Psychological predictors of injuries in circus artists: an exploratory study
Bibliographic record
Abstract
OBJECTIVES: To explore the relationship between potential psychological risk factors and injury risk in circus artists. DESIGN: Historical cohort study. SETTING: Cirque du Soleil training programme. PARTICIPANTS: Forty-seven circus artists training to become Cirque du Soleil artists. ASSESSMENT OF RISK FACTORS: Artists completed the validated REST-Q questionnaire (19 domains) during their first 2 weeks of training. MAIN OUTCOME: Injury risk ratio. RESULTS: Of the five a priori exposures of interest, injury, emotional exhaustion, self-efficacy and fatigue were associated with an increase in injury risk (risk ratios between 1.8 and 2.8), but Conflicts/Pressure was not (risk ratio=0.8). Of the several specific psychological aspects that are considered risk factors for injury, low self-efficacy had the strongest relationship. CONCLUSIONS: Most of the strong psychological risk factors for injuries previously identified in athletes also appear to be risk factors in circus artists.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".