Effectiveness of Stress Management Consultation for Quality of Life and Stress of Women Suffering from Breast Cancer
Bibliographic record
Abstract
BACKGROUND: Breast cancer is the most common cancer among women which endangers different aspects like individual, public health, and life quality. OBJECTIVES: The aim of the present study is to investigate the consultation effectiveness of stress management on the quality of life and stress of women suffering from breast cancer. METHODS: A semi-experimental research was performed with pre- and post-test design as well as control and test groups. For this purpose, 104 women suffering from breast cancer who referred to Mahdiyeh MRI and Hamedan Donors Assembly in 2015 were selected based on convenience sampling and randomly placed in two test and control groups including 52 people using permutation blocks. The test group received 9 two-hour consultation sessions of stress management, but the control group did not receive any consultation. Tools of gathering data included the questionnaire about demographic characteristics and standard questionnaire of life quality, (SF 36) and Harry's questionnaire completed by the patients of two groups before and at the end of the treatment. For the data analysis, descriptive statistics, two-factor variance, and multivariate covariance were used. RESULTS: The results of the research showed that cognitive-behavioral therapy group of stress management showed an increase in the quality of life in dimensions of physical performance, emotional health, social performance, and public health, and total score of quality of life, but there was no significant effect in limitation dimensions causing emotional, energy and exhilaration, pain, and physical problems. A significant difference was observed in the average scores of stress in the test and control groups before and after the intervention (P 0.000) and stress of the test group compared to the control was reduced in the post-test and follow-up. CONCLUSION: The obtained results showed that cognitive-behavioral therapy group of stress management had an increase inquality of life and its subscales and also experienced reduced stress in the test group after the intervention. Therefore, this method can be used as one of the complementary therapies besides medical therapy in oncology centers.
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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 | 0.001 | 0.004 |
| 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) | 0.002 | 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".