Personalized Coaching for Lifestyle Behavior Change through Large Language Models: A Qualitative Study
Files
Date
2025-01-07
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Narrator
Transcriber
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
3375
Ending Page
Alternative Title
Abstract
This paper investigates the impact of large language model (LLM)-based coaching interventions on enhancing physical activity and nutritional habits, following motivational interviewing guidelines. By exploring user perceptions through qualitative research involving eight interviews, five key themes emerged: the tension between the need for authenticity and reservations about AI humanization, the desire for personalized coaching and autonomy, the necessity of simplifying daily tasks, the aspiration for self-development, and the need for perceived privacy and trust. The findings reveal that perceptions of LLM-based coaching are multifaceted and cannot be easily classified as purely beneficial or concerning; they vary based on the specific implementation. This complexity indicates that certain aspects can simultaneously present both benefits and risks. The paper discusses theoretical implications and offers practical recommendations to enhance the advantages and mitigate the risks associated with LLM-based coaching interventions.
Description
Keywords
Health Behavior Change Support Systems, artificial intelligence, behavioral change, digital health, large language models
Citation
Extent
10
Format
Geographic Location
Time Period
Related To
Proceedings of the 58th Hawaii International Conference on System Sciences
Related To (URI)
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Collections
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.