People use chatbots gradually for emotional support despite challenges
"I Felt Very Seen, But Still Very Alone": Longitudinal Trajectories of General-Purpose LLM Use for Socioemotional Support
Human-Computer Interaction
Summary
Many people start using chatbots like ChatGPT first for practical tasks but begin to use them for emotional support over time, especially when other help isn’t available. The authors studied 18 adults over months to understand how their use changed and how updates to the chatbots or outside opinions affected their routines. They found that people set rules and boundaries for chatbot use, but these can be disrupted by changes in the AI or life circumstances. The researchers suggest that designers should consider users’ past experiences and support networks when improving chatbots for mental health help.
What this means in practice
- •For mental health app developers: Design chatbot experiences that respect users’ evolving emotional needs and consider how updates affect their established support habits.
- •For customer support platform teams: Incorporate user history depth and socioemotional context into chatbot update testing to avoid disrupting valuable support interactions.
Authors
Meryl Ye, Briana Vecchione, Livia Garofalo, Ranjit Singh
Abstract
People increasingly use general-purpose chatbots such as ChatGPT, Claude, and Gemini for mental health and emotional support. We report a multi-stage longitudinal qualitative study of 18 U.S. adults, conducted from April to December 2025, combining initial interviews, a four-week diary study, focus groups, and exit interviews. We find that socioemotional use often emerged gradually out of practical use and when other forms of support were unavailable. Participants developed routines and boundaries around chatbot use, which were disrupted by model updates, evolving public discourse about AI harms, and changes in personal circumstances. We demonstrate how longitudinal study captures factors beyond the human-AI dyad, and argue that HCI researchers and designers should account for users' histories with their chatbots and broader care ecologies when evaluating AI systems over time and introducing updates that may disrupt established sources of support.