Impact of adolescent dance participation on the development of disordered eating habits
Bibliographic record
Abstract
Dancers and adolescents are high-risk groups for developing disordered eating behaviors, making it critical to understand these eating behaviors for developing effective prevention and treatment strategies. However, there is limited literature on the impact of adolescent dance participation on the development of disordered eating, with even fewer studies addressing the potential long-term effects. This paper reviews current literature on eating disorders in the context of dance, while integrating insights from a neurocognitive perspective. It identifies the risk factors contributing to disordered eating in adolescent dancers and examines how these behaviors can develop into habits over time. The review suggests that these persistent disordered eating habits pose significant treatment challenges, emphasizing the need to break them early. Effective strategies involve reducing stimuli that reinforce unhealthy behaviors and shifting the dance community’s focus from appearance to health and skill. Long-term effects of disordered eating in adolescent dancers may extend beyond their dance years, potentially impacting brain health. This highlights the need for holistic treatment strategies that address both emotional disorders and disordered eating. Additionally, the review recommends integrating recreational dance into school curricula and community settings to promote collaborative, health-focused activities that enhance adolescent dancers’ well-being and cultural understanding. Future research should prioritize longitudinal studies to track the progression of disordered eating in adolescent dancers and their potential development into clinical eating disorders.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".