Intelligent support for digital wellbeing: A design framework through a systematic literature review

Recent advancements in AI, particularly Generative AI (GenAI) and Large Language Models (LLMs), have facilitated the integration of AI techniques into digital wellbeing applications, i.e., digital tools that aim at helping people’s wellbeing as a sum of mental and emotional wellness. These AI-powered systems hold the potential to foster healthier habits by collecting and analyzing user behavioral data to provide personalized and dynamic solutions tailored to each user’s needs and lifestyle, therefore improving the efficacy with respect to traditional non-AI interventions. Yet, their development presents significant challenges, including ethical concerns, privacy risks, and the potential for over-reliance on automated interventions. In this paper, we conduct a systematic literature review to examine the key characteristics, challenges, and opportunities in the existing research about AI-powered digital wellbeing tools. Based on our findings, we propose a design framework that outlines 6 critical dimensions and 23 sub-dimensions, spacing from user data and privacy to intervention strategies and personalization, offering practical guidance for researchers and practitioners developing AI-powered digital wellbeing applications. The framework emphasizes the importance of developing tailored and adaptive user-centered interventions adhering to scientific principles, psychological models and responsible data collection. We discuss the applicability and utility of our framework in evaluating and guiding the integration of AI in digital wellbeing applications. • Carry out a systematic literature review about AI-powered systems that support people’s digital wellbeing, considering their psychological and emotional aspects. • Elaborate a design framework based on the literature review results to provide researchers, designers and other practitioners with a tool that may guide them in the design of new technology and related studies. • Discuss the obtained results and the proposed framework with critical insights and examples, exploring the potentiality, key challenges and possibilities. • Provide an example of the application of the framework to a specific case study, highlighting how the reflection can be deeper and more accurate by considering each dimension and subdimension.