The role of appearance-related self-conscious emotions in sport participation among adolescent girls
Bibliographic record
Abstract
Despite well-documented benefits of sport participation in adolescence, girls are less likely to participate, commit to and enjoy sport compared to boys. Due to the highly evaluative social nature of sport, body-related self-conscious emotions may be important yet understudied predictors of sport participation outcomes. The purpose of this longitudinal study was to (i) assess changes in appearance-related self-conscious emotions (e.g., shame, envy and pride) and (ii) predict changes to sport commitment, enjoyment, and competitive anxiety outcomes across 1-year and two competitive seasons. Adolescent girls participating in organized sport (n = 215; Mage = 14.15 ± 1.36 years, MBMI = 19.91 ± 2.82) reported significantly higher appearance-related shame and envy and significantly lower pride (p < .001) in the follow-up competitive season. Changes in appearance-related shame (AŸ = -0.21) significantly predicted sport enjoyment (R2adj = 0.05, p < 0.05). Similarly changes in appearance-related shame (AŸ = -0.31) predicted changes in sport commitment (R2adj = 0.13, p < 0.05). Meanwhile, changes in appearance-related envy (AŸ = 0.25) significantly predicted competitive anxiety (R2adj = 0.20, p < 0.05). Based on these findings, appearance-related self-conscious emotions are associated with poorer sport outcomes longitudinally for girls engaged in sport. Strategies are needed to reduce negative and increase positive self-conscious emotions in hopes of fostering adaptive sport outcomes in adolescent girls.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".