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Record W4239333158 · doi:10.32920/ryerson.14645028

The long-term impact of an eating disorder prevention program for elite athletes: a follow-up study

2021· preprint· en· W4239333158 on OpenAlexaff
Rachel J. Bar

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBalletAthletesIntervention (counseling)Disordered eatingPsychological interventionPsychologyEating disordersMedicineWeight managementElite athletesPhysical therapyDanceGerontologyWeight lossClinical psychologyObesityPsychiatry

Abstract

fetched live from OpenAlex

Elite athletes involved in weight-based sports are at increased risk of developing eating disorders (EDs). While the utility of ED prevention programs has been assessed up to three years post-intervention, it is unclear whether participation in such interventions promotes any resilience against EDs in the long-term. To address this, the current study assessed self-reported disordered eating and body dissatisfaction in ballet dancers 15 or more years after participating in a reportedly successful ED prevention program at a professional ballet school. Graduates of the school before, during, and after the intervention were surveyed, and scores were compared across groups. Results revealed dancers who participated in the intervention and those who attended post-intervention endorsed fewer thoughts and behaviours associated with bulimia, had lower lifetime prevalence of laxative use, and showed a trend toward lower lifetime rates of vomiting to control weight than those who attended the ballet school prior to the intervention.

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)0.002
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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.043
GPT teacher head0.424
Teacher spread0.381 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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