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Background <p>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 <i>hidden care</i>, 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.</p> Methods <p>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.</p> Results <p>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.</p> Conclusions <p>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.</p> Clinical trial <p>No clinical trial.</p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月10日

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  • David Walter,
  • Jennifer Pengel,
  • Paul-Ferdinand Steuck,
  • Marco Di Maria,
  • Ralf Knackstedt,
  • Anne Meissner

摘要

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.