Association between dry eye and depressive symptoms: Large-scale crowdsourced research using the DryEyeRhythm iPhone application

Abstract

Purpose: Dry eye (DE) disease and depression are increasing in modern times. We investigated the association between DE and depressive symptoms using the iPhone application, DryEyeRhythm.

Methods: This large-scale crowdsourced observational study was conducted within iPhone users in Japan who downloaded DryEyeRhythm. Participants with a Zung Self-rating Depression Scale (SDS) score ≥ 40 were defined as having depressive symptoms, and those with an Ocular Surface Disease Index (OSDI) score ≥ 13 were defined as having DE symptoms (mild, 13-22; moderate, 23-32; and severe, 33-100). We compared SDS scores between participants with normal eye and mild, moderate, and severe OSDI-based DE symptoms. Logistic regression analyses were used to determine the association between DE severity and depressive symptoms after adjustment for demographic characteristics, medical history, and lifestyle habits.

Results: This study included 4454 participants (mean age, 27.9 ± 12.6 years; female, 66.7%). Participants with SDS scores ≥40 accounted for 58.2%, 70.9%, 79.4%, and 85.0% of normal controls and participants with mild, moderate, and severe DE symptoms, respectively (P trend < 0.001). The adjusted odds ratios (95% confidence interval) for depressive symptoms (SDS score of ≥40) were 1.62 (1.35-1.95) for mild, 2.39 (1.92-2.97) for moderate, and 3.29 (2.70-4.00) for severe DE symptoms.

Conclusion: This large-scale crowdsourced clinical study using DryEyeRhythm suggests that depressive symptoms are more common in individuals with more severe DE symptoms. DryEyeRhythm could play a role in earlier prevention or future prospective interventions for depressive symptoms in individuals with DE symptoms.

Keywords: Crowdsourced research; Depression; Dry eye disease; DryEyeRhythm; Researchkit.