在线社区作为阿尔茨海默病和痴呆症护理的支持系统:大规模探索性研究。

IF 5 Q1 GERIATRICS & GERONTOLOGY
JMIR Aging Pub Date : 2025-05-05 DOI:10.2196/68890
Sidharth Kaliappan, Chunyu Liu, Yoshee Jain, Ravi Karkar, Koustuv Saha
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引用次数: 0

摘要

背景:阿尔茨海默病(AD)是痴呆症的主要类型,需要全面的认识和干预策略。在美国,有超过600万人受到影响,阿尔茨海默病和相关痴呆(AD/ADRD)的患病率日益成为公共卫生挑战。然而,患有AD/ADRD的个体和他们的照顾者经常表达边缘化的感觉,描述了以患者幼稚化和缺乏尊重为特征的互动。目的:本研究旨在解决两个关键研究问题(RQs)。在RQ1中,我们调查了在线社交社区中关注AD/ADRD的参与者所表达的需求和关注,特别是在reddit的r/ alzheimer和ALZConnected两个平台上。对于RQ2,我们考察了与这些需求和关注相对应的社会支持的流行程度和分布,以及这些需求与获得的支持之间的关系。方法:我们收集了2014年7月至2023年11月r/ alzheimer子reddit上的13429篇帖子和评论,以及2020年12月(该社区最早的帖子)至2023年11月ALZConnected上的90113篇帖子和评论。我们使用潜在狄利克雷分配(LDA)进行主题建模,然后进行标记以确定讨论的主要主题。我们使用迁移学习分类器来识别讨论中的评论(或回应)中出现的情感支持(ES)和信息支持(IS)。我们建立了回归模型来检验各种主题是如何与所获得的支持类型相关联的。结果:我们的分析揭示了不同的主题范围,反映了社区成员对AD/ADRD患者不同的需求和关注。这些主题概括了在线社区内的主要讨论:记忆护理、护理和照顾、感激和感谢,以及法律和财务考虑。我们的研究结果表明,IS的患病率高于ES。回归模型显示,ES主要发生在与护理和护理相关的岗位,而IS主要发生在与医疗条件和诊断、法律和财务以及家庭护理相关的岗位。结论:这项研究表明,致力于AD/ADRD支持的在线社区参与了广泛的主题讨论,例如记忆护理,护理,护理以及法律和财务挑战。研究结果揭示了个人在家庭中管理AD/ADRD所面临的关键痛点和担忧,揭示了他们如何利用在线平台获得指导和支持。这些见解强调了有针对性的机构和社会干预措施的必要性,以解决AD/ADRD患者、护理人员和其他家庭成员的具体需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online Communities as a Support System for Alzheimer Disease and Dementia Care: Large-Scale Exploratory Study.

Background: Alzheimer disease (AD) is the leading type of dementia, demanding comprehensive understanding and intervention strategies. In the United States, where over 6 million people are impacted, the prevalence of AD and related dementias (AD/ADRD) presents a growing public health challenge. However, individuals living with AD/ADRD and their caregivers frequently express feelings of marginalization, describing interactions characterized by perceptions of patient infantilization and a lack of respect.

Objective: This study aimed to address 2 key research questions (RQs). For RQ1, we investigated the needs and concerns expressed by participants in online social communities focused on AD/ADRD, specifically on 2 platforms-Reddit's r/Alzheimers and ALZConnected. For RQ2, we examined the prevalence and distribution of social support corresponding to these needs and concerns, and the association between these needs and received support.

Methods: We collected 13,429 posts and comments from the r/Alzheimers subreddit spanning July 2014 to November 2023, and 90,113 posts and comments from ALZConnected between December 2020 (the community's earliest post) and November 2023. We conducted topic modeling using latent Dirichlet allocation (LDA), followed by labeling to identify the major topical themes of discussions. We used transfer learning classifiers to identify the occurrences of emotional support (ES) and informational support (IS) in the comments (or responses) in the discussions. We built regression models to examine how various topical themes are associated with the kinds of support received.

Results: Our analysis revealed a diverse range of topics reflecting community members' varying needs and concerns of individuals affected by AD/ADRD. These themes encapsulate the primary discussions within the online communities: memory care, nursing and caregiving, gratitude and acknowledgment, and legal and financial considerations. Our findings indicated a higher prevalence of IS compared to ES. Regression models revealed that ES primarily occurs in posts relating to nursing and caring, and IS primarily occurs in posts concerning medical conditions and diagnosis, legal and financial, and caregiving at home.

Conclusions: This study reveals that online communities dedicated to AD/ADRD support engage in discussions on a wide range of topics, such as memory care, nursing, caregiving, and legal and financial challenges. The findings shed light on the key pain points and concerns faced by individuals managing AD/ADRD in their households, revealing how they leverage online platforms for guidance and support. These insights underscore the need for targeted institutional and social interventions to address the specific needs of AD/ADRD patients, caregivers, and other family members.

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来源期刊
JMIR Aging
JMIR Aging Social Sciences-Health (social science)
CiteScore
6.50
自引率
4.10%
发文量
71
审稿时长
12 weeks
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