Message Framing, Source, and Personality in Older Adults' Perceptions and Behavioral Intentions with AI-driven Healthcare Treatment Recommendations

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Authors

Wood, Kara A.

Issue Date

2025

Type

Dissertation

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en_US

Keywords

Artificial Intelligence in Healthcare , Message Framing , Older Adults , Personality Traits (Big Five) , Technology Adoption , Trust and Adherence

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Abstract

As artificial intelligence (AI) continues to shape healthcare delivery, older adults represent a group with much to gain—but also much to lose—depending on how these technologies are introduced and implemented. Adoption remains uneven, often hindered by concerns about trust, privacy, and a lack of familiarity with AI-based technology. This study examined the impact of message framing (gain vs. loss), message source (AI, human provider, or a combination of the two), and personality traits on older adults’ trust in AI-driven healthcare recommendations and their predicted adherence to treatment plans. Grounded in prospect theory and personality research, a 2x3 experimental design tested how different message presentations interacted with individual differences to shape attitudes toward AI-based healthcare. The study also examined how healthcare and technological experience shaped perceptions of AI-generated recommendations. Results from the quantitative and qualitative analyses show that the source of the recommendation consistently shaped how comfortable and trusting respondents felt, with many expressing a preference for having a human involved in the process. Conscientiousness, in particular, played a role in how likely respondents said they would follow the treatment advice depending on who provided it. Comments in the open-ended responses pointed to a common trade-off: while AI was often seen as efficient and practical, many felt it lacked the personal touch they value in healthcare. `By integrating message features and individual traits, this study offers insight into how AI-based systems can be designed and communicated in ways that are more trustworthy, effective, and inclusive for older adults.

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