Clinical Summaries of Social Media Timelines for Mental Health Monitoring: Human Versus Large Language Model Comparative Evaluation Study

At this time medium-size LLMs can generate largely accurate and informative clinical summaries of social media timelines, and advanced prompting boosts performance modestly. However, at the time of this writing, they underperform human clinicians in capturing subtle psychological nuances and individual idiosyncrasies. Future work should integrate domain‑specific fine‑tuning and enhanced context modeling to improve LLM clinical fidelity.

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Publication Details

Journal
JMIR Formative Research
Published
2026-03-27
DOI
https://doi.org/10.2196/71230
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
0.00
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article

Clinical Summaries of Social Media Timelines for Mental Health Monitoring: Human Versus Large Language Model Comparative Evaluation Study

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JMIR Formative Research
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Clinical Summaries of Social Media Timelines for Mental Health Monitoring: Human Versus Large Language Model Comparative Evaluation Study

Ayal Klein, Jiayu Song, Liran Keren, Dana Atzil-Slonim, Jenny Chim, Andreas Triantafyllopoulos, Björn W. Schuller, Maria Liakata
article en

Abstract

At this time medium-size LLMs can generate largely accurate and informative clinical summaries of social media timelines, and advanced prompting boosts performance modestly. However, at the time of this writing, they underperform human clinicians in capturing subtle psychological nuances and individual idiosyncrasies. Future work should integrate domain‑specific fine‑tuning and enhanced context modeling to improve LLM clinical fidelity.

JMIR Formative ResearchVol. 10
Bar-Ilan University (IL), Queen Mary University of London (GB), The Alan Turing Institute (GB), Imperial College London (GB), Ariel University (IL), Technical University of Munich (DE)
Quality Education
Openalex Percentile: Top 12%
Mental Health via Writing
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