Digital technologies are now universal and have spread worldwide; thus, digital behaviour has dramatically changed peoples’ lifestyles. Previous studies have reported that individuals interact with digital screens for up to 12 hours daily [
Computer vision syndrome (CVS) is also called by other names as digital eye strain (DES) [
Smartphones are used extensively worldwide by people of all ages [
Most studies that reported a high prevalence of CVS were conducted on university students [
No study in the literature investigated macular integrity or function in CVS [
In this study, our primary goal was to document the potential visual and ocular sequelae among medical students using a subjective CVS questionnaire and a complete ophthalmic examination. Furthermore, our secondary goal was to calculate the CVS prevalence within the study cohort. Finally, we sought to document the correlation between the subjective survey and objective clinical findings.
This study obtained the approval of the Institutional Review Board (IRB) in the Faculty of Medicine, Sohag University, Egypt. The trial registry number was obtained from ClinicalTrials.gov (registry number:
Using an alpha level of 0.01 and the survey sample size determination table created by Bartlett et al. [
In 2017, our research team developed and piloted a well-structured CVS questionnaire form (CVS-F1). It consisted of 20 questions that detected CVS prevalence among medical students at Sohag University. Our main objective at this point was to assess the reliability and validity of the CVS-F1. After our study was published in January 2018 [
In this study, we modified the CVS-F1 by adding more questions on the environmental, screen-use habits, and associated screen factors. The new modified questionnaire was identified as CVS-F3 (28 questions, S1 appendix in Supplementary Materials), which we used in this study. Our main aim by using CVS-F3 was to document whether the users’ habits and screen-styles were affecting the number and frequency of CVS complaints and its role in preventing the development of CVS. This modification minimised standard errors in the new version of the questionnaire (CVS-F3) and ensured it was more specific.
Our study included 733 medical students who were randomly assigned to complete the CVS-F3 regardless of their grade or age. The potential complaints and consequences of CVS were carefully explained to all participants before they responded to CVS-F3. The 733 surveyed students were classified into two groups according to their final diagnosis following their ophthalmic examination. The two groups consisted of the CVS group, which included students who were diagnosed with CVS, and the No-CVS group (control group), which included students who were not diagnosed with CVS. We also defined an mfERG subgroup, which included a random sample of students from both the CVS and control groups who underwent an mfERG examination.
In our study, the CVS final diagnosis was documented based on four major criteria. The first criterion was the presence of one or more ocular complaints related to the time of screen-use. The second criterion was the presence of one or more extraocular complaints related to the time of screen-use. The third criterion was the presence of one or more complaint-attacks every month over the last 12 months. The fourth criterion was ophthalmic examinations documenting DED, conjuctival hyperemia, reduced visual acuity, associated refractive errors, and/or mfERG abnormalities.
For greater clarity, we assessed all students prior to their grouping. Based on their examination and final diagnosis, we managed to certify the students who had CVS and identified them as the CVS group. On one hand, the remaining students who did not have CVS were identified as the control group (No-CVS group). Thereafter, we created an additional subgroup named the mfERG subgroup. Our main aim was to randomly assign an equal and small number of the students from both the CVS and control groups, using STATA software program, version 14.2, as a sample to undergo mfERG assessments to minimise the expenses of the costly mfERG examinations. Therefore, the mfERG subgroup (
All students underwent a complete clinical ophthalmic assessment and evaluation at the Ophthalmology Examination Unit in the Department of Ophthalmology. All students underwent visual acuity assessments, which included an uncorrected distance visual acuity (UDVA) measurement, corrected distance visual acuity (CDVA) measurement, subjective refraction, cycloplegic refraction, testing ocular movements, slit-lamp examination, intraocular pressure measurement, pupillary reflexes, and fundus examination. All examined students also underwent DED testing, which included the tear film break-up time test (TBUT) and the Schirmer test. The exclusion criteria included amblyopia; strabismus; anisometropia; CDVA worse than 0.00 logMAR; refractive errors higher than 6 D myopia, 4 D hyperopia, or 4 D astigmatism; difference between subjective and cycloplegic refraction >1 D; near vision abnormalities; and previous or current systemic or eye disease or surgery. The excluded students were not included in this study.
To perform the Schirmer test, we temporally inserted a Schirmer strip (Schirmer Ophthalmic Strip; Surgi Edge) into the lower fornix. Eyes were gently closed for 5 minutes, after which the amount of wetting was measured. If it was <10 mm, we considered it abnormal. To perform the TBUT, we inserted a fluorescein strip (1 mg fluorescein sodium I.P.; Surgi Edge, Ahmedabad, Gujarat, India) into the lower fornix, and the students were requested to blink several times. The students then underwent a slit-lamp examination with the cobalt blue-filter; if black holes were found in the tear film in less than 10 seconds, it was considered abnormal.
A random subsample of 40 eyes of 40 students from both groups was examined with the mfERG device (RETIscan; Roland Instruments, Wiesbaden, Germany) in accordance with the standard protocol for mfERG of the International Society for Clinical Electrophysiology of Vision (ISCEV). The mfERG stimulus used was 61 hexagons in dilated subjects with system age-matched norms. The protocol adhered to ISCEV standards.
