Issue #012 — Relapse becomes the frontier: two independent 2026 reviews map AI for predicting psychiatric relapse and land at modest AUCs, while a 95-study scoping review calls the whole LLM-in-mental-health field 'nascent and exploratory.'
A second consecutive quiet in-window week; three out-of-window catch-up reviews shift the newsletter's measurement-discipline thesis onto a new axis — relapse and deterioration prediction — where a BMC Psychiatry systematic review and a JMIR psychosis-relapse scoping review both report promise undercut by small samples, and a 95-study LLM scoping review maps a field still nascent.
Issue #011 — A quiet in-window week, so three catch-up audits — a 105-study speech meta-analysis, a 42-study passive-sensing scoping review, and an LLM mental-health safety benchmark — widen the measurement-discipline thesis across three modalities at once.
No new primary detection result cleared the 7-day window; three out-of-window catch-up findings — an automatic-speech-analysis depression meta-analysis, a passive-sensing scoping review, and a role-aware LLM safety benchmark — independently report strong aggregate numbers undercut by heterogeneity, small samples, and unmeasured multi-turn failure.
Issue #010 — The in-window window finally produces its own story: two digital-phenotyping papers land six days apart — a Nature Mental Health comment celebrating the promise of early adolescent depression detection, and a 47-study Frontiers systematic review finding that methodological heterogeneity still blocks its translation.
After four catch-up weeks, two genuinely in-window digital-phenotyping papers frame the field's core tension — promise versus implementation heterogeneity — reinforced by two catch-up findings on speech-biomarker parsimony and just-in-time prediction.
Issue #009 — A fourth quiet in-window week, so three 2026 audits of the wearable-biomarker literature converge on one uncomfortable verdict: no single signal is diagnostic, passive sensing is population-level not clinical, and the leaderboards ranking detection models are unstable.
No new primary detection result cleared the 7-day window; three out-of-window catch-up findings — a 132-study depression digital-biomarker meta-analysis, a 10-month wearable brain-health study, and a five-dataset benchmark audit — independently land on the same measurement-discipline conclusion.
Issue #008 — A quiet in-window week, so three catch-up results converge on one theme: the modality, the validation gap, and the LLM that decide whether detection survives contact with real patients.
No new primary detection result cleared the 7-day window; three out-of-window catch-up findings — a visual-psychophysiology screener that catches 'silent' patients, a multimodal-MDD review exposing the external-validation gap, and a RAG-LLM depression/suicide-risk benchmark — anchor the issue.
Issue #007 — At WHA79, suicide-prevention bodies open a WHO-level front on AI and youth safety, pressing a 'warm handoff to a trained person, not a disclaimer' standard as the global axis the newsletter had not yet tracked.
A quiet week for primary detection research; the load-bearing development is an IASP-coordinated WHA79 side event (readout 10 June) opening a WHO/global-governance front on AI, social media, and youth suicide prevention.
Issue #006 — The EU AI Act's high-risk classification guidelines enter open consultation, giving mental-health detection tools their first read on Brussels' rules just as they layer atop the Medical Device Regulation.
The European Commission's draft high-risk AI classification guidelines are in open consultation through 23 June — the first EU-side regulatory signal material to AI mental-health detection tools, layered on top of MDR/IVDR.
Baseline — the state of human behavioral analysis for early identification of mental health conditions
Foundational state-of-the-field report. The dedup baseline against which every weekly issue is measured.
Every weekly issue is deduplicated against the Baseline — the foundational state-of-the-field report. Start here if you're new to the series.