Developing well-being in young people using generative artificial intelligence (GenAI): a systematic literature review

Purpose As young people experience depression and anxiety, the use of generative artificial intelligence (GenAI) applications have gained popularity as tools in improving well-being. This study aims to systematically review existing literature on GenAI use by young people to improve well-being outcomes, addressing a critical gap in understanding their effectiveness and consumption patterns. Design/methodology/approach Following a preferred reporting items for systematic reviews and meta-analyses methodology, a thematic analysis was conducted on 69 empirical studies. Findings The findings identified three types of GenAI tools designed for young people including chatbots, virtual assistants and robots. These tools address a variety of well-being outcomes such as psychological well-being, emotional regulation, social anxiety, generalised anxiety disorder, depression, autism spectrum disorder, weight management and diabetes and behavioural disorders. Originality/value The findings indicated a consensus on evidence-based approaches in achieving well-being outcomes and revealed limited literature on the long-term effects and consumption pattern on young people with AI use. This offers direction for future research and policy initiatives, informing ways to develop practices to improve well-being in young people.