# Seeking Late Night Life Lines: Experiences of Conversational AI Use in Mental Health Crisis

arXiv: https://arxiv.org/abs/2512.23859 · HTML: https://mlsanity.com/paper/2512.23859/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 109 references that are in the map.
- First posted on arXiv 29 Dec 2025.

## Builds on (most cited first, 12 of 12)

- [Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers](https://mlsanity.com/paper/2504.18412/) (2025)
- [Benefits and Harms of Large Language Models in Digital Mental Health](https://mlsanity.com/paper/2311.14693/) (2023)
- [Risks from Language Models for Automated Mental Healthcare: Ethics and Structure for Implementation](https://mlsanity.com/paper/2406.11852/) (2024)
- [From Lived Experience to Insight: Unpacking the Psychological Risks of Using AI Conversational Agents](https://mlsanity.com/paper/2412.07951/) (2024)
- [LLM-based Conversational AI Therapist for Daily Functioning Screening and Psychotherapeutic Intervention via Everyday Smart Devices](https://mlsanity.com/paper/2403.10779/) (2024)
- [Understanding the Impact of Long-Term Memory on Self-Disclosure with Large Language Model-Driven Chatbots for Public Health Intervention](https://mlsanity.com/paper/2402.11353/) (2024)
- [Dehumanizing Machines: Mitigating Anthropomorphic Behaviors in Text Generation Systems](https://mlsanity.com/paper/2502.14019/) (2025)
- [Deep Learning Mental Health Dialogue System](https://mlsanity.com/paper/2301.09412/) (2023)
- [Response Generation for Cognitive Behavioral Therapy with Large Language Models: Comparative Study with Socratic Questioning](https://mlsanity.com/paper/2401.15966/) (2024)
- [Advancing a Consent-Forward Paradigm for Digital Mental Health Data](https://mlsanity.com/paper/2404.14548/) (2024)
- [Moving Towards Epistemic Autonomy: A Paradigm Shift for Centering Participant Knowledge](https://mlsanity.com/paper/2501.14648/) (2025)
- [When Testing AI Tests Us: Safeguarding Mental Health on the Digital Frontlines](https://mlsanity.com/paper/2504.20910/) (2025)

## Built on by (most cited first, 2 of 2)

- [Psychological Influences of Conversational AI: Research and Design Directions for Reducing Harm and Promoting Well-Being](https://mlsanity.com/paper/2607.25057/) (2026)
- [LLMs as Oracles: Reliance on LLMs for Subjective Personal Questions](https://mlsanity.com/paper/2609.14849/) (2026)

## Abstract (arXiv)

Online, people often recount their experiences turning to conversational AI agents (e.g., ChatGPT, Claude, Copilot) for mental health support -- going so far as to replace their therapists. These anecdotes suggest that AI agents have great potential to offer accessible mental health support. However, it's unclear how to meet this potential in extreme mental health crisis use cases. In this work, we explore the first-person experience of turning to a conversational AI agent in a mental health crisis. From a testimonial survey (n = 53) of lived experiences, we find that people use AI agents to fill the in-between spaces of human support; they turn to AI due to lack of access to mental health professionals or fears of burdening others. At the same time, our interviews with mental health experts (n = 16) suggest that human-human connection is an essential positive action when managing a mental health crisis. Using the stages of change model, our results suggest that a responsible AI crisis intervention is one that increases the user's preparedness to take a positive action while de-escalating any intended negative action. We discuss the implications of designing conversational AI agents as bridges towards human-human connection rather than ends in themselves.