The Relationship between Passion and the Psychological Weil-Being of Professional Dancers
Bibliographic record
Abstract
The Dualistic Model of Passion defines passion as an intense desire or enthusiasm for a self-defining activity that people love, consider important, and devote significant amounts of time and energy to. The model proposes two distinct types of passion, harmonious (HP) and obsessive (OP). HP occurs when the activity is autonomously internalized into the individual's life and identity, while OP is a result of a controlled internalization of the activity. The aim of this study was to investigate the prevalence and type of passion professional dancers have for dance in relation to their psychological well-being, specifically eating attitudes, self-esteem, and perfectionism. Participants were 92 professional dancers, aged 19 to 35 years (M = 27.03, SD = 3.84), and mostly from the United States, the United Kingdom, and Canada. Results revealed that HP positively predicted self-esteem (SE), while OP positively predicted self-evaluative perfectionism (SEP), conscientious perfectionism (CP), and disordered eating attitudes (EAT-26). Additionally, SEP was found to mediate the relationship between OP and EAT-26, suggesting that OP may lead to SEP, which could in turn motivate disordered eating. Overall, the results of this study have supported and extended previous research suggesting that the two types of passion can have divergent effects on aspects of psychological well-being. Findings indicate that HP should be encouraged and OP discouraged among dancers, for example, via autonomy supportive behaviors of teachers.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".