The rapid proliferation of smartphones has revolutionised communication, education, and entertainment, particularly among young adults. Medical students, owing to their academic workload and dependence on digital resources, represent a group with high daily screen exposure. This extended use, often involving small text sizes, prolonged focus, and minimal breaks, predisposes them to digital eye strain (DES), also referred to as computer vision syndrome (CVS) [1].

Digital eye strain is characterised by a cluster of ocular and extraocular symptoms, including eye fatigue, blurred vision, dryness, burning sensation, and headaches [2]. The underlying mechanisms involve accommodative stress, reduced blink rate, and increased tear film evaporation due to prolonged near work [3,4]. Studies have reported prevalence rates of DES ranging from 50% to over 80% among university students, with smartphone usage contributing significantly to symptom severity [5,6].

Factors influencing smartphone-induced ocular strain include the total duration of daily use, continuous screen time without breaks, close viewing distance, poor lighting conditions, and lack of ergonomic practices [7,8]. Excessive near-focus demands and blue light exposure have also been implicated in the development of accommodative fatigue and circadian rhythm disturbances [9,10].

Despite the growing literature on DES among general populations, limited data exist specifically targeting medical students in the Indian context. Given their intensive academic schedules and reliance on smartphones for both academic and recreational purposes, this group may face a heightened risk of ocular strain. Understanding the prevalence and modifiable determinants in this population could help design targeted awareness and prevention programmes.

Therefore, the present study aimed to determine the prevalence and key determinants of smartphone-induced ocular strain among medical college students, with an emphasis on identifying modifiable behavioural risk factors.

A total of 80 undergraduate medical students, aged between 18 and 25 years, were recruited using simple random sampling from the first to final academic years. Students with pre-existing ocular pathology (such as refractive errors not corrected by spectacles, keratoconjunctivitis sicca, or glaucoma), history of ocular surgery, or systemic diseases affecting vision were excluded.

Data Collection Tools

Data were collected using a prevalidated, self-administered questionnaire consisting of three sections:

1. Demographic details – age, gender, academic year.
2. Smartphone usage patterns – average daily duration, continuous screen time without breaks, viewing distance, and lighting conditions during use.
3. Ocular symptoms – presence and frequency of eye strain, blurred vision, dryness, burning sensation, and headaches.

The questionnaire incorporated a symptom severity scale scored from 0 (absent) to 3 (severe) for each complaint. Visual acuity was assessed using a Snellen chart under standard illumination, and near vision was evaluated using a Jaeger chart.

Operational Definition of Smartphone-Induced Ocular Strain

Participants were classified as having smartphone-induced ocular strain if they reported at least two ocular symptoms occurring more than twice per week during or after smartphone use, persisting for at least three months.

Statistical Analysis

Data were entered into Microsoft Excel and analysed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA). Categorical variables were expressed as frequencies and percentages, while continuous variables were summarised as mean ± standard deviation (SD). The chi-square test was used to assess associations between categorical variables, and independent t-test was applied for continuous variables. Logistic regression analysis was performed to identify independent determinants of ocular strain. A p-value of <0.05 was considered statistically significant.

A total of 80 medical students participated in the study, with a mean age of 20.8 ± 1.9 years. Of the participants, 45 (56.3%) were female and 35 (43.7%) were male. The overall prevalence of smartphone-induced ocular strain was 65% (n = 52).

Smartphone Usage Patterns

Students with ocular strain reported significantly higher mean daily smartphone use (6.3 ± 1.4 hours) compared to those without strain (3.8 ± 1.1 hours, p < 0.001) (Table 1). Continuous screen use without breaks for more than 30 minutes was reported by 73.1% of the affected group, versus 37.5% in the unaffected group (p = 0.002). Viewing distances less than 30 cm were also more frequent among the affected group (63.5% vs 28.6%, p = 0.003).

Table 1. Comparison of smartphone usage patterns between students with and without ocular strain (n = 80)

Ocular Symptoms

The most frequently reported symptoms among affected students were eye fatigue (76.9%), blurred vision (65.4%), dryness (59.6%), and headaches (51.9%) (Table 2). Multiple symptoms were present in most affected individuals.

Table 2. Distribution of ocular symptoms among students with ocular strain (n = 52)

Determinants of Smartphone-Induced Ocular Strain

Multivariate logistic regression identified daily smartphone usage >4 hours (OR = 3.25, 95% CI: 1.42–7.42, p = 0.005) and viewing distance <30 cm (OR = 2.84, 95% CI: 1.19–6.78, p = 0.015) as independent predictors of ocular strain (Table 3).

Table 3. Logistic regression analysis of determinants of ocular strain (n = 80)

The analysis suggests that both prolonged daily usage and close viewing distance are significant determinants, whereas continuous use duration and lighting conditions showed weaker associations.

This study identified a high prevalence (65%) of smartphone-induced ocular strain among medical students, with prolonged daily screen time and close viewing distance emerging as significant determinants. These findings align with earlier studies reporting prevalence rates between 50% and 80% among university students, reflecting the growing burden of digital eye strain (DES) in academic populations [1,2].

The mean daily smartphone usage among affected participants (6.3 hours) was substantially higher than in the unaffected group, supporting evidence that prolonged near-work activities are a major risk factor for ocular discomfort [3]. Similar associations have been observed in studies from India, Malaysia, and the Middle East, where extended screen exposure beyond 4 hours was consistently linked to increased DES symptoms [4-6]. Prolonged use likely increases accommodative stress, reduces blink rate, and promotes tear film instability [7].

Viewing distance <30 cm was another strong predictor of ocular strain, consistent with prior findings that closer focal distances increase accommodative demand and convergence load [8,9]. The combination of small text, high screen luminance, and short viewing distance may exacerbate visual fatigue and lead to sustained accommodative spasm [10].

Eye fatigue, blurred vision, dryness, and headaches were the most commonly reported symptoms, comparable to previous reports among student populations [11,12]. The high proportion of dryness symptoms supports the hypothesis that reduced blink frequency during screen viewing plays a key role in symptom development [13]. Moreover, more than half of the affected participants reported headaches, indicating the possibility of asthenopic strain due to prolonged near work [14].

Interestingly, lighting conditions did not emerge as a statistically significant determinant in our multivariate analysis, contrasting with earlier studies where poor ambient lighting was associated with higher DES prevalence [5,15]. This could be due to the uniformity of lighting in hostel and classroom environments in our sample, limiting variation in exposure.

The findings have important implications for prevention. Awareness campaigns focusing on ergonomic practices such as maintaining a minimum viewing distance of 40 cm, following the 20-20-20 rule, and limiting continuous smartphone use could help reduce the risk. Furthermore, integrating eye health education into medical curricula may enhance preventive behaviours.

Limitations of this study include its cross-sectional design, which precludes establishing causal relationships, and reliance on self-reported data, which may be subject to recall bias. Nevertheless, the use of a validated questionnaire and objective visual assessments strengthens the reliability of the results.

Smartphone-induced ocular strain is common among medical students, with prolonged daily usage and close viewing distance identified as key modifiable risk factors. Promoting ergonomic habits and regular visual breaks may help reduce symptoms and protect long-term ocular health.

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