The effects of positioning and pursed-lip breathing exercise on dyspnea and anxiety status in patients with chronic obstructive pulmonary disease
Bibliographic record
Abstract
Background and objective: Chronic obstructive pulmonary disease (COPD) remains a significant burden for health. It is one of the most common respiratory disease and leads to limitation of airflow as well as deteriorating health status. The aim of the study was to determine the effects of positioning and pursed lip breathing exercise on dyspnea and anxiety status in patients with chronic obstructive pulmonary disease.Methods: The study was carried in the outpatient clinics in Mansoura University Hospital & Chest Hospital at Mansoura region, utilizing a quasi-experimental study design on sixty patients diagnosed COPD. Participation was randomized into both groups (study group and control group). Pretest, posttest and follow-up evaluation was done using Dyspnea Assessment Scale, Anxiety Assessment Scale and Demographic and Medical History Questionnaires (MHQ). The researcher established exercise program aimed at effecting dyspnea and anxiety in chronic obstructive pulmonary disease patients to help improve breathing and control anxiety. The research was accomplished over four steps namely assessment, planning, implementation and evaluation. Each patient was evaluated at baseline, immediately and three months after implementation of program.Results: There were statistically significant improvements after intervention of program on dyspnea symptoms and anxiety status at post and follow-up test (p < .05). There was a statistically significant improvement in temperature (T), heart rate (HR), blood pressure (BP) and respiratory rate (RR) throughout study (p < .05) after intervention. Also there are positive relation between anxiety and dyspnea after intervention.Conclusions: Developing breathing technique and forward leaning position in COPD patients help to improve physiological outcomes, dyspnea symptoms and anxiety status after implementing of program. It is recommended to implement exercise training program as a part of treatment by health professionals in the clinical setting.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".