ASSESSING THE NATURE OF PATRONAGE FOR TRADITIONAL MATERNAL HEALTH CARE SERVICES IN SOUTHWESTERN NIGERIA
Bibliographic record
Abstract
Background: The study assessed the nature of patronage for traditional maternal health care services in Southwestern Nigeria. These were in view of providing information on the nature of patronage of traditional maternal health care services (TMHCs) in Nigeria, thus assisting in meeting the 2030 target of the Sustainable Development Goals (SDGs). Methods: The study adopted a descriptive research design method approach. The study population was comprised of all pregnant women and nursing mothers attending TMHCs in Southwestern. The sample size consisted of 1020 pregnant women and nursing mothers. A self-designed questionnaire was used to gather information from the respondents. Data collected were analysed using frequency count, percentage, mean, standard deviation and ANOVA. Results: It showed that respondents patronized centre owned by a tradition and culture 351(41.1%), respondents attended their preferred TMHCs on Wednesdays (738), and respondents were introduced to using TMHCs by their in-laws, religious leaders and friends, respectively. However, a large number of the respondents agreed that they use TMHCs because of the passionate care shown towards them (28.9%), spiritual reasons (26.6%), belief in the efficacy of service (30.2%), accessibility (29.7%) and offer of good and quality service (31.2%). Also, the study shows that there is a significant influence of the husband's age (df=3,870, F=5.909, p<0.05), husband's income (df=4,869, F=3.747, p<0.05) and husband's education level (df=3,870, F=64.70, p<0.05) on the reasons for patronizing TMHCs in the study area. Conclusion: The study concluded that nature patronage is a contributing factor to the high usage of TMHCs, which encourages maternal mortality in Nigeria. Article visualizations:
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".