Computer vision syndrome and its relationship with sleep and fatigue in medical students

Abstract

Previous studies have suggested that medical students may be at considerable risk for Computer Vision Syndrome (CVS), partly because of the increasing amount of online content delivery via computer interface. This study used validated surveys to examine the prevalence of CVS in medical students and its relationship with fatigue and sleep impairments. Survey data showed that 83.1% of medical students exhibited a CVS score of 6 or above, suggesting they suffer from CVS, 57.3% of students scored above five on the Pittsburgh Sleep Quality Index (PSQI), indicating poor sleep quality, and 56.7% scored 36 or higher on the Fatigue Severity Scale (FSS), indicating significant fatigue. Data also showed that the CVS, PSQI, and FSS survey measures were correlated (p < 0.001) with each other. These results suggest that CVS in medical students may be related to poor sleep quality and fatigue.

Introduction

Computer Vision Syndrome (CVS) is a collection of eye or vision problems caused by prolonged computer use or “screen time”. Some of the main symptoms of CVS include tired and dry eyes, eye irritation and redness, headaches, blurred vision, and double vision [1]. Advances in computer technology have made teaching, learning, and communication more effective in recent years. Unfortunately, little is known about the effect of computer technology on the visual and behavioral health of students.

Technological advances have made computer and digital device usage essential in medical education [2]. Thus, it follows that several studies have shown high rates of CVS in medical student populations [3–7]. Furthermore, other work has shown that CVS among medical students has increased during the COVID-19 pandemic [8, 9]. Most of these studies have been conducted using medical student volunteers from countries outside of the United States, except one [9]. One of the goals of our study was to determine how levels of CVS in medical students in the United States compare with those from other countries.

Previous studies have examined sleep quality in medical and health science students [10–12]. Several of these studies have reported an association between CVS and poor sleep quality in medical students [7, 13]. Some work has shown that sleep quality is correlated with academic performance [14], while other studies suggest that there is not a strong relationship between sleep quality and academic performance [15]. The present study sought to build on these previous studies by examining the relationship between sleep quality, CVS, and fatigue in medical students.

Several studies have examined the construct of fatigue in medical students. For example, a study from Greece [16] showed that fatigue is correlated with anxiety, depression, and sleep quality in medical students. Another investigation studied medical students from Japan and showed that avoidance-oriented stress coping activity was associated with fatigue [17]. A study from Poland showed that medical students who use emotions effectively can reduce fatigue [18]. Our study sought to build on this work by administering a validated fatigue survey to medical students from the United States.

The present study sought to examine levels of CVS in medical students using a validated CVS survey. This study also aimed to determine if CVS in medical students is related to fatigue and sleep impairments. The present study provides a novel contribution to the CVS literature because only a handful of studies have examined CVS in medical students in the United States [9]. Similarly, there have only been a few studies that have examined the constructs of fatigue and sleep quality in medical students [11, 16–18], and most of these studies have been conducted in countries outside of the United States.

Methods

Medical students at Rocky Vista University College of Osteopathic Medicine (RVUCOM) were invited by email to complete a survey. The survey was not required, and no incentives were used to motivate survey completion. Respondents included medical students enrolled in RVUCOM from the academic year 2022–2023 in Years 1–4 on the Colorado and Utah campuses. Survey responses were collected using Qualtrics from November 1st to December 22, 2022. IRB approval (#2022-099) was obtained from the RVUCOM IRB. Subject consent was obtained prior to completing the surveys.

The survey was composed of the Fatigue-Severity-Scale (FSS) questionnaire [19], Pittsburgh Sleep Quality Index (PSQI) questionnaire [20], and the CVS questionnaire [21], all in their entirety without any changes to their scoring or questioning. Questions were also included about the assigned sex at birth and the year in medical school. Each symptom on the CVS questionnaire was scored (never = 0, occasionally = 1, often or always = 2), then multiplied by the intensity (1 = moderate, 2 = intense). Subjects who scored six or more on the symptom questionnaire were defined as having CVS [21]. Subjects scoring above five on the PSQI were defined as having poor sleep quality [20]. Subjects scoring 36 or higher on the FSS were defined as having significant fatigue [16]. There were 56 survey questions in total. Pearson correlations were used to measure associations between continuous variables. Independent t-tests were used to compare continuous variables between groups.

