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Record W2296844915 · doi:10.11575/prism/28116

The Effects of School Work Pressure on Depression and Substance Use: A Cross-National Study of School-Aged Children in Canada and Finland

2015· dissertation· en· W2296844915 on OpenAlexaboutno aff
Nahum Arguera

Bibliographic record

VenuePRISM (University of Calgary) · 2015
Typedissertation
Languageen
FieldSocial Sciences
TopicYouth Substance Use and School Attendance
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)Work (physics)Substance usePsychologyMedicinePsychiatryEngineeringEconomicsMechanical engineering

Abstract

fetched live from OpenAlex

Studies suggest that adolescents report a variety of academic stressors, which can have detrimental effects on mental health. Using the Health Behaviour in School-Aged Children survey (2005/6 data), this study provides an analysis of the effects of school work pressures on depressive symptomology and substance use in adolescents in Canada and Finland. Using Pearlin’s stress process framework, the study also examines how socio-demographic indicators affect these stress outcomes. Results indicate that regardless of context, school work pressure negatively affects the mental health of students net of all socio-demographic indicators. However, this relationship is stronger in Finland than in Canada. Secondary results show that depressive symptomology is associated with smoking and alcohol consumption in both countries. School work pressure, however, only has an additional effect on the likelihood to drink alcohol among students in Finland. Ultimately, this study demonstrates that the mechanisms through which the stress process model operates differs by national context.

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)0.000
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 score0.223
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.012
GPT teacher head0.247
Teacher spread0.235 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

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