Hassan Samah, Ibrahim Sarah, Bielecki Joanna, Stanimirovic Aleksandra, Mathew Suja, Hooey Ryan, Bowen James Marshall, Rac Valeria E
Program for Health System and Technology Evaluation, University Health Network, Toronto, Ontario, Canada
Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
BMJ Open. 2025 Jul 15;15(7):e100512. doi: 10.1136/bmjopen-2025-100512.
Marginalised populations-such as racialised groups, low-income individuals, newcomers and those in rural areas-disproportionately experience severe diabetes-related complications, including diabetic foot ulcers, retinopathy and amputations, due to systemic inequities and limited access to care. Although community-based programmes address cultural and accessibility barriers, their isolation from mainstream healthcare systems leads to fragmented care and missed opportunities for early intervention.Artificial intelligence (AI)-powered technologies can enhance accessibility and personalisation, particularly for underserved populations. However, integrating AI into community settings remains underexplored, with socioethical concerns around inclusion, diversity, equity and accessibility requiring urgent attention.This realist review aims to examine how, why and under what circumstances AI applications can be effectively integrated into community-based diabetic care for marginalised populations. The review will develop a programme theory to guide ethical, inclusive and effective AI implementation to ensure AI-driven innovations address health disparities and promote culturally sensitive, accessible care for all.
Using the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) extension for Reviews guidelines, this realist review will systematically search MEDLINE, Embase, CINAHL, Cochrane library, Google Scholar and Scopus, alongside grey literature. A two-stage screening process will identify eligible studies, and data extraction will use a developed tool. Synthesis will employ realist logic, analysing relationships between contexts (eg, organisational capacity), mechanisms (eg, AI functionalities) and outcomes (eg, reduced disparities).
Ethics approval is not required for conducting this realist review. Ethics approval will be obtained from the University of Toronto; however, following the completion of the realist review for patients and community members' engagement to support knowledge mobilisation and dissemination to ensure practical application and reciprocity.
This protocol was registered at PROSPERO (CRD42025636284).
由于系统性不平等和获得医疗服务的机会有限,边缘化人群,如种族化群体、低收入个体、新移民和农村地区居民,患糖尿病相关严重并发症(包括糖尿病足溃疡、视网膜病变和截肢)的比例过高。虽然基于社区的项目解决了文化和可及性障碍,但它们与主流医疗系统的隔离导致了医疗服务的碎片化以及早期干预机会的错失。人工智能驱动的技术可以提高可及性和个性化程度,特别是对于服务不足的人群。然而,将人工智能整合到社区环境中仍未得到充分探索,围绕包容性、多样性、公平性和可及性的社会伦理问题亟待关注。本实证性综述旨在研究人工智能应用如何、为何以及在何种情况下能够有效地整合到针对边缘化人群的社区糖尿病护理中。该综述将制定一个项目理论,以指导符合伦理、具有包容性且有效的人工智能实施,确保人工智能驱动的创新解决健康差距问题,并促进对所有人具有文化敏感性且可及的医疗服务。
本实证性综述将使用系统评价和Meta分析的首选报告项目(PRISMA)扩展版的综述指南,系统地检索MEDLINE、Embase、CINAHL、Cochrane图书馆、谷歌学术和Scopus以及灰色文献。两阶段筛选过程将确定符合条件的研究,数据提取将使用已开发的工具。综合分析将采用实证性逻辑,分析背景(如组织能力)、机制(如人工智能功能)和结果(如差距缩小)之间的关系。
进行本实证性综述无需伦理批准。将从多伦多大学获得伦理批准;然而,在完成实证性综述后,将征求患者和社区成员的参与意见,以支持知识的传播和推广,确保实际应用和互利互惠。
PROSPERO注册号:本方案已在PROSPERO注册(CRD42025636284)。