Results

One hundred seventy-eight medical students completed the CVS, PSQI, and FSS surveys. Table 1 shows demographic information about sex and year in medical school. Composite scores were computed for each of the three surveys administered in this study (i.e., CVS, PSQI, and FSS). Analyses revealed no significant differences in overall CVS, FSS, and PSQI scores between years in medical school, nor between sexes. Additional analyses compared Years 1 and 2 to Years 3 and 4, revealing no significant differences.

Table 1.

Survey response by year in medical school and sex

		Year in medical school				Total
		1	2	3	4
Sex	Male	19	19	16	15	69
	Female	40	37	19	13	109
Total		59	56	35	28	178

Table 2 shows mean values obtained for the questions on the CVS survey along with the standard deviation. Each value was calculated for each subject by multiplying the frequency by intensity [21]. It should be noted that the highest scoring questions on the CVS survey were Headache, Dryness, Heavy Eyelids, Sight is Worsening, Blurred Vision, Redness, Blinking, Sensitivity to Light, and Eye Pain (i.e., Means > 0.75). A total of 148/178 students (83.1%) exhibited a CVS score of 6 or above, suggesting they have CVS.

Table 2.

CVS categories

	Mean	Std. Deviation
CVS Freq X Intensity	12.3933	7.62484
Burning	0.7191	0.67210
Itching	0.5674	0.75797
Foreign Body	0.4494	0.63799
Tearing	0.6798	0.70007
Blinking	0.8588	0.91536
Redness	0.8933	0.91124
Eye Pain	0.7865	0.88262
Heavy Eyelid	1.0281	0.98823
Dryness	1.2640	1.15125
Blurred Vision	0.9326	0.98918
Double Vision	0.2022	0.63209
Difficulty Focusing	0.6067	0.91587
Sensitivity to Light	0.8146	0.99967
Colored Halos	0.3371	0.56135
Sight is Worsening	0.9775	1.14465
Headache	1.2809	1.08392

Table 3 shows mean values and standard deviations for PSQI questions. Using the formula Buysee et al. described [20], a global PSQI score was computed for each subject. 102 out of 178 students (57.3%) scored above five on the PSQI, indicating poor sleep quality.

Table 3.

PSQI scoring

PSQI Category	Mean	S.D.
Rate Sleep Quality (Q9, Component 1, 0–3)	1.04	0.87
Time Fall Asleep (Q2, Component 2, hrs)	0.45	0.37
Sleep Latency (Q5A, Component 2, hrs)	1.29	1.081
Amount of Sleep per Night (Q4, Component 3, hrs)	7.07	1.08
Sleep Efficiency (Component 4, 0–3)	0.26	0.61
Sleep Disturbance, (Q5b to Q5j, Component 5, 0–3)	1.62	0.93
Take Medicine to Sleep (Q6, Component 6, 0–3)	0.57	0.95
Trouble Staying Awake in Daytime (Q7, Component 7, 0–3)	0.53	0.782
Keep Up Enthusiasm in Daytime (Q8, Component 7, 0–3)	1.52	0.92
Global PSQI Score	6.86	3.57

Table 4 shows mean values and standard deviations obtained for questions on the FSS. This table shows that the highest scoring category for Fatigue was “Motivation was lower when fatigued”. A total FSS score was computed for each subject as described by Krupp et al. [22]. A total of 101/178 students (56.7%) scored 36 or higher on the FSS (mean = 37.2, S.D.=10.7), indicating significant fatigue [16].

Table 4.

