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Record W4414317181 · doi:10.1177/00049441251379098

Feasibility and Acceptability of a Classroom-Based Mental Health Literacy Program: An Australian Pilot Study

2025· article· en· W4414317181 on OpenAlexaff
Brae Anne McArthur, Kristine Lyn Pesigan, Lindsay Berg, Darian Mahmi

Bibliographic record

VenueAustralian Journal of Education · 2025
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsAlberta Children's HospitalUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsMental healthMental health literacyLiteracyHealth literacyPilot programPsychological intervention

Abstract

fetched live from OpenAlex

Given the escalating concern surrounding mental health issues among school-age children, this study evaluated the benefits, feasibility, and acceptability of the Open Parachute mental health literacy program, designed to foster mental health skills through classroom instruction. This study asked 37 Australian educators, spanning primary to secondary school, to report on their experiences with the Open Parachute program. 50 percent of participants reported the program improved student mental health literacy and support skills, with 89% of educators intending to use the program again and 92% reporting they would recommend it to a colleague, demonstrating high feasibility and acceptability. Educators reported that they observed greater skill use, and gains in emotional regulation and empathy, in primary students compared to secondary school students. The findings of this study provide preliminary evidence for the utility of the Open Parachute program and the potential benefits of universal early mental health literacy instruction in school.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.250
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

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

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 head0.111
GPT teacher head0.508
Teacher spread0.397 · 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.

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 routes1
Has abstractyes

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