Knowledge and Practice Related to Trachoma Among Children in Vietnam: A Cross-Sectional Study
Bibliographic record
Abstract
A cross-sectional descriptive survey to determine the magnitude and determinants of knowledge and practice in relation to trachoma among children in Vietnam is presented. Interviews were conducted with 358 children ages 6 to 15 years in three districts of Northern Vietnam using a closed-ended questionnaire. Responses related to causes, prevention methods, consequences, and observed preventive practices were standardized. The knowledge of causes of trachoma and prevention methods was assessed as "excellent" in 61.1% and 69.45% of female and male children, respectively. Mode of transmission and consequences of trachoma were very well known to 68.70% and 57.74% of female and male children, respectively. Trachoma control practice was excellent in 54.72% of children. Females had better knowledge, and practice of trachoma control was better in female than male children. Ten- to 15-year-olds had better knowledge and practices than 6- to 10-year-old children. Trachoma knowledge and practice was better in children of Vinh Loc District of Thanh Hoa Province than in those in Tu Ky District of Hai Duong Province. The schools were the best source of the information. Mass media had a limited role. The outcome suggested a limited positive impact of the 6 months intense initiatives of a health education campaign. Based on the study results, the campaign could be reorganized to focus on high-risk groups and to improve the impact. The findings could be compared to the results of a similar study after 2 years of the campaign.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".