The rapid integration of digital technology into everyday life has significantly altered patterns of visual task performance worldwide. The widespread adoption of computers, smartphones, tablets, and other digital devices has created a new public health concern: Computer Vision Syndrome (CVS), also referred to as Digital Eye Strain [1]. CVS encompasses a range of ocular and extraocular symptoms, such as eye strain, blurred vision, headache, neck and shoulder pain, resulting from prolonged screen use [2]. According to the American Optometric Association, CVS is defined as “a complex of eye and vision problems related to near work experienced during computer use” [3]. Its aetiology is multifactorial, involving sustained accommodation and convergence, reduced blink rate, glare, poor ergonomics, and prolonged exposure to digital screens [4].

Globally, the prevalence of CVS among digital device users has been reported to range from 12.1% to 97.3%, particularly among individuals with extended screen exposure, such as university students and women [5]. The academic environment has increasingly shifted toward digital learning platforms, resulting in prolonged screen time for both instructional and recreational purposes [6]. This trend has intensified following the COVID-19 pandemic, which normalized online learning and virtual interactions. While digital devices enhance educational opportunities, they also pose risks for ocular health when proper ergonomic and hygienic visual practices are not observed [7].

The consequences of CVS extend beyond transient visual discomfort. If unaddressed, CVS may reduce academic productivity, increase fatigue, and negatively impact quality of life [8–10]. Moreover, its symptoms often mimic or overlap with other neurological and systemic conditions, leading to misdiagnosis and unnecessary medical interventions [4]. Despite its high prevalence, knowledge and awareness about CVS remains suboptimal among university students, a population that spends considerable time on screens for study, communication, and leisure [11]. Inadequate awareness can delay symptom recognition and adoption of preventive measures, exacerbating ocular strain and related health complications.

While several studies have explored CVS in various global contexts [4, 5, 9, 11, 12], there is limited evidence from low- and middle-income countries (LMICs), including Zimbabwe. Context-specific data is critical, given that differences in digital device access, usage habits, and healthcare resources influence experiences. Understanding the prevalence and knowledge of CVS among university students in Zimbabwe is essential for developing targeted health education programs, informing institutional policies, and guiding preventive interventions in academic settings. Such evidence is particularly relevant in Sub-Saharan Africa, where the digitalization of education is rapidly expanding [13], but ocular health awareness remains inadequate.

This study, therefore, aims to determine the prevalence of Computer Vision Syndrome and assess the level of knowledge and awareness among students at Bindura University of Science Education. By identifying common symptoms, risk factors such as screen time and device type, and gaps in knowledge, the research seeks to provide actionable insights for eye health promotion in higher education institutions. Findings will not only inform local strategies but also contribute to the global discourse on mitigating the ocular impact of the digital era.

Participants were recruited using a convenience sampling approach. The online survey link was disseminated via course representatives and official student social media platforms (WhatsApp group) to ensure a broad reach. This method was selected for its practicality in an online setting and for its ability to efficiently obtain responses from the target population.

The minimum sample size that was needed in this survey was calculated using the formula below: n = N/ (1 + Ne²)

N = Estimated number of students at Bindura University during the study period = 5000

e = margin of error = 0.05

n = 370

Data was obtained using two validated, self-reporting online Google Questionnaire forms with 3 sections; namely socio-demographic data (includes faculty of study, year of study, age, gender, and academic year), prevalence of CVS, and knowledge and awareness of CVS (See Appendix 1). The CVS Questionnaire, developed by Segui et al in 2015, was utilized to collect data for the section on the prevalence of computer vision syndrome [15]. The form consisted of 16 questions that asked about the intensity and frequency of 16 symptoms of CVS using Rasch analysis, which is reliable for psychometric analysis. To answer frequency, which is how often symptoms occur when using electronic gadgets, 3 options were available: Never, Occasionally, and Often/Always. Never signifies that the symptom is completely absent, occasionally means the participant experiences sporadic episodes or CVS symptoms once a week, and often or always indicates a symptom that occurs twice or three times a week or daily, respectively. To measure intensity, participants had two response options available to them: moderate and intense. Respondents were reminded that if they indicated never for frequency, they should indicate “not applicable” as their response to the intensity question. Symptom severity scores were calculated using the expression: (Frequency of symptom occurrence) × (Intensity of symptom). Frequency was coded as: Never = 0, Occasionally = 1, and Often/Always = 2. Intensity was coded as: Moderate = 1 and Intense = 2. The total score was derived by summing the products across all symptom items. Knowledge of computer vision syndrome was assessed using 22 structured questions. Participant scores were categorized according to Bloom’s cut-off criteria: Good knowledge: 80–100%, Moderate knowledge: 60–79%, Poor knowledge: Below 60%.

