Motivations of wheelchair curling athletes to participate in sport: a qualitative research
Bibliographic record
Abstract
Introduction: Self-Determination Theory (SDT) is a holistic approach that provides a comprehensive framework for understanding individuals' intrinsic and extrinsic motivations, analyzing the nature of motivation and its relationship with psychological development. This study employs the SDT framework to examine the motivational processes of wheelchair curling athletes. Methods: This qualitative study involved eleven wheelchair curling athletes. Data were collected through a personal information form and semi-structured interviews. The collected data were analyzed using thematic analysis, and themes related to athletes' motivational experiences were identified. Results: The findings revealed that the motivation of wheelchair curling athletes to participate in sport is influenced by both intrinsic and extrinsic factors. Intrinsic motivation, nourished by physical, emotional, and social sources, strengthens athletes' participation in curling, enhances their enjoyment, and reinforces their commitment to the sport. In contrast, extrinsic motivation is shaped by elements such as external regulation, introjected regulation, identified regulation, and integrated regulation. However, a motivation mainly stems from lack of resources and organizational deficiencies, which negatively affect athletes' participation in and continuity of the curling sport. Discussion: The study emphasizes the importance of individual and structural factors influencing the motivation of wheelchair curling athletes. Strengthening organizational support and improving resource accessibility can enhance athletes' intrinsic motivation, thereby promoting participation and sustainability in adapted sports.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".