Rural Health Workers and Primary Health Care Promotion in Southeast Nigeria: Challenges and Their Implication to Community and Sustainable Development
Bibliographic record
Abstract
Community health workers are the inalienable agent of sustainable development across the globe especially, in the developing nations where majority of the population are located in the rural areas.While the basic structure of primary healthcare is in dear need of grass root personnel in the rural communities, the community health workers are readily trained and provided to fill this gap.In Nigeria, the actualization of the aforementioned in line with sustainable development goal-SDG-3, which emphasizes the sacrosanct of comprehensive and inclusive healthcare, is still in doubt owing to the scanty of community health workers in the rural areas.In view of the above situation, this study focused on the social indicators affecting the performances of the community health workers in Southeast Nigeria.The study involved 252 men and women employed as community health workers in different capacities in government health facilities in the rural communities.The study, which was guided by Douglas McGregor X, Y Theory, applied survey design and quantitative data gathering techniques, while the collected data were analyzed using descriptive and inferential statistics such as Mean and standard deviation as well as t-test and linear model.Among the major findings, age, familiarity with the host communities as well as receptivity by the communities are the among the sustainable factors to rural health workers, while improved communication, welfare of the health workers and improvement in skill among the health workers predicted the effective promotion of primary health care services delivery among Community Health Workers.
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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 | 0.002 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".