Educational Interventions for Labor Epidural Awareness: A Scoping Review Protocol (Preprint)
Bibliographic record
Abstract
Background: Labor pain is among the most intense forms of pain, and neuraxial analgesia, including epidural, spinal, and combined spinal-epidural techniques, is considered the gold standard for its management. Despite its effectiveness, persistent misconceptions, cultural barriers, and disparities in awareness contribute to underuse among certain populations. Educational interventions have been developed to address these gaps, yet a comprehensive synthesis of such efforts in the United States is lacking. Objective: This scoping review aims to map the extent, range, and nature of current literature describing educational interventions designed to improve knowledge, awareness, and acceptance of neuraxial analgesia during labor among pregnant women. Methods: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework, peer-reviewed studies published in English were identified through PubMed, Embase, and Scopus from inception to August 2025. Eligible studies include those focusing on pregnant individuals eligible for neuraxial analgesia who received educational or counseling interventions during prenatal or perinatal care. Extracted data include study design, intervention type, delivery method, timing, and outcomes of interest, including patient understanding of risks and benefits, awareness of neuraxial analgesia options, acceptance of or preference for neuraxial analgesia, satisfaction with education, and uptake during labor. Data will be synthesized descriptively using summary tables and figures, with a narrative synthesis to categorize interventions by type, timing, and delivery method and identify patterns and gaps across studies. Results: This project was conceived in August 2024, and the protocol was registered in the Open Science Framework in January 2025. The database search was conducted in August 2025. As of protocol submission in October 2025, full-text screening and data extraction are pending and are scheduled for May 2026 to June 2026. Data synthesis and drafting of the results will be completed in September 2026. The manuscript will be submitted in October 2026. Conclusions: This scoping review will map existing educational interventions related to neuraxial labor analgesia and identify gaps in the current literature. The findings may help inform future research and the development of more consistent and accessible patient education approaches.
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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 | 0.139 | 0.237 |
| Meta-epidemiology (narrow) | 0.004 | 0.007 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.095 | 0.021 |
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".