Ethical clearance was obtained from the ethics committee of Bindura University of Science Education. Informed written (electronic) consent was sought from all participants before data collection. Participants were first provided with a research participation information sheet and a consent form with a detailed explanation of the survey to seek their consent. Confidentiality was assured throughout the procedure as information obtained was shared with only authorized personnel; moreover, names and email addresses were not part of the questionnaire. Participation of respondents was completely optional, and participants were permitted to withdraw from the survey at any moment without penalty. The study followed the guidelines of the Declaration of Helsinki.

A total of 374 students participated in this study, comprising 212 (56.7%) females and 162 (43.3%) males, with an age range of 19 to 45 years, and a mean age of 25.16 ± 4.64 years. Most participants were enrolled in the Faculties of Science and Engineering (30.7%) and Commerce (30.6%), with participants from the remaining faculties of the institution. The highest representation by year of study was from second-year students (32.1%). Also, the most commonly used single device was smartphones 96 (25.7%), but most participants used multiple devices 228 (60.9%), Table 1.

Out of 374 participants assessed with the CVS-Q, 133 (35.6%) met the criteria for Computer Vision Syndrome (CVS). CVS prevalence was higher among females (38.7%) compared to males (31.5%), though the difference was not statistically significant (p = 0.158). Across faculties, CVS prevalence ranged from 30.7% in Commerce to 39.0% in Social Sciences and Humanities, with no significant association observed (p = 0.608). By year of study, CVS prevalence increased from 25.7% in Year One to 37.4% in Year Four, but this trend was not statistically significant (p = 0.095), Table 2.

Figure 1 Frequency (Left bar graph) and Intensity (Right bar graph) of the observed CVS symptoms among participants. For the frequency of CVS symptoms plot, Never (blue bars): symptom does not occur at all, occasionally (Yellow bars): sporadic episodes or once per week, often or always (Grey bars): 2 or 3 times a week or almost every day. With respect to the intensity of symptoms plot, participants were asked to indicate “not applicable” if they selected “never” for frequency. This is represented in the blue bars. The yellow and grey bars represent intense and moderate intensity CVS symptoms, respectively.

This study provides insight into the prevalence, symptom burden, and awareness of Computer Vision Syndrome (CVS) among undergraduate students in a LMIC. Overall, more than one-third of participants (35.6%) reported clinically significant CVS symptoms, with headaches and blurred vision being the most common complaints. Despite nearly half of students (48.4%) having prior awareness of CVS, detailed knowledge regarding risk factors and preventive strategies was limited. Importantly, CVS symptoms were significantly associated with prior awareness, prolonged and continuous screen use, refractive error, and perceived screen-related health effects, highlighting behavioural contributors to symptom experience.

The predominance of female participants in this sample (56.7%) likely reflects several interrelated factors. First, the gender distribution in Bindura and Zimbabwe generally skews slightly towards females, as documented in national census statistics [16]. Additionally, women may be more inclined to participate in online surveys, possibly due to greater engagement with health and community issues or higher responsiveness to online recruitment efforts. This trend of female predominance is consistent with findings from similar online studies conducted in Saudi Arabia [17], Columbia [18], Thailand [19], Peru [20], Ghana [21], Bangladesh [22] and Paraguay [23], although other studies, such as those in South Africa [24], and Ethiopia [25] have reported male predominance. These differences may be attributable to regional variations in internet access, digital literacy, cultural norms, or recruitment strategies that impact gender representation in online research.

The observed prevalence of 35.6% falls within the lower range of global estimates (12.1–97.3%) [5]. Notably, higher prevalence rates have been documented among university populations worldwide, with estimates ranging from 41.7–96% [5], which is higher than those reported in this study. However, prevalence figures can vary significantly depending on the measurement tools and criteria used. For instance, previous reports show that the CVS-Q used in this study tends to report lower prevalence rates [5]. These elevated rates in university settings are likely attributable to several factors, including increased academic demands, greater exposure to screens, and heightened stress levels commonly experienced by students. Additionally, methodological differences across studies (most studies were conducted during the COVID-19 pandemic), may contribute to the discrepancies in reported prevalence rates. Headaches, dryness, and blurred vision emerged as the most frequently reported symptoms in this study, a finding consistent with results from global research [5, 26]. Variation in the ranking and prevalence of specific symptoms across different studies may be explained by several factors, including differences in screen ergonomics, the types of devices used, and cultural tendencies in symptom recognition and reporting. These factors can influence both the experience and the reporting of symptoms, contributing to the variability observed in the literature.

