This study aimed to identify the factors affecting dry eye syndrome and quality of life (QoL) among college students. Methods: This cross-sectional study administered a descriptive survey to 184 college students across Korea. Data collection was conducted from August 27 to 28, 2024, using an online survey platform (Google Forms). The self-reported survey comprised the Health-Related Quality of Life Instrument with 8 Items scale, the Dry Eye Questionnaire 5, and the Ocular Surface Disease Index. Data analysis was performed using SPSS version 27.0. Results: The participants had a mean age of 21.37 (standard deviation 1.96) years. Regression analysis identified sleep satisfaction, vision-related functions, and dry eye symptoms as statistically significant predictors of QoL, accounting for 18.4% of the variance (F = 14.71, p < .001). Dry eye symptoms were significantly influenced by the use of artificial tears, vision-related functions, and environmental factors, which accounted for 41.3% of the variance (F = 43.93, p < .001). Additionally, significant determinants of ocular surface disease included the use of vision correction tools, the presence of ophthalmic diseases, sleep satisfaction, and dry eye symptoms. These factors explained 45.7% of the variance, confirming the model's robustness (F = 31.84, p < .001). Conclusion: It is necessary to identify strategies to alleviate dry eye syndrome in college students and develop comprehensive prevention and management programs to improve their QoL.

This study aimed to identify the factors affecting dry eye syndrome and quality of life (QoL) among college students. Methods: This cross-sectional study administered a descriptive survey to 184 college students across Korea. Data collection was conducted from August 27 to 28, 2024, using an online survey platform (Google Forms). The self-reported survey comprised the Health-Related Quality of Life Instrument with 8 Items scale, the Dry Eye Questionnaire 5, and the Ocular Surface Disease Index. Data analysis was performed using SPSS version 27.0. Results: The participants had a mean age of 21.37 (standard deviation 1.96) years. Regression analysis identified sleep satisfaction, vision-related functions, and dry eye symptoms as statistically significant predictors of QoL, accounting for 18.4% of the variance (F = 14.71, p < .001). Dry eye symptoms were significantly influenced by the use of artificial tears, vision-related functions, and environmental factors, which accounted for 41.3% of the variance (F = 43.93, p < .001). Additionally, significant determinants of ocular surface disease included the use of vision correction tools, the presence of ophthalmic diseases, sleep satisfaction, and dry eye symptoms. These factors explained 45.7% of the variance, confirming the model's robustness (F = 31.84, p < .001). Conclusion: It is necessary to identify strategies to alleviate dry eye syndrome in college students and develop comprehensive prevention and management programs to improve their QoL.

This study aimed to identify the factors affecting dry eye syndrome and quality of life (QoL) among college students. Methods: This cross-sectional study administered a descriptive survey to 184 college students across Korea. Data collection was conducted from August 27 to 28, 2024, using an online survey platform (Google Forms). The self-reported survey comprised the Health-Related Quality of Life Instrument with 8 Items scale, the Dry Eye Questionnaire 5, and the Ocular Surface Disease Index. Data analysis was performed using SPSS version 27.0. Results: The participants had a mean age of 21.37 (standard deviation 1.96) years. Regression analysis identified sleep satisfaction, vision-related functions, and dry eye symptoms as statistically significant predictors of QoL, accounting for 18.4% of the variance (F = 14.71, p < .001). Dry eye symptoms were significantly influenced by the use of artificial tears, vision-related functions, and environmental factors, which accounted for 41.3% of the variance (F = 43.93, p < .001). Additionally, significant determinants of ocular surface disease included the use of vision correction tools, the presence of ophthalmic diseases, sleep satisfaction, and dry eye symptoms. These factors explained 45.7% of the variance, confirming the model's robustness (F = 31.84, p < .001). Conclusion: It is necessary to identify strategies to alleviate dry eye syndrome in college students and develop comprehensive prevention and management programs to improve their QoL.

This study aimed to identify the factors affecting dry eye syndrome and quality of life (QoL) among college students. Methods: This cross-sectional study administered a descriptive survey to 184 college students across Korea. Data collection was conducted from August 27 to 28, 2024, using an online survey platform (Google Forms). The self-reported survey comprised the Health-Related Quality of Life Instrument with 8 Items scale, the Dry Eye Questionnaire 5, and the Ocular Surface Disease Index. Data analysis was performed using SPSS version 27.0. Results: The participants had a mean age of 21.37 (standard deviation 1.96) years. Regression analysis identified sleep satisfaction, vision-related functions, and dry eye symptoms as statistically significant predictors of QoL, accounting for 18.4% of the variance (F = 14.71, p < .001). Dry eye symptoms were significantly influenced by the use of artificial tears, vision-related functions, and environmental factors, which accounted for 41.3% of the variance (F = 43.93, p < .001). Additionally, significant determinants of ocular surface disease included the use of vision correction tools, the presence of ophthalmic diseases, sleep satisfaction, and dry eye symptoms. These factors explained 45.7% of the variance, confirming the model's robustness (F = 31.84, p < .001). Conclusion: It is necessary to identify strategies to alleviate dry eye syndrome in college students and develop comprehensive prevention and management programs to improve their QoL.