Intensive monitoring and interpersonal counselling by lady health worker improves the coverage of vitamin A among children between ages 6 and 59 months in selected low performing provinces of Pakistan
Bibliographic record
Abstract
Background: Nutrition International, previously known as Micronutrient Initiative, has been supporting the government of Pakistan to address vitamin A deficiency in 24 districts of Balochistan and Khyber Pakhtunkhwa and 78 union councils of Lahore and Karachi. The program aims to improve capacity of health managers and frontline workers on supply chain management and monitoring; monitoring of stock-outs at health facilities and frontline distribution points; and focus on regular monitoring and supervision through EPI and health departments. Challenge however remains in achieving meaningful coverage. The Nutrition International piloted an intensive monitoring strategy in a sub-set of four districts of Balochistan and KPK and 14 union councils in Karachi and Lahore with an aim to improve coverage of vitamin A. The study assessed the changes in coverage of vitamin A supplementation 2011 to 2012 due to the intensive monitoring.Methods: Two rounds of repeated cross-sectional mixed-methods surveys were conducted on a sample of 2,579 and 2,580 caregivers during baseline and end-line respectively. Low performing districts identified in each of the four provinces constituted the study domain. The sample of households in each region was selected using a two stage cluster sampling strategy.Results: The coverage of Vitamin A registered an absolute increase of 35.7 percent points in the intensive monitoring districts compared to the other districts, where it was 29.6 percent points in the end-line over the baseline.Conclusions: It was observed that intensive monitoring and interpersonal counselling by lady health worker is instrumental in improving the coverage of Vitamin A in certain programmatic settings in Pakistan.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".