Evaluation of the Bonapace Method: a specific educational intervention to reduce pain during childbirth
Bibliographic record
Abstract
OBJECTIVE: As pain during childbirth is very intense, several educational programs exist to help women prepare for the event. This study evaluates the efficacy of a specific pain management program, the Bonapace Method (BM), to reduce the perception of pain during childbirth. The BM involves the father, or a significant partner, in the use of several pain control techniques based on three neurophysiological pain modulation models: (1) controlling the central nervous system through breathing, relaxation, and cognitive structuring; (2) using non-painful stimuli as described in the Gate Control Theory; and (3) recruiting descending inhibition by hyperstimulation of acupressure trigger points. METHODS: A multicenter case control study in Quebec on pain perception during labor and delivery compared traditional childbirth training programs (TCTPs) and the BM. Visual analog scales were used to measure pain perception during labor. In all, 25 women (TCTP: n = 12; BM: n = 13) successfully reported their perceptions of pain intensity and unpleasantness every 15 minutes. RESULTS: A POSITIVE CORRELATION BETWEEN THE PROGRESSION OF LABOR AND PAIN WAS FOUND (PAIN INTENSITY: P < 0.01; pain unpleasantness: P < 0.01). When compared to TCTP, the BM showed an overall significant lower pain perception for both intensity (45%; P < 0.01) and unpleasantness (46%; P < 0.01). CONCLUSION: These significant differences in pain perception between TCTP and the BM suggest that the emphasis on pain modulation models and techniques during labor combined with the active participation of a partner in BM are important variables to be added to the traditional childbirth training programs for childbirth pain management.
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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 | 0.042 | 0.004 |
| 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) | 0.004 | 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".