Impact of a Local Vision Care Center on Glasses Ownership and Wearing Behavior in Northwestern Rural China: A Cluster-Randomized Controlled Trial
Bibliographic record
Abstract
Visual impairment is common among rural Chinese children, but fewer than a quarter of children who need glasses actually own and use them. To study the effect of rural county hospital vision centers (VC) on self-reported glasses ownership and wearing behavior (primary outcome) among rural children in China, we conducted a cluster-randomized controlled trial at a VC in the government hospital of Qinan County, a nationally-designated poor county. All rural primary schools (n = 164) in the county were invited to participate. Schools were randomly assigned to either the treatment group to receive free vision care and eyeglasses, if needed, or control group, who received glasses only at the end of the study. Among 2806 eligible children with visiual impairment (visual acuity ≤ 6/12 in either eye), 93 (3.31%) were lost to follow-up, leaving 2713 students (45.0% boys). Among these, glasses ownership at the end of the school year was 68.6% among 1252 treatment group students (82 schools), and 26.4% (p < 0.01) among 1461 controls (82 schools). The rate of wearing glasses was 55.2% in the treatment group and 23.4% (p < 0.01) among the control group. In logistic regression models, treatment group membership was significantly associated with spectacle ownership (Odds Ratio [OR] = 11.9, p < 0.001) and wearing behavior (OR = 7.2, p < 0.001). County hospital-based vision centers appear effective in delivering childrens’ glasses in rural China.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".