Editorial: Exercise and transplant sport—the journey to a more active life
Bibliographic record
Abstract
The goal of this special issue was to further our knowledge of exercise related responses in 13 organ-recipients from rehabilitation to competitive sport. The studies presented indeed reflect 14 our aim considering organ recipients over the first 12 months post-transplantation (Vecchiato et 15 al, 2024) to those competing nationally and internationally (Hames et al, 2024) and the support 16 received at such events (Duncan et al, 2024). Furthermore, the impact of high intensity training 17 was reviewed (Kayeye et al, 2024) and the utility of web-based exercise and training resources 18(Da Silva et al, 2024) and telehealth monitoring (Vecchiato et al, 2024) joy, hope and celebration of life to the complex interplay between gratitude and guilt, an aspect 69 that is not generally experienced in other competitions. With the health vulnerabilities of the 70 population, the service placed well-being first and performance second, with priority given to 71 listening to athletes' stories. The resultant emotional experiences of the group and emotional 72 labour of the Games placed considerable importance on peer supervision. Practical aspects of 73 signposting, access to the service and finding a quiet space for consultations at a live event 74were highlighted. For trainees the service provided an opportunity to work with a broader client 75 base than may usually be experienced. However, this re-emphasises the need for greater 76 resources, for athletes, early career practitioners and those new to working with organ 77 recipients, enabling volunteers to be fully prepared for supporting all involved. 78The need for clear educational resources is addressed by Da Silva et al (2024) in examining 79 online content and quality of website and video resources relating to physical activity, with a 80 focus on promoting engagement and adherence to activity post-transplant. Of the 49 resources 81 included, most were of low quality, understandability and actionability. More comprehensive 82 content scores were noted for resources from Foundations and advocacy websites than for 83 scientific organisations and news/media articles. Importantly, balanced and unbiased 84 information was frequently observed, although only the minority of sources discussed safety 85 and educational aspects, lacking in additional resources for reference. 86Overall, the studies comprising this special issue have demonstrated diverse interdisciplinary 87 work, utilising collaborative partnerships across aspects of applied research and practice. As practitioners and researchers in this area, we are responsible not only for ensuring integration of 89 this research into practice, but also facilitating future, truly international collaborations. The ball 90 is firmly in our court to enhance such developments as well as high quality resources for organ 91 recipients and those professionals beginning their practice journey within this population. 92 93 94
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.014 | 0.018 |
| Insufficient payload (model declined to judge) | 0.021 | 0.013 |
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".