Factors Influencing Women’s Preferred Mode of Delivery in Kericho County Hospitals, Kenya
Bibliographic record
Abstract
PURPOSE: To evaluate the factors influencing women’s preferred mode of delivery among postnatal mothers in Kericho County Hospitals. METHODOLOGY: Descriptive cross-sectional design was adopted and mixed methods used for data collection. A total of 310 participants were randomly selected using a systematic sampling for quantitative and qualitative approach that used Focus Group Discussion among postnatal mothers in both sampled private and public facilities of Kericho County Hospitals. Data entry and analysis was done with mean and standard deviation computed with results presented in tables. The study used descriptive and inferential statistical analysis. To determine association of variables bivariate and multivariate logistic analysis was adopted. Odds ratios were calculated and the p-value of<0.05 was considered statistically significant. FINDINGS: The preferred mode of delivery by most respondent was vaginal delivery at 81.3% and 18.7% wanted caesarean section. Bivariate analysis of variables showed that level of education p=0.002, marital status p=0.0001, occupation p=0.007. Cultural beliefs that prohibit certain mode of delivery among postnatal mothers had statistical significant of p=0.02. With focus group discussion, a major concern for almost all women was the severity, duration and patterns of labor pains. UNIQUE CONTRIBUTION OF THE STUDY: The study results showed that health provider’s attitudes, care and support influenced their mode of birth. Most respondents showed confidence of been delivered by midwives as compared with other carders Cultural beliefs that prohibit certain mode of delivery was a variable that had significant association with preferred mode of delivery with a value of p=0.02. The findings will be useful in designing interventions and strategies that focuses individualized care of mothers during childbirth to meet individual needs and expectations.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".