Quality of Life After Pulmonary Rehabilitation: Assessing Change Using Quantitative and Qualitative Methods
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The purpose of this study was to use quantitative and qualitative research methods to evaluate quality-of-life (QOL) changes in patients with chronic obstructive pulmonary disease after pulmonary rehabilitation. SUBJECTS: Twenty-nine individuals with COPD (18 women and 11 men), with a mean age of 69 years (SD=8.6, range=53-92), participated. METHODS: Subjects were assessed before and after a 5-week control phase and after a 5-week rehabilitation phase using the Chronic Respiratory Questionnaire (CRQ), the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36), and spirometry. Our qualitative research was based on a subsample of 7 subjects who were interviewed after pulmonary rehabilitation. RESULTS: Pulmonary rehabilitation improved QOL, as demonstrated by increases of 22% and 14% in the physical function categories of the CRQ and the SF-36, respectively, and by an increase of 10% in the CRQ's emotional function category. The qualitative data indicated how pulmonary rehabilitation influenced QOL. CONCLUSION AND DISCUSSION: The use of both quantitative and qualitative methods illustrated the nature of improvement in QOL after pulmonary rehabilitation. Improved physical function, less dyspnea, and a heightened sense of control over the subjects' COPD resulted in increased confidence and improved emotional well-being.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.055 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".