PREVALENCE AND RISK FACTORS OF DIGITAL EYE STRAIN 1.pptx

Prevalence and risk factors of digital eye strain among university students study research

1. PREVALENCE AND RISK FACTORS OF DIGITAL EYE STRAIN AMONG UNIVERSITY STUDENTS PRESENTED BY: NIHARIKA RATHOR ROLL NO:232112027040 SEMESTER:5 TH SEM,3 RD YEAR SUBMITTED TO: MS. AYUSHI AHUJA CAMPUS NAME: SIR C.V.RAMAN,DSEU,DHEER2PUR CAMPUS DATE: 21- OCT-2025 This Photo by Unknown Author is licensed under CC BY-NC-ND

2. INTRODUCTION Digital Eye Strain (DES)- also known as computer vision syndrome-refers to a groups of eye and vision –related problems caused by prolonged screen use. With increased dependence on Digital Devices for education and entertainment , university students are at higher risk. Common symptoms : eye fatigue ,blurred vision, dryness, headache, neck/shoulder pain. Understanding its prevalence and risk factors is crucial for developing preventive strategies.

3. Research Question Q1-What is the prevalence of digital eye strain among university students? Q2-What are the risk facto rs (e .g., screen time, posture ,lighting ,breaks , device type)? Q3-Is there an association between usage habits and severity of DES symptoms? This Photo by Unknown Author is licensed under CC BY

4. Hypotheses H1 : There is a high prevalence of digital eye strain among university students. H2: Longer screen time is significantly associated with higher risk of DES. H3:Poor ergonomic practices (e.g., improper lighting, lack of breaks) increase the likelihood of DES. H0 :There is no significant association between screen usage patterns and DES symptoms. This Photo by Unknown Author is licensed under CC BY-SA

5. Literature Review Studies report DES prevalence ranging from 50-90% among computer users. Shanta Kumari et al. (2014): 68% of students experienced eye strain after continuous screen use. Reddy et al. (2013) : screen time >4 hours/day strongly associated with eye discomfort. Rosenfield (2016 ): improper viewing distance and poor lighting are modifiable risk factors. Majority of studies focus on working professionals, with limited focus on university students.

6. Lacunae in Literature(Research Gap) Limited recent data on DES among university students , especially in the post-pandemic digital learning context . Few studies explore combined effects of ergonomics, device type, and screen time. Lack of standardized assessment tools for DES symptoms in student populations.

7. Rationale of the study The pandemic has increased screen exposure due to online classes and digital assignments. Students may lack awareness of preventive eye health practices. This study aims to fill the gap by assessing current prevalence and risk factors among university students.

8. Aim and Objectives AIM: To determine the Prevalence and risk factors of digital eye strain among university students. OBJECTIVES: To estimate the prevalence of digital eye strain among students. To identify associated risk factors (screen time ,posture, lighting etc.) To assess the relationship between screen habits and symptom severity.

9. Methodology Study Design: Cross-sectional descriptive study. Study Population: University students aged 18-25 years. Sample size : (specify number) selected through convenience sampling Data Collection Tool: Structured questionnaire using subjectively (through questionnaires) like CVS-Q ,CVSS17 or objectively (through clinical test) like TBUT , Schirmer test ,NPC and Contrast sensitivity test. Variables: - Independent : Screen time ,device type ,posture ,lighting , breaks frequency. - Dependent: Presence and severity of digital eye strain symptoms.

10. Data Collection Procedure 1.Ethical clearance obtained from institutional review board. 2.Online /Offline survey distributed among students. 3.Informed consent obtained prior to participation. 4.Questionnaire includes demographic info, screen habits ; and DES symptom checklist Subjectively (CVS-Q , CVSS17,OSDI and visual fatigue questionnaire) and Objectively (TBUT , Schirmer test , NPC and Contrast Sensitivity). 5. Data Analysis : Using SPSS/Excel- descriptive stats, chi- square , regression.

11. Expected Outcome Estimated prevalence rate of DES among university students. Identification of major risk factors influencing DES. Evidence-based recommendations for prevention(e.g.,20-20-20 rule , ergonomic education). Contribution to student wellness programs and digital health awareness.