101 artifacts matching
Preprint
Delusions and Harms Associated with AI Chatbot Use: Early Evidence from 185 Real-World Reports
Cross-sectional secondary analysis of 185 deidentified accounts of mental-health harm linked with AI chatbot use (95 first-hand, 90 from relatives, partners or friends) submitted through the web form…
Peer-reviewed
Exploring generalizability and explainability of LLMs in classifying clinically rated suicidal ideation using heterogeneous data
Hong Kong study asking whether a language-model classifier of clinician-rated suicidal ideation performs unequally across patient subgroups because of linguistic heterogeneity. Cantonese clinical-int…
Preprint
Will My Assistant Remember My Allergy? What Personal LLM Assistants Forget When Conversation Memory Is Compressed
Tests whether on-device personal assistants (health companions, elder-care agents, accessibility aides) retain safety-critical facts such as an allergy or a medication mentioned in passing when conve…
Preprint
When Seeing Overrides Knowing: Visual Dominance and Deferral-Based Method for Personalized Safety in VLMs
Extends personalized safety to vision-language models. MPS-Bench pairs 5,181 image-plus-query scenarios, built from 584 real-world images across 12 high-risk domains (including Health, Relationship,…
Peer-reviewed
Privacy assurances and professional-boundary warnings in generative AI mental health chatbots: a randomized vignette experiment on calibrated trust, overreliance risk, and professional help-seeking intentions
2 by 2 randomized vignette experiment with 768 Chinese college students testing whether a privacy-assurance message and a professional-boundary warning in a mental-health chatbot interface change per…
Government report
Through Children's Eyes: How Digital Technologies Enable Child Sexual Abuse
Synthesis of two rounds of the Disrupting Harm surveys, nationally representative household surveys of around 21,000 internet-using children aged 12 to 17 across 21 countries in Africa, Asia, Latin A…
Preprint
Sources of Truth: A Multi-Platform, Multilingual Audit of Citations in AI Mental Health Information Queries
An audit of what three free consumer generative-search products (ChatGPT, Perplexity, Google AI Overview) cite when answering mental-health questions. Twenty English questions were run under two prom…
Peer-reviewed
Affective Generative Artificial Intelligence Use and Youth Mental Health
Cross-sectional study of 39,761 students in grades 4-12 across four Ontario school boards (Ontario Health and Peer Relations Study, May 2025 - March 2026) examining the association between affective…
Preprint
Whose Assessment of Distress? Community Perspectives and LLM Alignment on Well-Being Posts
A perspectivist annotation study asking whether large language models used for distress detection capture the perspectives of the communities whose language they assess. 321 participants provided 9,5…
Peer-reviewed
Latent profiles of generative artificial intelligence use among Chinese college students: Associations with depression and anxiety
Cross-sectional survey of 5,748 Chinese college students identifying four latent profiles of generative-AI use (Rational-Tool, Moderate-Recreational, Problem-Dependent, Light-Exploratory) and their a…
Industry survey
From Diagnoses to Treatments, Why Americans Use AI Chatbots for Health
A national survey of 3,488 US adults on the American Trends Panel about how and why they use AI chatbots for health, how helpful they find the information, and how comfortable they are sharing person…
Preprint
AI emotional support is better only when chosen, but shifts preferences even when it is not
Three experiments plus a 28-day field study examining how people choose between human and AI emotional support and what happens when the support they receive does not match what they chose. Participa…
Preprint
Affective Context Amplifies Sycophancy in LLM Responses
A study of how a user's disclosed emotional state modulates sycophancy in subjective, evaluative exchanges. Drawing on ingratiation theory, the authors measure sycophancy as the divergence between a…
Peer-reviewed
A scoping review on the mental health harms of LLM-based chatbots
A PRISMA-based scoping review synthesising research on mental health harms associated with chatbots built on large language models. A systematic search with a validated search string across five data…
Peer-reviewed
Generative AI in Youth Mental Health Apps: Rapid Review
A rapid review of how generative AI has been integrated into mental health apps for young people, and of what the evaluation literature reports about benefits and disadvantages. The authors searched…
Lab publication
Introducing ChatGPT for Teens: Built for learning, backed by protections
OpenAI announced a distinct under-18 product tier that users are placed into automatically when the age-prediction system estimates they are under 18 or when they state an age between 13 and 17. The…
Peer-reviewed
The new first listener: Daydreaming styles and self-compassion predict adolescent disclosure to AI, differently in ADHD
Cross-sectional survey of 2,115 adolescents and young people in the United States and Hong Kong examining how daydreaming styles and self-compassion relate to disclosing inner thoughts to an AI chatb…
Preprint
How LLMs Respond to Escalating Delusions: Four Longitudinal Trajectories of Model Behavior
Longitudinal qualitative evaluation of whether mainstream chatbots exacerbate an unfolding psychotic process. Fifteen widely used models were prompted across 30 days with the same 30-message script s…
Benchmark / dataset
ConVAWG: A Retrieval-Grounded Framework for Controlled Synthetic Dialogue Generation in Violence Against Women and Girls
Framework and released corpus for generating synthetic multi-turn dialogues depicting Violence Against Women and Girls (VAWG) scenarios, built because privacy and legal constraints prevent release of…
Preprint
Beyond "I Can't Help With That": How Child Safety Experts Evaluate AI Chatbot Safety
Interview study with 19 practitioners who work directly with youth in vulnerable situations — social workers, therapists and psychologists — asking them to assess chatbot responses to risky situation…