Knowledge and practices of teachers associated with eye health of primary school children in Rawalpindi, Pakistan
Bibliographic record
Abstract
Purpose: Teachers' perspectives on eye health can be limited, particularly in developing countries. The aim of this study was to assess teachers' knowledge and practices associated with eye health of primary students in Rawalpindi, Pakistan.Methods: This was a cross-sectional survey of primary school teachers. Simple random sampling technique was used to select 443 participants from 34 private and 17 public schools. A self-administered questionnaire was used.Results: Teachers' knowledge ranged from “high” (35.89%), “moderate” (49.89%), and “low” (14.22%). Teachers' practices associated with students' eye health ranged from “high” (10.16%), “moderate” (23.02%), and “low” (66.82%). The teachers' knowledge index scores increased 4.28 points with successive age groups and increased 2.41 points with each successive level of education. For teachers whose close relatives experienced eye disease, their knowledge index score was 4.51 points higher than those teachers whose relatives never had any eye disease. Teachers' age, education level, and their close relatives experiencing eye disease were significant predictors of their knowledge (R2 = 0.087, P< 0.001). Female teachers' practices index score was 10.35 points higher than the male teachers and public school teachers had 10.13 points higher than the private school teachers. Teachers' gender and type of school were significant predictors of their practices (R2 = 0.06, P< 0.001).Conclusion: There was a significant gap among primary school teachers' knowledge and practices related to students' eye health. Innovative strategies are needed to improve how teachers address students' eye health issues in the classroom.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".