A Study of the Influence of Group-Based Learning of Stress Management on Psychology Symptoms Levels of Hemodialysis Patients
Bibliographic record
Abstract
INTRODUCTION: Patients with kidney failure often need to change their lifestyles, which can result in various psychological-social problems. The present study aims to evaluate the influence of group-based learning of stress management on psychology symptoms levels of hemodialysis patients. METHOD: This is a quasi-experimental, single-blind study in which 50 patients with kidney failure were randomly divided into two groups. Sampling was based on the purposeful method. Before undergoing dialysis, the patients in the experimental group were trained in stress management; the training lasted 60 minutes and was presented in 5 sessions. The patients in the control group received the standard education all the patients undergoing hemodialysis at the hospital receive. The stress levels of the patients before and after the intervention were measured by the reliable and valid questionnaire of DASS 21. To analyze the collected data, the researchers employed the statistical tests one-way ANOVA and the software SPSS 18. RESULT: The 50 patients under study were divided into two equal groups. In terms of such demographic characteristics as age, gender, and stress level, there were no significant differences between the two groups before the intervention. However, after the 5-week education, the stress level in the experimental group decreased from 16.96±0.90 to 8.36±1.03. In the control group, the stress level decreased from 15.92±1.44 to 13.76±1.44. After the intervention, the difference between the means of the groups’ stress scores was found to be significant (p<0.001). CONCLUSION: The result is expected to provide new knowledge to support the effective follow-up for hemodialysis patient in order to improve their emotional and health status.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".