Al Bayrakdar Amani, Dragone Mauro, Wojcik Gosha, McConnell Alistair, King Maria, Paterson Ruth
School of Health and Social Care, Edinburgh Napier University, Edinburgh, UK.
School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK.
J Diabetes Sci Technol. 2025 Jul 20:19322968251356298. doi: 10.1177/19322968251356298.
Diabetes prevalence is rising and projected to affect 783 million globally by 2045. Effective diabetes self-management relies on diabetes knowledge, lifestyle modifications, and health care support; yet global health care workforce shortages hinder the provision of adequate care. Socially assistive technologies, such as robots or artificial intelligence, are proposed as potential solutions to meet rising demands.
To map the current literature on Socially Assistive Robots for diabetes care, identifying robotic types, barriers and enablers to use, and impact on health-related outcomes. A scoping review using Arskey and O'Malley's Framework was conducted, screening studies published between 2013 and 2025 across key databases and extracting data using COVIDENCE.
Twenty-two studies met the inclusion criteria, mostly focused on children with type 1 diabetes. Studies were largely conducted in Europe, cross-sectional, and with small sample sizes. Socially assistive robots demonstrated high acceptability, especially among younger children, positively affecting knowledge acquisition, self-management, and self-efficacy. Personalized interactions, gamified features, and emotional responsiveness were key enablers of engagement. However, engagement waned over time, particularly when participants' practical and emotional expectations were unmet. Barriers included usability challenges, privacy concerns, and lack of customization. Economic and sustainability evaluations were absent.
Despite growing evidence for robotics in diabetes care, research remains methodologically limited and focused primarily on younger populations. Future studies should include adults, employ multi-faceted robotics designs, and be adequately powered to assess acceptability and efficacy across diverse groups, facilitating broader application in diabetes care.
糖尿病患病率正在上升,预计到2045年全球将有7.83亿人受其影响。有效的糖尿病自我管理依赖于糖尿病知识、生活方式的改变以及医疗保健支持;然而,全球医疗保健劳动力短缺阻碍了提供充分的护理。社会辅助技术,如机器人或人工智能,被提议作为满足不断增长需求的潜在解决方案。
梳理当前关于用于糖尿病护理的社会辅助机器人的文献,确定机器人类型、使用的障碍和促进因素,以及对健康相关结果的影响。使用阿斯基和奥马利的框架进行了一项范围综述,筛选了2013年至2025年期间在主要数据库上发表的研究,并使用COVIDENCE提取数据。
22项研究符合纳入标准,大多聚焦于1型糖尿病儿童。研究主要在欧洲进行,为横断面研究,样本量较小。社会辅助机器人显示出较高的可接受性,尤其是在年幼儿童中,对知识获取、自我管理和自我效能产生了积极影响。个性化互动、游戏化功能和情感反应能力是参与的关键促进因素。然而,随着时间的推移,参与度有所下降,尤其是当参与者的实际和情感期望未得到满足时。障碍包括可用性挑战、隐私问题和缺乏定制。缺乏经济和可持续性评估。
尽管有越来越多的证据表明机器人技术可用于糖尿病护理,但研究在方法上仍存在局限性,且主要集中在较年轻人群体。未来的研究应纳入成年人,采用多方面的机器人设计,并有足够的样本量来评估不同群体的可接受性和疗效,以促进在糖尿病护理中的更广泛应用。