设计一个人工智能伴侣来支持非正式护理人员的角色转换:来自设计科学方法的见解。

IF 3.9 2区 医学 Q1 NURSING
David Walter, Jennifer Pengel, Paul-Ferdinand Steuck, Marco Di Maria, Ralf Knackstedt, Anne Meissner
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引用次数: 0

摘要

背景:随着人口老龄化,非正式照护者在长期照护中发挥着越来越重要的作用,在欧洲,80%的照护由家庭成员提供。然而,许多人并没有立即意识到自己是照顾者,尤其是在早期阶段。这种意识的缺乏会增加身体和精神压力,并延误获得支持服务的时间。隐性护理现象,即在没有正式承认其作用的情况下提供实质性护理,进一步加剧了这些问题。为了解决这个问题,我们开发了一个人工智能驱动的聊天机器人,旨在帮助非正式护理人员认识到他们的角色,反思他们的情况,并确定相关的支持选项。本文探讨了如何设计基于人工智能的聊天机器人来支持非正式护理人员反思和重新评估他们的护理角色。方法:采用设计科学研究方法,我们通过集中的半结构化访谈和与非正式护理人员的思考会话来评估聊天机器人的设计,以评估其效用、完整性和通过遗忘视角支持角色转换的潜力。数据通过Braun和Clarke的主题分析进行分析。结果:聊天机器人有可能支持护理人员认识到他们的角色并反思他们的经历,参与者报告说,反思提示和有用的个性化支持资源的建议引发了自我意识的增强。确定了在过渡性非正式护理环境中基于人工智能的聊天机器人开发的七个初始设计原则。这些原则强调个性化的评估、透明的信息、角色意识支持、可及性和持续的陪伴。结论:本研究证明了人工智能驱动的聊天机器人在关键角色转换期间支持非正式护理人员的潜力。未来的研究应该以这些见解为基础,设计情境感知的解决方案,负责任地将人工智能嵌入到护理现实中。临床试验:无临床试验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Designing an AI companion to support informal caregivers in role transition: insights from a design science approach.

Designing an AI companion to support informal caregivers in role transition: insights from a design science approach.

Designing an AI companion to support informal caregivers in role transition: insights from a design science approach.

Designing an AI companion to support informal caregivers in role transition: insights from a design science approach.

Background: As populations age, informal caregivers play an increasingly vital role in long-term care, with 80% of care provided by family members in Europe. However, many individuals do not immediately recognize themselves as caregivers, especially in the early stages. This lack of awareness can increase physical and emotional stress and delay access to support services. The phenomenon of hidden care, where substantial care is provided without formally acknowledging the role, further exacerbates these issues. To address this, we developed an AI-driven chatbot designed to support informal caregivers recognize their role, reflect on their situation, and identify relevant support options. This paper explores how an AI-based chatbot can be designed to support informal caregivers in reflecting on and re-evaluating their caregiving roles.

Methods: Following a design science research approach, we evaluate the chatbot design via focused semistructured interviews and think-aloud sessions with informal caregivers to assess its utility, completeness and potential for supporting role transitions through the lens of unlearning. The data were analyzed via Braun and Clarke's thematic analysis.

Results: The chatbot has the potential to support caregivers in recognizing their role and reflecting on their experiences, with participants reporting increased self-awareness triggered by reflective prompts and recommendations of useful personalized support resources. Seven initial design principles for AI-based chatbot development in transitional informal care contexts were identified. These principles emphasize personalized assessment, transparent information, role awareness support, accessibility, and continuous companionship.

Conclusions: This study demonstrates the potential of AI-driven chatbots to support informal caregivers during critical role transitions. Future research should build on these insights to design context-aware solutions that responsibly embed AI into caregiving realities.

Clinical trial: No clinical trial.

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来源期刊
BMC Nursing
BMC Nursing Nursing-General Nursing
CiteScore
3.90
自引率
6.20%
发文量
317
审稿时长
30 weeks
期刊介绍: BMC Nursing is an open access, peer-reviewed journal that considers articles on all aspects of nursing research, training, education and practice.
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