The refractive status of the human eye is defined by the physiological relationship between its dioptric components and the anatomical position of the retina. This state is fundamentally classified into emmetropia, characterized by an ideal alignment between the eye’s focal point and the retinal plane, and ametropia, where a focal discrepancy exists [1].   Refractive errors represent a leading global cause of visual impairment across all demographics, including young adults. This condition comprising myopia, hyperopia, astigmatism, and presbyopia stem from optical abnormalities that prevent light from focusing precisely on the retina [2]. These conditions result from imperfections in the eye’s ability to focus light properly on the retina, leading to blurred vision and, if uncorrected, can significantly impact academic performance and quality of life [3]. Rising rates of refractive error among students globally are frequently linked to environmental factors. Specifically, the combination of restricted outdoor exposure and a surge in near-focus activities, like extended screen use, has accelerated this public health concern. [4,5].   Medical students appear particularly vulnerable to these conditions due to the rigorous nature of their curriculum, which necessitates prolonged periods of reading and digital device usage alongside limited natural light exposure [6]. While myopia has reached epidemic proportions in various Asian regions [7].   In the Kingdom of Saudi Arabia (KSA), while epidemiological studies have documented escalating rates of refractive errors among university students, a critical regional disparity exists in the current literature. Medical students are particularly vulnerable due to a curriculum requiring prolonged near-work and digital device usage [8,9]. However, most existing Saudi data is concentrated in major metropolitan hubs, leaving a significant research gap regarding the refractive profiles of students in the northern regions of the Kingdom.   Because refractive patterns are heavily influenced by local environmental factors and regional lifestyle habits, the lack of localized data in the North hinders the development of targeted screening programs. To address this, the present study evaluates the prevalence and patterns of refractive errors among medical students in Northern Saudi Arabia. Establishing this local baseline is essential not only to provide immediate corrective interventions but also to create regional public health strategies that enhance academic performance and prevent long-term visual complications

An electronic-based cross-sectional survey was implemented over a two-month period (March–April 2025). The study sample included male and female participants from the Faculty of Medicine at Northern Border University. Arar, Kingdom of Saudi Arabia.   Inclusion Criteria The study population consisted of male and female medical students across all academic levels (Years 1–6) currently enrolled at Northern Border University. Participants were included based on their voluntary consent to complete an electronic survey and their access to the university’s official social media platforms, such as WhatsApp and Facebook.   Exclusion Criteria Included Individuals not enrolled in the Faculty of Medicine, questionnaires with incomplete data and students with pre-existing organic ocular pathologies (e.g., cataracts, glaucoma, or retinal diseases) that could confound refractive error measurements.   The questionnaire was validated by two expert optometrists (including one co-author) to ensure professional accuracy. We employed a forward-backward translation method to translate the content from English to Arabic, ensuring consistent medical terminology and linguistic equivalence between both versions. The data section is one of the limitations of this study because only one medical college present in the Northern Border region, so Sampling method appears to be convenience-based rather than random or stratified   The study evaluated demographic profiles and the distribution of refractive conditions—specifically myopia, hyperopia, and astigmatism—measured by dioptric power. Investigators also analysed hereditary patterns and the frequency of daily screen time among participants. Furthermore, information was gathered on existing vision correction strategies and the barriers preventing patients from choosing laser surgery. The questionnaire used is attached to the manuscript. Notably, the study population was characterized by uniform daily routines, professional responsibilities, and time spent outdoors.   Questionnaire Design The questionnaire was designed and administered using a premium Google Forms account. It consisted of ten systematic and accurate questions. Two questions addressed demographics, including gender and age (categorized as ‘less than 18 years’, ‘18–20 years’, ‘21–23 years’, ‘24–25 years', and 'more than 25 years’).   