Article

Mental Health Benchmarks for Large Language Models: A Systematic Scoping Review

2026-08-01

Abstract excerpt

<p>Large language models (LLMs) are increasingly used for mental health support, yet standards for evaluating their safety and competence remain unsettled. Benchmarks, standardized tests with predetermined scoring criteria, are the most common evaluation approach, but this landscape has not been systematically mapped. In this systematic scoping review, we searched four databases, machine-learning repositories, and...

Topics

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

Identifiers and source

Literature Corpus work: 40062bc4-6b15-56e7-a22c-9d8e2f916907
DOI: 10.31234/osf.io/fahuk_v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Mental Health Benchmarks for Large Language Models: A Systematic Scoping ReviewDOI 10.31234/osf.io/fahuk_v1Read

Systematic Review of Large Language Models for Mental Health TherapySemantic proximity Read

A Systematic Review of Testing and Evaluation of Healthcare Applications of Large Language Models (LLMs)Semantic proximity Read

An interdisciplinary, randomized, single-blind evaluation of state-of-the-art large language models for their implications and risks in medical diagnosis and managementSemantic proximity Read

One and a Half Year of ChatGPT: An Umbrella Review of Large Language Model (LLM) Perception Across Time and Research FieldsSemantic proximity Read

The TRIPOD-LLM Statement: A Targeted Guideline For Reporting Large Language Models UseSemantic proximity Read

Beyond Benchmarks: Dynamic, Automatic And Systematic Red-Teaming Agents For Trustworthy Medical Language ModelsSemantic proximity Read

Artificial Intelligence in Mental Health Treatment and ResearchSemantic proximity Read

Simulated Reasoning and Self-Verification in Generalist Large Language Models for Psychiatric Diagnostic Performance: Cross-Sectional StudySemantic proximity Read

Evaluating Diagnostic Accuracy and Clinical Reasoning of Multiple Large Language Models in PsychiatrySemantic proximity Read

The Role of Large Language Models in Clinical Psychology: Current Applications, Efficacy, Challenges, and Future DirectionsSemantic proximity Read

Large Language Models for Cardiovascular Disease, Cancer, and Mental Disorders: A Review of Systematic ReviewsSemantic proximity Read

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