Stata statistical software (version 14.2; StataCorp LP, College Station, TX, USA) was used for data analysis. The mean, standard deviation, range, and median values were used to describe the quantitative data. Numbers and percentages were used to describe the qualitative data. The chi-square test or Fisher’s exact test were used for comparisons between categorical variables. The Mann–Whitney
This study included 733 medical students (305 males [41.6%] and 428 females [58.4%]) with a mean age of 21.8 ± 1.5 years. The survey group (
CVS-F3 documented that 87.9% of the surveyed students had one or more ocular and/or extraocular complaints. However, only 70.8% of them reported that these complaints were associated with their screen use, that is, during or immediately after screen-use. In short, we will address here the most relevant CVS-F3 statistical analysis outcomes.
The most common ocular symptom included blurred vision in 40.9% of students, while the most common extraocular symptom was headache (46.8%). All ocular and extraocular complaints worsened with prolonged screen-hours, except for depression
Our survey outcomes revealed that the most common screen used by students was a smartphone. In addition, 504 students (68.8%) used various types and systems of smartphones. Specifically, 397 students (54.2%) used Android smartphones, 97 students (13.2%) used iOS smartphones (i.e., iPhones), and 10 students (1.4%) used other smartphone brands (Table
Relationship between symptoms and type of commonest/primary screen used.
Apple | Android | Laptop | Desktop computer | iPad/Tab | Other screens | ||
---|---|---|---|---|---|---|---|
Blurred vision | 47.4% | 47.6% | 41.1% | 15.8% | 0 | 40.0% | <0.0001 |
Dry eyes | 24.7% | 26.5% | 20.9% | 10.5% | 20.0% | 30.0% | 0.02 |
Eye strain/fatigue | 43.3% | 50.1% | 41.1% | 19.0% | 40.0% | 60.0% | <0.0001 |
Eye redness | 17.5% | 24.7% | 24.0% | 8.4% | 0 | 40.0% | 0.002 |
Double vision | 2.1% | 3.0% | 0.8% | 0 | 0 | 0 | 0.41 |
Refocusing difficulties | 20.6% | 20.7% | 17.8% | 6.3% | 0 | 10% | 0.02 |
Near vision difficulties | 13.4% | 16.1% | 15.5% | 4.2% | 0 | 10% | 0.04 |
Unclear objects | 44.33% | 45.1% | 38.0% | 16.8% | 0 | 70.0% | <0.0001 |
Headache | 44.3% | 53.9% | 45.0% | 20.0% | 40.0% | 70.0% | <0.0001 |
Insomnia | 22.7% | 21.7% | 18.6% | 5.3% | 20.0% | 10.0% | 0.003 |
Depression | 1.0% | 0.8% | 0 | 0 | 0 | 0 | 0.80 |
Neck pains | 45.4% | 49.9% | 38.0% | 22.1% | 40.0% | 40.0% | <0.0001 |
Joint pains | 35.1% | 36.3% | 18.6% | 10.5% | 0 | 30.0% | <0.0001 |
Inability to hold objects | 3.1% | 5.0% | 3.1% | 1.1% | 0 | 10.0% | 0.35 |
Difficulty to write | 13.4% | 6.3% | 2.3% | 5.3% | 0 | 10.0% | 0.03 |
Mean ± SD | 3.8 ± 2.9 | 4.1 ± 2.8 | 3.2 ± 3.0 | 1.5 ± 2.4 | 1.6 ± 1.8 | 4.3 ± 1.8 | 0.0001 |
Median (range) | 4 (0 : 13) | 4 (0 : 12) | 3 (0 : 11) | 0 (0 : 10) | 1 (0 : 4) | 3.5 (2 : 7) | |
CVS diagnosed with ophthalmic examination | 77 (79.4%) | 340 (85.6%) | 92 (71.3%) | 36 (37.9%) | 2 (40.0%) | 10 (100%) | <0.0001 |
The most common associated screen behaviour CVS factors recorded by our CVS-F3 were a close eye-screen distance (42.6% of surveyed students), watching the screen in the dark (33.7%), improper gaze angle as the screen edge was at/above horizontal eye level (28.2%), texting with both thumbs (28.8%), small font size (23.9%), and poor or improper lighting conditions (20.9%).
Regarding the frequency and severity of CVS complaints, 75% of total surveyed students reported that their complaints were frequently in the form of symptoms-attacks (repeated complaints on a monthly basis); however, only 70.8% of students stated that their symptoms-attacks were directly related to screen use, that is, typically during or immediately after their screen-use. On the other hand, 3.8% of students reported that their symptom-attacks were not related to screen use, that is, mostly not in the form of CVS symptoms. CVS-F3 recorded that the mean number of symptom-attacks/month was 3.6 ± 2.9 (ranging from 0 to 15 attacks/month). In contrast, the mean number of years that subjects had these symptom-attacks was 3.6 ± 2.9 (ranging from 0 to 8 years). Therefore, CVS may be responsible for chronic complaints in some cases.
