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Record W4403824657 · doi:10.1093/eurpub/ckae144.2257

Public health prevention programmes for mental illness in school-age children and adolescents

2024· article· en· W4403824657 on OpenAlexaff
F Serazzi, Franca Barbic, Saverio Stranges

Bibliographic record

VenueEuropean Journal of Public Health · 2024
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsWestern University
Fundersnot available
KeywordsPublic healthMental healthMental illnessPsychiatryMedicineFamily medicinePsychologyNursing

Abstract

fetched live from OpenAlex

Abstract Background Psychiatrists, psychotherapists and other mental health professionals have long stated the importance of adequate social groups and early intervention for the prevention of severe mental diseases. With psychiatric illness incidence increasing most in the adolescent and young adult populations, we propose the use of school-age directed public mental health initiatives to combat remaining social stigma and promote mental wellbeing, as well as educate children and adolescents in how to recognise symptoms and ask for help. Methods We conducted a systematic review on PubMed as well as government and NGO websites to identify public health initiatives in the prevention and early identification of mental illness among young individuals. Results Preliminary results show that, while certain countries have delineated guidelines on how to support students’ mental health, very few have implemented nation-wide, or even region-wide programmes that directly target prevention and education. A particular note should be made regarding substance abuse and addiction, one of the few illnesses for which many countries have already enacted in-school programmes, that however often overlook the medical aspect of such diseases. Of further note are certain local programmes aimed at offering quality and accessible care to adolescents struggling with mental diseases. Conclusions With psychiatric diseases projected to become one of the greatest contributors to the global burden of disease by 2030, and the importance of early intervention in preventing severe psychiatric illness, we advocated for European public health initiatives implemented in schools, which could be crucial in curbing the spread of mental illness. Key messages • Adolescent and young adults are those most affected by the rising prevalence of mental illness. Consequently, we advocate for in-school programmes to aid in early identification and intervention. • Early identification of mental diseases is crucial in the prevention of severe psychiatric illness, but little has been done so far in terms of public health interventions to tackle such problems.

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)0.031
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0310.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.151
GPT teacher head0.455
Teacher spread0.304 · 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 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

Citations3
Published2024
Admission routes1
Has abstractyes

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