This pilot study explored the use of machine learning algorithms to analyze visual behaviors and assess their feasibility in predicting participants’ educational background. Findings confirm the association between specific near-viewing behaviors and ultra-Orthodox men, who are graduates of an intensive educational system. These results lay the groundwork for further studies that explore the potential causal links between specific behavioral patterns and their impact on the onset and progression of myopia. By identifying and quantifying specific behavioral patterns, such algorithms could eventually be used to monitor children during critical developmental periods when myopia typically onsets and progresses leading to insights regarding the role of visual behavior in the pathogenesis of myopia.
This pilot study focused on college students who had attended intensive (ultra-Orthodox) schools or standard (non-ultra-Orthodox) schools prior to college. Boys who attended intensive school systems begin their education as early as age three, attending schools that emphasize extensive reading of religious texts with small fonts and with a significantly higher number of study hours compared to standard schools20. In contrast, students who attended standard schools start formal education at age six22 attending schools that follow a state curriculum with a broader range of subjects, including arts, mathematics, and science50. The advantage of studying this population is its genetic homogeneity and geographical concentration, which minimizes confounding variables such as ethnicity and geographic location.
As hypothesized, those who attended intensive school systems exhibited significantly different near work behavior in three aspects: (1) the percentage of time spent at near viewing, (2) the average viewing distance, and (3) the patterns of continuous episodes of near viewing. Specifically, those who attended the intensive school system spent more time viewing things at very near distances and less time on intermediate near viewing, and their near viewing distance was significantly shorter than the group who attended a standard school system. Additionally, during near work, the graduates of the intensive school system took fewer long breaks and spent less time on them, while taking more frequent short breaks and spending more time on these compared to the graduates of the standard school system.
The machine learning model developed to predict whether an individual had attended an intensive school system based on objectively measured near viewing behaviors showed that the most influential features that increased the likelihood of classifying a participant’s attendance to an intensive school system were related to two aspects of near work behavior: shorter near-viewing distances and fewer long breaks during near work. The ability to predict the participant’s school system based on current near viewing behavior suggests that the distinct educational demands in kindergaren through high school (approximately ages 3–18 years) are associated with different near viewing behaviors that persisted into adulthood.
While the current study did not address causality between near-viewing and myopia, one may apply abductive reasoning to propose that the distinct near-viewing behaviors observed in graduates of intensive educational systems may contribute to differences in refractive status and the prevalence of myopia observed in this population level8,14,23,51,52. However, future research needs to be carried out to effect alone is measured relative to other known correlations with a magnitude and compared against a baseline.
The distinct educational systems examined in this study, characterized by significantly different near viewing demands, may help explain trends seen in East Asia, where high educational demands and intensive near work12,21 from an early age are linked to elevated rates of myopia53. The parallels between the Israeli intensive educational system and those in countries such as China, South Korea, and Japan highlight the global relevance of these findings. By examining the shared educational practices and their impact on near-viewing behaviors, this study provides insights applicable beyond the specific populations studied here. However, in general, categorizing educational systems or populations into two broad groups may not fully capture the complexity of educational experiences and their impact on visual behavior. However, it should be noted that the current study did not assess causal relationship between near viewing behavior and myopia. Future research should investigate this potential link, considering that educational environments exist on a spectrum, with variations in curriculum structure, teaching methods, and extracurricular demands that could influence near viewing behaviors and myopia development.
This study examined near work behavior in college students, based on the assumption that near work habits formed in childhood may persist into adulthood. This study confirms near viewing patterns observed in a previous laboratory-based study in young adults30. Findings from both studies reveal similar behavioral trends across these two groups, suggesting consistent patterns in both controlled and real-life conditions. In the previous laboratory-based study, participants who had attended the intensive school system read books and viewed tablets at closer distances than participants who had attended a standard school system30. The average near work distances for different tasks ranged from 31.4 cm to 41.7 cm. In the current study, the average near-viewing distance was 45 cm. While we did not collect information on specific tasks performed at these distances, we found a significant difference of approximately 7 cm between students who had attended intensive school systems (41 cm) and those from standard school systems (48 cm).
