Objective Evaluation for Relationship between Visual Fatigue and Tear Film Stability in Smartphone Use

doi:10.21203/rs.3.rs-3718154/v1

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Objective Evaluation for Relationship between Visual Fatigue and Tear Film Stability in Smartphone Use

https://doi.org/10.21203/rs.3.rs-3718154/v1

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Purpose:

To investigate whether tear film instability induces visual fatigue, we used the binocular fusion maintenance (BFM) test and non-invasive tear film break-up time (NI-BUT).

Methods:

Eleven young adult volunteers (age [mean ± standard deviation], 20.7 ± 1.4 years) participated in this study. BFM was assessed by measuring the transmittance of liquid crystals placed in front of the subject’s non-dominant eye when binocular fusion was broken, and non-dominant eye was shifted to heterophoric. The NI-BUT was determined using the distortion of the Meyer ring. The volunteers were administered the BFM, NI-BUT, and subjective symptom questionnaire before and after a 30-minute visual task.

Results:

BFM (pre vs. post: 0.95 ± 0.09 vs. 0.75 ± 0.16) was significantly lower in the post-visual task than in the pre-visual task (P = 0.012). NI-BUT (9.12 ± 1.00 s vs. 5.69 ± 3.11 s) was significantly shorter in the post-visual task than in the pre-visual task (P = 0.011). Total subjective eye symptom (2.91 ± 0.79 vs. 5.45 ± 2.02) was significantly greater in the post-visual task than in the pre-visual task (P = 0.012). The change in BFM (− 0.20 ± 0.18) was significantly and positively correlated with the change in NI-BUT (− 3.43 ± 3.19) (R² = 0.385, P = 0.042) and was significantly and negatively correlated with the change in total subjective eye symptom score (2.54 ± 2.23) (R² = 0.470, P = 0.020).

Conclusion:

The findings suggest that tear film instability induces visual fatigue objectively.

Health sciences/Health care/Occupational health

Health sciences/Medical research/Translational research

Smartphones are becoming increasingly popular worldwide because they permit easy access to the internet,¹ with more than 50% of youths in Asia,^2,3 the United States,⁴ and Europe⁵ using smartphones daily to access social networking services. Although smartphones are useful for communication and are widely used in daily life, health problems are associated with their use.^6–8

Computer vision syndrome (CVS) is the most severe disease caused by smartphones and personal computers. The American Optometric Association defines CVS as a vision-centered physical and mental syndrome caused by the prolonged use of digital devices, particularly during work, thus stressing the eyes.⁹ The main symptoms of CVS include dry eyes, eye fatigue, headache, blurred vision, and neck and shoulder pain.^9,10 CVS has been called the greatest occupational disease of the 21st century, with a recent meta-analysis reporting that approximately 66% of digital device users experience some CVS symptoms.¹¹ Furthermore, Khan et al. reported an increase in CVS prevalence from 64.3% before the coronavirus disease 2019 lockdowns to 87.3% during the lockdowns.¹²

Dry eye and visual fatigue (asthenopia or eye strain) are the main symptoms of CVS.^9,10 It has been reported that 51.4% of patients who complain of ocular fatigue have dry eyes, and patients with severe dry eye symptoms are more likely to be aware of ocular fatigue.¹³ However, the objective indicator linking dry eye and visual fatigue has not been established.

Dry eye is a multifactorial condition that is characterized by a loss of the natural balance of the tear film and ocular surface and is accompanied by symptoms and signs.^14,15 In clinical practice, tear film instability, which is the shortening (< 5 s) of the tear film break-up time (BUT), has been established as a diagnostic criterion for dry eye.^15,16 A short BUT have been reported in the majority of patients.¹⁷ Therefore, tear film instability due to BUT is a common feature of dry eye.

