Mental Skills in Norwegian Elite Swimmers: A cross-sectional study to investigate the sport specific mental skills of national elite swimmers and differences across gender and age
Bibliographic record
Abstract
Mental skills are important for athletes’ success. The goal of mental training in elite sport is to develop mental skills needed to achieve high level performance outcomes (Vealey, 2007). To reach a high level in any sport, a basic principle is that the physical training needs to be sport specific. This principle of specificity is also applicable for mental skills training. The best way to facilitate for high level performance in a sport is to incorporate the mental skills training with the physical training (Vealey, 2007), surely this is a reason to find out which mental skills that are important in the specific sport and for the individual athlete. The aims of this study were to provide an overview of Norwegian elite swimmers’ mental skills and to further suggest sport specific mental skills for swimming. Also, based on the conflicting findings in literature, we sought to identify if there were any differences in mental skills scores between gender (males/females) and age (senior/junior) in elite swimmers. To investigate this a cross-sectional study design was applied in form of a questionnaire, a translated version of the Ottawa Mental Skills Assessment Tool (OMSAT-3*; Durand-Bush et al., 2001) was used. This questionnaire had 48 items on 12 mental skill subscales, divided in to three broader psychological concepts (Foundation skills; goal setting, self-confidence, and commitment, Psychosomatic skills; relaxation, activation, stress reactions, and fear control, Cognitive skills; competition planning, imagery, mental practice, focusing, and refocusing). To further elaborate on mental skills in swimming, the differences between gender (female/male) and age (senior/junior) within the elite swimming population was analyzed. The results showed that Norwegian elite swimmers scored highest in the foundation skills: goal setting, self-confidence, and commitment. The results indicated differences between females and males in several of the mental skill subscales (self-confidence, activation, relaxation, stress reactions, imagery and focusing), no differences were found between senior and junior swimmers on the mental skill subscales. Results from multiple regression analyses indicated that selected mental skills (mental practice, focusing, activation, relaxation, and competition planning) contributed to the variance in the foundation skill scores. Swimming coaches should consider gender differences in mental training for elite swimmers. The results from the multiple regression analysis imply that mental practice, focusing, activation, relaxation and competition planning are important factors for the foundation skills scores in elite swimmers. This master thesis is written as a research article, including an extended introduction and method part. Firstly, the extended introduction and method is presented followed by the research article.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".