2024

Large Language Models in Mental Health Care: a Scoping Review

Hua, Yining, Liu, Fenglin, Yang, Kailai et al.

Understand

Objectieve:This review aims to deliver a comprehensive analysis of Large Language Models (LLMs) utilization in mental health care, evaluating their effectiveness, identifying challenges, and exploring their potential for future application.

Materials and Methods: A systematic search was performed across multiple databases including PubMed, Web of Science, Google Scholar, arXiv, medRxiv, and PsyArXiv in November 2023.
The review includes all types of original research, regardless of peer-review status, published or disseminated between October 1, 2019, and December 2, 2023.
Studies were included without language restrictions if they employed LLMs developed after T5 and directly investigated research questions within mental health care settings.

Built on

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Then

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Ask an Expert: Leveraging Language Models to Improve Strategic Reasoning in Goal-Oriented Dialogue Models
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The Plasticity of ChatGPT’s Mentalizing Abilities: Personalization for Personality Structures
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