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Germany International Students: 46% Depression, 47% Anxiety

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A 2026 survey of 327 international students in Germany found high symptom burden: 46.5% screened positive for moderate-to-severe depression, 46.8% for moderate-to-severe anxiety, and 31.2% endorsed recent death or self-harm thoughts on PHQ-9 item 9. Only 10.9% of students with moderate-to-severe depression and/or anxiety reported professional help.1 Research Highlights 327 international students were surveyed: Karing …

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Semaglutide Did Not Increase Suicidality in 102,361 Veterans

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A 2026 target-trial emulation involving 102,361 U.S. veterans with type 2 diabetes found no increased suicidality risk after starting semaglutide vs. sodium-glucose cotransporter-2 inhibitors (SGLT2 inhibitors): suicidal ideation HR 0.99 and suicide attempt/death HR 1.05 after overlap weighting.1 That does not prove semaglutide prevents suicide, but it weakens the broad claim that semaglutide initiation itself …

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AI Suicide-Risk Agent Detected 91.5% vs. ChatGPT Health

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A 2026 preprint found that an independent supervisory safety agent detected suicide-risk signals in 205 of 224 synthetic evaluations, compared with 41 of 224 for native ChatGPT Health crisis safeguards.1 The result is a strong benchmark signal for external monitoring, not proof that AI systems can safely manage suicidal patients without human oversight. Research Highlights …

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ME/CFS Memorial Entries: 505 Death Narratives Show Suicide Risk Gaps

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Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disabling multisystem illness marked by post-exertional malaise, cognitive dysfunction, pain, sleep disruption, and autonomic symptoms; a 2026 PLOS One qualitative analysis of 505 memorial entries found that bereaved accounts repeatedly placed death inside 4 overlapping contexts: systemic neglect, clinical dismissal, social disconnection, and personal functional collapse.1 Research Highlights …

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XGBoost Suicide Risk Model Reached 96% PPV at Top 0.1% Threshold

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A 2026 Scientific Reports study of Maryland suicide-death records found that an XGBoost machine-learning model could reach 96.1% positive predictive value in hospital-discharge data at the top 0.1% risk threshold, but it still detected only 46.7% of suicide deaths in that cohort. Research Highlights Precision improved at the narrowest threshold: XGBoost reached PPV 0.961 in …

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