Effects of Selected Socio-Demographic Characteristics of Community Health Workers on Performance of Home Visits during Pregnancy: A Cross-Sectional Study in Busia District, Kenya
Bibliographic record
Abstract
OBJECTIVE: Appropriate performance of home visits facilitates adoption of best practices at home and increased demand for facility based services. METHODS: It was a cross-sectional study in which community health workers were observed conducting home visits during pregnancy. Data was collected using a structured questionnaire and the Consultant Quality Index (CQI-2 tool) on record keeping, use of job aids, counselling, client satisfaction and client enablement. Descriptive and inferential statistics were used. Relationships were determined using chi square and odds ratios. RESULTS: The study showed significant relationships of age with good record keeping (p = 0.0001), appropriate use of job aids (p=0.0001), client satisfaction (p = 0.018) and client enablement (p = 0.001). Male CHWs were 1.6 times more likely to keep better records than females (OR 1.64 CI (1.02-2.63), while females were more likely to counsel and enable their clients OR 0.42 CI (0.25-0.71) and OR 0.29 CI (012-070) respectively when compared to men. Moreover, higher levels of education were associated with good record keeping OR 0.30 CI (0.19-0.49), p=0.0001; appropriate use of job aids OR 0.30 CI (0.15-0.61) and to appropriately counsel their clients OR 0.34 CI (0.20-0.58) than their lower literacy level counterparts. Experience of CHWs was associated with appropriate use of job aids (p = 0.049); client satisfaction (p = 0.0001) and client enablement (p = 0.032). CONCLUSIONS: Socio-demographic characteristics of community health workers affect the performance of home visits in various ways. The study also confirmed that CHWs with lower literacy levels satisfy and enable their clients effectively.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".