The onset of dry eye is related to a decrease in the blink rate.^8,18 Smartphone users often become absorbed in using their devices that they forget to blink.¹⁹ A reduction in the blink rate leads to a short BUT because blinking is necessary for coating and smoothing the tear fluid.²⁰ A short BUT leads to increased corneal aberrations, which induce blurred vision.²¹ The non-invasive tear film BUT (NI-BUT) can be measured by corneal refraction that is changed by tear film instability.^22,23

Generally, visual fatigue is related to vergence and accommodation parameters.^24,25 However, evaluating visual fatigue using vergence and accommodation as parameters is not reproducible and is affected by the aging effect. ^26–30 In the previous study, Hirota M et al. developed a binocular fusion maintenance (BFM) test to determine visual fatigue objectively.^31–33 The BFM test has good reproducibilit, and BFM scores significantly decrease after a visual task, showing a negative correlation with subjective eye symptom scores.

We hypothesized that visual fatigue caused by dry eye is related to binocular stress, because tear film instability leads to blurred vision. In this study, we investigated the relationship between BFM and NI-BUT to elucidate whether a short BUT, which is the main symptom of dry eye, induces visual fatigue.

Subjects

A total of 11 young adult volunteers (age [mean ± standard deviation], 20.7 ± 1.4 years) participated in this study. All subjects underwent complete ophthalmologic examinations, including the determination of ocular dominance using the hole-in-the-card test, assessment of best-corrected visual acuity at a distance (5.0 m) near the point of convergence, evaluation of stereoscopic acuity at 40 cm (Titmus Stereo test; Stereo Optical Co., Inc., Chicago, IL, USA), assessment of heterophoria using the alternating cover test at near (33 cm) and far (5.0 m) distance assessments, and examinations of the fundus. Stereoacuity was converted to the logarithm of the arcsec (log arcsec).

Table 1 presents the characteristics of the participants. The mean ± standard deviation of the refractive errors (spherical equivalents) of the dominant eye was − 1.72 ± 3.15 D and that of the non-dominant eye was − 2.08 ± 3.11 D. The best-corrected visual acuity was 0.0 logMAR units or better in all subjects. The average heterophoria was − 4.7 ± 1.9 prism diopters (PDs) at a distance and − 3.6 ± 2.5 PDs up close. All healthy volunteers had a stereoacuity of 40.9 ± 2.9 log arcsec (range: 40–50 s).

Table 1

Characteristics of volunteers.
			Spherical equivalent (D)		Ocular deviation (PD)
ID	age	gender	RE	LE	Near	Distant	Stereo acuity (log arcsec)
1	19	F	−2	−1.875	−4	−6	1.60
2	19	F	0	0.25	−4	−8	1.60
3	19	M	−2	−3.625	−6	−2	1.60
4	22	F	0.25	−2.125	−4	−4	1.70
5	21	F	−0.625	0.5	−4	−2	1.60
6	20	F	−0.25	−0.375	−6	−2	1.60
7	20	F	−5	−5.5	−4	−4	1.60
8	23	M	−6.875	−6.875	−8	−2	1.60
9	21	F	−2.375	−2.375	−4	−8	1.60
10	21	M	5.25	4.5	−4	0	1.60
11	23	M	−5.25	−5.375	0	−2	1.60
F, female; M, male; RE, right eye; LE, left eye; D, diopter; PD, prism diopter. The ocular deviations of minus and plus signs indicate exodeviation and esodeviation, respectively.

Table 2

Change in the subjective symptoms in the pre- and post-visual task.
Questions	Pre	Post	P-value
1	1.18 ± 0.38	2.64 ± 0.64	0.009
2	0.54 ± 0.50	1.09 ± 0.90	0.063
3	1.00 ± 0.43	1.91 ± 0.67	0.008
4	1.09 ± 0.67	1.73 ± 1.14	0.038
5	1.09 ± 0.67	2.00 ± 1.04	0.026
6	0.82 ± 0.57	1.36 ± 0.88	0.063
7	1.54 ± 0.50	2.00 ± 0.85	0.025

Participants in this study were enrolled between May 1, 2023, and September 31, 2023. After explaining the nature of the study and possible complications, all subjects provided informed consent. This study adhered to the Declaration of Helsinki of the World Medical Association. The Institutional Review Board of Teikyo University approved the experimental protocol and consent procedures (approval no. 19–224-3).

