Acceptability of an oscillating positive expiratory pressure (OPEP) device by respiratory disease patients
Bibliographic record
Abstract
Introduction: Despite OPEP therapy being an established treatment, device satisfaction among users is not well understood. In this study, we investigated whether the Aerobika* OPEP device (TMI) is considered effective and accepted by patients with various respiratory diseases. Methods: A survey was sent out to patients across Canada who were registered with myAerobika*, a voluntary platform for Aerobika* OPEP users. Questions included asking which symptoms patients found most bothersome, which device attributes were most important, and device satisfaction. Depending on the question, patients were to select one or multiple provided responses. Results: Data was analyzed from 151 patients. Conditions included COPD/chronic bronchitis (n=75), bronchiectasis (n=31), asthma (n=13), respiratory infection (n=12), cystic fibrosis (n=5), and other (n=15). 75% and 60% of patients selected excess mucus or shortness of breath as their first or second most bothersome symptom, respectively. This finding was generally independent of disease type. In terms of the most important device attributes, 70% of patients valued being easy to use and clean. Regarding device satisfaction, 60% of patients were extremely satisfied or very satisfied with the device’s ability to clear mucus, and 58% reported such satisfaction for ability to improve breathing. 85% and 81% of patients were extremely or very satisfied with the device being easy to use and easy to clean, respectively. Finally, the device scored 8.3/10 in terms of likelihood of continued use. Conclusion: Respiratory disease patients provided favorable feedback for the OPEP device, in terms of both addressing symptom concerns and usability.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".