Moshirpour, MohammadDuffett-Leger, LindaRanjbar, Payam2025-02-052025-02-052025-01-30Ranjbar, P. (2025). Personalizing reminiscence therapy experiences through the use of generative AI in dementia care (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.https://hdl.handle.net/1880/120698Dementia is a global health challenge affecting millions, significantly diminishing the quality of life for people living with dementia (PLWD) and their caregivers. Reminiscence Therapy (RT) is a non-pharmacological intervention that enhances the well-being of PLWD by prompting them to recall and share past experiences through photographs, and artifacts. Although effective when personalized, scaling RT interventions remains challenging due to their labor and time-intensive design. To address this, we developed the Autobiography Gallery, an AI-powered system that uses Generative AI and Large Language Models to transform narrated memories into personalized photo albums. This thesis evaluates the effectiveness of AI-generated images in RT through feedback from dementia care stakeholders, identifying refinement needs, and proposing features like user-driven customization. We also provide design recommendations for scalable, AI-based RT interventions. Our findings highlight the potential of AI to enhance personalization and scalability in RT, advancing the development of accessible, user-centered solutions for dementia care.enUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Human-Computer InteractionHCIDementia CareDementia Care InterventionsReminiscence TherapyLarge Language ModelsGenerative AIEmpirical StudyEducation--Technologymaster thesis