Our CVS-F3 outcomes revealed that refractive errors represented a major CVS factor associated with CVS occurrence and the number of symptoms. In our sample, 56.5% of students had refractive errors and showed statistically significantly higher percentages of most of CVS ocular and extraocular symptoms.
We discovered statistically significant differences between students who were texting with both thumbs (
Tables
Univariate logistic regression analysis model of factors affecting the occurrence of computer vision syndrome.
Variable | No CSV | CSV | Odds ratio (95% confidence interval) | |
---|---|---|---|---|
Age/years | 21.4 ± 1.9 | 22.0 ± 1.4 | 1.3 (1.2 : 1.4) | <0.0001 |
Gender | ||||
Males | 88 (50.0%) | 217 (39.0%) | 1 | |
Females | 88 (50.0%) | 340 (61.0%) | 1.6 (1.1 : 2.2) | 0.01 |
Total daily screen-hours | 3.8 ± 1.2 | 5.3 ± 1.9 | 1.7 (1.5 : 2.0) | <0.0001 |
Screen-years | 4.1 ± 1.7 | 4.7 ± 1.9 | 1.2 (1.1 : 1.3) | <0.0001 |
Screen-time | ||||
Day | 64 (36.4%) | 176 (31.6%) | 1 | |
Night | 112 (63.6%) | 381 (68.4%) | 1.2 (0.9 : 1.8) | 0.24 |
Screen-mode | ||||
Interrupted | 127 (72.2%) | 452 (81.2%) | 1 | |
Continued | 49 (27.8%) | 105 (18.9%) | 0.6 (0.4 : 0.9) | 0.01 |
Commonest used screen | ||||
Desktop computer screen | 59 (33.5%) | 36 (6.5%) | 1 | |
Apple smartphone | 20 (11.4%) | 77 (13.8%) | 6.3 (3.3 : 12.0) | <0.0001 |
Android smartphone | 57 (32.4%) | 340 (61.0%) | 9.8 (5.9 : 16.1) | <0.0001 |
Laptop | 37 (21.0%) | 92 (16.5%) | 4.1 (2.3 : 7.2) | <0.0001 |
iPad/tablet/other screens | 3 (1.7%) | 12 (2.2%) | 6.5 (1.7 : 24.8) | 0.01 |
Screen size | ||||
Large | 93 (52.8%) | 258 (46.3%) | 1 | |
Medium/small | 83 (47.2%) | 299 (53.7%) | 1.3 (0.9 : 1.8) | 0.13 |
Screen-version | ||||
New | 158 (89.8%) | 453 (81.3%) | 1 | |
Old | 18 (10.2%) | 104 (18.7%) | 2.0 (1.2 : 3.4) | 0.01 |
Screen brightness (%) | 43.3 ± 23.3 | 39.2 ± 24.5 | 0.99 (0.98 : 1.00) | 0.054 |
Study medicine using | ||||
Books | 33 (18.8%) | 82 (14.7%) | 1 | |
Screens/both | 143 (81.2%) | 475 (85.3%) | 1.3 (0.9 : 2.1) | 0.20 |
Main screen-time purpose is | ||||
Medicine | 112 (63.6%) | 249 (44.7%) | 1 2.2 (1.5 : 3.1) | |
Social | 64 (36.4%) | 308 (55.3%) | <0.0001 | |
Previous DED diagnosis | 14 (8.0%) | 84 (15.1%) | 2.1 (1.1 : 3.7) | 0.02 |
Refractive errors/wearing | 82 (46.6%) | 332 (59.6%) | 1.7 (1.2 : 2.4) | 0.003 |
Contact lenses wearer | 14 (8.0%) | 29 (5.2%) | 0.6 (0.3 : 1.2) | 0.18 |
Poor lighting conditions | 12 (6.8%) | 141 (25.3%) | 4.6 (2.5 : 8.6) | <0.0001 |
Watch screen in the dark | 36 (20.5%) | 211 (37.9%) | 2.4 (1.6 : 3.6) | <0.0001 |
Upper screen edge at/above horizontal eye level | 2 (1.1%) | 205 (36.8%) | 50.0 (12.4 : 206.4) | <0.0001 |
Close eye-screen distance | 14 (8.0%) | 298 (53.5%) | 13.3 (7.5 : 23.6) | <0.0001 |
Uncomfortable seating postures | 2 (1.1%) | 77 (13.8%) | 14.0 (3.4 : 57.4) | <0.0001 |
Texting with both thumbs | 10 (5.7%) | 201 (36.1%) | 9.4 (4.8 : 18.2) | <0.0001 |
Screen-glare | 2 (1.1%) | 43 (7.7%) | 7.3 (1.7 : 30.4) | 0.01 |
Poor screen-resolution or design | 2 (1.1%) | 49 (8.8%) | 8.4 (2.0 : 34.9) | 0.003 |
Small font size | 21 (11.9%) | 154 (27.7%) | 2.8 (1.7 : 4.6) | <0.0001 |
Multivariate logistic regression analysis model of factors affecting the occurrence of computer vision syndrome.
