Participant-selected music listening during pulmonary rehabilitation in people with chronic obstructive pulmonary disease: A randomised controlled trial
Bibliographic record
Abstract
To evaluate the impact of participant-selected music listening as an adjunct to pulmonary rehabilitation (PR) in people with COPD. Adults with COPD referred to PR were randomly assigned to participant-selected music listening (intervention group, [IG]) or usual care (control group [CG]) during an 8-weeks PR program. Prior to training, the IG completed an interview with a registered music therapist to identify music preferences. IG participants listened to an individualised playlist; CG participants had usual care. Primary outcomes included end-6-min walk test symptoms (dyspnoea and exertion) and dyspnoea (Multidimensional Dyspnoea Profile [MDP]), measured pre and post PR and 6-months follow-up. 58 participants, FEV1 52.4 (25.9)% pd) were recruited. There were no between-group differences following the intervention ( p > .05 for all outcomes at all time points). Within-group differences following PR were significant for MDP sensory quality: IG mean difference [95% CI] −2.2 [−3.3 to −1.2]; CG −1.5 [−2.5 to −0.5] points; MDP emotional response: IG −3.2 [−4.2 to −2.3]; CG −2.2 [−3.2 to −1.3] points). Participant-selected music listening during PR offered no greater benefit to symptoms of dyspnoea or exertion compared to usual care. With the study limited by COVID-19 restrictions, the role of this adjunct remains to be clarified.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".