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Record W2078884365 · doi:10.1300/j013v44n01_01

The Association Between Disordered Eating and Substance Use and Abuse in Women: A Community-Based Investigation

2006· article· en· W2078884365 on OpenAlexaff
Niva Piran, Shannon R. Robinson

Bibliographic record

VenueWomen & Health · 2006
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDietingPsychiatryEating disordersClinical psychologySubstance abuseDisordered eatingMedicineSubstance usePillPsychologyAlcohol use disorderSubclinical infectionObesityAlcoholWeight loss

Abstract

fetched live from OpenAlex

A behavioral analysis was conducted of various eating disorder behaviors and their relationship with the lifetime use of different substances in a community-based sample of young adult women, aged 18-25 years. Women with particular eating disorder behaviors were selected from the 517 women who completed the Women's Health Survey. Analyses compared the frequencies of lifetime use of a range of licit and illicit substances as well as the abuse of prescription medications between each of the eating disorder groups and the normal control group. Results showed that as eating disorder behaviors became more severe, or were clustered together, the number of substance classes used, increased. Severe bingeing was consistently associated with alcohol use. Dieting and purging, with or without bingeing, was associated with the use of stimulants/ amphetamines and the abuse of sleeping pills. The results of this study suggest that the co-occurrence between subclinical levels of eating disorders and the use and abuse of a wide range of substances should inform assessment and treatment planning for adult women.

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)0.002
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 score0.040
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.035
GPT teacher head0.302
Teacher spread0.267 · 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

Citations46
Published2006
Admission routes1
Has abstractyes

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