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Record W4413026151 · doi:10.12927/hcq.2025.27633

Stepped Care 2.0: A Framework to Facilitate Leadership in Youth Mental Health System Building

2025· article· en· W4413026151 on OpenAlexaffvenueabout
Kaitlin G. Saxton, Alexia Jaouich, Mary Bartram, Mélanie Hood, Janis Dawson, Hajin Lee, Peter Cornish

Bibliographic record

VenueHealthcare Quarterly · 2025
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsWomen's College HospitalGRi Simulations (Canada)Acadia UniversityCollège BoréalPublic Works and Government Services Canada
Fundersnot available
KeywordsMental healthBest practiceMental health carePsychologyHealth careHealth administrationMental healthcareNursingPublic relationsApplied psychologyMedicinePolitical sciencePublic healthPsychiatry

Abstract

fetched live from OpenAlex

In Canada, there has been an effort to address youth mental health through various initiatives and investments, although mental health struggles among young Canadians continue to increase. Despite these challenges, there is also recognition of the strength and resilience of youth, as well as the increasing empowerment and engagement of young people in shaping mental health support systems. In this article, the authors explore the role of leadership in facilitating the co-design and implementation of a comprehensive continuum of care, leveraging the Stepped Care 2.0 framework, to facilitate effective and sustainable youth mental health support systems.

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)0.016
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.019
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0080.011
Scholarly communication0.0110.006
Open science0.0040.015
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0080.002

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 head0.163
GPT teacher head0.407
Teacher spread0.244 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

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