The Quality and Intensity of Labor Pain based on McGill pain Questionnaire in Parturient Women Admitted in the Maternity Ward of Afzalipour Hospital in Kerman
Bibliographic record
Abstract
Abstract: Background & Aims: Fear of labor pain is a principal factor in pregnant women's tendency for cesarean section. This study was done to investigate the factors that affect quality and intensity of labor pain in order to decrease the rate of elective cesarean sections. Method: a prospective randomized study was performed on 208 parturient women in Maternity ward of afzalipour Hospital by using McGill Pain Questionnaire. Results: Mean age of participants was 25.23±5.54 years old. Comparison of intensity and quality of pain between stage I and Stage II of labor showed higher pain intensity in stage II (P<0.0001). Nuliparous women reported higher pain intensity during stage II (P=0.002), whereas multiparous women experienced shorter labor (P<0.0001). In stage II of labor with increase of age, a decrease of labor pain intensity was observed (P<0.001). There were no significant statistical relationships between labor pain and variables of job, education al level, weight of neonate and number of previous pregnancies in multiparous women. Labor pain intensity in women who had prenatal care in obstetrician's clinics was lower than others. Conclusion: Lower intensity of labor pain in women who had prenatal care in obstetrician's clinics emphasizes on the role of obstetricians in recommending vaginal delivery to pregnant women as a physiologic phenomenon. Keywords: Vaginal birth, McGill Pain Questionnaire, Labor Pain, Pain measurement, Kerman
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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".