Griffin Murch

@griffinmurch.bsky.social

Clinical Research Assistant | Personalized distress intervention + data science | TEDY Lab @McLeanHospital

I dug into NSDUH data on depression in U.S. teens (12-17) and made the below figure. Rates increased far more sharply for girls than boys, peaking around COVID before modest declines. Shaded region = % with depression receiving mental health treatment. Both depression and unmet need remain high.

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Seems GPT-5.2 reaches expert level in peer review: 45 scientists took 469 hours evaluating human & AI reviews on 82 papers. "Surprisingly, current AI reviewers are competitive even with the top-rated reviewers in Nature’s official peer review..." though not without weaknesses, so use AI + humans.

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It was great presenting recent work at Harvard Psychiatry Day! Higher sleep reactivity, a trait describing how much sleep is impacted by daily stress, is associated with many psychological and physical dx’s. We quantified this with EMA, finding that it predicts future new internalizing symptoms.

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Now out in npj Digital Medicine 🎉 www.nature.com/articles/s41... Our systematic review and meta-analysis examines how well language-based models detect depression from text. We reviewed 123 studies (40,000 + observations) using NLP and machine learning.

Language-based detection of depression with machine learning: systematic review and meta-analysis - npj Digital Medicine

npj Digital Medicine - Language-based detection of depression with machine learning: systematic review and meta-analysis

nature.com

We're hiring! The Emotion and Psychopathology in Context Lab at Harvard invites applications for a full-time RA/lab manager to start in 2026 summer. Ideal for students preparing for graduate study (e.g., clinical psych). Please consider sharing & applying! jobs.smartrecruiters.com/HarvardUnive...

Research Assistant I

Company Description: By working at Harvard University, you join a vibrant community that advances Harvard's world-changing mission in meaningful ways, inspires innovation and collaboration, and builds...

jobs.smartrecruiters.com

New paper from our team: Can ML identify which adolescents benefit most from school-based mindfulness? In 8,376 students (MYRIAD trial), models detected statistically significant but clinically negligible differential effects (d ≈ .07–.08). Precision prevention is hard...

JAMA Psychiatry@jamapsychiatry.com · 6mo ago

Machine learning analyses in the MYRIAD trial found only clinically trivial personalization of school-based mindfulness for adolescent #Depression prevention, underscoring limited differential benefit in universal programs. ja.ma/3OkeH2P

Two bar graphs compare changes in CES-D scores between SBMT and TAU interventions using a causal forest model and an elastic net regression model. The causal forest model shows a d=0.07, P=.007 for SBMT and d=-0.01, P=.82 for TAU.

Interesting to see how our lab's recruitment sources have shifted over the last 3 years (see plot). FB/Instagram used to pull 100+ responses/month, now much less productive. Methods like flyers and mailing lists remain steady. Curious if any other labs are seeing this or have found new methods?

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Younger adolescents and preteens have become an alarming portion of patients admitted for serious suicide attempts, in addition to those dying by suicide. Refinement in screening and treatment is required. 2/2

I’ve spent the last 8 years(!) working from the position that HiTOP relies too much on analyses of traditional diagnoses, baking in limitations of the DSM, and that we need to move to symptom-level analyses to fix it It turns out that rebuilding HiTOP from the ground up doesn’t change much 💀 1/

A figure of the results from our study, showing a model that looks remarkably similar to the official HiTOP model. There are also important differences like a pathological introversion domain and a combined hypomania/disinhibition dimension.
PsyArXivBot@psyarxivbot.bsky.social · 9mo ago

Rebuilding HiTOP from the ground up: Symptom-level analyses and a revised mapping to the DSM: https://osf.io/8tm6c