Teachers' influence on purchase and wear of children's glasses in rural China: The PRICE study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
IMPORTANCE: Uncorrected refractive error causes 90% of poor vision among Chinese children. BACKGROUND: Little is known about teachers' influence on children's glasses wear. DESIGN: Cohort study. PARTICIPANTS: Children at 138 randomly selected primary schools in Guangdong and Yunnan provinces, China, with uncorrected visual acuity (VA) ≤6/12 in either eye correctable to >6/12 in both eyes, and their teachers. METHODS: Teachers and children underwent VA testing and completed questionnaires about spectacles use and attitudes towards children's vision. MAIN OUTCOME MEASURES: Children's acceptance of free glasses, spectacle purchase and wear. RESULTS: A total of 882 children (mean age 10.6 years, 45.5% boys) and 276 teachers (mean age 37.9 years, 67.8% female) participated. Among teachers, 20.4% (56/275) believed glasses worsened children's vision, 68.4% (188/275) felt eye exercises prevented myopia, 55.0% (151/275) thought children with modest myopia should not wear glasses and 93.1% (256/275) encouraged children to obtain glasses. Teacher factors associated with children's glasses-related behaviour included believing glasses harm children's vision (decreased purchase, univariate model: relative risk [RR] 0.65, 95% CI 0.43, 0.98, P < 0.05); supporting children's classroom glasses wear (increased glasses wear, univariate model: RR 2.20, 95% CI 1.23, 3.95, P < 0.01); and advising children to obtain glasses (increased free glasses acceptance, multivariate model: RR 2.74, 95% CI 1.29, 5.84, P < 0.01; increased wear, univariate model: RR 2.93, 95% CI 1.45, 5.90, P < 0.01), but not teacher's ownership/wear of glasses. CONCLUSIONS AND RELEVANCE: Though teachers had limited knowledge about children's vision, they influenced children's glasses acceptance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it