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Trajectories of BMI and internalizing symptoms: Associations across adolescence

2015· article· en· W1762712709 on OpenAlexaffabout
Megan E. Ames, Maxine Gallander Wintre, David B. Flora

Bibliographic record

VenueJournal of Adolescence · 2015
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsYork University
Fundersnot available
KeywordsPsychologyLatent growth modelingLongitudinal studyBody mass indexDepressive symptomsDevelopmental psychologyYoung adultAdolescent developmentClinical psychologyDemographyAnxietyPsychiatryMedicine

Abstract

fetched live from OpenAlex

The present study examined the longitudinal relations between body mass index (BMI) and internalizing symptoms among youth ages 10-17. Adolescents were selected from Statistics Canada's National Longitudinal Survey of Children and Youth (NLSCY). Latent growth curve modeling was used to investigate: 1) whether initial level (at age 10) or change in BMI were associated with changes in internalizing symptoms; and, 2) whether initial level or change in internalizing symptoms were associated with changes in BMI across adolescence. Associations between trajectories differed for boys and girls. Boys who started out with higher BMI experienced more internalizing symptoms across early- to mid-adolescence, but not more depressive symptoms at ages 16 and 17. For girls, there was a bidirectional relation between BMI and internalizing symptoms which persisted into later adolescence. Results suggest the bidirectional relation between BMI and internalizing symptoms is more salient for girls than for boys.

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)0.003
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 score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.042
GPT teacher head0.361
Teacher spread0.319 · 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

Citations15
Published2015
Admission routes2
Has abstractyes

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