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Record W2022689708 · doi:10.1037/0893-164x.21.3.420

Environment modifies the association between depression symptoms and smoking among adolescents.

2007· article· en· W2022689708 on OpenAlexaffabout
Michael Chaiton, Bo Zhang

Bibliographic record

VenuePsychology of Addictive Behaviors · 2007
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDepression (economics)DemographicsPsychologyAssociation (psychology)Clinical psychologyPsychiatryDemography

Abstract

fetched live from OpenAlex

Previous studies have shown a strong correlation between depression and smoking, but the mechanism underlying the relationship is not well understood. This study examined whether the prevalence of smoking in schools influences the relationship between smoking and depression symptoms at the individual level. Information on demographics, tobacco use, and depression symptoms for 3,382 students in Grades 7-12 from 126 schools in Ontario, Canada, was obtained from the 2003 Ontario Student Drug Use Survey (E. Adlaf & A. Paglia, 2003). The effect of school-level smoking was strongly negative (coefficient = -1.05, p = .01), suggesting that depression and smoking at the individual level were strongly related in schools with a lower smoking prevalence but that this relationship diminished as the prevalence of smoking increased. Contextual effects may be important to understanding the link between smoking and depression in adolescents.

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 score0.031
Threshold uncertainty score0.427

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)0.0000.000

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 head0.018
GPT teacher head0.311
Teacher spread0.293 · 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

Citations6
Published2007
Admission routes2
Has abstractyes

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