Designing a just-in-time adaptive intervention with trigger detection and a generative chatbot: Smoking cessation use case.

ABSTRACT:

Objective

This research aims to address the challenges of just-in-time adaptive interventions (JITAIs) in behaviour change by introducing an architecture that integrates both the tailoring of the message to the user profile and context, and the timing of the intervention by detecting the trigger of the behaviour.

Methods

We designed a system that integrates trigger detection to determine optimal intervention moments and uses prompt engineering on a large language model (LLM) to give personalised support based on the detected trigger, the context, and personal information of the person. As a proof of concept, we applied this intervention to the domain of smoking cessation. We conducted an in-depth semi-structured interview with a domain expert to evaluate the correctness, rel

SUBMITTER: Bosschaerts K 

PROVIDER: S-EPMC12535633 | biostudies-literature | 2025 Jan-Dec

REPOSITORIES: biostudies-literature