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Record W4389317094 · doi:10.1123/jcsp.2023-0025

Predictive Factors for Compulsive Exercise in Adolescent Athletes: A Cross-Sectional Study

2023· article· en· W4389317094 on OpenAlexaff
Martine Fortier, Christopher Rodrigue, Camille Clermont, Anne‐Sophie Gagné, Audrey Brassard, Daniel Lalande, Jacinthe Dion

Bibliographic record

VenueJournal of Clinical Sport Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsUniversité de MontréalUniversité de SherbrookeUniversité LavalUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsAthletesPsychologyPerfectionism (psychology)AnxietyClinical psychologyDisordered eatingIntervention (counseling)Eating disordersPsychiatryPhysical therapyMedicine

Abstract

fetched live from OpenAlex

Although exercise is generally considered a healthy lifestyle habit, it may be problematic for some people. This has led to growing research on compulsive exercise—an uncontrollable urge for physical activity despite its deleterious effects. A maintenance model of compulsive exercise has been developed for adults exhibiting weight and shape concerns, weight control behaviors, and specific psychological states (including depression and anxiety) as predictive factors. We identified predicting factors for compulsive exercise in adolescent athletes using the same model framework. These athletes completed the compulsive exercise test and several well-validated psychometric measures. Gender-specific multiple regression models identified stronger drive for thinness, perfectionism, and body image investment in sport as significant predictors of compulsive exercise in boys and girls. Among girls, asceticism and bulimia symptoms were also significantly associated with compulsive exercise. These findings support the relevance of the model for clinical intervention and research on compulsive exercise in adolescent athletes.

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)0.003
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 score0.008
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.172
GPT teacher head0.523
Teacher spread0.352 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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