Depression and Burnout among Health Extension Workers in Ethiopia: A Cross-Sectional Study
Bibliographic record
Abstract
Background: The emergence of COVID-19 pandemic has disrupted the supply chain and stock of medicines and drugs across the globe. Tracer drugs are essential medicines that address the population's priority health problems. Thus, this study aimed to assess availability of tracer drugs and basic diagnostics at public primary health care facilities in Ethiopia. Methods: Facility based cross-sectional study was employed in four regions and one city administration. The primary health care units (PHCUs) were purposively selected in consultation with respective regional health bureaus. Finally, 16 hospitals, 92 health centers and 344 health posts were included. This study adopted WHO's tool that was being used to rapidly assess the capacity of health facilities to maintain the provision of essential health services during the COVID-19. Descriptive analysis was done using frequency and percentage, and results were presented. Results: The overall mean availability of tracer drugs in PHCUs was 77.6%. Only 2.8% of PHCUs have all tracer drugs. The mean availability of basic diagnostic at national level was 86.6% in PHUs except health posts where it was less. Health facilities with all basic diagnostic services was 53.7%. Of the total 344 health posts assessed, 71% were providing diagnostic testing for malaria using either laboratory equipment or rapid diagnostic test (RDT) while 43% provide urine test for the pregnancy. Conclusion: This study shows availability of all tracer drugs in PHCUs in Ethiopia was extremely low. There was regional variation in availability of tracer drugs and basic diagnostics. It is very crucial to increase availability of tracer drugs and diagnostics. Drugs and diagnostic materials should be supplied according to the capacity and location of health facilities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".