Fatigue severity scale

FSS Question	Mean	Standard Deviation
Motivation lower when fatigued	6.31	0.997
Exercise brings on fatigue	2.52	1.302
Easily fatigued	3.75	1.602
Fatigue interferes with physical activities	4.89	1.590
Fatigue causes frequent problems for me	3.82	1.729
Fatigue prevents sustained physical functioning	3.50	1.742
Fatigue interferes with my duties and responsibilities	4.31	1.741
Fatigue is among my three most disabling symptoms	4.03	2.001
Fatigue interferes with my work, family or social life	4.14	1.750

Analyses revealed a significant relationship between CVS, PSQI, and FSS. See Table 5 for a correlation summary. It may be possible that CVS contributed to fatigue and poor sleep quality, or perhaps alternatively, that fatigue and poor sleep quality augment CVS. Regardless, the causal direction of the data cannot be inferred from these correlation analyses.

Table 5.

Correlation of composite scores for CVS, PSQI, and FSS

		CVS	PSQI	FSS
CVS	Pearson Correlation	1	0.404**	0.452**
PSQI	Pearson Correlation	0.404**	1	0.409**
FSS	Pearson Correlation	0.452**	0.409**	1
	N	177	168	177

**. Correlation is significant at the 0.001 level (2-tailed)

Table 6 shows, from each survey, the two individual survey questions that showed the highest correlations with other total survey measures. For example, although the Global PSQI score correlated with numerous individual CVS questions, the Global PSQI measure showed the highest correlation with the CVS questions of “Headache” and “Eye pain”. The Global PSQI measure also correlated with the FSS questions “Causes frequent problems for me” and “Interferes with work, family, and social life”. Similarly, the FSS survey totals showed the highest correlation with the CVS questions of “Headache” and “Sensitivity to light”. The CVS and FSS measures showed the highest correlations with the PSQI questions of “Trouble Staying Awake” and “Sleep Disturbances”. These consistencies across the individual survey questions may suggest that they are linked to some of the causal factors that account for the correlations between CVS, fatigue, and sleep disturbances. It is also important to note that none of the individual CVS or FSS survey questions showed a significant correlation with reported hours of sleep.

Table 6.

Highest individual question correlations with CVS, PSQI, and FSS

	CVS Headache	CVS Eye Pain	FSS Causes frequent problems for me		FSS Interferes with work, family, and social life
Global PSQI	0.425**	0.331**	0.432**		0.360**
p	< 0.001	< 0.001	< 0.001		< 0.001
n	168	168	168		168
	CVS Headache	CVS Sensitivity to light	PSQI Component 7, Trouble Staying Awake		PSQI Component 5, Sleep Disturbances
FSS	0.428**	0.355**	0.568**		0.305**
p	< 0.001	< 0.001	< 0.001		< 0.001
n	168	168	173		174
	FSS Causes frequent problems for me	FSS Interferes with work, family, and social life	PSQI Component 7, Trouble Staying Awake		PSQI Component 5, Sleep Disturbances
CVS	0.520**	0.433**	0.451**		0.345**
p	< 0.001	< 0.001	< 0.001		< 0.001
n	177	177	173		174

**. Correlation is significant at the 0.001 level (2-tailed)

Discussion

The present study revealed that a high proportion of the medical students at our institution suffer from CVS, poor sleep quality, and fatigue. Moreover, the survey data showed that 83.1% of medical students suffer from CVS, 57.3% have poor sleep quality, and 56.7% suffer from fatigue. Previous studies have shown comparable levels of CVS in medical students, ranging from 69.1 to 82.5 [3–7]. This may suggest that there is a relatively consistent level of CVS in medical students from various institutions.

Fatigue is a frequent topic of discussion in medical education [18]. The construct of burnout has been studied extensively in medical education as well and may have considerable overlap with fatigue [23]. The present study suggests that fatigue may have a high prevalence among medical students. Similarly, the present study also suggests that sleep impairments may have a high prevalence among medical students. There was a significant relationship between sleep quality and fatigue in this study. Other work has speculated that improvements in sleep quality could mitigate fatigue symptoms [24].