The subsequent sections identified the presence and type of refractive errors (myopia, hyperopia, astigmatism, or combinations thereof). Furthermore. The duration of the refractive error was recorded in ranges of ‘less than 2 years’, ‘3–5 years’, and ‘more than 5 years.   Participants indicated their family history and daily electronic device usage (none, less than 2 hours, or more than 2 hours). Treatment methods were categorized into spectacles, contact lenses, laser refractive surgery, or no correction. For those who had not undergone surgery, the specific reasons (cost, lack of interest, or other) were obtained. Participants also selected their academic year (1st through 6th year).   After the survey was developed, it was distributed digitally through restricted Facebook and WhatsApp groups dedicated to medical student cohorts at Northern Border University. Access to these groups was strictly limited to verified students. Collected responses were organized in a spreadsheet and analysed using IBM SPSS software. We reported categorical data as frequencies and percentages, while continuous variables with a normal distribution were presented as mean ± standard deviation. To evaluate the relationships between categorical variables, we utilized the Chi-square test to determine statistical significance.   Sample Size Calculation Finally, the sample size was confirmed by the Slovin’s formula which is the most common method used when you have a well-known, finite population and want a standard margin of error (usually 5%).   n = N/1+N(e2)   Where   N : Sample size N : Total population (803 medical students according to the web site of Faculty of Medicine, Northern Border University) E : Margin of error (0.05 for a 95% confidence level), e2 = 0.0025 N : 803/1+803(0.0025) N : 803/1+2.0075=266.999   The sample size of 257 is sufficient and strong for a population of 803 (total number of students), as it aligns almost perfectly with the standard requirements for a 95% confidence interval and a 5% margin of error. Results Participants included 257 students from the College of Medicine, of whom 63.4% (n =163) were female and 36.6% (n = 94) were male. according to the web site of the college of medicine, Northern Border University, Saudi Arabia the number of male students 415 while the total number of female students 388 so the response of student to the study in male about 22.5% and in female about 42% (Table 1).   Table 1: Demographics Details of Studied Subjects Percentage n Subjects Age 62.6 162 18 -20 years 31.9 82 21-23 years 2.7 7 24 years 1.2 2 Less than 18 1.6 4 More than 25 Gender: 36.6 94 Males 63.4 163 Females Academic year 26.1 67 1st year 27.2 70 2nd year 21.8 56 3rd year 12.5 32 4th year 7.4 19 5th year 5.1 13 6th year 26.1 67 1st year 27.2 70 2nd year   The study analyzed a total sample of 257 students. Among the participants, 105 individuals (40.9%) exhibited no refractive errors, while 152 (59.1%) were found to have some form of refractive impairment. The most prevalent condition was myopia, identified in 72 students (28.0%), followed by myopia combined with astigmatism in 44 students (17.1%). Other conditions included isolated astigmatism (n = 21, 8.1%), hypermetropia (n =11, 4.2%), and hypermetropia combined with astigmatism (n = 4, 1.7%) (Table 2).   Table 2: Errors of Refraction and Related Variables among the Studied Students Variables N Percentage Presence of refractive errors Yes 152 59.1 No 105 40.9 Type of refractive errors Myopia alone 72 28 Myopia and astigmatism 44 17.1 Astigmatism alone 20 7.8 Hyperopia alone 10 3.9 Hyperopia and astigmatism 4 1.7 Time per day of electronic device use 0 hours 11 4.3 less than 2 hours 8 3.1 more than 2 hours 238 92.6 Method of correction (out of 257) Spectacles 118 45.9 Contact lens 6 2.3 Laser refractive surgery 13 5.1 No correction 4 1.6 Time of refractive error less than 2 years 51 18.5 between 3 and 5 years 44 16. 5 years 50 18.2 Family history Positive family history of refractive error 128 49.8 Negative family history of refractive error 129 50.2   Regarding lifestyle habits, a significant majority of the cohort (n = 238, 92.6%) reported using electronic devices for more than two hours per day, compared to only 3.1% (n=8) who used them for less than two hours. Ultimately, these results indicated that myopic conditions represented the highest proportion of refractive errors within this population.   Among the students with refractive errors, 118 (45.9%) used glasses for correction, while 6 (2.3%) used contact lenses. Additionally, 24 students (9.3%) with refractive errors did not use any form of correction. Out of the 257 medical students, only 13 (5.1%) had undergone laser refractive surgery. Regarding the duration of their conditions, 52 students (20.2%) stated their refractive errors were diagnosed less than two years ago, 51 (19.8%) were diagnosed five years ago, and 46 (17.9%) were diagnosed between three and five years ago. Finally, regarding family history, 128 students (49.8%) reported a positive family history of refractive error.   