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Record W4415219568 · doi:10.33921/y5976wg2

School Climate Factors Associated with Remote Help-Seeking Preferences and Behaviors among Ontario Adolescents

2025· article· en· W4415219568 on OpenAlexvenueaboutno aff
Graham J. Reid

Bibliographic record

VenueJournal of Interpersonal Relations Intergroup Relations and Identity · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthPerceptionSchool climatePsychological interventionSocial environment

Abstract

fetched live from OpenAlex

Less than 20% of Canadian adolescents with mental health difficulties receive professional help. Prior research indicates that social dimensions of school climate (e.g., students’ perception of belongingness) are positively related to perceptions and use of in-person mental health resources, such as school counselors. However, no studies have examined the relationship between school climate and preferences/use of remote mental health services (RMHS), defined as services which are offered virtually. The present study addresses this gap through secondary analyses (N = 7,552) of the 2019 dataset of the Ontario Student Drug Use and Mental Health Survey. Analyses indicated that school climate was positively related to student preferences/use of in-person mental health services. However, school climate was not associated with preferences/use of RMHS. These results broaden our understanding of factors related to adolescent helpseeking.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.301
Teacher spread0.285 · 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 designObservational
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

Citations0
Published2025
Admission routes2
Has abstractyes

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Same venueJournal of Interpersonal Relations Intergroup Relations and IdentitySame topicImpact of Technology on AdolescentsFrench-language works237,207