بررسی ارتباط مهارت های روانی با آسیب بازیکنان فوتبال تیم های تهرانی لیگ برتر ایران
Bibliographic record
Abstract
Introduction: Numerous empirical studies suggest that specific psychological factors influence the frequency and severity of sport injuries. Method: The aim of present study was to examine the relationship between fundamental psychological skills, psycho-somatic skills, cognitive skills and incidence of injuries in football players of Tehran premier league. 108 players from four teams of Iran premier league participated in the study. Research data was collected by injury report form and Ottawa mental skills assessment tool-3. Pearson correlation test at significant level of 95% were used for analyzing the data. Result: Results indicated that 89.5% of players experienced at least one injury during one season which 90.7 % of them resulted in 1-3 days missing of match or training. The findings also indicated that in football players of premier league there is inverse and significant relationship between psychological skills (p=0/0001) and its subdivisions including fundamental psychological skills (p=0/006), psycho-somatic skills (p=0/0001), cognitive skills (p=0/0001) and incidence of sport injuries. Conclusion: The findings of present study show that having high levels of psychological skills helps premier league players to handle stressful situations in sports through enhancing self-confidence and other psychological factors confronting harmful psychological factors such as stress and anxiety and lead to decrease in injury incidence. Thus officials, coaches, physicians and sport psychologists are recommended to educate essential psychological skills.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.036 | 0.008 |
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".