Closer near viewing distances among students who had attended intensive school systems may be associated with early exposure to reading small text, which is typical in their religious books20. Reading smaller font sizes may require closer viewing distances to increase the angular size of the text54 a pattern also observed in Chinese children, where smaller font was associated with shorter viewing distances55. These reading habits, established in childhood, may persist into adolescence and adulthood, contributing to the closer working distances seen in this group.
Research on educational demands has suggested that specific aspects of near work, in addition to near-viewing distance, such as the duration of near viewing and the frequency of breaks, may influence the development of myopia more than the total time spent on near work18,19.
In the current study, the time spent viewing at near distances (10 and < 40 cm) and intermediate distances (40 and < 100 cm) was found to differ between students who had attended intensive versus standard school systems. Students who had attended intensive school systems tend to spend more time viewing at short distances, while students who had attended standard school systems spend more time viewing at intermediate distances. Further research should focus on understanding how the percentage of viewing time at each distance impacts myopia.
There were not significant differences in the overall percentage of breaks (i.e. far viewing breaks during near work) taken by the students who had attended either intensive school or standard school systems. However, when looking at the characteristics of the breaks, distinct behavioral differences emerged. Students who had attended intensive school tended to take more short break episodes and spend more time in short breaks, while those who had attended standard school tended to take longer breaks and spend more time in long breaks. Interestingly, Wallman and colleagues demonstrated that 2-minute interruptions of visual experience significantly reduced or prevented the development of myopia in chicks56. This underscores the importance of far-viewing episodes in myopia progression. Also in our study we found that far viewing episodes longer than 5 min were associated with standard school systems. Further research should focus on understanding how viewing breaks impact myopia progression in humans.
Ultra-Orthodox graduates of an intensive schools system are known to have a higher prevalence and degree of myopia compared to non-ultra-Orthodox males who attended standard schools, which is often attributed to the intense near work demands in the intensive school educational system23,52. The myopia prevalence among ultra-Orthodox participants who had attended intensive school educational systems in this study (82%) was not significantly different from those who had attended non-ultra-Orthodox systems (69%). However, there was a significantly higher degree of myopia among participants from intensive school educational systems. Additionally, the prevalence of high myopia was greater among ultra-Orthodox participants who had attended an intensive school educational system compared to those who had attended a standard school system. The observed myopia prevalence aligns with previous findings from our lab (87%) and reports in ultra-Orthodox Jewish males recruited into the army (82%)23. The prevalence of myopia among participants from non-ultra-Orthodox educational backgrounds (69%) in this study closely matches rates observed in our previous study (68%)30 and studies of male and female college students in Israel (66%)57. However, it is higher than the myopia rate reported among Jewish males recruited into the army23. It is important to note that college students, in general, tend to have higher prevalence rates of myopia compared to the general population57. This may be due to the academic demands and near work associated with higher education, which can exacerbate myopia progression. This context highlights that the high myopia rates observed in both groups in this study may be influenced by the college student population itself. We speculate that myopia prevalence between the two groups studied here may have been influenced by the recruitment process, as all participants were college students. Importantly, the high prevalence of myopia among participants in both groups, combined with the similar myopia rates between the groups, enables a more balanced investigation of near-work behavior across educational backgrounds.
It is possible that the different viewing behaviours observed were a result of the ultra-Orthdox cohort having a significantly more myopic refractive error. However, no correlation was found between the degree of myopia and either the working distance or the duration of near viewing. This is similar to findings from previous studies in young adults28 and children29,55 which also showed no differences in near viewing distance between myopes and non-myopes for both in-lab tasks and for real world tasks41. However, another study using a near-work analyzer reported that high myopes had significantly shorter reading distances compared to low and non-myopes25.