Measures of fatigue, sleep quality, and CVS were all correlated with each other in this study. It is impossible to determine if any of these measures is a causal factor of the others, however, it is not surprising that all three of these constructs are related. Interestingly, the individual survey questions that showed the highest correlations with overall scores of CVS, FSS, and PSQI were as follows: CVS “Headache” and “Eye pain”; PSQI “Trouble staying awake” and “Sleep disturbances”; and FSS “Causes frequent problems for me” and “Interferes with work, family, and social life”. These consistencies across the overall survey measures may suggest that these individual survey questions are linked with some of the causal factors that account for the correlations between CVS, fatigue, and poor sleep quality.

Analyses showed a significant relationship between CVS, sleep quality, and fatigue. Other studies have shown a similar relationship between CVS and sleep quality [12, 13]; however, no previous studies have examined the relationship between CVS and fatigue. Although no causal relationships can be determined from the present correlational study, there are several hypothetical interpretations of our results. Medical students are required to endure long hours of study in front of computer screens. These long hours of computer screen time may contribute to the symptoms of CVS, particularly those of headache and eye pain. These CVS symptoms may in turn contribute to sleep disturbances which could lead to fatigue. A second possible interpretation of these data is that the long hours of study and computer screen time may contribute to fatigue or sleep impairments, and higher levels of fatigue or sleep impairments could make students more vulnerable to CVS. It is also important to note that none of the individual CVS or FSS survey questions showed a significant correlation with reported hours of sleep. This suggests that CVS and FSS are related to the quality of the sleep more so than the duration of sleep. Future work should aim to understand the causal factors that result in the correlation between CVS, sleep impairments, and fatigue. Future work should also determine whether some methods or practices can prevent CVS, fatigue, and poor sleep quality in medical students. Furthermore, it may be possible to develop methods of content delivery that reduce computer screen time for medical students.

The results of this study suggest that medical students are at considerable risk for CVS, poor sleep quality, and increased fatigue. This is one the few studies that has described significant levels of CVS in students from a United States medical school. The curriculum at our medical school is typical of most medical schools in the United States as it relies heavily on didactic content that is accessed via computer. Thus, it is not surprising that we see a high prevalence of students who suffer from CVS. There are several tracking tools that are used to compare content delivery methods across medical schools in the United States [25]. These tools may be useful for tracking different content delivery methods relative to computer screen time. It would be interesting to compare CVS across medical schools in the United States to see if curricular approaches that require more screen time result in higher levels of CVS, sleep impairments, or fatigue.

It is important to acknowledge several limitations of the present study. First, this study relied on self-reported survey data and did not include objective measures of CVS, sleep quality, and fatigue. Thus, it is impossible to know if some student respondents may have inaccurately represented their conditions related to CVS, sleep quality, and fatigue. The present study was cross-sectional in design and only represents data from a single point in time. Thus, the data in the present study could have been impacted by unique ongoing curricular events at that time point. Future studies could examine these variables at multiple time points, which may provide a better understanding of how certain curricular variables (e.g., exams, clinical rotations, seasons) impact these measures over time. It is important to acknowledge that students experiencing CVS symptoms or other visual problems may have been more likely to complete the survey. This may have created a selection bias in the data, potentially inflating prevalence estimates. It is also important to emphasize that the analyses in this study were primarily correlational, and thus, it is impossible to determine any causal relationships from these types of analyses. Finally, the present study could have been strengthened by including objective data from clinical eye exams. Future studies should combine clinical eye exam data with CVS, FSS, and PSQI survey data.

Author contributions

M.G. and M.S:: Conceptualization, data curation, investigation, writing– review and editing. M.M.: formal analysis, supervision, writing– review and editing. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

Funding

No external funding was received for this study.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Human ethics and consent to participate declarations

Approval was received by Rocky Vista University IRB Board: IRB# 2022-099. Written informed consent was obtained from the patient(s) for their anonymized information to be published in this article.

This study adhered to the principles outlined in the Declaration of Helsinki by insuring informed consent was obtained from all participants and by securing approval from an appropriate ethics review board.

Competing interests

The authors declare no competing interests.

Informed consent

Informed consent was obtained from all participants in the study. Written consent was obtained via Qualtrics.