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Record W4283167587 · doi:10.1186/s40337-022-00603-z

Developmental trajectories of eating disorder symptoms: A longitudinal study from early adolescence to young adulthood

2022· article· en· W4283167587 on OpenAlexafffund
Édith Breton, Rachel Dufour, Sylvana M. Côté, Lise Dubois, Frank Vitaro, Michel Boivin, Richard E. Tremblay, Linda Booij

Bibliographic record

VenueJournal of Eating Disorders · 2022
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsMcGill UniversityUniversité de MontréalUniversité LavalUniversity of OttawaConcordia UniversityCentre Hospitalier Universitaire Sainte-Justine
FundersFonds de Recherche du Québec - SantéFondation Lucie et Andre ChagnonCanadian Institutes of Health ResearchCentre hospitalier universitaire Sainte-Justine
KeywordsEating disordersFeelingOverweightPsychologyLongitudinal studyCohortYoung adultDemographyObesityClinical psychologyMedicinePediatricsDevelopmental psychologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Adolescence is a critical period for the development of eating disorders, but data is lacking on the heterogeneity of their evolution during that time-period. Group-based trajectories can be used to understand how eating disorders emerge and evolve over time. The aim of this study was to identify groups of individuals with distinct levels of eating disorder symptoms between 12 and 20 years and the onset of different types of symptoms. We also studied sex differences in the evolution and course of eating disorder symptoms from early adolescence to adulthood. METHODS: Using archival data from the QLSCD cohort, trajectories of eating disorder symptomatology were estimated from ages 12 to 20 years using semiparametric models. These trajectories included overall eating disorder symptomatology as measured by the SCOFF (Sick, Control, One Stone, Fat, Food), sex, and symptom-specific trajectories. RESULTS: Two groups of adolescents following distinct trajectories of eating disorder symptoms were identified. The first trajectory group included 30.9% of youth with sharply rising levels between 12 and 15 years, followed by high levels of symptoms between 15 and 20 years. The second trajectory group included 69.1% of youth with low and stable levels of symptoms between 12 and 20 years. Sex-specific models indicated that the proportion of girls in the high trajectory group was 1.3 times higher than the proportion of boys (42.8% girls vs. 32.3% boys). Trajectories of SCOFF items were similar for loss-of-control eating, feeling overweight, and attributing importance to food. The weight loss item had a different developmental pattern, increasing between 12 and 15 years and then decreasing between 17 and 20 years. CONCLUSIONS: The largest increase in eating disorder symptoms in adolescence is between the ages of 12 and 15 . Yet, most prevention programs start after 15 years of age. Our findings suggest that, unlike common practices, eating disorder prevention programs should aim to start before puberty.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalmedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.034
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.018
GPT teacher head0.298
Teacher spread0.280 · 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

Labeled directly by 2 models reading the full record.

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

Citations77
Published2022
Admission routes2
Has abstractyes

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