Machine learning analysis demonstrated that participants’ elementary and high school educational system could be predicted by their current adult viewing behavior, despite the relatively small sample size of 64 participants. Among the models tested, logistic regression performed best, achieving an AUC of 80%, precision of 74%, and recall of 72%. The ability of the model to achieve such high performance underscores the predictive strength of objective behavioral measurements, such as viewing distances and the percentage of long far-viewing episodes. Our focus on purely objective behavioral variables distinguishes this work from much of the existing literature58,59,60,61 on educational outcomes, where survey-based or clinical measures are often used. The model’s ability to differentiate between participants from intensive school and standard school educational backgrounds, without reliance on non-behavioral features like refractive error or myopia, highlights the distinctiveness of visual behavior in these groups.
The SHAP analysis added further granularity by identifying specific cutoff values that distinguished the groups. For example, near-viewing distances shorter than 44 cm and far-viewing episodes longer than 5 min occurring less than 1% of the time were strongly associated with intensive school education.
Limitations of the study include the following: Participants were young adults with stable refractive status. Studying children in their habitual environments will provide more insight into behaviors during the critical period when myopia develops and progresses. Additionally, the study had only a small number of non-myopic participants, which could limit generalizability. However, the primary aim of this study was not to compare visual behavior between myopes and non-myopes; therefore, the limited number of non-myopic participants is less critical in this context. Future research exploring the relationship between myopia and near viewing behavior would benefit from a more balanced and diverse representation of refractive error groups to better assess behavioral differences in relation to myopia. Another limitation was the age difference between participants who attended intensive school educational systems and standard school systems, reflecting cultural differences in education timing; intensive school graduates tend to continue studying directly after high school, while standard school graduates typically attend university after military service. However, since myopia progression tends to stabilize after age 1862, this age difference is unlikely to have significantly affected the results. Cycloplegic refraction was not performed in this study, which may lead to an overestimation of myopia. However, in adults, this effect is expected to be minimal. Cycloplegia is particularly important in children to ensure accurate classification into refractive error categories63. A recent study in young adult myopes found a difference between cycloplegic and noncycloplegic refraction, but the mean difference was relatively small, averaging − 0.2 D (− 0.25 to − 0.14 D)64. Given that this study does not assess myopia progression or compare visual behavior between myopes and non-myopes, the use of cycloplegia was deemed less critical. Another consideration is the small sample size of the participants. However, as this is a pilot study, one of its key objectives was to evaluate the feasibility of using machine learning. Despite the limited sample, the machine learning model demonstrated strong performance, supporting its potential for future studies with larger populations using objective wearable sensors to collect behavioral data. The categorization of educational systems into two simplified groups—intensive and standard—does not reflect the full complexity and diversity of educational systems in Israel. These systems include distinctions such as ultra-Orthodox, religious, and secular systems, each with unique educational demands. Additionally, within the non-ultra-Orthodox category, there are both religious and secular subgroups, which have different rates of myopia despite sharing similar school systems. However, non-ultra-Orthodox men attending religious and secular schools experience no significant differences in the intensity of educational demands20,22. Future research should aim to identify and include more nuanced features to provide a more comprehensive understanding of how specific educational environments influence near-viewing behaviors and myopia development.
Furthermore, although this study focused on educational practices, it is important to acknowledge that other lifestyle factors associated with strict ultra-Orthodox observance such as reduced outdoor exposure, specific dietary habits, and cultural norms10 may also contribute to differences in myopia prevalence. These potential confounding factors were not measured in the current study and should be considered in future investigations aiming to isolate the contribution of educational demands to myopia development.
The Clouclip device used in the study also presented limitations. It enters sleep mode if no movement is detected for 40 s, resulting in about 2.5 min of lost data per occasion. However, there were no significant differences between the groups in this respect. Another limitation is the potential misalignment between the clouclip’s beam and the participants’ actual line of sight, as eye position was not tracked. The device’s sampling rate of every 5 s may also miss short viewing breaks, but this limitation was consistent across both groups and unlikely to have influenced trends. Future experiments should be performed in other populations with different educational systems to assess whether the results observed here are consistent across other intensive education systems to provide a broader understanding of how educational environments impact near viewing behaviors and fundamental links between behavior and myopia development.
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