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Decrease in Adolescent Cannabis Use From 2002 to 2006 and Links to Evenings Out With Friends in 31 European and North American Countries and Regions

2009· article· en· W2127533607 on OpenAlexaboutno aff
Emmanuel Kuntsche

Bibliographic record

VenueArchives of Pediatrics and Adolescent Medicine · 2009
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsnot available
FundersNational Institutes of HealthBundesamt für Gesundheit
KeywordsCannabisDemographyPsychologyGeographyPsychiatrySociology

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare adolescent cannabis use between 2002 and 2006 and to investigate links to the frequency of evenings spent out with friends. DESIGN: The Health Behavior in School-Aged Children study, an international study carried out in collaboration with the World Health Organization/Europe. SETTING: A total of 31 mostly European and North American countries and regions. PARTICIPANTS: A total of 93 297 students aged 15 years. OUTCOME MEASURE: Cannabis use in the last 12 months in relation to the mean frequency of evenings out with friends per week. RESULTS: A decrease in the prevalence of cannabis use was found in most of the 31 participating countries and regions. The most marked decreases were found in England, Portugal, Switzerland, Slovenia, and Canada. Increases occurred only in Estonia, Lithuania, Malta, and among Russian girls. The more frequently adolescents reported going out with their friends in the evenings, the more likely they were to report using cannabis. This link was consistent for boys and girls and across survey years. Across countries, changes in the mean frequency of evenings spent out were strongly linked to changes in cannabis use. CONCLUSIONS: The findings are consistent with the hypothesis that by going out less frequently in the evenings with friends, adolescents had fewer opportunities to obtain and use cannabis. Future research is needed to learn more about the nature of evenings out with friends and related factors that might explain changes in adolescent cannabis use over time.

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 score0.018
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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

Citations52
Published2009
Admission routes1
Has abstractyes

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