Binocular fusion maintenance

BFM can be assessed by reducing the intensity of the incident light on one eye, which is defined by the number of photons, because the perceptive size of the retinal image depends on the intensity of the incident light.³⁴

In this study, we used a custom-made system to measure the BFM (Fig. 1). This system consisted of spectacle-type video-oculography (VOG) (Pupil Core, Pupil Labs, Berlin, Germany), a liquid crystal shutter (LCS) (Large Liquid Crystal Light Valve - Controllable Shutter Glass, Adafruit, New York, NY, USA), and a starburst target at 33 cm. The LCS could arbitrarily change the transmittance from 0.7–34.1% relative to the voltage sent from the microcomputer (Arduino Uno, Arduino, Turin, Italy).

The participants continued to fixate on the starburst target through the LCS, and both eye positions were recorded continuously for 34 s (Movie 1). The transmittance of the LCS in the non-dominant eye, which was determined by the hole-in-the-card test, was set at 34.1% for 3 s and was then reduced sequentially by 1.66% every second. Between 23 and 28 s, the transmittance was maintained at 0.7%; thereafter, it increased and remained at 34.1% between 28 and 34 s. The transmittance for the dominant eye was sustained at 34.1% throughout the 34 s period. The BFM test evaluated the intensity of the incident light ratio in both eyes during the binocular fusion break and was conducted three times before the visual task and three times after the visual task.

The eye positions and pupil diameters in both eyes were exported to a comma-separated values file. Data were excluded when the pupil diameter was > 2 mm/frame because of blinking, and the missing values were replaced with a linearly interpolated value calculated from an algorithm written in Python 3.11.1. The BFM analysis followed the procedure of Hirota et al.³¹ The BFM was calculated using the following equation:

$$Binocular Fusion Maintenance \left(BFM\right)=1- \frac{Transmitance \left(nondominant eye\right) at binocular fusion break}{Transmitance \left(dominant eye\right)}$$

In this study, the change in BFM was defined as the difference between the post-BFM and pre-BFM values.

Non-invasive tear film break-up time

NI-BUT was measured using RT-7000 (Tomey Corp., Aichi, Japan) with a tear stability analysis system (TSAS),²² which irradiates the anterior eye using infrared light, and 15 mire rings from the blue-lighted cone were projected onto the corneal surface. The anterior eye images were captured every second for 10 s. The participants were instructed to refrain from blinking as long as possible and to look at the central target during the measurement. The examiner began the measurements after blinking.

In the NI-BUT analysis, mire ring data were decomposed into 256 individual data points, and 3,840 measurement points were obtained. The TSAS compares the brightness of the wire rings with the initial brightness at 0 s. If the brightness decreased below a predefined threshold, the computer recorded the point at which the threshold crossed the tear film BUT, i.e., the NI-BUT. The NI-BUT was measured in the participants’ right eye before and once after the visual task. Participants were excluded if their NI-BUT was less than 5 s before the visual task.

In this study, the change in NI-BUT was defined as the difference between the post-NI-BUT and pre-NI-BUT values.

Measurement of the blink rate

This study measured the number of blinks by using spectacle-type VOG (Pupil Core, Pupil Labs, Berlin, Germany). Pupil Core captures both eyes at a sampling rate of 120 Hz. Blinks can be detected from the velocity of the vertical pupil diameter, which is reduced by closing the upper eyelid and increased by opening the upper eyelid. All subjects wore VOG spectacles to calculate the number of blinks.

