Clinical ophthalmology (Auckland, N.Z.) · 2025
Agreement Between the Smartphone Application Farnsworth D-15 Test and the Standard Farnsworth D-15 Test for Color Vision Assessment.
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Thammakumpee Kanyarat, Thammakumpee Katkanit, Thammakumpee Koranat, Tiantanyatip Soyci
Аннотация
PURPOSE: The primary aim of this study was to evaluate the level of agreement in color vision assessment between the smartphone application Farnsworth D-15 (FD-15) test and the standard FD-15 test.
MATERIALS AND METHODS: A cross-sectional study was conducted involving participants aged ≥ 18 years. Inclusion criteria included the ability to follow test instructions and provide informed consent. Eyes with visual acuity worse than 20/200 were excluded. Standardized score sheets were used for both tests to calculate the color confusion index (CCI). Agreement between the two tests was assessed using the Pearson correlation coefficient, adjusted R-squared (R2), calibration slope, calibration-in-the-large (CITL), and root mean square error (RMSE), and Bland-Altman plots.
RESULTS: A total of 200 eyes from 101 participants were included in the study. The CCI data showed a strong correlation (Pearson correlation coefficient = 0.9924). The adjusted R 2 of 0.9839 indicated high explanatory power. A calibration slope of 0.9861 and CITL of 0.0957 indicated minimal proportional and systematic bias, respectively. RMSE was 0.1211, within acceptable limits. The Bland-Altman analysis demonstrated limits of agreement within clinically acceptable range.
CONCLUSION: The smartphone application FD-15 test demonstrated high agreement with the standard FD-15 test. This study serves as a pilot validation demonstrating the potential of the smartphone-based FD-15 application for color vision screening. However, the current findings should be interpreted considering the use of a single smartphone model and the low prevalence of color vision defects. These findings support its potential utility as a practical and accessible tool for remote care and occupational health assessments.
MATERIALS AND METHODS: A cross-sectional study was conducted involving participants aged ≥ 18 years. Inclusion criteria included the ability to follow test instructions and provide informed consent. Eyes with visual acuity worse than 20/200 were excluded. Standardized score sheets were used for both tests to calculate the color confusion index (CCI). Agreement between the two tests was assessed using the Pearson correlation coefficient, adjusted R-squared (R2), calibration slope, calibration-in-the-large (CITL), and root mean square error (RMSE), and Bland-Altman plots.
RESULTS: A total of 200 eyes from 101 participants were included in the study. The CCI data showed a strong correlation (Pearson correlation coefficient = 0.9924). The adjusted R 2 of 0.9839 indicated high explanatory power. A calibration slope of 0.9861 and CITL of 0.0957 indicated minimal proportional and systematic bias, respectively. RMSE was 0.1211, within acceptable limits. The Bland-Altman analysis demonstrated limits of agreement within clinically acceptable range.
CONCLUSION: The smartphone application FD-15 test demonstrated high agreement with the standard FD-15 test. This study serves as a pilot validation demonstrating the potential of the smartphone-based FD-15 application for color vision screening. However, the current findings should be interpreted considering the use of a single smartphone model and the low prevalence of color vision defects. These findings support its potential utility as a practical and accessible tool for remote care and occupational health assessments.