12 A qualitative study of factors that helped prepare athletes for Special Olympics sport programs
Bibliographic record
Abstract
Abstract Primary Subject area Developmental Paediatrics Background Special Olympics (SO) is working to introduce more child and youth programs provincially and improve currently available programs. To date, there is little research published surrounding the experiences of SO athletes. Given the aim of SO to improve and grow the experience and health of youth, the present study explores the experiences of SO athletes and caregivers to understand what prepares athletes for SO programs and competition. Objectives 1. To describe the experience of SO athletes and caregivers and understand what best prepared them for their involvement in organized sport and physical activity. 2. To offer evidence-based strategies for creating an inclusive and encouraging environment for sports and physical activity for healthy active living and/or preparation for SO involvement. Design/Methods Both athletes and caregivers participated in semi-structured, conversation-based interviews. Eight English-speaking athletes involved in a variety of sports from around the province were interviewed, and four of these interviews included caregivers. Interviews were transcribed and coded using thematic analysis. Results Five themes were identified throughout these interviews. The importance of a supportive environment emerged as a strong theme. Athletes valued the support of caregivers, coaches, and other players and felt this helped them improve and garner more enjoyment from their sport. Many athletes and caregivers discussed what motivated them to get involved and stay involved in SO. Common motivators included: a healthy, active lifestyle, friendships, and social skills. Barriers to involvement also were commonly discussed and included parental support, transportation, dissemination of information, and health concerns. Additionally, many athletes and caregivers felt that early involvement, starting with the basics, was important for developing skills to help transition to sports and competition. Finally, types of programming, including non-specialized vs. specialized activities, were discussed. Advantages of non-specialized activities included more time for practice and integration into society. Conclusion It is important that programs create a supportive environment, as this helps athletes improve and leads to further enjoyment. There is benefit to participation in non-specialized activities. Future programs could consider the addition of inclusive activities, or promotion of these activities. The motivators for involvement should be encouraged, including friendships/social skills and a healthy/active lifestyle. The barriers identified should be addressed when developing programming. Early involvement and learning basic motor skills play an important role in preparing athletes for sports, and competition and may lead to further involvement in sports. Early participation should be encouraged, and programs should find ways to reach more of this population, possibly through schools or physicians.
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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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".