To propose a framework for integrating generative AI in mental health care for older adults that emphasizes meaning-centered approaches addressing existential concerns.
Key Findings:
Current AI applications in mental health are primarily symptom-centric, neglecting existential concerns of older adults.
Generative AI can serve as an interactional infrastructure for meaning-centered care, enhancing rather than replacing human interactions.
The framework emphasizes the importance of dignity, continuity of self, relational quality, and the need for human oversight in mental health care for older adults.
Interpretation:
Generative AI should be viewed as a supportive tool that enhances human interactions while addressing the complex mental health needs of older adults by focusing on their existential and relational dimensions.
Limitations:
The framework does not assume current AI technologies are capable of conducting psychotherapy independently.
There are concerns regarding trust, dependency, and the quality of human-technology interactions, particularly in the context of older adults.
Conclusion:
Generative AI may enhance public mental health for older adults when used as a human-supervised, culturally responsive tool that supports meaning-centered care.
