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Record W2069164404 · doi:10.1080/02791072.2013.825029

Non-Medical Use of Psychotropic Prescription Drugs Among Adolescents in Substance Use Treatment

2013· article· en· W2069164404 on OpenAlex
Tunde Apantaku-Olajide, Bobby P. Smyth

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 Psychoactive Drugs · 2013
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsDalhousie UniversityHorizon Health Network
Fundersnot available
KeywordsMedical prescriptionMedicinePsychiatrySubstance abusePrescription Drug MisuseSedativeStimulantPolysubstance dependenceOpioidPharmacologyOpioid use disorderInternal medicine

Abstract

fetched live from OpenAlex

Little is known about the extent of non-medical use of prescription drugs among European adolescents with substance use disorders. This cross-sectional study examined non-medical use of seven categories of psychotropic prescription drugs (opioid analgesics, ADHD stimulant, sleeping, sedative/anxiolytic, antipsychotic, antidepressant, and anabolic steroid medications) in a clinical sample of Irish adolescents with substance use disorders. Of the 85 adolescents (aged 13-18 years) invited to participate, 65 adolescents (M = 16.3 years, SD = 1.3) took part (response: 74%). Among respondents, 68% reported lifetime non-medical use of any of the prescription drugs; sedative/anxiolytic (62%) and sleeping medications (43%) were more commonly abused. The most frequently reported motives for abuse were "seeking high or buzz" (79%), "having good time" (63%), and "relief from boredom" (56%). Sharing among friends and street-level drug markets were the most readily available sources. Innovative solutions of control measures and intervention are required to address the abuse of prescription drugs.

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 score0.828

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 communication0.0000.002
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.318
Teacher spread0.282 · 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