Training regimen involving cyclic induction of pupil constriction during far accommodation improves visual acuity in myopic children
Bibliographic record
Abstract
PURPOSE: Myopia in school-age children has become increasingly prevalent in industrialized countries, especially in Asia. A large population of school-age children still suffers from low visual acuity. We have developed a novel, safe and noninvasive training method to activate a pupillary constriction response during far accommodation that results in improved visual acuity. METHODS: Myopic children (n = 95) were treated for 3-minute sessions up to twice a week for 12-106 weeks. We stimulated quick cycles of near/far accommodation by displaying a visual object on a LCD screen and moving the screen in cycles from a near (25 cm) to a far (70 cm) point and back, while keeping the retinal projection size and brightness of the object constant. RESULTS: Mechanistically, we noted pupillary constriction upon far accommodation in trained myopic children, which was not seen in normal subjects or in untrained myopic children. Eighty five percent (52/61) of trained myopic right eyes with two sessions weekly experienced improved visual acuity (VA) by more than 0.1 logMAR units with an average improvement of 0.30 +/- 0.03 standard error of mean (SEM) logMAR units. With maintained training, most eyes' improved VA stayed almost constant, for more than 50 weeks in the case of 12 long trained subjects. CONCLUSIONS: This simple, short and safe accommodation training greatly improves the quality of vision in a large population suffering from refractive abnormalities.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".