The ball's in our court: The development of sport-specific supportive care programming for testicular cancer survivors
Bibliographic record
Abstract
Testicular cancer is the most common cancer diagnosis in men aged 18 to 39 years. Although treatments have advanced, age appropriate supportive care targeting the management of challenging side-effects have yet to be developed. Physical activity (PA) has been shown to be safe and effective in improving health and well-being, yet integration into supportive care plans has yet to occur. Since the physical, emotional, and social benefits of PA are well known, sport programs may offer unique foundations for supportive care for testicular cancer survivors. As such, there exists an opportunity to build sustainable partnerships between cancer centres and existing sport programs. The main purpose of this study was to explore the feasibility of a sport-specific supportive care program for men with testicular cancer. Preliminary semi-structured interviews were held with key clinical and local sport stakeholders and patient end-users to identify enablers and barriers to involvement, feasibility, interest and required support for development and delivery. Data were analyzed using thematic content analysis, and emergent themes included: need for specialized programming; interest and support for a sport-specific care plan; athlete and trainer specific mentoring was available and important; desirable peer mentoring models; and sport program specifics (e.g., competition, technique, strategy). Given these findings, a peer mentoring sport program connecting varsity athletes to men with testicular cancer will be developed and tested for improvements in perceptions of care, quality of life, and well-being. The long-term goal is to build partnerships between local cancer clinics and sport organizations for improvements in personalized supportive care programming. Acknowledgments: This research is supported by a Faculty of Kinesiology and Physical Education Internal Grant.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".