Exploring the Role of Large Language Models for Increasing Health Promotion and Psychological Well-being

This project explores the potential of Large Language Models (LLMs) in advancing digital health interventions for mental health and well-being, with a focus on non-clinical and self-directed contexts. It aims to address the underexplored intersection of LLMs and health promotion by investigating two critical aspects: operationalizing LLMs through emerging LLMOps practices and understanding cognitive biases in LLM-based reasoning. With a strong emphasis on technological innovation, the project will conduct a comprehensive review of existing LLM-based mental health apps, create datasets for simulated and real user data, evaluate personalized recommendation systems using interpretable machine learning, and examine the impact of cognitive biases on user well-being. Additionally, it will design and deploy a robust IT architecture for personalized health interventions. This interdisciplinary effort seeks to bridge gaps in research while fostering autonomy and psychological well-being through cutting-edge AI technologies.