Variable | Odds ratio (95% confidence interval) | |
---|---|---|
Gender | ||
Males | 1 | |
Females | 1.8 (1.0 : 3.2) | 0.047 |
Total daily screen-hours | 2.1 (1.7 : 2.6) | <0.0001 |
Commonest used screen | ||
Desktop computer screen | 1 | |
Apple smartphone | 1.0 (0.3 : 3.3) | 0.94 |
Android smartphone | 3.2 (1.2 : 8.1) | 0.02 |
Laptop | 1.7 (0.7 : 4.8) | 0.23 |
iPad/tablet/other screens | 3.8 (0.4 : 40.5) | 0.27 |
Screen size | ||
Large | 1 | |
Medium/small | 1.7 (0.96 : 2.9) | 0.07 |
Screen-version | ||
New | 1 | |
Old | 0.8 (0.3 : 2.2) | 0.63 |
Main screen-time purpose is | ||
Medicine | 1 | |
Social | 1.44 (0.7 : 3.0) | 0.33 |
Previous DED diagnosis | 3.8 (0.9 : 15.7) | 0.06 |
Refractive errors/wearing | 2.1 (1.2 : 3.8) | 0.01 |
Contact lenses wearer | 0.03 (0.005 : 0.1) | <0.0001 |
Poor lighting conditions | 1.46 (0.6 : 3.7) | 0.42 |
Watch screen in the dark | 0.9 (0.5 : 1.8) | 0.75 |
Upper screen edge at/above horizontal eye level | 47.5 (10.1 : 225.1) | <0.0001 |
Close eye-screen distance | 11.2 (5.1 : 24.6) | <0.0001 |
Uncomfortable seating postures | 13.4 (2.4 : 75.5) | 0.003 |
Texting with both thumbs | 7.6 (3.1 : 18.6) | <0.0001 |
Screen-glare | 2.0 (0.3 : 15.5) | 0.52 |
Poor screen-resolution or design | 35.8 (4.4 : 295.1) | 0.001 |
Small font size | 1.9 (0.88 : 4.1) | 0.11 |
Final multivariate logistic regression analysis model of factors affecting the occurrence of computer vision syndrome.
Variable | Odds ratio (95% confidence interval) | |
---|---|---|
Total daily screen-hours | 2.0 (1.7 : 2.5) | <0.0001 |
Commonest used screen | ||
Desktop computer screen | 1 | |
Apple smartphone | 1.5 (0.6 : 3.9) | 0.43 |
Android smartphone | 4.6 (2.24 : 9.6) | <0.0001 |
Laptop | 1.8 (0.8 : 4.2) | 0.17 |
iPad/tablet/other screens | 4.3 (0.6 : 31.0) | 0.15 |
Previous DED diagnosis | 5.2 (1.4 : 19.0) | 0.01 |
Refractive errors/wearing spectacles | 2.3 (1.4 : 4.0) | 0.002 |
Contact lenses wearer | 0.03 (0.01 : 0.1) | <0.0001 |
Upper screen edge at/above horizontal eye level | 44.3 (10.0 : 196.5) | <0.0001 |
Close eye-screen distance | 10.8 (5.2 : 22.5) | <0.0001 |
Uncomfortable seating postures | 19.1 (3.7 : 98.5) | <0.0001 |
Texting with both thumbs | 6.1 (2.7 : 14.2) | <0.0001 |
Poor screen-resolution or design | 48.2 (6.6 : 354.9) | <0.0001 |
Multivariate logistic regression analysis of factors affecting the occurrence of blurred vision.
Variable | Odds ratio (95% confidence interval) | |
---|---|---|
Age/years | 1.1 (0.99 : 1.3) | 0.06 |
Gender | ||
Males | 1 | |
Females | 1.2 (0.8 : 1.7) | 0.38 |
Total daily screen-hours | 1.0 (0.9 : 1.2) | 0.37 |
Screen-years | 0.98 (0.88 : 1.1) | 0.63 |
Commonest used screen | ||
Desktop computer screen | 1 | |
Apple smartphone | 2.4 (1.0 : 5.5) | 0.04 |
Android smartphone | 2.0 (0.95 : 4.2) | 0.07 |
Laptop | 2.1 (0.99 : 4.5) | 0.054 |
iPad/tablet/other screens | 0.9 (0.2 : 3.9) | 0.88 |
Screen brightness (%) | 1.00 (0.99 : 1.0) | 0.44 |
Study medicine using | ||
Books | 1 | |
Screens/both | 1.6 (0.97 : 2.7) | 0.07 |
Main screen-time purpose is | ||
Medicine | 1 | |
Social | 1.3 (0.8 : 1.9) | 0.30 |
Previous DED diagnosis | 2.1 (1.2 : 3.8) | 0.01 |
Refractive errors/wearing | 2.0 (1.4 : 2.8) | <0.0001 |
Contact lenses wearer | 0.7 (0.3 : 1.6) | 0.41 |
Poor lighting conditions | 2.6 (1.7 : 4.1) | <0.0001 |
Watch screen in the dark | 1.0 (0.68 : 1.6) | 0.87 |
Upper screen edge at/above horizontal eye level | 2.0 (1.3 : 2.9) | 0.001 |
Close eye-screen distance | 2.1 (1.5 : 3.0) | <0.0001 |
Uncomfortable seating postures | 1.3 (0.7 : 2.3) | 0.38 |
Texting with both thumbs | 1.7 (1.2 : 2.5) | 0.004 |
Screen-glare | 2.8 (1.2 : 6.5) | 0.02 |
Poor screen-resolution or design | 1.9 (0.8 : 4.4) | 0.13 |
Small font size | 1.5 (0.97 : 2.3) | 0.07 |
Final multivariate logistic regression analysis of factors affecting the occurrence of blurred vision.
