mlsanityData to 14 Oct 2026

The Typing Cure: Experiences with Large Language Model Chatbots for Mental Health Support

arXiv 2401.14362 ↗First posted 25 Jan 2024cs.HC cs.AI cs.CYcited by 24

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Abstract (arXiv)

People experiencing severe distress increasingly use Large Language Model (LLM) chatbots as mental health support tools. Discussions on social media have described how engagements were lifesaving for some, but evidence suggests that general-purpose LLM chatbots also have notable risks that could endanger the welfare of users if not designed responsibly. In this study, we investigate the lived experiences of people who have used LLM chatbots for mental health support. We build on interviews with 21 individuals from globally diverse backgrounds to analyze how users create unique support roles for their chatbots, fill in gaps in everyday care, and navigate associated cultural limitations when seeking support from chatbots. We ground our analysis in psychotherapy literature around effective support, and introduce the concept of therapeutic alignment, or aligning AI with therapeutic values for mental health contexts. Our study offers recommendations for how designers can approach the ethical and effective use of LLM chatbots and other AI mental health support tools in mental health care.

Key facts. Cited by 24 papers in the map (data through 14 Oct 2026). Builds on 17 of its 108 references that are in the map. First posted on arXiv 25 Jan 2024.

Builds on

17 of 108 references.

References · 17

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2021Ethical and social risks of harm from Language Modelscited by 966
  3. 2023Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedbackcited by 759
  4. 2020It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learnerscited by 669
  5. 2020Artificial Intelligence, Values and Alignmentcited by 448
  6. 2023Towards Measuring the Representation of Subjective Global Opinions in Language Modelscited by 437
  7. 2023MEGA: Multilingual Evaluation of Generative AIcited by 293
  8. 2023On the Risk of Misinformation Pollution with Large Language Modelscited by 128
  9. 2021Detoxifying Language Models Risks Marginalizing Minority Voicescited by 107
  10. 2018From Eliza to XiaoIce: Challenges and Opportunities with Social Chatbotscited by 85
  11. 2024A Computational Framework for Behavioral Assessment of LLM Therapistscited by 62
  12. 2023Facilitating Self-Guided Mental Health Interventions Through Human-Language Model Interaction: A Case Study of Cognitive Restructuringcited by 53
5 more
  1. 2023Benefits and Harms of Large Language Models in Digital Mental Healthcited by 40
  2. 2022Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imagingcited by 32
  3. 2023ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Eventscited by 31
  4. 2023Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision Makingcited by 18
  5. 2023Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classificationscited by 15

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 5; 2025: 11; 2026: 8.

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  1. 2024Survey of Cultural Awareness in Language Models: Text and Beyondcited by 103
  2. 2024Towards Trustworthy AI: A Review of Ethical and Robust Large Language Modelscited by 22
  3. 2025CounselBench: A Large-Scale Expert Evaluation and Adversarial Benchmarking of Large Language Models in Mental Health Question Answeringcited by 21
  4. 2025Exploring User Security and Privacy Attitudes and Concerns Toward the Use of General-Purpose LLM Chatbots for Mental Healthcited by 13
  5. 2025Linguistic Comparison of AI- and Human-Written Responses to Online Mental Health Queriescited by 6
  6. 2024"I Like Sunnie More Than I Expected!": Exploring User Expectation and Perception of an Anthropomorphic LLM-based Conversational Agent for Well-Being Supportcited by 5
  7. 2026Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interactioncited by 3
  8. 2025Beyond Chat: a Framework for LLMs as Human-Centered Support Systemscited by 2
  9. 2024An Empirical Design Justice Approach to Identifying Ethical Considerations in the Intersection of Large Language Models and Social Roboticscited by 1
  10. 2025MoPHES:Leveraging on-device LLMs as Agent for Mobile Psychological Health Evaluation and Supportcited by 1
  11. 2026A Conditional Companion: Lived Experiences of People with Mental Health Disorders Using LLMscited by 1
  12. 2024Kuaiji: the First Chinese Accounting Large Language Modelcited by 0
12 more
  1. 2025Mind2: Mind-to-Mind Emotional Support System with Bidirectional Cognitive Discourse Analysiscited by 0
  2. 2025"Is This Really a Human Peer Supporter?": Misalignments Between Peer Supporters and Experts in LLM-Supported Interactionscited by 0
  3. 2025A Mathematical Theory of Discursive Networkscited by 0
  4. 2025Context-Emotion Aware Therapeutic Dialogue Generation: A Multi-component Reinforcement Learning Approach to Language Models for Mental Health Supportcited by 0
  5. 2025Tell Me: An LLM-powered Mental Well-being Assistant with RAG, Synthetic Dialogue Generation, and Agentic Planningcited by 0
  6. 2025Words to Describe What I'm Feeling: Exploring the Potential of AI Agents for High Subjectivity Decisions in Advance Care Planningcited by 0
  7. 2026Generative Confidants: How do People Experience Trust in Emotional Support from Generative AI?cited by 0
  8. 2026Structure Matters: Evaluating Multi-Agents Orchestration in Generative Therapeutic Chatbotscited by 0
  9. 2026Multi-Level Narrative Evaluation Outperforms Lexical Features for Mental Healthcited by 0
  10. 2026When AI Says "I have been in similar situations": Synthetic Lived Experience in Peer-Like Caregiver Supportcited by 0
  11. 2026CCBENCH: Assessing LLM Cultural Competence via Implicitly Signaled Norms using Health Queriescited by 0
  12. 2026Beyond the Sycophancy Score: How Task, Model, and Pressure Shape LLM Yieldingcited by 0