Association between Sex and Error of Refraction There was no statistically significant association between sex and the type of refractive error (p = 0.9066). Because the p-value was well above 0.05, the Chi-square test indicates that these variables are independent within this study (Table 3).   Table 3: Association between Sex and Error of Refraction Sex Normal Myopia Myopia + Astigmatism Astigmatism Hypermetropia Hyper. + Astigmatism. Female 66 47 31 13 6 3 Male 39 25 13 8 5 1   Association between Age and Error of Refraction Data were organized into five age groups. With a p-value of 0.9395, the results indicate that the type of refractive error is independent of the age group, as no significant association was observed (p>0.05) (Table 4).   Table 4: Association between Age and Error of Refraction Age Group Normal Myopia Myopia + Astigmatism. Astigmatism Hypermetropia Hyper. + Astigmatism. from 18-20 years 67 45 25 16 7 3 from 21-23 years 31 24 16 5 4 1 24 years 2 2 3 0 0 0 more than 25 years 3 1 0 0 0 0 less than 18 2 0 0 0 0 0   Association between Sex and Myopia The p-value (0.4999) is higher than the standard significance level of 0.05, There is no statistically significant association between Sex and Myopia in this dataset (Table 5).   Table 5: Association between Sex and Myopia Sex No Myopia Myopia (Yes) Total Female 85 72 163 Male 56 38 94 Total 141 116 257   Association between Age and all Cases of Myopia Including Myopia with Astigmatism The p-value (0.4002) is greater than 0.05. Therefore, there is no statistically significant association between Age Group and Myopia in this dataset (Table 6).   Table 6: Association between Age and all Cases of Myopia Including Myopia with Astigmatism Age Group No Myopia Myopia (Yes) Total <18 2 0 2 18-20 93 70 163 21-23 41 40 81 24+ 5 6 11 Total 141 116 257   Association between Myopia and Astigmatism p-value: 0.0005, There is a highly significant association between myopia and astigmatism (p<0.001). Individuals with myopia are significantly more likely to have astigmatism compared to those without myopia (Table 7).   Table 7: Association between Myopia and Astigmatism Myopia Status No Astigmatism Has Astigmatism Total No Myopia 116 25 141 Has Myopia 72 44 116 Total 188 69 257   Association between the Refractive Error and Correction Method There is a Highly statistically significant between the refractive error and the use of glasses p-value:<0.00001, so the medical glasses are the dominant correction method for all errors (Table 8).   Table 8: Association between the Refractive Error and Correction Method Refractive Error Glasses LASIK Contacts None/Other Total Normal 0 0 0 105 105 Myopia 53 8 4 7 72 Myopia + Astigmatism 34 3 1 5 44 Astigmatism 19 1 0 2 21 Hypermetropia 8 1 1 1 11 Hypermetropia + Astigmatism 4 0 0 0 4 Total 118 13 6 120 257   Association between Refractive Error and Time Spent in Front of Screen This analysis tests if the type of eye condition is related to the amount of time spent on electronic devices. p-value: 0.0015, Since p<0.05, there is a statistically significant association (Table 9).   Table 9: Association between Refractive Error and time spent in front of Screen Refractive Error None Less than 2 Hours More than 2 Hours Total Normal 20 13 72 105 Myopia (Nearsighted) 1 1 70 72 Myopia + Astigmatism 2 4 38 44 Astigmatism 1 1 19 21 Hypermetropia (Farsighted) 1 2 8 11 Hypermetropia + Astigmatism 0 1 3 4 Total 26 21 210 257   Association between the error of refraction and the family history p-value: <0.0001, There is a highly significant statistical association between refractive error and family history in this dataset. Individuals with a family history are significantly more likely to have a refractive error compared to those without (Table 10).   Table 10: Association between the Error of Refraction and the Family History Vision Category Family History: Yes Family History: No Total Refractive Error 107 45 152 Normal Vision 21 84 105 Total 128 129 257

The current study revealed that the prevalence of refractive errors in medical students in northern border faculty of medicine was high 56.4%. This high frequency may be to the intensive near-work activities and prolonged study hours characteristic of medical education. 45% of them was suffered from myopia (with or without astigmatism) so the myopia was the most common type of refractive error. Interestingly, our analysis showed a highly significant association between myopia and astigmatism (p<0.001). Individuals with myopia are significantly more likely to have astigmatism compared to those without myopia, this finding is supported by many other studies [10-12]. Which found high prevalence of refractive error in the medical students in different countries also in different regions inside the same country [7,8,10] so there is no specific cause or specific environmental factor in the region of this study but it’s a general causes that present everywhere, which it may be anatomical, genetic or environment factors [13]. the specific environment of a medical college like the academic demands may act as a uniform pressure across all demographic factors.   