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Record W2736298090 · doi:10.1037/adb0000296

The association between nonmedical use of prescription drugs and extreme weight control behavior among adolescents.

2017· article· en· W2736298090 on OpenAlexaff
Sherry Owens, Keith J. Zullig, Amanda L. Divin, Emily Johnson, Robert M. Weiler, J. David Haddox

Bibliographic record

VenuePsychology of Addictive Behaviors · 2017
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsPurdue Pharma (Canada)
FundersPurdue Pharma
KeywordsMedical prescriptionPillMedicinePsycINFOPsychiatryPsychologyMEDLINEPharmacology

Abstract

fetched live from OpenAlex

Although extreme weight control behavior (EWCB) is associated with substance use, no research has examined the association between the nonmedical use of prescription drugs (NMUPD) and EWCB. Self-report data were collected from a sample of 4,148 students in Grades 9-12 enrolled in 5 high schools across the United States. Logistic regression models were constructed to examine the nonmedical use of prescription pain relievers, depressants, stimulants, and a composite measure for any NMUPD, and the EWCB of fasting, use of diet pills, powders, or liquids, and vomiting or laxative use. Models were estimated before and after controlling for key covariates for males and females. Approximately 16% of respondents reported any EWCB during the past 30 days, while 11% reported any NMUPD during the past 30 days. After covariate adjustment, any NMUPD was associated with any EWCB in both males and females (p < .05), and all EWCB remained significant in females who reported prescription pain reliever use (p < .01), with 2 out of 3 remaining significant for prescription stimulant and depressant use (p < .01). The only significant association detected for males was between prescription pain reliever use and using diet pills, powders, or liquids (OR = 2.2, p < .01). Results suggest significant associations between NMUPD and EWCB, with variations by sex. These findings provide directions for additional research and point to several potential identification and intervention efforts. (PsycINFO Database Record

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)0.001
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 score0.028
Threshold uncertainty score0.886

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.034
GPT teacher head0.329
Teacher spread0.294 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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