Clinicians’ priorities for exercise programming for people receiving peritoneal dialysis: Qualitative content analysis from an international survey
Bibliographic record
Abstract
Exercise and physical activity have been shown to improve health outcomes among people receiving peritoneal dialysis (PD), however, little is known about PD clinicians' perceptions and practices regarding exercise counselling. To inform exercise program design and implementation, we distributed a cross-sectional online questionnaire to PD clinicians between July and December 2021 through professional nephrology societies and networks. As part of this survey, participants were asked, "What are the most important aspects you would like to see incorporated in an exercise program for PD patients?" Six hundred and nine respondents provided 1249 unique perspectives. Responses were coded using summative content analysis and grouped into themes. The overarching theme identified was the need for individualized and accessible programming. Under this umbrella, the four main sub-themes identified were: promotion of specific exercises, overcoming common barriers to exercise, perceived cornerstones of exercise prescriptions, and program design to address patient-relevant outcomes. Overall, PD clinicians believed that PD does not preclude exercise participation and recognized the potential for exercise to improve physical, mental, and social well-being. The involvement of exercise professionals was valued in PD clinical programs. However, additional education for practitioners and patients regarding safety and the benefits of exercise is required to assist in widespread implementation and acceptance of exercise programming in the PD population.
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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 | 0.021 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".