Despite the high prevalence of refractive errors, our statistical analysis revealed no significant association between refractive errors and demographic variables such as age (p = 0.9395) and gender (p = 0.9066). While some studies suggest a higher prevalence of myopia in females due to earlier physiological maturation or different lifestyle habits [14,15].   The age of students in the current study ranges from 18 to 25years from all academic years, the female (163 students) more than of male (94 students) due to the high response of female students while other similar studies in Saudia Arabia showed the sharing of male medical students was more than that of females [16].   The amount of hours/day of electronic device use by medical students was impressive. More than 92% of students use these devices more than 2 h/day, p. value 0.001 statistically significant. In the current the participants with normal vision represent the largest group of users who report none for screen time, whereas those with Myopia are almost exclusively more than 2 hours for screen time.This may indicate that new technology may have a role as risk factor for refractive errors in medical students and in the general population or increase the chance for discovering these refractive errors this findings align with Kumar, et al (2018) they found that the refractive error was found statistically significant among females, students spending more reading hours, watching television, mobile use [17,18]   The correction of the refractive error can be done by many methods but the glasses remain the first easy choice for the correction of the refractive errors, in this study There is a Highly statistically significant between the refractive error and the use of glasses p-value:<0.00001, so the medical glasses are the dominant correction method for all errors. This may be due to fear of undergoing surgery or other methods of correction [19]   In our report, family history of refractive errors was present in 128 students, representing 49.8% of the total group, p-value:<0.0001, There is a highly significant statistical association between refractive error and family history in this dataset. Individuals with a family history are significantly more likely to have a refractive error compared to those without this finding supported by many studies found a positive association between the family history and refractive error [10,20-22].   This research explores the multifaceted causes of refractive errors, emphasizing the interplay between genetic predispositions and environmental influences. The findings reinforce the correlation between prolonged near-work activities and an increased prevalence of refractive conditions, particularly myopia. This relationship is notably evident among medical students, who serve as a primary demographic for high-intensity near-work habits. Furthermore, despite the advancements and accessibility of refractive surgery, this study indicates that corrective lenses remain the most popular option, utilized by 45.9% of the surveyed students.

This study demonstrates a high prevalence of refractive errors (59.1%) among medical students at Northern Border University, with myopia being the predominant type. A significant correlation was established between myopia and astigmatism, suggesting a complex refractive profile in this population. While age and gender did not significantly influence the type of error, the high prevalence of positive family history and extensive electronic device usage are notable.   Given the correlation between visual health and academic success, the following measures are recommended:   Preventative Screening: Establish mandatory vision checks for all first-year medical students Digital Wellness: Launch awareness campaigns focused on reducing the strain of prolonged screen time Targeted Intervention: Prioritize early correction for nearly 10% of students with refractive errors to optimize their performance and long-term well-being   Limitations This study is limited by its reliance on self-reported data and its cross-sectional design, which precludes the establishment of a temporal relationship between electronic device use and the onset of refractive errors. Additionally, the higher response rate among females (42%) compared to males (22.5%) may introduce a degree of selection bias.   Scientific Responsibility Statement The authors declare full responsibility for the scientific content of this work. This includes involvement in the study's conception, data analysis, manuscript preparation, and a thorough review of the final text prior to submission   Ethical Approval The local committee of bioethics (AHP-09-043) at Northern Border university has issued decision no.(37/25/H) dated 17/3/2025 concerning the approval of this research   Animal and Human Rights Statement All experimental protocols followed the ethical standards of the national research committee and the 1964 Helsinki Declaration, including its later amendments.   Conflict of Interest The authors declare that there is no conflict of interest.