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Record W4385807044 · doi:10.1038/s41380-023-02202-z

Towards a youth mental health paradigm: a perspective and roadmap

2023· review· en· W4385807044 on OpenAlexaff
Peter J. Uhlhaas, Christopher G. Davey, Urvakhsh Meherwan Mehta, Jai Shah, John Torous, Nicholas B. Allen, Shelli Avenevoli, Tolulope Bella‐Awusah, Andrew M. Chanen, Eric Chen, Christoph U. Correll, Kim Q., Helen L. Fisher, Sophia Frangou, Ian B. Hickie, Matcheri S. Keshavan, Kerstin Konrad, Francis S. Lee, Cindy H. Liu, Beatriz Luna, Patrick D. McGorry, Andreas Meyer‐Lindenberg, Merete Nordentoft, Döst Öngür, George Patton, Tomáš Paus, Ulrich Reininghaus, Akira Sawa, Michael Schoenbaum, Günter Schumann, Vinod H. Srihari, Ezra Susser, Swapna Verma, Tsung‐Ung W. Woo, Lawrence H. Yang, Alison R. Yung, Stephen J. Wood

Bibliographic record

VenueMolecular Psychiatry · 2023
Typereview
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineUniversity of TorontoUniversity of British ColumbiaMcGill University
FundersNational Center for Advancing Translational SciencesEconomic and Social Research Council
KeywordsPsychopathologyMental healthTransformative learningPerspective (graphical)Psychological interventionIntervention (counseling)PsychologyParadigm shiftPsychiatryDevelopmental psychology

Abstract

fetched live from OpenAlex

Most mental disorders have a typical onset between 12 and 25 years of age, highlighting the importance of this period for the pathogenesis, diagnosis, and treatment of mental ill-health. This perspective addresses interactions between risk and protective factors and brain development as key pillars accounting for the emergence of psychopathology in youth. Moreover, we propose that novel approaches towards early diagnosis and interventions are required that reflect the evolution of emerging psychopathology, the importance of novel service models, and knowledge exchange between science and practitioners. Taken together, we propose a transformative early intervention paradigm for research and clinical care that could significantly enhance mental health in young people and initiate a shift towards the prevention of severe mental disorders.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0030.006
Open science0.0010.003
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.365
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations288
Published2023
Admission routes1
Has abstractyes

Explore more

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