The Last JITAI? The Unreasonable Effectiveness of Large Language Models in Issuing Just-in-Time Adaptive Interventions: Fostering Physical Activity in a Prospective Cardiac Rehabilitation Setting
<|reference_start|>The Last JITAI? The Unreasonable Effectiveness of Large Language Models in Issuing Just-in-Time Adaptive Interventions: Fostering Physical Activity in a Prospective Cardiac Rehabilitation Setting: We investigated the viability of using Large Language Models (LLMs) for triggering and personalizing content for Just-in-Time Adaptive Interventions (JITAIs) in digital health. JITAIs are being explored as a key mechanism for sustainable behavior change, adapting interventions to an individual's current context and needs. However, traditional rule-based and machine learning models for JITAI implementation face scalability and flexibility limitations, such as lack of personalization, difficulty in managing multi-parametric systems, and issues with data sparsity. To investigate JITAI implementation via LLMs, we tested the contemporary overall performance-leading model 'GPT-4' with examples grounded in the use case of fostering heart-healthy physical activity in outpatient cardiac rehabilitation. Three personas and five sets of context information per persona were used as a basis of triggering and personalizing JITAIs. Subsequently, we generated a total of 450 proposed JITAI decisions and message content, divided equally into JITAIs generated by 10 iterations with GPT-4, a baseline provided by 10 laypersons (LayPs), and a gold standard set by 10 healthcare professionals (HCPs). Ratings from 27 LayPs and 11 HCPs indicated that JITAIs generated by GPT-4 were superior to those by HCPs and LayPs over all assessed scales: i.e., appropriateness, engagement, effectiveness, and professionality. This study indicates that LLMs have significant potential for implementing JITAIs as a building block of personalized or "precision" health, offering scalability, effective personalization based on opportunistically sampled information, and good acceptability.<|reference_end|>
@article{haag2024the,
    title={The Last JITAI? The Unreasonable Effectiveness of Large Language Models
  in Issuing Just-in-Time Adaptive Interventions: Fostering Physical Activity
  in a Prospective Cardiac Rehabilitation Setting},
    author={David Haag, Devender Kumar, Sebastian Gruber, Mahdi Sareban, Gunnar
  Treff, Josef Niebauer, Christopher Bull, Jan David Smeddinck},
    journal={arXiv preprint arXiv:2402.08658},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.08658},
    primaryClass={cs.HC cs.AI}
}