The images recorded in both eyes by spectacle-type VOG were analyzed using Pupil Capture (Pupil Labs, Berlin, Germany), which calculates the velocity of the vertical pupil diameter and then normalizes it from 0–100%. In this study, we defined a blink as a normalized velocity of 50% for the vertical pupil diameter in both the closing and opening phases. The default setting in Pupil Capture was used as the threshold value.

The blink rate was calculated by dividing the number of blinks by the duration of the visual task (30 min).

Questionnaire for evaluating subjective symptoms

Participants were asked to complete a subjective symptom questionnaire at the beginning and end of the examination. The questionnaire was the same as that used in a previous study (Fig. 2).^31–33 The questionnaire was based on the earlier studies of Nakazawa et al., Sheedy and Bergstrom, and Hoffman et al.^10,35,36 Q1 to Q3 were designed to assess subjective eye symptoms, and Q4 to Q7 assessed physical and mental discomfort. Each question was scored from zero to four, and the participants were asked to provide a score for each question.

Visual task

In this study, we used an iPod Touch to simulate smartphone use. The participants played Mario Kart Tour (Nintendo Co., Ltd., Kyoto, Japan) as the visual task. The participants played the game under fully corrected vision for 30 min. The visual distance between the participant’'s eyes and the smartphone display was set at 20 cm by using a neck strap (Fig. 3).

Statistical analysis

Differences in BFM, NI-BUT, and subjective symptoms between the pre- and post-visual tasks were analyzed using the Wilcoxon signed-rank test. The P values for the subjective symptoms were adjusted using Holm correction.

The relationship between the changes in BFM, NI-BUT, and total subjective eye symptom scores (Q1, Q2, and Q3) was evaluated using a single linear regression analysis.

The relationship between blink rate and NI-BUT was analyzed using the Kendall rank correlation coefficient.

SPSS version 26 (IBM Corp., Armonk, NY, USA) was used to determine the significance of the differences, and P < 0.05 was considered statistically significant.

The BFM (pre vs. post: 0.95 ± 0.09 vs. 0.75 ± 0.16) was significantly lower in the post-visual task than in the pre-visual task (P = 0.012) (Fig. 4). The NI-BUT (9.12 ± 1.00 s vs. 5.69 ± 3.11 s) was significantly shorter in the post-visual task than in the pre-visual task (P = 0.011) (Fig. 5). The subjective symptoms of Q1 (1.18 ± 0.38 vs. 2.64 ± 0.64) and Q3 (1.00 ± 0.43 vs. 1.91 ± 0.67) were significantly greater in the post-visual task than in the pre-visual task (Q1, P = 0.009; Q3, P = 0.008) (Table. 2). The total subjective eye symptom (2.91 ± 0.79 vs. 5.45 ± 2.02) was significantly greater in the post-visual task than in the pre-visual task (P = 0.012) (Fig. 6).

The change in BFM (− 0.20 ± 0.18) was significantly and positively correlated with the change in NI-BUT (− 3.43 ± 3.19 s) (R² = 0.385, P = 0.042) (Fig. 7A) and was significantly and negatively correlated with the change in the total subjective eye symptom score (2.54 ± 2.23) (R² = 0.470, P = 0.020) (Fig. 7B). The change in the NI-BUT was not significantly correlated with the change in the total subjective eye symptom score (R² = 0.057, P = 0.48).

The blink rate (11.8 ± 6.7 times/min) was significantly and negatively correlate with the change in NI-BUT (τ = −0.55, P = 0.019) (Fig. 8).

We evaluated the relationship between NI-BUT and BFM to investigate whether dry eyes induce visual fatigue. The BFM and NI-BUT scores were significantly lower in the post-visual task than in the pre-visual task (Figs. 4 and 5). Furthermore, the change in BFM was significantly and positively correlated with that in NI-BUT (Fig. 7A). Binocular fusion is broken by the different retinal images in the left and right eyes.^34,37 The retinal image quality depends on tear film stability because higher-order aberrations are increased by reductions in tear film stability.^21,38,39 Therefore, these findings suggest that dry eye in short BUT increases the load of binocular fusion and induces visual fatigue.

