تأثیر آموزش هوش هیجانی بر مهارت های روانی نوجوانان ورزشکار
Bibliographic record
Abstract
The aim of the present research was to investigate the effect of emotional intelligence training on mental skills in athlete teenagers. For this purpose, 80 volunteer students (40 boys and 40 girls, mean age of 15±0.53 years) were selected with simple random sampling method and divided into two experimental and control groups. Bradberry and Greaves emotional intelligence questionnaire was used to measure emotional intelligence and Ottawa Mental States Assessment Tool (OMSAT 3) to measure mental skills. Also, the questionnaires used in Iran were reliable and valid. The program of emotional intelligence skill training to teenager athletes lasted 10 sessions. Data were analyzed using consistency of variances, Kolmogorov Smirnov test and independent t test (the mean comparisons of the two groups based on the difference of scores between pretest and posttest) at P<0.05. Results showed a significant difference between posttest means in the two groups in four components of emotional intelligence (self-awareness, self-management, social awareness and relationship management) and mental skills (P˂0.05). Thus, it seems that the training of emotional intelligence skills is one of the important parts of mental preparation that is necessary to achieve optimum athletic 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 | 0.001 | 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.013 |
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".