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Record W2059507434 · doi:10.1177/0829573512468858

The Psychology School Mental Health Initiative

2013· article· en· W2059507434 on OpenAlexaboutno aff
Golden M. Millar, Debra Lean, Susan D. Sweet, Sabrina C. Moraes, Victoria Nelson

Bibliographic record

VenueCanadian Journal of School Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthConceptualizationPsychologyIntervention (counseling)School psychologyApplied psychologyService delivery frameworkMedical educationService (business)PsychiatryMedicine

Abstract

fetched live from OpenAlex

Evidence suggests that schools have, by default, become the primary mental health system for students in Canada. The goal of the present study was to design, implement, and evaluate the Psychology School Mental Health Initiative (PSMHI). The PSMHI is an innovative attempt to increase the capacity of school-based psychology staff to deliver evidence-based mental health intervention to children and adolescents with mental health concerns. The conceptualization, implementation, and initial outcomes of the PSMHI are outlined. Advantages and challenges of delivering cognitive–behavioural intervention in a school setting are discussed. Preliminary data indicated that participation in the initiative increased the capacity of school psychology staff in the provision of mental health service. Furthermore, results revealed that a higher number of students with mental health issues received evidence-based intervention. Finally, recommendations for enhancing effective service delivery and the expanding role of psychology with the school system are highlighted.

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)0.005
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score0.815

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0030.001
Open science0.0020.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.044
GPT teacher head0.342
Teacher spread0.297 · 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
GenreEmpirical

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

Citations9
Published2013
Admission routes1
Has abstractyes

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