caregiver networks. Among people living with Alzheimer’s disease (PWD), there is a significant population heterogeneity in how individuals define “family” caregivers. Most studies concentrate on the caregiver-PWD dyad with one singular primary caregiver. This dyad approach may not be represent real-life, since multiple family members and friends support the care of PWD. Multiple caregivers may also have differing ideas of obligation, expectations of care, and positive/negative aspects of care. Our prior research has shown that interactions between caregivers can be positive (e.g., teamwork to convince PWD to accept help) or negative (e.g., conflicts causing emotional distress). There is a lack of research on how these interpersonal interactions can be measured on a network level. To mitigate these relationship measurement gaps, our team has built a free, open-source, NIH funded software suite for researchers called Network Canvas, that identifies and maps social network data. We aim to: Aim 1. Measure and map the social network of caregivers of PWD using the Network Canvass methodology, to examine the population heterogeneity in how individuals define “family” caregivers. Aim 2. Measure network predictors of positive wellbeing for caregivers and PWD. We will conduct a large multi-site (IL, IN, HI) study of 200 PWD caregiver networks (up to 1000 people) - using snowball recruitment to identify/interview members of the networks – and the Network Canvas methodology. Recruitment will be through interdisciplinary community partners, physician offices, and ongoing NIH- funded cohorts - representing rural/urban, ethnic/racially diverse, LGBTQ groups. We anticipate multiple tiers of PWD-Caregiver networks: 1.) consentable PWD (mild, moderate AD) with caregivers, 2.) Caregivers only (PWD with severe dementia/unable to consent), 3.) consentable PWD only, no caregivers (un-befriended). Mixed method interviews will examine detailed patient-centered outcome measures, interpersonal interactions (positive/negative), and effects of the networks on the individual. Through this research, we plan to have a 1.) Better understanding of how to measure caregiver networks, 2.) Identify which aspects of caregiver networks are most predictive of the impact on psychological and physical well-being of caregivers and PWD, and 3.) Operationalize a network measurement approach to understand caregiver systems that will be shareable with other researchers to provide larger benefit for the caregiver-PWD research community.