Article

mpathic Psychologist-led AI Clinical Tests Eating Disorders Benchmark (mPACT-ED-v1.0)

2026-05-15

Abstract excerpt

<p>The mpathic Psychologist-led AI Clinical Tests Eating Disorders Index (mPACT-ED-v1.0) benchmark is a comparison of large language models (LLM) in their response to mental health content involving disordered eating presentations. Eating disorders are among the most lethal psychiatric conditions, yet standardized benchmarks for evaluating AI conversations in this domain remain scarce, limiting rigorous cross-syst...

Topics

Open a Topic to create a Post that cites this publication.

Uncategorized literature

Identifiers and source

Literature Corpus work: fd4859ca-3bf9-511d-b67c-b25582d8809b
DOI: 10.31234/osf.io/htzcn_v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

mpathic Psychologist-led AI Clinical Tests Eating Disorders Benchmark (mPACT-ED-v1.0)DOI 10.31234/osf.io/htzcn_v1Read

mpathic Psychologist-led AI Clinical Tests Suicide Benchmark (mPACT-S-v1.0)Semantic proximity Read

Safety Evaluation of a Generative AI Agent for Anxiety and Depression SymptomsSemantic proximity Read

Evaluating and Enhancing an AI Mental Health Guide in High-Risk Mental Health ContextsSemantic proximity Read

Safety Evaluation of a Clinical-Grade Generative AI Agent for Anxiety and Depression SymptomsSemantic proximity Read

Conversational trajectory degrades large language model detection of suicidal ideation relative to clinicians: a preregistered studySemantic proximity Read

Risk Governance for Generative AI Mental Health Support: A Multi-Turn Safety ArchitectureSemantic proximity Read

A Scoping Review of Generative AI in Mental Health SupportSemantic proximity Read

A Scoping Review of Generative AI in Mental Health SupportSemantic proximity Read

Large language models could change the future of behavioral healthcare: A proposal for responsible development and evaluationSemantic proximity Read

Large language models could change the future of behavioral healthcare: A proposal for responsible development and evaluationSemantic proximity Read

AI-Driven Mental Healthcare 5.0: A Survey of Opportunities and Challenges in Leveraging Large Language Models and Generative AISemantic proximity Read

Leveraging simulation to provide a practical framework for assessing the novel scope of risk of LLMs in healthcareSemantic proximity Read