Massage reduced severity of pain during labour: a randomised trial
Bibliographic record
Abstract
QUESTION: Does massage relieve pain in the active phase of labour? DESIGN: Randomised trial with concealed allocation, assessor blinding for some outcomes, and intention-to-treat analysis. PARTICIPANTS: 46 women pregnant at ≥ 37 weeks gestation with a single fetus, with spontaneous onset of labour, 4-5cm of cervical dilation, intact ovular membranes, and no use of medication after admission to hospital. INTERVENTION: Experimental group participants received a 30-min lumbar massage by a physiotherapist during the active phase of labour. A physiotherapist attended control group participants for the same period but only answered questions. Both groups received routine perinatal care. OUTCOME MEASURES: The primary outcome was pain severity measured on a 100mm visual analogue scale. Secondary outcomes included the Short Form McGill Pain Questionnaire, pain location, and time to analgesic medication use. After labour, a blinded researcher also recorded duration of labour, route of delivery, neonatal outcomes, and the participant's satisfaction with the physiotherapist during labour. RESULTS: At the end of the intervention, pain severity was 52mm (SD 20) in the experimental group and 72mm (SD 15) in control group, which was significantly different with a mean difference of 20mm (95% CI 10 to 31). The groups did not differ significantly on the other pain-related outcome measures. Obstetric outcomes were also similar between the groups except the duration of labour, which was 6.8hr (SD 1.6) in the experimental group and 5.7hr (SD 1.5) in the control group, mean difference 1.1hr (95% CI 0.2 to 2.0). Patients in both groups were satisfied with the care provided by the physiotherapist. CONCLUSION: Massage reduced the severity of pain in labour, despite not changing its characteristics and location.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".