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Record W4401777418 · doi:10.1002/casp.2873

Mental health needs assessment for youth in out of school programs: A scoping review

2024· review· en· W4401777418 on OpenAlexafffund
Sabrina Brodkin, Annabel Sibalis, Anne‐Claude Bedard, Anthony Deluca, Anjali Suri, Alice-Simone Balter, Nicole Racine, Dina Al‐Khooly, Desiree Sylvestre, Brendan F. Andrade

Bibliographic record

VenueJournal of Community & Applied Social Psychology · 2024
Typereview
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of OttawaUniversity of TorontoPublic Health Agency of CanadaCentre for Addiction and Mental Health
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMental healthPsychologyMedical educationNeeds assessmentApplied psychologyGerontologySociologyMedicinePsychiatrySocial science

Abstract

fetched live from OpenAlex

Abstract Out‐of‐school programs are an accessible option to bolster the mental well‐being of youth, who may be at risk of developing further emotional and behavioural concerns. Developing a more nuanced understanding of the tools and methods available to understand youth mental health needs, in the context of out‐of‐school programs is needed to provide relevant services. However, many out‐of‐school programs do not include such an assessment. One barrier to doing so may be a lack of knowledge regarding the tools that can be used in this specialised context. The present scoping review was conducted to identify the tools that have been used to determine the emotional and behavioural needs of youth attending out‐of‐school programs and to synthesise information regarding the context in which these tools have been used. Fifty‐seven articles met the criteria for the review, and within these articles, 69 unique measures of emotional and behavioural needs were identified. The measures were sorted into six thematic categories (self‐concept, emotion and behaviour regulation, mood, general mental health, social skills and resilience) and relevant characteristics were described. The findings of the present review may be helpful to out‐of‐school programs as a step to best meet the needs of participating youth. Please refer to the Supplementary Material section to find this article's Community and Social Impact Statement .

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.839
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.233
GPT teacher head0.517
Teacher spread0.284 · 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 teacher head, not a consensus.

Study designOther design
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

Citations2
Published2024
Admission routes2
Has abstractyes

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