In terms of the distribution of CVS according to sex, our findings indicate that females exhibited a higher prevalence compared to males; however, there was no significant association between sex and CVS. The higher proportion in our study is consistent with the majority of previous studies on CVS [5, 27, 28]. Several factors may account for the higher prevalence of CVS observed among females. Women in some populations tend to spend more time using visual display terminals (VDTs) for both professional and personal activities [5, 27, 28]. Physiological and hormonal differences, such as greater susceptibility to ocular surface disorders like dry eye disease and hormonal fluctuations affecting tear film stability, may increase the risk of CVS symptoms among female students [29]. Ergonomic challenges are also relevant in the university context, as female students may more frequently encounter suboptimal workstation setups in study environments, contributing to symptom development [30]. Additionally, women are generally more likely to report symptoms and participate in health-related surveys, which can influence prevalence data [31].

Although awareness of Computer Vision Syndrome (CVS) among university students was relatively moderate in this study (48.4%), detailed knowledge was generally poor, a trend echoed in various student populations worldwide [26, 32, 33]. This discrepancy may be explained by several factors. Most students are exposed to the term "CVS" through general awareness campaigns or informal discussions, but lack access to comprehensive education on its causes, symptoms, and prevention [26, 32]. University curricula rarely cover eye health or CVS unless students are in health-related programs, limiting detailed understanding [26]. Additionally, many students perceive CVS symptoms as temporary or non-serious, reducing motivation to seek further information [34, 35]. The normalization of digital device use for studying and socializing may also lead students to dismiss CVS symptoms or view them as an inevitable part of university life [32]. Finally, reliance on online sources and peer discussions often results in incomplete or inaccurate knowledge about CVS [26, 32]. These factors collectively contribute to the observed gap between awareness and detailed understanding, underscoring the need for targeted educational efforts among university students, in support of the Sustainable Development Goal (SDG)-3, which promotes good health and well-being of all people [36].

The analysis revealed significant associations between CVS symptoms and prior knowledge of CVS, continuous screen use, prolonged screen exposure (≥ 5 years), medium screen size, refractive error, and perceived health impacts. These findings align with existing literature; for instance, a study among undergraduate students in Malaysia found that individuals with refractive errors or those wearing glasses had nearly twice the odds of developing CVS compared to those without refractive errors [26]. Similarly, research among medical students in Saudi Arabia indicated that using electronic devices for more than five hours daily was associated with a higher likelihood of experiencing CVS symptoms [37]. Additionally, a study in Mozambique identified that the absence of anti-glare treatment on monitors significantly increased the risk of CVS [38]. These studies collectively highlight the multifactorial nature of CVS, emphasizing the importance of addressing both individual behaviours and environmental factors to mitigate its prevalence among at-risk groups like university students.

Study strengths and limitations

A key strength of this study is the use of a validated screening instrument (CVS-Q) and a relatively large sample size, which enhances the credibility and robustness of the findings. However, several limitations should be noted. As is the case for all cross-sectional studies, the study is restricted in making causal inferences from the results. It is also possible that the results may be influenced by recall or reporting bias since data were collected from self-reported symptoms of the participants. The lack of ophthalmic examinations prevents differentiation of CVS from other ocular conditions, and conducting the study at a single institution may limit the generalizability of the results. Future studies could explore ways of eliminating these limitations in order to fully address this topic and provide a fuller picture of the prevalence and knowledge of CVS among university students, particularly in LMICs, to support targeted interventions.

CVS affects a substantial proportion of university students, with headaches, dryness, and blurred vision emerging as the predominant symptoms. Despite high levels of screen exposure, detailed knowledge of CVS remains limited, and several modifiable factors are significantly associated with symptom occurrence. These findings underscore the need for targeted educational interventions, improved ergonomic practices, and regular vision screening to reduce the burden of CVS in higher education settings. Such measures could help promote ocular health and overall well-being among university students.