Ours is a technologically driven generation and digital devices including smartphones are an essential part of our lives. Smartphones are mini-computers that bring the world at our finger-tips. Besides communication and entertainment, the smartphone has evolved into an important educational tool that provides instant access to reference materials and databases on the go. In the medical field also smartphones serve a vital role in diagnosis, discussion, record keeping, and health education [1-5].

The downside of this digital revolution is that the increased screen-time has a negative impact on ocular health. The small size and distance at which the handheld smartphone screen is used, require increased accommodative effort by the eye muscles which leads to asthenopic symptoms such as blurring, fatigue, dryness, and grittiness which are referred to as Computer vision syndrome (CVS) [6]. Added to that is the reduced blink-rate, which causes Dry Eye Disease (DED) by altering the tear film dynamics [7,8]. Long-standing dry eye disease leads to corneal epithelial changes which further aggravate the symptoms. Recently there is evidence to suggest that blue light emitted by the phone screens has a damaging effect on retinal and corneal epithelium [9]. The use of blue light blocking glasses and screen guards has been shown to reduce the symptoms of eye strain and fatigue [10].

There are many national and international studies on Computer Vision Syndrome and Dry Eye Disease associated with computer use, but the number of studies on the effect of smartphone use on symptoms of eye strain and tear film parameters is limited. Thus, the purpose of this study was to look for any correlation between smartphone usage and dry eye, as well as report the frequency of computer vision syndrome (asthenopic) symptoms in smartphone users.

The current study selected medical students for our work because at present there was no data on thesmartphone-related ocular problems faced by this vulnerable group which has to rely on their phones for educational purposes besides the other routine uses. To the best of our knowledge, no studies are showing a correlation of dry eye symptoms with screen brightness and the use of blue-blocking mobile-screen guards. Thus, these points were also explored.

The questions of dry eye symptoms had 4 possible responses “never”, “sometimes”, “often” and “always”. Subjects who responded to more than 2 of the questions by “always” or “often” were considered positive for symptoms of DED. The mean of all the points was the dry eye disease score. (DED score) [13].

Clinical Evaluation: It consisted of a comprehensive eye examination on slit-lamp, and evaluation of tear film parameters such as Schirmer’s test, Tear film break-up time, tear meniscus height, and corneal surface staining. All the clinical measurements were carried out in a single, non-air-conditioned room with constant temperature and humidity.

Tear film quantity was tested by Schirmer’s test. (Non-invasive superficial procedure) It was performed with the help of a 5x35mm strip of the Whatman-41 filter paper. The strip was folded 5mm from one end and kept in the lower fornix of both eyes at the junction of lateral one-third and medial two-thirds. After 5 minutes, the strips were removed and the length of filter paper wetted was noted in mm. Tear film stability was assessed by the Tear film breakup time (TBUT). The patient was seated on a slit lamp and the eye was stained with fluorescein dye strip. The patient was asked to blink 2-3 times and then instructed to look straight ahead without blinking. The interval between the last blink and the appearance of the first corneal dark spot was measured in seconds. The tear meniscus height (TMH) was measured at the slit lamp (Haag Streit model) with a narrow vertical beam of light of 0.3 and 1.0mm from the lower lid margin to the top of the tear meniscus. Keratoepitheliopathy was measured by multiplying the area score by density score after staining with 0.5% fluorescein dye. The staining area was graded on a numerical scale of 0–3, with 0 representing no punctate staining; 1, less than one-third; 2, one-third to two-thirds; and 3, more than two-thirds. The staining density was graded on a numerical scale of 0–3, with 0 representing no punctate staining; 1, sparse density; 2, moderate density; and 3, high density with overlapping lesions.

Diagnosis and scoring of dry eye disease: The presence of DED was diagnosed based on the criteria defined by the Dry Eye Society in 2006 [14]. These criteria include the presence of (1) dry eye symptoms, (2) qualitative or quantitative abnormalities of the tear film in one or both eyes (Schirmer's test results of ≤5 mm or TBUT of ≤5

The mean Schirmer’s score was 19.08mm±8.24. 95.6% (376) participants had a Schirmer’s score of more than 5mm. The mean TBUT was 7.93 ± 3.05 and 71.06% (279) had a TBUT>5mm. In 62.18% (244) subjects the tear meniscus height was >0.3mm, the average TMH was 0.28±0.12mm.

The mean values of all the three tear film parameters were lower in the DED group compared to the non-DED group and the difference was statistically significant as inferred by the student’s t-test.

Table 2 shows the relative frequency of symptoms of computer vision syndrome (CVS) among the DED and non-DED groups. Fatigue was the most common symptom in the DED group (64.4%)while heaviness was the most commonly reported symptom in the non-DED group (44.5%).

The frequency of fatigue (64.4% vs. 44.55% , p 0.0012) watering (56.09% vs.37.82%,p 0.0036), blurring (57.3% vs. 36.21%, p 0.0006), dryness (30.48% vs. 15.7%, p=0.0039) and photophobia (57.31% vs. 39.74% p =0.0056) were significantly higher in the DED group as compared to the non DED. However, the reported frequency of redness, grittiness, and heaviness was not significantly different in the two groups. The average DED score was higher in the DED group(1.56±0.234) than in the non-DED group it was (1.35±0.248), with a p-value of 0.0001.

