JMIR Publications

ABSTRACT

Background:

Population aging has emerged as a global concern, older adults’ ability to access health knowledge and manage their well-being significantly impacts their health outcomes. In the AI era, Generative AI (GAI) videos hold promise for enhancing geriatric health management. However, their potential and the needs of older adults in utilizing GAI videos for health-related purposes deserve a more in-depth investigation.

Objective:

This study aims to explore the application potential and multifaceted needs of older adults in employing GAI videos for health information acquisition and management, while providing actionable recommendations for future aging-friendly GAI video tools.

Methods:

A qualitative approach was adopted. Twenty older adults (aged ≥ 60 years) with basic digital literacy were recruited from communities for the participation in iterative GAI video workshops. Semi-structured interviews were conducted. Thematic analysis, following Braun and Clarke’s six-phase reflexive framework, was employed to identify key themes from interview transcripts.

Results:

Our results have identified a three-layer hierarchical structures of needs when older adults interact with GAI videos. The first layer of needs suggests the direct barriers preventing them to operate GAI tools independently. The second layer depicts the needs of age-friendly design adaptations, which can help older adults to better use GAI features. The final layer highlights the needs for integrating professional medical information resources with GAI tools, so that the GAI videos can be more appropriately used for health management purposes. By triangulating the core needs of older adults, the capabilities of GAI, and their remaining gaps, we have found that the existing gaps limit the extent to which the health needs of older adults are met, and also inversely restrain the acceptance and use of GAI videos by older adults.

Conclusions:

This study explored the potential and gaps of using GAI videos in older adults’ health management. GAI videos are prominent for self-management of health, but our triangular model reveals coexisting opportunities and challenges. While the core needs drive the development directions of GAI video technologies, our study suggests that GAI health videos can be benefited from the improvements in technical capabilities, service innovation, localization and integration of health resources.