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Smoking, alcohol consumption, and drug use among adolescents with psychiatric disorders compared with a population based sample

2014· article· en· W1974240748 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Adolescence · 2014
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsTellabs (Canada)
FundersSt. Olavs Hospital Universitetssykehuset i TrondheimHelse Midt-NorgeNorges Teknisk-Naturvitenskapelige Universitet
KeywordsPsychiatryPopulationMood disordersOddsIllicit drugMoodPsychologyMedicineClinical psychologyDrugLogistic regressionEnvironmental healthAnxiety

Abstract

fetched live from OpenAlex

This study investigated frequencies of smoking, alcohol use, and illicit drug use by diagnostic category in 566 adolescent psychiatric patients, comparing this sample with 8173 adolescents from the general population in Norway who completed the Young-HUNT 3 survey. Frequencies of current alcohol use were high in both samples but were lower among psychiatric patients. Compared with adolescents in the general population, adolescents in the clinical sample had a higher prevalence of current smoking and over four times higher odds of having tried illicit drugs. In the clinical sample, those with mood disorders reported the highest frequencies of smoking, alcohol use, and illicit drug use, whereas those with autism spectrum disorders reported the lowest frequencies. Our results show an increased prevalence of risky health behaviors among adolescents with psychiatric disorders compared with the general population. The awareness of disorder-specific patterns of smoking and substance use may guide preventive measures.

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.

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 score0.010
Threshold uncertainty score0.439

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 head0.020
GPT teacher head0.272
Teacher spread0.252 · 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