Increasing Staff Knowledge and Intent to Implement Physiological Birthing Positions
Bibliographic record
Abstract
Purpose. The purpose of this quality improvement (QI) project is to increase knowledge of physiological labor positions and intent to utilize various birthing positions among labor and delivery (L&D) staff through education at level II hospital in Gilbert, AZ.Background. Labor and birth are heavily influenced by many factors, including fetal status, maternal anatomy, placental sufficiency, contractions, the mother’s psyche, and maternal positioning (King et al., 2018). Primary cesarean sections (c-sections) are becoming more prevalent in United States (US), which raises concern among healthcare professionals with associated risks and complications (Lagrew et al., 2018). C-section births are associated with preventable maternal morbidity and mortality (Lagrew et al., 2018). Maternal morbidity rates are rising in US and more than double compared to other nations (e.g., Canada, France), actions must be taken to decrease unnecessary cesarean births (Tikkanen et al., 2020). Methods. This QI project adapted positions from Spinning Babies and Bundle Birth approaches implemented in local labor and delivery unit in Gilbert, AZ. New reference guides for labor and birthing positions were implemented in unit. Two in-person sessions led by principal investigator were completed with education on physiological birthing positions using Spinning Babies research. Participants involved in project were labor and delivery (L&D) nurses. Pre- and post-anonymous surveys were conducted at in-person sessions and evaluated participants’ knowledge, comfort, and intent to use information presented. Results. Results supported goal of project to increase knowledge and intent of labor and delivery nurses using various birthing positions. There was a total of 16 participants in two in-person education sessions held. Pre- and post-survey responses were collected from labor and delivery staff who attended sessions, evaluating their opinions and current understanding of physiological birth. Data from responses of pre- and post-surveys were analyzed using descriptive statistics. Data collected was formulated using tables and bar charts found in results section. Based on participants’ pre- and post-surveys, results showed increase in staff knowledge and intent when comparing survey questions and mean scores calculated. Primary c-section data was initially analyzed to determine intervention’s short-term effects, rates did decrease in post-implementation months, but is unclear if due to intervention. Conclusions. QI project addressed ongoing maternal morbidity and mortality rates seen from cesarean section complications. Project met objective of increasing awareness of physiological birth positions among labor and delivery staff in local hospitals.
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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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".