Fine-tuning LLMs for Passive Depression Severity Estimation from AI Mental Health Dialogue

arXiv:2606.17973v1 Announce Type: new Abstract: Depression is the leading cause of disability worldwide, and early detection of symptom change is essential for timely intervention. Validated instruments such as the Patient Health Questionnaire-9 (PHQ-9) support symptom monitoring at scale, but real-world completion rates are low, introducing response bias and systematic missingness. Passive approaches that infer severity from routinely generated data could close this gap. We address this by predicting PHQ-9 total scores directly from transcripts of conversations between users and an AI mental

Source: arXiv cs.CL — read the full report at the original publisher.

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