Assessing the Impact of a Community-Based Health and Nutrition Education on the Management of Diarrhea in an Urban District, Cairo, Egypt
Bibliographic record
Abstract
Diarrhea is considered as a major cause of mortality in children aged less than five years old. This pre/post interventional study was designed to assess maternal knowledge about diarrhea and implement a community-based health and nutrition education messages. The study was held in Al-Darb Al-Ahamar (ADAA) district, Cairo, Egypt and targeted a random sample of 600 mothers having at least one child under-five years old and complained of at least one previous attack of diarrhea. The study was conducted in three phases. The pre-intervention phase included a base line survey for the mothers and training activities for the community health workers (CHWs). Intervention phase included health and nutrition education sessions; performance evaluation for the CHWs during providing the message. In phase three, the mothers had no instructions for 3 months then the post- intervention interview and feedback sessions were conducted. Results showed that knowledge of mothers about diarrhea (etiological factors and preventive measures) had improved significantly after the intervention. During observation CHWs' scored 50% of the required tasks in education and communication skills. In the feedback sessions, all the mothers declared that nutrition education sessions were highly valuable, and asked for on-going support and training programs. The current study found that health and nutrition education sessions were successful in improving mothers' knowledge regarding preventive measures and management of diarrhea. CHWs are effective health education providers especially in household based intervention. Thus, health services should support community based interventions to reinforce mothers' knowledge and practices towards their sick children.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".