Investigating the effect of Swedish massage with chamomile oil on labor pain and anxiety of primiparous women: A clinical trial
Bibliographic record
Abstract
BACKGROUND: Labor pain and fear of childbirth increase anxiety and stress in pregnant women. Therefore, the present study was conducted with the aim of determining the effect of Swedish massage with chamomile oil on pain and anxiety in a clinical trial. MATERIALS AND METHODS: The present study is a clinical trial on 159 women who were referred to 22 Bahman Hospital in Masjid Sulaiman City in 2021. The samples were randomly divided into three groups (Swedish massage with and without chamomile oil and control group). Pain intensity was assessed using the McGill Pain Scale and anxiety was assessed using the Vandenberg Anxiety Questionnaire. The data were analyzed with SPSS-20 software at a significance level of 0.05. Descriptive statistics (frequency, percentage, mean, and standard deviation) and inferential statistics (Chi-square, Fisher's exact, analysis of variance, and paired t ) were used for data analysis. RESULTS: There were no significant statistical differences between the three groups in terms of obstetric and demographic information ( P > 0.05). There was no significant relationship between the studied groups before the intervention in terms of labor pain intensity ( P = 0.9) and anxiety ( P -value = 0.426). After the intervention, the intensity of labor pain and mother's anxiety was significantly lower in the two intervention groups compared to the control group, and it was lower in the Swedish massage group with chamomile oil than the other two groups ( P < 0.001). CONCLUSION: In the present study, Swedish massage with and without chamomile oil led to a decrease in pain intensity and anxiety. As a result, this method can be used as an effective method to reduce the intensity of pain and anxiety of pregnant mothers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".