The Last JITAI? Exploring Large Language Models for Issuing Just-in-Time Adaptive Interventions: Fostering Physical Activity in a Prospective Cardiac Rehabilitation Setting

要旨

We evaluated the viability of using Large Language Models (LLMs) to trigger and personalize content in Just-in-Time Adaptive Interventions (JITAIs) in digital health. As an interaction pattern representative of context-aware computing, JITAIs are being explored for their potential to support sustainable behavior change, adapting interventions to an individual’s current context and needs. Challenging traditional JITAI implementation models, which face severe scalability and flexibility limitations, we tested GPT-4 for suggesting JITAIs in the use case of heart-healthy activity in cardiac rehabilitation. Using three personas representing patients affected by CVD with varying severeness and five context sets per persona, we generated 450 JITAI decisions and messages. These were systematically evaluated against those created by 10 laypersons (LayPs) and 10 healthcare professionals (HCPs). GPT-4-generated JITAIs surpassed human-generated intervention suggestions, outperforming both LayPs and HCPs across all metrics (i.e., appropriateness, engagement, effectiveness, and professionalism). These results highlight the potential of LLMs to enhance JITAI implementations in personalized health interventions, demonstrating how generative AI could revolutionize context-aware computing.

著者
David Haag
Ludwig Boltzmann Institute for Digital Health and Prevention, Salzburg, Austria
Devender Kumar
Ludwig Boltzmann Institute for Digital Health and Prevention, Salzburg , Austria
Sebastian Gruber
Johannes Kepler University Linz, Linz, Austria
Dominik P.. Hofer
Ludwig Boltzmann Institute for Digital Health and Prevention, Salzburg, Austria
Mahdi Sareban
University Institute of Sports Medicine, Prevention and Rehabilitation, Salzburg, Austria
Gunnar Treff
Ludwig Boltzmann Institute for Digital Health and Prevention, Salzburg, Austria
Josef Niebauer
Ludwig Boltzmann Institute for Digital Health and Prevention, Salzburg, Austria
Christopher N. Bull
Newcastle University, Newcastle, Tyne and Wear, United Kingdom
Albrecht Schmidt
LMU Munich, Munich, Germany
Jan David. Smeddinck
Ludwig Boltzmann Institute for Digital Health and Prevention, Salzburg, Austria
DOI

10.1145/3706598.3713307

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713307

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: LLM for Health

Annex Hall F206
6 件の発表
2025-04-30 18:00:00
2025-04-30 19:30:00
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