Community-based exercise program for solid organ transplant recipients: Views of exercise professionals and patients
Bibliographic record
Abstract
Purpose of the study: Although transplantation improves quality of life in solid organ transplant (SOT) recipients, recipients continue to have limitations in exercise capacity and decreased levels of physical activity (PA) years after transplant. Community Based Exercise (CBE) programs have been shown to successfully increase PA levels in other populations, however none exist for SOT recipients. Objective: To identify important factors when developing and implementing a CBE program for SOT recipients. Methods: We conducted a qualitative study using semi-structured interviews with seven SOT recipients, and six exercise professionals (EPs). The data was analyzed using thematic analysis. Main findings: Six themes were identified: 1) Motivators to exercise; 2) Perceived barriers to exercise (financial vulnerability post-transplantation, fear of injury, lack of exercise recommendations and medication side effect); 3) Level of supervision (recipients wanted guidance without overprotective supervision, while EPs were torn between extensive monitoring, and promoting independence); 4) Required education and foundational knowledge in EPs; 5) The importance of CBE programs for the SOT population; and 6) Tailored program structure (group setting with individualized exercise prescription). Principal conclusions: Recommendations may be used to develop an effective CBE program for SOT recipients, and thus improve PA levels among this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".