BFM was significantly lower in the post-visual task than in the pre-visual task (Fig. 4), and the total subjective eye symptom score was significantly greater in the post-visual task than in the pre-visual task (Fig. 6). Furthermore, the change in BFM was significantly and negatively correlated with the change in the total subjective eye symptom score (Fig. 7B). Our findings are consistent with those of Hirota et al.³¹, although the apparatus used was different. They reported that BFM was significantly correlated with eye symptoms and that visual fatigue was highly detected compared with conventional examinations, which included fusional range, high-frequency component of accommodative microfluctuations, and near point of convergence. Our study contributes to the development of a minimally viable product for evaluating BFM and demonstrates that BFM can be measured using commercially available LCS and VOG. In previous studies, BFM was measured using a binocular wavefront aberrometer (BWFA) to simultaneously evaluate the consistency of ocular refraction and eye positions.⁴⁰ However, the BWFA is a large apparatus and is expensive.

The blink rate during the visual task was significantly and negatively correlated with the change in the NI-BUT (Fig. 8). Our finding supports earlier studies that reported that the blink rate increased with decreasing tear film instability.^20,41 Higher-order aberrations are induced to blur vision³⁹, and binocular fusion is overloaded to merge the blurred images in both eyes into one image.

The change in NI-BUT did not correlate with the total subjective eye symptoms in this study. Our findings suggest that evaluating visual fatigue using the NI-BUT is challenging. The NI-BUT is the only index used to evaluate dry eye, and it is appropriate to evaluate ocular fatigue with BFM.

We did not examine the recovery time from visual fatigue and tear film instability induced by the visual task. In future studies, we plan to investigate the process of recovery of visual fatigue that was deteriorated by visual tasks to determine whether the recovery of BFM is faster or preceded by the recovery of NI-BUT.

BFM, NI-BUT and subjective eye symptom were detriorated after the visual task. Significant positive and negative correlations were observed between BFM and NI-BUT and between BFM and subjective eye symptoms. These findings suggested that tear film instability induces visual fatigue.

Acknowledgments

We would like to thank Editage (www.editage.jp) for English language editing. This work was supported by Early-Career Scientists, Scientific Research (A) and (B), Japan Society for the Promotion of Science (22K18231 [M.H.], 20K04271 [M.H.], 22H00539 [M.H.]); Nakatani Foundation (M.H.); Inamori Foundation (M.H.); Japan Medical Herb Association Research Grant Program (M.H.); TERUMO LIFE SCIENCE FOUNDATION (22-III 1009 [M.H.]); and Intensive Support for Young Promising Researchers, Japan Agency for Medical Research and Development (23he0422031j0001 [M.H.]).

Author contributions

M.H. conceived the study, designed the experiments, and developed the apparatus. M.W. performed the experiments. M.H., M.W., R.T., K.K., and Y.I. analyzed the data. M.H. and M.W. drafted the manuscript. All authors reviewed the manuscript.

Conflict of interest

The authors without M.H. have no competing interests to declare. M.H. has WO2017159225 (P).

Data availability

The data of this study have been uploaded to zenodo (doi: 10.5281/zenodo.10039342) after removing personal information, and are available to anyone.

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Competing interest reported. M.H. has WO2017159225 (P). WO2017159225 is an international patent for a method of binocular fusion maintenance test.

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Objective Evaluation for Relationship between Visual Fatigue and Tear Film Stability in Smartphone Use

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Methods

Subjects

Binocular fusion maintenance

Non-invasive tear film break-up time

Measurement of the blink rate

Questionnaire for evaluating subjective symptoms

Visual task

Statistical analysis

Results

Discussion

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