Caregiver's Evaluation of LLM-Generated Treatment Goals for Patients with Severe Mental Illnesses
Publication date
2024-06-26
Editors
Karim, Enamul
Nikanfar, Sama
Pavel, Hamza Reza
Advisors
Supervisors
Document Type
Part of book
Metadata
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License
cc_by
Abstract
The potential of LLMs to generate context-specific content for psychiatric patients could possibly be used to support treatment. Patients diagnosed with Severe Mental Illnesses face a significant challenge in the realm of goal setting. Caregivers work closely with patients with SMI to establish treatment goals. However, most goals are often immeasurable, hindering their integration into mHealth. This is a missed opportunity since mHealth has the potential to aid healthcare professionals in tracking a patient's progress and help motivate patients to work on their goals using behavior change concepts like personalization and gamification. Recognizing the time-consuming nature of creating measurable goals. This study validates an LLM-powered goal system aiming to provide a time-efficient way of goal creation for patients with SMI, on the quality of the goals it generates in collaboration with caregivers.
Keywords
Behavior change, Gamification, Goal generation, LLM, mHealth, SMI, Human-Computer Interaction, Computer Networks and Communications, Computer Vision and Pattern Recognition, Software, SDG 3 - Good Health and Well-being
Citation
James, L J, Genga, L, Montagne, B, Hagenaars, M & Van Gorp, P 2024, Caregiver's Evaluation of LLM-Generated Treatment Goals for Patients with Severe Mental Illnesses. in E Karim, S Nikanfar & H R Pavel (eds), Proceedings of the 17th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2024. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 187-190, 17th ACM International Conference on PErvasive Technologies Related to Assistive Environments, PETRA 2024, Crete, Greece, 26/06/24. https://doi.org/10.1145/3652037.3663955, conference