Relative energy deficiency in dance (RED-D): a consensus method approach to REDs in dance
Bibliographic record
Abstract
Relative energy deficiency in sport (REDs) is a potentially severe, challenging, broad-spectrum syndrome with potential negative health and performance outcomes. The numerous research publications and International Olympic Committee consensus statements relating to REDs testify to the challenges faced in early identification or screening, diagnosis and management. Like sport, dance, in its simplest form, can be identified as an activity resulting in physiological energy demands and, as such, requires appropriate energy availability concerning energy expenditures. However, the specificity of physiological and psychological demands in dance must be considered when considering REDs. An environment where physical activity can exceed 30 hours per week and where culture may instil a value that thinness is required puts dancers at increased risk for REDs. The purpose of this study was to provide dance-specific guidance dance on this complex condition. An RAND/UCLA Delphi Panel method with nominal group technique was used to review the literature from REDs to evaluate how it may relate to dance. In addition to the EP, which was assembled from a multidisciplinary background with expertise in REDs and multiple genres of dance, six focus groups were commissioned. Four of the focus groups were drawn from the EP members and two additional focus groups formed by dancers and artistic leaders. These panels were used to guide the development of a RED-D diagnosis pathway, management plan and risk stratification and return to dance pathway. The dance-specific pathways are designed to be a practical tool for guiding and supporting clinicians managing RED-D. Furthermore, this paper represents an important focus of this area in dance and serves to stimulate discussion and further research within the sector.
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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 | 0.242 | 0.206 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.019 | 0.015 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.007 | 0.018 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".