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Record W154487271 · doi:10.1093/pch/16.10.e71

Prevalence and risk indicators of smoking among on-reserve First Nations youth

2011· article· en· W154487271 on OpenAlexaffabout
Mark Lemstra, Marla Rogers, Adam Thompson, John Moraros, Raymond Tempier

Bibliographic record

VenuePaediatrics & Child Health · 2011
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSmoking prevalenceEnvironmental healthMedicineSuicidal ideationYouth smokingDemographyPublic healthSuicide preventionTobacco controlPoison controlPopulationNursingSociology

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the current prevalence of smoking among First Nations youth living on reserve within the Saskatoon Tribal Council, and to determine the independent risk indicators associated with smoking among First Nations youth. METHODS: Students in grades 5 to 8 attending school within the Saskatoon Tribal Council were asked to complete a youth health survey. RESULTS: Of 271 eligible students, 204 completed the consent protocol and the school survey, yielding a response rate of 75.3%; 26.5% of youth were defined as current smokers. Regression analysis indicated that older age, not having a happy home life, suicide ideation and having three or more friends who smoke cigarettes were independent risk indicators of smoking in First Nations youth. DISCUSSION: Smoking prevalence among on-reserve First Nations youth is quite high. The identification of four main risk indicators should assist with the design of youth smoking prevention and cessation programs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.979
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.283
Teacher spread0.253 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2011
Admission routes2
Has abstractyes

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