Variable | Odds ratio (95% confidence interval) | |
---|---|---|
Age/years | 1.1 (1.0 : 1.3) | 0.02 |
Commonest used screen | ||
Desktop computer screen | 1 | |
Apple smartphone | 2.7 (1.2 : 5.7) | 0.01 |
Android smartphone | 2.5 (1.3 : 4.7) | 0.01 |
Laptop | 2.2 (1.1 : 4.6) | 0.03 |
iPad/tablet/other screens | 1.0 (0.3 : 4.1) | 0.97 |
Previous DED diagnosis | 2.1 (1.3 : 3.6) | 0.004 |
Refractive errors/wearing | 1.9 (1.3 : 2.7) | <0.0001 |
Poor lighting conditions | 2.6 (1.7 : 4.0) | <0.0001 |
Upper screen edge at/above horizontal eye level | 2.0 (1.4 : 3.0) | <0.0001 |
Close eye-screen distance | 2.2 (1.5 : 3.0) | <0.0001 |
Screen-glare | 3.0 (1.5 : 6.2) | 0.003 |
Multivariate linear regression analysis of factors affecting the total number of symptoms.
Variable | Regression coefficient (95% confidence interval) | |
---|---|---|
Age/years | 0.1 (−0.04 : 0.2) | 0.23 |
Gender | ||
Males | 1 | |
Females | 0.5 (0.2 : 0.8) | 0.001 |
Total daily screen-hours | 0.2 (0.1 : 0.3) | <0.0001 |
Screen-years | 0.03 (−0.1 : 0.1) | 0.53 |
Commonest used screen | ||
Desktop computer screen | 1 | |
Apple smartphone | 0.3 (−0.3 : 0.9) | 0.36 |
Android smartphone | 0.4 (−0.2 : 0.9) | 0.19 |
Laptop | 0.2 (−0.3 : 0.8) | 0.39 |
iPad/tablet/other screens | 0.4 (−0.7 : 1.5) | 0.50 |
Screen size | ||
Large | 1 | |
Medium/small | 0.3 (0.04 : 0.6) | 0.02 |
Study medicine using | ||
Books | 1 | |
Screens/both | 0.5 (0.1 : 0.9) | 0.03 |
Main screen-time purpose is | ||
Medicine | 1 | |
Social | 0.2 (−0.1 : 0.6) | 0.24 |
Previous DED diagnosis | 0.9 (0.5 : 1.4) | <0.0001 |
Refractive errors/wearing | 0.6 (0.3 : 0.9) | <0.0001 |
Contact lenses wearer | 0.2 (−0.5 : 0.9) | 0.53 |
Poor lighting conditions | 1.3 (0.9 : 1.7) | <0.0001 |
Watch screen in the dark | 0.0003 (−0.3 : 0.3) | 0.998 |
Upper screen edge at/above horizontal eye level | 1.5 (1.1 : 1.8) | <0.0001 |
Close eye-screen distance | 1.2 (0.9 : 1.6) | <0.0001 |
Uncomfortable seating postures | 1.2 (0.7 : 1.7) | <0.0001 |
Texting with both thumbs | 1.7 (1.3 : 2.00) | <0.0001 |
Screen-glare | 1.6 (0.9 : 2.3) | <0.0001 |
Poor screen-resolution or design | 1.6 (0.9 : 2.3) | <0.0001 |
Small font size | 0.7 (0.4 : 1.1) | <0.0001 |
Final multivariate linear regression analysis of factors affecting the total number of symptoms.
