Scholarlink

Background <p>Generative AI has reshaped healthcare, yet multimorbid older adults face digital divide barriers limiting its safe application. Existing qualitative evidence on their AI-assisted complex health decision-making remains scarce, lacking integrated theoretical interpretation.</p> Objectives <p>Guided by an integrated framework combining the Technology Acceptance Model, Senior Technology Acceptance Model and Burden of Treatment Theory, this study explored older adults’ perceived usefulness and ease of generative AI for health decisions, mobilizable personal-social resources, and how technology perceptions shape dynamic usage behaviors and decision quality.</p> Methods <p>From September to December 2025, 16 multimorbid seniors were recruited via purposive maximum variation sampling from an urban community health center in eastern China. Face-to-face semi-structured interviews were conducted, with reflexive thematic analysis following COREQ guidelines.</p> Results <p>Based on interviews with 16 participants, four themes were identified: (1) Perceived usefulness, which was mainly reflected in four dimensions: initial situational triggers prompting AI consultation, convenient access to information, integrated support for multimorbidity management, and enhanced decision-making confidence. (2) Perceived ease of use: Participants’ perceptions of the ease of use of generative AI showed significant individual differences and context dependence. (3) Resource mobilization: Successful use of generative AI rarely depended on independent individual effort but required the mobilization of diverse personal resources and social support. (4) Behavioral intention and actual use: The generative AI usage behavior of older adults with multimorbidity exhibited dynamic evolutionary characteristics; its trajectory was not linear acceptance and continuous use, but a complex process involving attempts, interruptions, resumption, or permanent abandonment.</p> Conclusions <p>This study reveals that AI use among older adults with multimorbidity is not merely a technology adoption behavior, but an adaptive strategic choice made under the pressure of managing multiple chronic conditions. Only by fully considering the special needs of patients with multimorbidity in technology design and service provision can the safe and effective application of generative AI in elderly chronic disease management be truly realized.</p> Trial registration number <p>Not applicable. This study did not involve clinical trials.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Dialoguing with algorithms: experiences of generative AI use in navigating complex health decisions among older adults with multimorbidity: a qualitative study

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月23日

查看全文
  • Qin Lin,
  • Mengxue Fu,
  • Pei Chen,
  • Jiaorong Zhao,
  • Yanhua Liu,
  • Yanping Niu,
  • Minmin Jiang,
  • Jijun Wu

摘要

Background

Generative AI has reshaped healthcare, yet multimorbid older adults face digital divide barriers limiting its safe application. Existing qualitative evidence on their AI-assisted complex health decision-making remains scarce, lacking integrated theoretical interpretation.

Objectives

Guided by an integrated framework combining the Technology Acceptance Model, Senior Technology Acceptance Model and Burden of Treatment Theory, this study explored older adults’ perceived usefulness and ease of generative AI for health decisions, mobilizable personal-social resources, and how technology perceptions shape dynamic usage behaviors and decision quality.

Methods

From September to December 2025, 16 multimorbid seniors were recruited via purposive maximum variation sampling from an urban community health center in eastern China. Face-to-face semi-structured interviews were conducted, with reflexive thematic analysis following COREQ guidelines.

Results

Based on interviews with 16 participants, four themes were identified: (1) Perceived usefulness, which was mainly reflected in four dimensions: initial situational triggers prompting AI consultation, convenient access to information, integrated support for multimorbidity management, and enhanced decision-making confidence. (2) Perceived ease of use: Participants’ perceptions of the ease of use of generative AI showed significant individual differences and context dependence. (3) Resource mobilization: Successful use of generative AI rarely depended on independent individual effort but required the mobilization of diverse personal resources and social support. (4) Behavioral intention and actual use: The generative AI usage behavior of older adults with multimorbidity exhibited dynamic evolutionary characteristics; its trajectory was not linear acceptance and continuous use, but a complex process involving attempts, interruptions, resumption, or permanent abandonment.

Conclusions

This study reveals that AI use among older adults with multimorbidity is not merely a technology adoption behavior, but an adaptive strategic choice made under the pressure of managing multiple chronic conditions. Only by fully considering the special needs of patients with multimorbidity in technology design and service provision can the safe and effective application of generative AI in elderly chronic disease management be truly realized.

Trial registration number

Not applicable. This study did not involve clinical trials.