Effectiveness of Eye Movement Exercise Application on Pain and Stress among Patients undergoing Hemodialysis
Bibliographic record
Abstract
Background: Stress and pain are high among patients undergoing hemodialysis. Extra calcium and phosphate can also settle in the eyes and cause eye pain and irritation in dialysis patients. Eye movement exercise application affected a wide range of physical and psychological signs and symptoms among patients undergoing hemodialysis. Aim: To evaluate the effectiveness of eye movement exercise application on eye pain and stress among patients undergoing hemodialysis Subjects and methods Design: Quasi-experimental research design pre-post-test was utilized in this study. Settings: The study was conducted at hemodialysis units at Sohag University Hospital, Egypt. Sample: Purposive samples of 100 patients undergoing hemodialysis were enrolled in this study. Tools: Three tools were used for data collection; Tool I: Structured Interview Questionnaire that contains two parts part one; patients' personal demographic data and part two; medical data history, Tool II: Short Form McGill Pain Scale (SF-MPS) to assess eye pain, and Tool III: Perceived Stress Scale (PSS-10). Results: The current study results revealed that; post- eye movement exercise application was significantly affected in reducing eye pain and stress mean scores among patients undergoing hemodialysis compared to pre-application. Conclusion: The study concluded that; the eye movement exercise application has a significant positive effect on reducing eye pain and stress among patients undergoing hemodialysis. Recommendations: The eye movement exercise should be integrated into the care of patients undergoing hemodialysis to help in the reduction of eye pain and stress reduction especially when they had fluids and electrolyte disturbances. Eye movement training should be promoted in practice because it can reduce negative emotions and alleviate pain sensations.
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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 | 0.000 | 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 | 0.000 |
| 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".