mlsanityData to 14 Oct 2026

Private Yet Social: How LLM Chatbots Support and Challenge Eating Disorder Recovery

arXiv 2412.11656 ↗First posted 16 Dec 2024cs.HC cs.LGcited by 8

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Abstract (arXiv)

Eating disorders (ED) are complex mental health conditions that require long-term management and support. Recent advancements in large language model (LLM)-based chatbots offer the potential to assist individuals in receiving immediate support. Yet, concerns remain about their reliability and safety in sensitive contexts such as ED. We explore the opportunities and potential harms of using LLM-based chatbots for ED recovery. We observe the interactions between 26 participants with ED and an LLM-based chatbot, WellnessBot, designed to support ED recovery, over 10 days. We discovered that our participants have felt empowered in recovery by discussing ED-related stories with the chatbot, which served as a personal yet social avenue. However, we also identified harmful chatbot responses, especially concerning individuals with ED, that went unnoticed partly due to participants' unquestioning trust in the chatbot's reliability. Based on these findings, we provide design implications for safe and effective LLM-based interventions in ED management.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 27 of its 134 references that are in the map. First posted on arXiv 16 Dec 2024.

Builds on

27 of 134 references.

References · 27

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15 more
  1. 2024TrustAgent: Towards Safe and Trustworthy LLM-based Agentscited by 64
  2. 2023"It's a Fair Game", or Is It? Examining How Users Navigate Disclosure Risks and Benefits When Using LLM-Based Conversational Agentscited by 60
  3. 2023MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journalingcited by 50
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  6. 2024LLM-based Conversational AI Therapist for Daily Functioning Screening and Psychotherapeutic Intervention via Everyday Smart Devicescited by 21
  7. 2024Can AI Relate: Testing Large Language Model Response for Mental Health Supportcited by 21
  8. 2024Supporting Self-Reflection at Scale with Large Language Models: Insights from Randomized Field Experiments in Classroomscited by 20
  9. 2024Understanding the Impact of Long-Term Memory on Self-Disclosure with Large Language Model-Driven Chatbots for Public Health Interventioncited by 15
  10. 2024Evaluating the Experience of LGBTQ+ People Using Large Language Model Based Chatbots for Mental Health Supportcited by 14
  11. 2024Contextual AI Journaling: Integrating LLM and Time Series Behavioral Sensing Technology to Promote Self-Reflection and Well-being using the MindScape Appcited by 14
  12. 2023Do You Trust ChatGPT? -- Perceived Credibility of Human and AI-Generated Contentcited by 9
  13. 2022The Distressing Ads That Persist: Uncovering The Harms of Targeted Weight-Loss Ads Among Users with Histories of Disordered Eatingcited by 5
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  15. 2024A Browser Extension for in-place Signaling and Assessment of Misinformationcited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 5.

8 papers.

  1. 2025From Symptoms to Systems: An Expert-Guided Approach to Understanding Risks of Generative AI for Eating Disorderscited by 1
  2. 2026Food Noise & False Safety: A Systematic Evaluation of How LLMs Fail to Adapt to Eating Disorder Queries with Clinician Feedbackcited by 1
  3. 2025Collective Voice: Recovered-Peer Support Mediated by An LLM-Based Chatbot for Eating Disorder Recoverycited by 0
  4. 2025Lived Experience in Dialogue: Co-designing Personalization in Large Language Models to Support Youth Mental Well-beingcited by 0
  5. 2026Structure Matters: Evaluating Multi-Agents Orchestration in Generative Therapeutic Chatbotscited by 0
  6. 2026Trust Stack for Mental Health AI: A Survey of Calibration across Human, Interaction, and AI Layerscited by 0
  7. 2026Psychological Influences of Conversational AI: Research and Design Directions for Reducing Harm and Promoting Well-Beingcited by 0
  8. 2026Right Words, Wrong Moment: A Clinician-Grounded Analysis of Distress in 19,930 Conversations between Young People and ChatGPTcited by 0