Variable | Regression coefficient (95% confidence interval) | |
---|---|---|
Gender | ||
Males | 1 | |
Females | 0.6 (0.3 : 0.9) | <0.0001 |
Total daily screen-hours | 0.2 (0.1 : 0.3) | <0.0001 |
Screen size | ||
Large | 1 | |
Medium/small | 0.3 (0.05 : 0.6) | 0.02 |
Previous DED diagnosis | 1.1 (0.:1.5) | <0.0001 |
Refractive errors/wearing | 0.7 (0.4 : 1.0) | <0.0001 |
Poor lighting conditions | 1.3 (1.0 : 1.7) | <0.0001 |
Upper screen edge at/above horizontal eye level | 1.5 (1.2 : 1.8) | <0.0001 |
Close eye-screen distance | 1.3 (1.00 : 1.6) | <0.0001 |
Uncomfortable seating postures | 1.3 (0.8 : 1.7) | <0.0001 |
Texting with both thumbs | 1.8 (1.4 : 2.1) | <0.0001 |
Screen-glare | 1.4 (0.8 : 2.0) | <0.0001 |
Poor screen-resolution or design | 1.4 (0.9 : 2.0) | <0.0001 |
Small font size | 0.8 (0.4 : 1.1) | <0.0001 |
Table
Differences between the control and CVS groups.
Parameters | Control group | CVS group | Mean difference | |
---|---|---|---|---|
Visual outcomes (logMAR): | ||||
UDVA | 0.13 ± 0.12 | 0.31 ± 0.25 | −0.18 | <0.0001 |
0.1 (−0.1 : 0.5) | 0.3 (−0.1 : 1.1) | (−0.22 : −0.09) | ||
CDVA | −0.016 ± 0.04 | −0.002 ± 0.01 | −0.014 | <0.0001 |
0 (−0.1 : 0) | 0 (−0.1 : 0) | (−0.018 : −0.008) | ||
Subjective refraction (D): | ||||
Sphere | −0.51 ± 1.13 | −0.90 ± 1.12 | 0.39 | <0.0001 |
−0.13 (−4:2.5) | −0.75 (−5:4) | (−0.02 : 0.53) | ||
Cylinder | −0.25 ± 0.61 | −0.51 ± 0.74 | 0.26 | <0.0001 |
0 (−4:1) | −0.25 (−4:2.75) | (0.17 : 0.41) | ||
SE | −0.63 ± 1.19 | −1.16 ± 1.42 | 0.53 | <0.0001 |
−0.5 (−4:2.5) | −0.88 (−6.25 : 4.25) | (0.24 : 0.68) | ||
DED tests: | ||||
Tear film break-up time: | <0.0001 | |||
TBUT in seconds | 12.38 ± 1.78 | 8.93 ± 2.16 | 3.45 | |
12 (7 : 17) | 9 (2 : 15) | (4.26 : 3.12) | ||
Abnormal TBUT test (<10 seconds) | 5 eyes (2.8%) | 336 eyes (60.3%) | <0.0001 | |
Schirmer test: Schirmer test in mm | 19.57 ± 4.07 | 10.68 ± 4.37 | 8.89 | <0.0001 |
20 (8 : 29) | 9 (5 : 26) | (10.94 : 8.46) | ||
Abnormal Schirmer test (<10 mm) | 5 eyes (2.8%) | 301 eyes (54%) | <0.0001 | |
Slit-lamp examination: | ||||
Conjunctival hyperemia (eye redness) | 11 eyes (6.3%) | 181 eyes (32.5%) | <0.0001 | |
Watery/mucous discharge | 0 eyes (0%) | 3 eyes (0.5%) | <0.0001 | |
Normal fundus examination: | 100% | 100% | ||
Students/eyes documented with | ||||
Diagnosed CVS cases | 0 cases (0%) | 557 cases (100%) | <0.0001 | |
Reduced UDVA (worse than 0.00 logMAR) | 101 eyes (57.4%) | 409 eyes (73.4%) | 0.001 | |
Reduced CDVA (worse than 0.00 logMAR) | 0 eyes (0%) | 0 eyes (0%) | 1.00 | |
Diagnosed DED cases | 5 eyes (2.8%) | 336 eyes (60.3%) | <0.0001 |
UDVA: uncorrected distance visual acuity; CDVA: corrected distance visual acuity; TBUT: tear film break-up time test; CVS: computer vision syndrome; DED: dry eye disease; SE: spherical equivalent; logMAR logarithm of the minimum angle of resolution.
The mfERG subgroup included 40 eyes of 40 students (16 males and 24 females). The mfERG examination took nearly 15–20 minutes to be completed. In the mfERG analysis, the normal mfERG ranges were determined internal to the system. Table
Data summary of the mfERG subgroup.
