Evaluating the Effect of Slow-Stroke Back Massage on the Anxiety of Candidates for Cataract Surgery
Bibliographic record
Abstract
Background: The patients under cataract sur-gery often experience anxiety not only during the surgery, but also prior to the surgery.Purpose: We sought to determine the effects of slow-stroke back massage on anxiety in patients undergoing cataract surgery. Setting: The study was conducted in the Amiral-momenin Hospital of Zabol city, south-east of Iran.Participants: A total of 60 candidates of cataract surgery participated in the study.Research Design: The participants were ran-domly allocated to either control or intervention groups. The intervention group received slow-stroke back massages, while patients in control group received routine interventions.Intervention: The slow-stroke back massage was performed on the patients assigned to the interven-tion group. The intervention was performed in the morning of the surgery day at 30 minutes before the surgery. The researcher performed each mas-sage session in a sitting position. The duration of each massage session was 15 minutes. Main Outcome Measures: Anxiety was assessed in the both groups in the morning of the surgery, before and immediately after the intervention. In-dependent samples Student’s t test, paired samples Student’s t test, and chi-squared test were used to analyze the data.Results: Anxiety was not significantly different between the two groups before and after the mas-sage (p = .816). On the other hand, paired samples Student’s t test showed a significant difference comparing the anxiety scores before (49.7±5.43) and after (45.16±3.89) the massage in the interven-tion group (p < .001). Conclusions: Based on our results, slow-stroke back massage, which is a low-cost and safe method, reduced anxiety in patients who were candidates for cataract surgery.
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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 | 0.015 | 0.009 |
| 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 | 0.001 | 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 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".