Impact of feedback on physical activity levels of individuals with chronic obstructive pulmonary disease during pulmonary rehabilitation
Bibliographic record
Abstract
This study aimed at investigating whether providing feedback on physical activity (PA) levels to patients with chronic obstructive pulmonary disease (COPD) is feasible and enhances daily PA during pulmonary rehabilitation (PR). Patients with COPD participated in a 12-week PR program. Daily PA was measured using activity monitors on weeks 1, 7, and 12, and feedback was given in the following weeks on the number of steps, time spent in sedentary, light, and moderate-to-vigorous intensity activities, and time spent standing, sitting, and lying. Compliance with PA monitoring was collected. Two focus groups were conducted to obtain patients' perspectives on the use of activity monitors and on the feedback given. Differences in PA data were also assessed. Sixteen patients (65.63 ± 10.57 years; forced expiratory volume in one second (FEV1) 70.31 ± 22.74% predicted) completed the study. From those, only eleven participants used the activity monitors during all monitoring days. Participants identified several problems regarding the use of activity monitors and monitoring duration. Daily steps (p = 0.026) and standing time (p = 0.030) were improved from week 1 to week 7; however, the former declined from week 7 to week 12. Findings suggest that using feedback to improve PA during PR is feasible and results in improved daily steps and standing time on week 7. The subsequent decline suggests that additional strategies may be needed to stimulate/maintain PA improvements. Further research with more robust designs is needed to investigate the impact of feedback on patients' daily PA.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".