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探究弱势群体中英语水平有限的老年人在视频会诊使用方面的交叉性及障碍:定性叙事访谈研究

Examining Intersectionality and Barriers to the Uptake of Video Consultations Among Older Adults From Disadvantaged Backgrounds With Limited English Proficiency: Qualitative Narrative Interview Study.

作者信息

Husain Laiba, Greenhalgh Trisha

机构信息

Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.

出版信息

J Med Internet Res. 2025 Jan 6;27:e65690. doi: 10.2196/65690.

Abstract

BACKGROUND

The rapid shift to video consultation services during the COVID-19 pandemic has raised concerns about exacerbating existing health inequities, particularly for disadvantaged populations. Intersectionality theory provides a valuable framework for understanding how multiple dimensions of disadvantage interact to shape health experiences and outcomes.

OBJECTIVE

This study aims to explore how multiple dimensions of disadvantage-specifically older age, limited English proficiency, and low socioeconomic status-intersect to shape experiences with digital health services, focusing on video consultations.

METHODS

Following familiarization visits and interviews with service providers, 17 older people with multiple markers of disadvantage (older age, low socioeconomic status, and limited English proficiency) were recruited in the Redbridge borough of London. Data collection included narrative interviews and ethnographic observations during home visits. Field notes captured participants' living conditions, family dynamics, and technological arrangements. Guided by intersectionality theory and digital capital concepts, interviews explored participants' experiences accessing health care remotely. Intersectional narrative analysis was used to identify key themes and examine how different forms of disadvantage interact. We developed theoretically informed narrative portraits and user personas to synthesize findings.

RESULTS

Analysis revealed that the digitalization of health care can exacerbate existing inequities, erode trust, compound oppression, and reduce patient agency for multiply disadvantaged patient populations. Examining intersectionality illuminated how age, language proficiency, and socioeconomic status interact to create unique barriers and experiences. Key themes included the following: weakened presence in digital interactions, erosion of therapeutic relationships, shift from relational to distributed continuity, increased complexity leading to disorientation, engagement shaped by previous experiences of discrimination, and reduced patient agency.

CONCLUSIONS

This study provides critical insights into how the digitalization of health care can deepen disparities for older patients with low income and limited English proficiency. By applying intersectionality theory to digital health disparities, our findings underscore the need for multifaceted approaches to digital health equity that address the complex interplay of disadvantage. Recommendations include co-designing inclusive digital services, strengthening relational continuity, and developing targeted support to preserve agency and trust for marginalized groups in an increasingly digital health care landscape.

摘要

背景

在新冠疫情期间迅速转向视频咨询服务引发了人们对加剧现有健康不平等现象的担忧,尤其是对弱势群体而言。交叉性理论为理解多种不利因素如何相互作用以塑造健康体验和结果提供了一个有价值的框架。

目的

本研究旨在探讨多种不利因素——具体而言,老年、英语水平有限和社会经济地位低下——如何相互交叉以塑造数字健康服务体验,重点关注视频咨询。

方法

在对服务提供商进行走访和访谈之后,在伦敦的雷德布里奇区招募了17名具有多种不利因素特征(老年、社会经济地位低下和英语水平有限)的老年人。数据收集包括家访期间的叙事访谈和人种志观察。实地记录捕捉了参与者的生活条件、家庭动态和技术安排。在交叉性理论和数字资本概念的指导下,访谈探讨了参与者远程获取医疗保健的经历。采用交叉性叙事分析来确定关键主题,并研究不同形式的不利因素如何相互作用。我们开发了基于理论的叙事画像和用户角色来综合研究结果。

结果

分析表明,医疗保健数字化会加剧现有的不平等现象,侵蚀信任,加剧压迫,并削弱多重弱势患者群体的患者自主性。审视交叉性揭示了年龄、语言能力和社会经济地位如何相互作用,造成独特的障碍和体验。关键主题包括:在数字互动中存在感减弱、治疗关系受到侵蚀、从关系性连续性转向分布式连续性、复杂性增加导致迷失方向、受以往歧视经历影响的参与度,以及患者自主性降低。

结论

本研究为医疗保健数字化如何加深低收入且英语水平有限的老年患者的差距提供了重要见解。通过将交叉性理论应用于数字健康差距问题,我们的研究结果强调了采取多方面方法实现数字健康公平的必要性,这种方法要解决不利因素的复杂相互作用。建议包括共同设计包容性数字服务、加强关系性连续性,以及在日益数字化的医疗保健环境中制定有针对性的支持措施,以维护边缘化群体的自主性和信任。

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Achieving Digital Health Equity by Personalizing the Patient Experience.通过个性化患者体验实现数字健康公平。
Telemed Rep. 2023 Jun 27;4(1):166-173. doi: 10.1089/tmr.2023.0018. eCollection 2023.

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