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.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.