What question did this study set out to answer?

This research aims to explore the unique capabilities of large language models (LLMs) in clinical mental health assessment and identify future research directions.

August 5, 2026Journal of Psychopathology and Clinical Science

Large language model applications for real-time clinical mental health assessment: Current potential and future directions.

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Authors

KDKatie Aafjes‐van DoornNew York University Shanghai FTFrancine Cheng TyNew York University Shanghai AHAntonia Yuxin HuaUniversity of Illinois Urbana-Champaign

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Implication

Scoping review explores large language models for clinical mental health assessment, suggesting promising future applications.

Key Points

This research aims to explore the unique capabilities of large language models (LLMs) in clinical mental health assessment and identify future research directions.
Conducted a preregistered scoping review of studies published in Chinese and English.
Included 10 studies focused on direct LLM-based mental health assessment, varying in formats like text, voice, and multimodal approaches.
Assessed studies on diagnostic interviewing, symptom severity assessment, and future applications of LLMs.
Only 10 studies met the criteria for LLM-based mental health assessment, highlighting a small evidence base.
Studies showed better performance using structured interviewing logic and domain-specific adaptations.
Current evidence suggests LLMs are emerging tools for assessment support rather than replacements for clinical evaluation.

Cite This Study

Doorn et al. (2026) studied this question.

synapsesocial.com/papers/6a72e84e226790f370658065 https://doi.org/10.1037/abn0001155

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Large language model applications for real-time clinical mental health assessment: Current potential and future directions.

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Key Points

Cite This Study

Large language model applications for real-time clinical mental health assessment: Current potential and future directions.

Discussion

Member takes

Implication

Key Points

Cite This Study

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