Parameters | mfERG students from control group | mfERG of students from CVS group | Mean difference (mini−control−risk) 95% confidence of interval | |
---|---|---|---|---|
Age | 22.35 ± 1.53 | 21.95 ± 2.14 | 0.4 | 0.50 |
22 (19 : 25) | 21 (19 : 25) | (−0.79 : 1.59) | ||
Gender: | ||||
Male | 8 (40%) | 8 (40%) | 1.00 | |
Female | 12 (60%) | 12 (60%) | ||
Screen-hours: | ||||
1 h | 4 (20%) | 0 | ||
2 h | 3 (15%) | 1 (5%) | 0.09 | |
3 h | 3 (15%) | 1 (5%) | ||
4 h | 2 (10%) | 4 (20%) | ||
5 h | 5 (25%) | 5 (25%) | ||
≥6 h | 3 (15%) | 9 (45%) | ||
- mfERG students < 3 screen-hours | 10 (50%) | 2 (10%) | 0.006 | |
- mfERG students ≥3 screen-hours | 10 (50%) | 18 (90%) | ||
Screen-time: | ||||
Day | 12 (60%) | 5 (25%) | 0.03 | |
Night | 8 (40%) | 15 (75%) | ||
Screen-illumination: | ||||
10% | 5 (25%) | 1 (5%) | 0.06 | |
30% | 7 (35%) | 3 (15%) | ||
50% | 5 (25%) | 5 (25%) | ||
80% | 2 (10%) | 6 (30%) | ||
100% | 1 (5%) | 5 (25%) | ||
- mfERG students ≤50% illumination | 17 (85%) | 9 (45%) | 0.01 | |
- mfERG students >50% illumination | 3 (15%) | 11 (55%) | ||
Commonest screen used: | ||||
Desktop computers | 0 | 2 (10%) | 0.4 | |
Laptops | 1 (5%) | 2 (10%) | ||
Apple | 4 (20%) | 4 (20%) | ||
Android | 14 (70%) | 12 (60%) | ||
Other screens | 1 (5%) | 0 | ||
mfERG findings: | ||||
I-amplitudes P1 (nV/deg2): | ||||
Ring 1 (normal 66.6–130.8) | 80.60 ± 19.71 | 54.01 ± 9.17 | 26.59 (16.75 : 36.43) | <0.0001 |
76.49 (45.26 : 141.4) | 52.86 (40.43 : 74.09) | |||
Ring 2 (normal 30.9–77.8) | 35.75 ± 6.94 | 30.55 ± 5.97 | 5.20 (1.05 : 9.34) | 0.02 |
34.76 (25.08 : 52.74) | 30.97 (15.17 : 40.61) | |||
Ring 3 (normal 21.7–59) | 19.80 ± 3.80 | 18.57 ± 3.67 | 1.22 (−1.17 : 3.62) | 0.31 |
20.08 (13.38 : 25.3) | 18.27 (11.54 : 25.36) | |||
Ring 4 (normal 12.9–37.1) | 12.62 ± 2.52 | 10.50 ± 2.40 | 2.11 (0.54 : 3.69) | 0.01 |
12.87 (8.87 : 17.38) | 10.21 (4.98 : 14.37) | |||
Ring 5 (normal 10–28.2) | 9.69 ± 2.55 | 7.82 ± 1.81 | 1.88 (0.46 : 3.29) | 0.01 |
9.13 (5.51 : 14.51) | 7.74 (4.57 : 10.93) | |||
II-amplitudes P1 (nV/deg2): | ||||
Quadrant 1 (normal 15.8–42.74) | 11.26 ± 3.76 | 9.17 ± 2.01 | 2.09 (0.16 : 4.03) | 0.03 |
10.83 (5.05 : 19.41) | 9.29 (5.12 : 12.48) | |||
Quadrant 2 (normal 15.98–42.75) | 14.39 ± 2.81 | 12.03 ± 2.98 | 2.36 (0.51 : 4.22) | 0.01 |
13.91 (9.58 : 18.71) | 12.09 (5.63 : 17.54) | |||
Quadrant 3 (normal 15.18–42.05) | 15.13 ± 3.06 | 12.80 ± 3.46 | 2.33 (0.24 : 4.42) | 0.03 |
13.69 (10.6 : 21.02) | 12.60 (5.23 : 18.4) | |||
Quadrant 4 (normal 13.87–39.61) | 10.27 ± 2.41 | 9.20 ± 2.18 | 1.07 (−0.40 : 2.54) | 0.15 |
9.98 (6.62 : 16.02) | 8.49 (6.09 : 16.02) | |||
III-foveal functions: | ||||
Normal foveal response (21 eyes) | 20 eyes (100%) | 3 eyes (15%) | <0.0001 | |
Reduced foveal response (19 eyes) | 0 (0%) | 17 eyes (85%) |
mfERG subgroup outcomes. (a) Plot showing the main differences in mfERG Rings P1 amplitudes between the control and the CVS groups. (b) Plot showing the main differences in mfERG Quadrants P1 amplitudes between the control and the CVS groups.
In the control group, all 20 eyes exhibited a normal mfERG examination with normal foveal responses, including a preserved foveal peak (first positive peak, P1), and the amplitude density (AD) was within the normal range, demonstrating normal foveal function. In the CVS group, only three eyes exhibited a normal foveal response, while the remaining 17 eyes exhibited a reduced foveal response and were identified as positive cases.
In these 17 positive cases, the P1 AD for Ring 1 was 51.53 ± 7.24 nV/deg2 (mean ± SD). The parafoveal and perifoveal rings also showed a significant reduction as Rings 3, 4, and 5 showed P1 AD of 18.87 ± 3.85, 10.72 ± 2.64, and 8.02 ± 2.07 nV/deg2, respectively. These findings reveal foveal dysfunction and may explain the reduction in CDVA. Figure
Multifocal electroretinography outcomes: (a) and (b) two students from the control group with normal foveal responses; (c) and (d) two students from the CVS group with reduced foveal responses.
