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Record W4404693611 · doi:10.1080/03323315.2024.2430298

Secondary school staff experiences of supporting and promoting adolescent mental health in Ireland

2024· article· en· W4404693611 on OpenAlexaff
Anna Blix, Maeve Dwan-O'Reilly, Laura Walsh, Ailbhe Booth, Caroline Heary, Eilis Hennessy

Bibliographic record

VenueIrish Educational Studies · 2024
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsOntario Centre of Excellence for Child and Youth Mental Health
FundersIrish Research Council
KeywordsMental healthPsychologyPedagogyMedical educationMedicinePsychiatry

Abstract

fetched live from OpenAlex

Teachers and other school staff are increasingly relied on to address student mental health in secondary schools in Ireland. As part of the Wellbeing Policy Statement and Framework for Practice (2019), the Department of Education set out the ambition to place the promotion of wellbeing at the core and ethos of all schools in Ireland by 2023. This study investigates secondary school staff’s experiences of addressing mental health in schools through qualitative analysis of open question data provided by n = 359 school staff. Reflexive thematic analysis was used to analyse the data, resulting in three themes. The themes highlighted the salience of mental health in schools, the wide variety of ways mental health is integrated in Irish secondary schools, and how mental health in schools can be a source of pressure for staff. The findings of this study suggest that staff, while generally positive towards mental health engagement in schools, do not feel adequately prepared to deliver this content to the extent expected of them. Findings are discussed in relation to the Wellbeing Framework as well as the existing international literature on school based mental health content, and implications for policy and practice are proposed.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.398

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.064
GPT teacher head0.470
Teacher spread0.406 · 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 designQualitative
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

Citations1
Published2024
Admission routes1
Has abstractyes

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