Addressing feasibility challenges to delivering intradialytic exercise interventions: a theory-informed qualitative study
Bibliographic record
Abstract
BACKGROUND: Intradialytic exercise (IDE) may improve physical function and health-related quality of life. However, incorporating IDE into standard hemodialysis care has been slow due to feasibility challenges. We conducted a multicenter qualitative feasibility study to identify potential barriers and enablers to IDE and generate potential solutions to these factors. METHODS: We conducted 43 semistructured interviews with healthcare providers and patients across 12 hospitals in Ontario, Canada. We used the Theoretical Domains Framework and directed content analysis to analyze the data. RESULTS: We identified eight relevant domains (knowledge, skills, beliefs about consequences, beliefs about capabilities, environmental context and resources, goals, social/professional role and identity, and social influences) represented by three overarching categories: knowledge, skills and expectations: lack of staff expertise to oversee exercise, uncertainty regarding exercise risks, benefits and patient interest, lack of knowledge regarding exercise eligibility; human, material and logistical resources: staff concerns regarding workload, perception that exercise professionals should supervise IDE, space, equipment and scheduling conflict concerns; and social dynamics of the unit: local champions and patient stories contribute to IDE sustainability. We developed a list of actionable solutions by mapping barriers and enablers to behavior change techniques. We also developed a feasibility checklist of 47 questions identifying key factors to address prior to IDE launch. CONCLUSIONS: Evidence-based solutions to identified barriers to and enablers of IDE and a feasibility checklist may help recruit and support units, staff and patients and address key challenges to the delivery of IDE in diverse clinical and research settings.
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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 | 0.046 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".