Airway clearance therapy: experiences and perceptions of adults living with cystic fibrosis
Bibliographic record
Abstract
Purpose: Adherence to airway clearance therapy (ACT) among individuals with cystic fibrosis (CF) is often inconsistent. This study aims to explore the perceptions of adults with CF regarding their experiences with ACT and what influences their selection of specific ACTs. Findings may help inform clinician approaches to patient care and ACT. Materials and Methods: A qualitative descriptive study was conducted using individual, semi-structured interviews. Eight participants [six male and two female, median (min–max) age 42.5 (27–52)] were purposively recruited from the Toronto Adult CF Centre at St. Michael’s Hospital, Unity Health Toronto. Results: Four key themes were generated from participants’ accounts. First, they described the intensive nature of CF self-management and its influence on their perceptions and selection of ACT techniques. Second, they emphasized the importance of healthcare professional guidance in treatment decisions. Third, physical health status, exercise, and CF transmembrane conductance regulator modulator therapy also shaped participants’ self-management approaches. Lastly, their social context influenced how they navigated self-management, which evolved over time. Conclusion: This study shows that ACT technique selection is influenced by various evolving needs across the lifespan. Understanding the role that patient experiences play in ACT technique selection may help clinicians personalize recommendations and promote patient-centred care.
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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 | 0.008 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".