We found that the students who were spending more than 3 screen-hours daily
The main purpose of this study was to document the CVS-associated visual or ocular sequelae. In addition, we also sought, as a secondary purpose, to detect the actual CVS prevalence among the medical students included in our study sample size. There were three primary outcomes in our study. First, we demonstrated that comprehensive ophthalmic examinations and investigations were more accurate than subjective questionnaires regarding the diagnosis of the actual CVS-related sequelae, severity, and prevalence. Second, our findings revealed that the misuse of smartphones is mainly responsible for the increase in CVS prevalence and severity. Third, our mfERG findings might be a sign of potential CVS visual sequelae in high-risk CVS subjects, which could be confirmed or denied in future studies.
Although CVS-F3 outcomes reported potential CVS-related symptoms in 87.9% of surveyed students, ophthalmic examinations documented only a 76% CVS prevalence rate among the assessed students. Therefore, we think that subjective questionnaires might be overestimating the actual prevalence rates of CVS, while comprehensive ophthalmic examinations are more accurate in documenting actual CVS prevalence rates. The relatively better statistical outcomes of a desktop computer in comparison with smartphones and laptops can be explained based on the larger screen size, further screen distance, low cost, and the fact that these are neither easily portable nor handheld screens.
We believe that the smartphone itself might not be the underlying cause for exacerbating CVS but the way of its usage by the subjects might be the problem. Our conclusion was based on the outcomes of the final logistic regression analysis which found that improper close eye-screen viewing distance, improper gaze angle, poor screen design, poor screen-resolution, incorrect seating posture, texting with both thumbs, and associated refractive errors represented the main risk factors of CVS occurrence
Prolonged and continuous screen-hours require the bilateral use of both sets of intraocular and extraocular muscles (e.g., ciliary, constrictive pupillae, and medial recti muscles) to adjust the focus and achieve the best visual performance. Poor eye coordination or inadequate eye focusing might be caused by improper or extremely close viewing distance, improper screen brightness, poor screen-resolution, screen-glare in old screens, and/or uncorrected refractive errors, which finally increase CVS severity. The small screen size and small font size also increase eye strain and fatigue due to inadequate eye focusing. We observed that the distance between the screen and the user’s eyes decreases as the screen size decreases and the severity of CVS increases. Therefore, the greatest CVS severity was associated with misuse of smartphones, whereas the lowest severity was associated with desktop computers.
Similar to our outcomes, Golebiowski et al. [
Comparisons between the CVS-F3 outcomes and other studies’ surveys have revealed major differences that could be attributed to our larger sample size, behavioural practices, and different study demographics. Mowatt et al. [
Al Rashidi and Alhumaidan [
Our mfERG findings pointed to macular cone/bipolar cell dysfunction. We posit that CVS might have elicited these recorded mfERG changes in this small subsample of students from light exposure as a result of cone adaptation, electrode/focusing effects, or the spectral output of the devices which varied between subjects. Exposure to high levels of longer wavelength light could adapt L and M cones better than a shorter wavelength exposure. However, we remain unsure of whether or not these students were using colour adjustments to their smartphones or study displays, as we did not investigate this point.
The main limitation of our study consisted in our inability to perform mfERG on many participants due to costs. mfERG is also difficult and time-consuming; therefore, it might not be suitable for all study participants. Another limitation to our study included the subjects’ tendency to use multiple screens, which made it difficult to isolate a particular effect for a particular screen. Finally, we do acknowledge that our study was not a population-based study. Therefore, our recorded CVS prevalence rate can be only applied to the medical students’ category in our region, but not to the population in our country.
In conclusion, subjective questionnaire surveys alone, without an ophthalmic examination, are not ideal for documenting true CVS prevalence. CVS can be only accurately diagnosed with comprehensive ophthalmic examinations and investigations. The misuse of smartphones, regardless of the manufacturer, was the main aetiological agent responsible for the development and sequelae of CVS. Our study showed that CVS might have caused mfERG changes with reduced foveal responses; however, this potential screen-induced foveal dysfunction and its impact on visual acuity need to be confirmed in future studies.
Patients’ data used to support the findings of this study are available from the corresponding author upon request.
The authors declare that there are no conflicts of interest regarding the publication of this paper.
The authors would like to thank Prof. Fouad Metry Yosef, the expert statistician who performed all statistical analyses, and Prof. Youssef Waheeb, professor of community medicine at Suez Canal University, for his advice and guidance. The authors are also grateful for the great help and support of Dr. Mona Abo-Ali, Mr. Hamza Mohammed, Seif Mohammed, and Lina Mohammed.
S1 appendix: CVS-F3. S2 appendix: multivariate logistic regression analysis of factors affecting the occurrence of dry eye. S3 appendix: final multivariate logistic regression analysis of factors the affecting occurrence of dry eye. S4 appendix: univariate linear regression analysis of factors affecting the total number of symptoms.