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Record W4413478082 · doi:10.63050/jpps.21.04.942

SCHOOL-BASED MENTAL HEALTH: PARADIGM SHIFT IN ADDRESSING MENTAL HEALTH OF PAKISTANI YOUTH

2024· article· en· W4413478082 on OpenAlexaboutno aff
Muhammad Waqar, Sadiq Naveed

Bibliographic record

VenueJournal of Pakistan Psychiatric Society · 2024
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthParadigm shiftPsychologyPsychiatry

Abstract

fetched live from OpenAlex

About 20-25% of the youth suffer from mental and substance use disorders. About 50% of these mental disorders have an onset before age 15, and 75% by 25 years contributing to about five trillion dollars of economic losses every year. Youth’s mental health is imperative in how they think, behave, and learn. School is a critical place in the lives of developing youth, presenting a unique place for prevention and early interventions. Developed countries, such as the United States of America (USA), Canada, the United Kingdom, and Australia, have established a framework that focuses on enhancing teachers' efficacy in recognizing warning signs for mental health problems. They also liaise with school counselors and mental health professionals to ensure that at-risk individuals get appropriate help for early prevention. Moreover, students are also taught about mental health problems to raise awareness and reduce the stigma associated with it. Pakistan is also making considerable progress to counter mental health in its youth. The School Mental Health Programmes for teachers and Theory of Change model are a few examples of initiatives taken by our government in collaboration with other stakeholders which have shown promise in addressing the mental health problems in children. Moving forward it is essential for the stakeholders, policymakers, and state institutions to collaboratively build a framework that serves the mental health needs of the Pakistani youth, keeping in perspective the cultural context and limited infrastructure.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.037
GPT teacher head0.425
Teacher spread0.388 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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