順天堂醫事雑誌
Online ISSN : 2188-2126
Print ISSN : 2187-9737
ISSN-L : 2187-9737
Reviews: 49th Health Topics for Tokyoites “Mobile Health for Predictive, Preventive, Personalized, and Participatory Medicine”[1]
P4 Medicine for Heterogeneity of Dry Eye: A Mobile Health-based Digital Cohort Study
TAKENORI INOMATA JAEMYOUNG SUNGALAN YEEAKIRA MURAKAMIYUICHI OKUMURAKEN NAGINOKENTA FUJIOYASUTSUGU AKASAKIAKIE MIDORIKAWA-INOMATAATSUKO EGUCHIKEIICHI FUJIMOTOTIANXIANG HUANGYUKI MOROOKAMARIA MIURAHURRAMHON SHOKIROVAKUNIHIKO HIROSAWAMIZU OHNOHIROYUKI KOBAYASHI
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ジャーナル オープンアクセス

2023 年 69 巻 1 号 p. 2-13

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During the 5th Science, Technology, and Innovation Basic Plan, the Japanese government proposed a novel societal concept -Society 5.0- that promoted a healthcare system characterized by its capability to provide unintrusive, predictive, longitudinal care through the integration of cyber and physical space. The role of Society 5.0 in managing our quality of vision will become more important in the modern digitalized and aging society, both of which are known risk factors for developing dry eye. Dry eye is the most common ocular surface disease encountered in Japan with symptoms including increased dryness, eye discomfort, and decreased visual acuity. Owing to its complexity, implementation of P4 (predictive, preventive, personalized, participatory) medicine in managing dry eye requires a comprehensive understanding of its pathology, as well as a strategy to visualize and stratify its risk factors.

Using DryEyeRhythm®, a mobile health (mHealth) smartphone software (app), we established a route to collect holistic medical big data on dry eye, such as the subjective symptoms and lifestyle data for each individual. The studies to date aided in determining the risk factors for severe dry eye, the association between major depressive disorder and dry eye exacerbation, eye drop treatment adherence, app-based stratification algorithms based on symptomology, blink detection biosensoring as a dry eye-related digital phenotype, and effectiveness of app-based dry eye diagnosis support compared to traditional methods. These results contribute to elucidating disease pathophysiology and promoting preventive and effective measures to counteract dry eye through mHealth.

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© 2023 The Juntendo Medical Society. This is an open access article distributed under the terms of Creative Commons Attribution License (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original source is properly credited.

This article is licensed under a Creative Commons [Attribution 4.0 International] license.
https://creativecommons.org/licenses/by/4.0/
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