Web Query Behaviour Concerning HEV (Blue) Light in Ophthalmology

Ahmed Al-Imam; Hend Jaddoa Al-Doori; Luay Mahmoud Hassan

doi:10.32007/jfacmedbagdad.6331840

Authors

Ahmed Al-Imam College of Medicine, University of Baghdad
Hend Jaddoa Al-Doori 1. Specialist Pediatrician, Al-Betool Teaching Hospital, Diyala Health Directorate, Iraqi Ministry of Health, Iraq. 2. Fellow (Pediatrics), Iraqi Board for Medical Specialities, Iraq. 3. Member (Pediatrics), the Council Arab Board of Health Specializations, Syria.
Luay Mahmoud Hassan 1. Specialist Ophthalmologist, Diyala Health Directorate, Iraqi Ministry of Health, Iraq. 2. Member, the Royal College of Surgeons (Edinburgh), United Kingdom. 3. Member (Ophthalmology), the Council Arab Board of Health Specializations, Syria.

DOI:

https://doi.org/10.32007/jfacmedbagdad.6331840

Keywords:

Blue light, digital epidemiology, frequentists statistics, high-energy visible light, machine learning, macular degeneration, photochemically-induced retinal injury, retinal detachment, retinal perforation, retinal tear

Abstract

Background: High-energy visible (HEV) possesses high-frequency in the violet-blue band of the visible light spectrum. Blue light has relevance to ophthalmology via photochemically-induced retinal injury.

Objectives: To explore the spatial-temporal mapping of online search behavior concerning HEV light.

Materials and Methods: We retrieved raw data of web search volume, via Microsoft Google Trends, using five search topics; "Biological effects of HEV light", "Vision impairment", "Macular degeneration", "Retinal tear", and "Retinal detachment", for the period 2004-2020.

Results: Web users, mainly from Far-East Asia and Australasia, were most interested in seeking online information concerning "Macular degeneration" and "Vision impairment" search topics, moderately interested in "Biological effects of HEV light" and "Retinal detachment", and least interested in "Retinal tear". Internet users from the Middle East and Arab world contributed minimally to the holistic map. Web queries increased at both chronological ends, 2004-2006 and 2018-2020; however, these trends were respondent to specific search topics. For instance, the search volume for the "Biological effects of HEV light" increased significantly in 2018-2020. Predictive modeling was most accurate for "Biological effects of HEV light". The strongest correlation was for "Vision impairment" versus "Macular degeneration". ANOVA, linear modeling, and machine learning unanimously agreed on predictors' significant effect (search topics and time) on the web search volume.

Conclusion: Web queries' mapping provided indirect evidence on the causality between HEV light and retinal damage. Future research mandates rigor observational and experimental studies.