Reframing Life Experiences: Emotional Reappraisal Through AI-Generated Memory Videos for Older Adults

Abstract

Reframing negative past experiences is crucial for the psychological well-being of older adults. While Generative AI has shown potential in automating reminiscence material creation, existing systems often overlook the delicate process of handling negative emotions. This study proposes a novel photo-based reminiscence system designed to support "emotional reappraisal" by creating psychological distance. Using Generative AI, the system transforms personal dialogues into "memory videos" featuring third-person narratives and cinematic effects. We conducted an exploratory pilot study with four older adults to compare the emotional impact of these AI-generated videos against a static photo viewing condition. Preliminary results indicated that while static photos tended to sustain high-intensity negative emotions (e.g., anger, sadness), the AI-generated videos significantly reduced negative affect. Notably, three out of four participants reframed their primary emotion from negative states to "Joy" after viewing the video. These findings suggest that the objective narrative structure and visual presentation provided by the system can facilitate emotional reframing, helping older adults integrate painful experiences into a positive life story. This research highlights the potential of Generative AI in fostering ego integrity and resilience in the aging population.

Keywords: Emotional Reappraisal, Reminiscence, Generative AI, Autobiographical Memory, Older Adults, Human–AI Interaction

DOI: 10.54941/ahfe1007574