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Record W1523792568 · doi:10.1177/070674371205701206

Adolescent Use of Prescription Drugs to Get High in Canada

2012· article· en· W1523792568 on OpenAlexafffundvenueabout
Cheryl L. Currie, T. Cameron Wild

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2012
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of AlbertaUniversity of Lethbridge
FundersHealth CanadaAlberta Innovates
KeywordsMedical prescriptionMedicinePrescription Drug MisusePsychological interventionPsychiatryPopulationFamily medicineSubstance abuseEnvironmental healthPharmacology

Abstract

fetched live from OpenAlex

OBJECTIVE: To present epidemiologic information on adolescent use of prescription drugs to get high, and not for medical purposes, in Canada. METHODS: Data were obtained from 44 344 adolescents in grades 7 to 12 living across Canada's 10 provinces who completed the Youth Smoking Survey in 2008/2009. RESULTS: Nationally, 5.9% of adolescents in grades 7 to 12 reported the use of prescription drugs to get high in the past 12 months in 2008/2009. Females were more likely to report use of pain relievers, sedatives, or tranquilizers to get high, while males were more likely to report the use of prescription stimulants for this purpose. The use of prescription drugs to get high was elevated among older youth, those living in British Columbia, and those who identified as First Nations, Métis, or Inuit. School connectedness was associated with a reduction in this form of prescription drug misuse for all adolescents; however, this protective effect was particularly strong for Aboriginal youth, and may be an important preventative factor for this population. CONCLUSIONS: Use of prescription drugs to get high was prevalent among adolescents in Canada in 2008/2009. Findings highlight the need for clinicians to include questions about prescription drugs when screening adolescents for substance abuse in Canada. Findings also highlight the need for evidence-informed strategies to reduce prescription drug misuse among Aboriginal youth living outside First Nations communities in Canada. The results of this study suggest school connectedness may be a particularly important target for these interventions.

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 score0.075
Threshold uncertainty score0.875

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 head0.022
GPT teacher head0.237
Teacher spread0.215 · 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

Citations47
Published2012
Admission routes4
Has abstractyes

Explore more

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