Challenges in implementing continuous support during childbirth in selected public hospitals in the North West Province of South Africa
Bibliographic record
Abstract
BACKGROUND: According to a Cochrane review, continuous support during childbirth increases the mother's chances of a vaginal birth without identified adverse effects. However, this evidence-based practice is not universally implemented. The objective of the study was to identify challenges encountered in implementing continuous support during childbirth in public hospitals in the North West Province of South Africa. METHOD: An explorative, descriptive and contextual qualitative approach was used. The data were collected during 2013 by conducting focus group interviews with 33 registered midwives who had worked in maternity units in three selected public hospitals in the North West Province for at least two years. RESULTS: Midwives identified challenges that negatively impacted the implementation of continuous support during childbirth at organisational and interpersonal levels. At the organisational level, challenges included human resources, policies and guidelines as well as the architectural outlay of the maternity units. The personal challenges related to communication and attitudes of nurses, patients and their families. CONCLUSIONS: Organisational and personal challenges had a negative impact on the provision of continuous care during childbirth.
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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 | 0.014 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".