Female paralympic athlete preferences of effective coaching practices
Bibliographic record
Abstract
According to the World Health Organization (World Health Organization, 2016), over one billion people, or 15% of the population, have some type of disability. In Canada, approximately 3.8 million people reported having a disability, and over three million adults (11%) reported having a physical disability (Statistics Canada, 2012a). People living with physical disabilities are at a higher risk of developing secondary physical and mental health conditions such as fatigue, obesity, and depression (Goodwin & Compton, 2004; Heron, Kee, Cupples, & Tully, 2015). The occurrence of secondary conditions has been associated with a lower quality of life and decreased independence for people with a physical disability (Motl & McAuley, 2014). Physical activity is one way to decrease the severity and prevalence of these secondary conditions (Goodwin & Compton, 2004). One type of physical activity is sport, which has been identified as a way of providing many psychological, physiological, and social benefits for people with a physical disability (Stephens, Neil, & Smith, 2012). The largest sporting competition for elite athletes with a physical disability is the Paralympic Games and despite the exponential growth of the Games, the same growth and development has not occurred with empirical literature in this context, for either the coaches or the athletes participating in this event. Additionally, most of the samples in elite disability sport have been male only or mixed gender, most attributable to the small proportion of female athletes competing as a Paralympian. Thus, the purpose of the current study was to explore female Paralympic athlete preferences of effective coaching practices. Individual semi-structured interviews were conducted with eight female Paralympic athletes who each attended multiple Paralympic Games and achieved an average of eight combined Paralympic and Para Pan American medals. Interviews were transcribed verbatim and organized into themes and subthemes using thematic analysis, which provided the reader with a comprehensive understanding of each participants' experience (Braun & Clarke, 2013; Sparkes & Smith, 2014). Results from the analysis revealed that athletes preferred coaches who were able to adapt to the various needs of the individual, were knowledgeable of their sport, engaged in effective communication, and challenged athletes to reach their potential. Athletes also described negative coaching experiences and described coaches who insulted them based on their gender and disability, and engaged in selfish or manipulative behaviours. The athletes felt the coaches' behaviours impacted their satisfaction and success on both a personal and professional level. These results add to the small body of coaching knowledge in disability sport, and is one of the first studies to include an all-female sample of Paralympic athletes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".