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The team

• Dr Yanyan Li Link opens in a new window(Project Lead), Associate Fellow, Institute of Advanced Study

The project

This project explored how university students experiencing loneliness use conversational artificial intelligence (AI) tools for mental health and emotional support. The study aimed to understand why students turn to AI, what kinds of emotional or relational support they feel it provides, and how these experiences compare with support from other people.

The project involved 16 online one-to-one semi-structured interviews, each lasting around 60 minutes. Participants were º£½ÇÉçÇø students from undergraduate, postgraduate taught and postgraduate research programmes across a range of disciplines, including the social sciences, sciences and arts. All participants reported moderate to high levels of loneliness based on the 11-item De Jong Gierveld Loneliness Scale and had experience using conversational AI for mental health-related purposes.

Participants ranged in age from 18 to 34 years old and represented a diverse range of genders, ethnic backgrounds and levels of experience with AI technologies. The interviews explored their reasons for using conversational AI, the benefits and limitations they experienced, and the role these technologies played in supporting their wellbeing.

The intended outcome of the project was to generate new insights into the growing role of AI in students' everyday lives and wellbeing practices. The findings will contribute to discussions about how universities can better support students in an increasingly AI-enabled environment and will inform future research on digital wellbeing, human-AI interaction and mental health support.

Project outcomes

The project was completed successfully and achieved its core objectives.

Sixteen in-depth online interviews were conducted and analysed, generating a substantial qualitative dataset on students' experiences of using conversational AI for mental health and emotional support. Participants described a range of motivations for engaging with AI systems, including seeking emotional validation, non-judgemental listening, practical advice, companionship, and support during periods of loneliness.

The findings demonstrate the growing importance of conversational AI within students' personal wellbeing practices and highlight how students negotiate the relationship between AI-mediated support and human relationships. The project provides timely evidence regarding the opportunities and limitations of AI-enabled support in higher education contexts.

The only deviation from the original proposal concerned participant recruitment. While the proposal anticipated recruiting 20 participants, 16 participants were successfully recruited and interviewed. Recruitment proved more challenging than expected, particularly given the specific eligibility criteria requiring participants to have experience using conversational AI for mental health-related purposes and to report moderate to high levels of loneliness. Nevertheless, the final sample provided a substantial body of in-depth qualitative data, generating rich insights into students' experiences and enabling the project to achieve its research objectives.

The project contributes to º£½ÇÉçÇø's Digital Spotlight priorities by examining how emerging AI technologies are being adopted and experienced by students in everyday life, and by identifying implications for digital wellbeing, student support, and responsible AI use in higher education.

Outputs: A journal article reporting findings from this project is currently being drafted.

Enhancing interdisciplinarity

The project has supported ongoing interdisciplinary collaboration between applied linguistics, education, digital technologies, human-AI interaction, and mental health research.

The project has also helped refine future interdisciplinary research directions concerning AI-supported wellbeing, digital mental health, and human-AI relationships among young adults