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Record W2002301272 · doi:10.1080/10640260903439516

Family Dinner and Disordered Eating Behaviors in a Large Cohort of Adolescents

2009· article· en· W2002301272 on OpenAlexfundno aff
Jess Haines, Matthew W. Gillman, Sheryl L. Rifas‐Shiman, Alison E. Field, S. Bryn Austin

Bibliographic record

VenueEating Disorders · 2009
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesCanadian Institutes of Health Research
KeywordsDietingBinge eatingDemographyLogistic regressionDisordered eatingCohortMedicineIncidence (geometry)Longitudinal studyPsychologyAssociation (psychology)Eating disordersClinical psychologyWeight lossObesityInternal medicine

Abstract

fetched live from OpenAlex

We aimed to examine longitudinal associations between family dinner and disordered eating behaviors among adolescents. We studied 7535 females and 5913 males, 9 to 14 years of age in 1996. We performed multivariable logistic regression to assess the associations of previous year family dinner with 1-year incidence of each of 3 outcomes: purging, binge eating, and frequent dieting. Compared to those who ate family dinner "never or some days," female adolescents who ate family dinner at least most days were less likely to initiate purging, binge eating, and frequent dieting. Estimates of association among males were similar in direction and magnitude, although lower frequency of the outcomes resulted in less precise estimates and fewer statistically significant results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.293
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), 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

Citations76
Published2009
Admission routes1
Has abstractyes

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