Myopes Show Greater Visually Induced Postural Responses Than Emmetropes
Bibliographic record
Abstract
PURPOSE: The literature already establishes that vision plays a crucial role in postural control and that this visual dependence shows intra- and interindividual variability. However, does ametropia also have an effect on postural control? This question leads to our study, which aims primarily to determine if myopes and emmetropes behave differently in terms of postural control when subjected to visual stimulation, and secondarily, if this difference persists in the presence of barrel and pincushion distortions. The results could lead, among other things, to improved lens design. METHODS: Twenty-four subjects (12 myopes of -2.00 to -9.00 diopters [D] and 12 emmetropes of -0.50 to +0.50 D), between 19 and 35 years of age, participated in the study after comprehensive eye examinations were carried out. Of the 12 myopes, the preferred type of correction was divided equally within the group. While standing in front of a projection system and fixating on an immobile point, a checkerboard stimulus was displayed in their peripheral visual field, in either a static or dynamic state. Three conditions of optical distortion (plan, pincushion, and barrel distortions) were presented to the subjects. Their postural response was measured and recorded using a system of infrared cameras and optical sensors positioned on a helmet. RESULTS: The results show that postural instability induced by a dynamic peripheral stimulus is higher for myopes compared with emmetropes (ANOVA Refractive Error, F1,22 = 5.92, P = 0.0235). When exposed to optical distortions, the two groups also have significant differences in postural behaviors (ANOVA Refractive Error*Optical Distortion, F2,44 = 5.67, P = 0.0064). CONCLUSIONS: These results suggest that refractive error could be a factor in explaining individual variations of the role of vision in postural control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.005 | 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".