Related Experiment Video
Updated: Aug 14, 2026

Quantification of Oculomotor Responses and Accommodation Through Instrumentation and Analysis Toolboxes
Published on: March 3, 2023
Accuracy of accommodation in heterophoric patients: testing an interaction model in a large clinical sample
Satoshi Hasebe1, Fumitaka Nonaka, Hiroshi Ohtsuki
1Department of Ophthalmology, Okayama University Medical School, 2-5-3 Shikata-cho, Okayama 700-8558, Japan. shasebe@md.okayama-u.ac.jp
Abstract:
A model of the cross-link interactions between accommodation and convergence predicted that heterophoria can induce large accommodation errors (Schor, Ophthalmic Physiol. Opt. 1999;19:134-150). In 99 consecutive patients with intermittent tropia or decompensated phoria, we tested these interactions by comparing their accommodative responses to a 2.50-D target under binocular fused conditions (BFC) and monocular occluded conditions (MOC). The accommodative response in BFC frequently differed from that in MOC. The magnitude of the accommodative errors in BFC, ranging from an accommodative lag of 1.80 D (in an esophoric patient) to an accommodative lead of 1.56 D (in an exophoric patient), was correlated with distance heterophoria and uncorrected refractive errors. These results indicate that heterophoria affects the accuracy of accommodation to various degrees, as the model predicted, and that an accommodative error larger than the depth of focus of the eye occurs in exchange for binocular single vision in some heterophoric patients.
Related Concept Videos
Two-Way ANOVA
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the means for...
Accuracy and Errors in Hypothesis Testing
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5% chance...
Horney's Sociocultural Approach
Test for Homogeneity
Stereotype Content Model
Expected Frequencies in Goodness-of-Fit Tests