The Effectiveness of a Pain Management Program on Intensify of Pain and Quality of Life Among Cancer Patients in Myanmar
Bibliographic record
Abstract
Introduction: Cancer is one of the leading causes of death worldwide and is rapidly becoming a global pandemic. Cancer pain significantly affects the diagnosis, quality of life and survival of patients with cancer. The aim of this study is to analyse the effect of a Pain Management Program (PMP) on pain and quality of life in a patient with cancer.Methods: This study used a quasi-experimental design with a randomised pre-post test design approach. The data was collected from cancer patients in No 2 Military Hospital (500-Bedded), Yangon, Myanmar. The patients were recruited using a random allocation sampling technique and consisted of 30 respondents (experimental group) and 30 respondents (control group) taken according to the inclusion criteria. The Short Form-McGill Pain Questionnaire 2 (SF-MPQ 2) was used to assess pain, and The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30) was used to assess the quality of life.Results: A MANOVA test was used to analyse the effect of PMP. It showed that 1) PMP decreased the pain and 2) PMP increased the quality of life in patients with cancer.Conclusion: Improvements in the quality of life and to do with pain-related cancer suggests that the vicious cycle of chronic pain may be alleviated by PMP. As we look at the results, PMP can be an effective treatment to be used by nurses for decreasing pain and increasing the quality of life in patients with cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".