An investigation into the associations between psychological skills, anaerobic fitness, and aerobic fitness in elite Iranian taekwondo athletes
Bibliographic record
Abstract
This study investigated the relationship between psychological skills and fitness levels among elite taekwondo athletes. A total of ten Iranian male elite taekwondo athletes (mean age of 20.6±2 years, BMI 18.78±0.62 kg/m2, and fat percentage of 8.87±1.46%) participated in the study. The Sports Emotional Intelligence Questionnaire, Sports Success Scale, Sport Mental Toughness Questionnaire, and Mindfulness Inventory for Sport were used to assess psychological factors. The Wingate test was used to determine anaerobic power, and the Bruce test to determine aerobic fitness. Descriptive statistics and Spearman rank correlation coefficients were utilised to examine any relationships between subscales. Statistically significant correlations were recorded between the evaluation of feelings (EI scale) and VO2peak (ml/kg/min) (r = -0.70, p = 0.0235) and between social skills (EI scale) and relative peak power (W/kg) (r = 0.84, p = 0.0026). Also, between optimism (EI scale) and VO2peak (ml/kg/min) (r = -0.70, p = 0.0252) and between optimism (EI scale) and HR-MAX (r = -0.75, p = 0.0123); and, finally, between control (mental toughness scale) and relative peak power (W/kg) (r = 0.67, p = 0.0360). These findings demonstrate relationships between psychological factors and the advantages of good anaerobic and aerobic capabilities. Finally, the study also demonstrated that elite taekwondo athletes have high mental performance abilities that are interrelated with anaerobic and aerobic performance.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".