Table-2: Comparison of Frequency of Symptoms of CVS in the DED and non-DED group.

^⃰ Fisher’s exact test, ^† CVS (computer vision syndrome)

The mean daily usage of smartphones in hours per day was 3.58±1.186. The mean duration of usage in years was 3.195±0.78, ranging from 1-6 years. Table 3 shows the comparison between the DED and non-DED groups in terms of daily usage in hours and duration of usage in years.

⃰Odds ratios calculated by univariate logistic regression analysis, ^‡95% confidence intervals, ^†p<0.05 considered significant

Similarly, the association between duration of use in years and CVS symptoms was studied (Table 5). It was found that only heaviness (OR 1.66 p=0.015) was significantly associated with usage of more than 3 years while blurring, watering, and grittiness (OR 1.30,1.24, 1.247 respectively) had higher odds but were not statistically significant.

Table-5: Effect of Duration of usage in years on CVS symptoms.

⃰Odds ratios calculated by univariate linear regression analysis,^† p-value of < 0.05 considered significant, ^‡Confidence intervals 95%

Refractive errors were present in 247 (62.69%) students, out of which 176 (71.25%) were using spectacles. 71 wore spectacles with a special coating, while 105 wore plain spectacles without any coating and 5 were not aware of any coating. The effect of different types of spectacle coating on the mean DED score is shown in table 6. One way Anova showed a significant difference in the mean DED scores among different groups, especially a comparison between group 2 (blue cut coating) and group 4 (no coating) showed a significantly lower mean DED score in group 2 with p< 0.05 and a q value of 4.083.

Table-6: Effect of the type of special coating on spectacles on the average DED score.

It was found the prevalence of dry eye disease in smartphones using college students to be 20.8%. DED (dry eye disease) was defined based on asthenopia symptoms and tear film parameters (Schirmer's test, Tear film break up time, Tear meniscus height, and corneal staining). Various previous studies carried out with different populations have used different diagnostic criteria and thus come up with different prevalence rates. Ayman et al reported a prevalence of 49.4% which was based on only subjective symptoms assessed by questionnaire [15]. A similar study conducted by Bukhari et al in the same region had reported a much higher prevalence of 93.2%, which was based on clinical parameters plus reported symptoms, but the study population was different, consisting of all age groups, including the elderly [16]. A Korean Study by Jun Moon et al on the smartphone-using pediatric population found a rate of 6.6% [17]. As pointed out earlier, our literature search revealed numerous studies on digital display terminals and computer use on DED but specific literature on smartphone-related DED and CVS is sparse. There are especially no Indian studies to compare with.

The ocular symptoms of CVS (computer vision syndrome) are grouped as asthenopia. Studies have reported that 60-90% of people working on computers develop asthenopia [18]. The same observation was made by us in this study, it was that found greater DED scores and lower values of tear film parameters in the DED group, as compared to the non-DED group. Tear film abnormalities concerning DED have been reported by various studies [19-22]. There are several factors at work that lead to more severe asthenopic symptoms from using the smartphone than the computer screen [6-8]. The smaller screen size coupled with the shorter viewing distance of about 35cm for smartphones, as compared to the normal reading distance of 40cm, requires greater accommodative effort by the ciliary muscles and thus gives rise to eye strain [23]. Another factor is the reduced blink rate reported with the use of any digital visual device such as smartphones, tablets, computer screens, and electronic book readers. This leads to greater evaporation of the tear film and symptoms of dryness and grittiness [24]. The third factor which has been recently studied and found to be of increasing importance in the etiology of smartphone-related dry eye and asthenopia is the blue light emitted by the LED (light-emitting diode) display. This light has a peak emission wavelength of 400-490nm, which is in the blue range [25].

Presently there are not many studies exploring the effect of phone screen brightness on the asthenopic symptoms and tear film parameters. However, experts believe that the ideal screen brightness depends on the ambient light. As a simple rule, the brightness of our gadget should be equivalent to the light surrounding us, such that both the lights' radiance is similar. By doing so, they will blend in, causing the least damage to our eyes.

The current study evaluated the effect of different screen-brightness levels on the DED scores and concluded that <50% setting was the most comfortable, with the lowest DED scores. Many kinds of screen guards or protectors are available, meant to be applied over the smart-phone screen for physical protection from scratches and cracks as well as to curb the reflective nature of the screen to limit the glare on eyes. There is no clinical data on the efficacy of any particular type of screen guard in ameliorating symptoms of eye strain. The present study found significantly lower DED scores in the few users who chose anti-blue screen filters.

due to the Questionnaire format of data collection, the information gathered could suffer from recall and information bias. Also because the current study population is comprised of medical students from a single institute, there could be selection bias, as the prevalence of CVS and DED may vary with the curriculum and environmental and regional factors.

The current study included large sample size and after removing the confounding factors, the current study tried to estimate not only the prevalence of DED but also its association with the duration of exposure. This study has sought answers to thus far unexplored questions about the usefulness of blue light filtering screens and the optimal screen brightness on ocular health.

This study shows that smartphone use increases the symptoms of CVS and DED, even more than computer work and that the duration of exposure plays an important role in the severity of these symptoms.