The Ocular Surface 16 (2018) 430–435

Contents lists available at ScienceDirect

The Ocular Surface
journal homepage: www.elsevier.com/locate/jtos

Original Research

The evaluation of dry eye mobile apps for screening of dry eye disease andeducational tear event in JapanT

Miki Uchinoa,∗, Motoko Kawashimaa, Yuichi Uchinoa, Natume Suzukia, Hiroto Mitamuraa,
Miki Mizunoa, Yuichi Horib, Norihiko Yokoic, Kazuo TsubotaaaDepartment of Ophthalmology, Keio University School of Medicine, Tokyo, Japan
Department of Ophthalmology, Toho University School of Medicine, Tokyo, Japanc
Department of Ophthalmology, Kyoto, Prefectural University of Medicine, Kyoto, Japanb

A R T I C LE I N FO

A B S T R A C T

Keywords:
Dry eye disease
Functional visual acuity
Application
Screening
Tear ﬁlm breakup time
Tear ﬁlm breakup pattern

Purpose: To evaluate the usefulness of a dry eye mobile application (app) for screening dry eye disease (DED) at
educational tear events in Japan.
Methods: In this cross-sectional study, Japanese subjects visiting a “Tears Day” event were selected randomly.
They completed questionnaires and underwent ophthalmic evaluations for DED (using Japanese revised diagnostic criteria) including a functional visual acuity (FVA) test. The app calculated FVA using the average of thecontinuous VA over 30 s.
Results: Sixty-three general-population subjects were included: 25 men and 38 women (average age,
50.8 ± 15.9 years). The prevalence of DED was 66.7% (42 subjects); age was signiﬁcantly higher among
subjects with DED (55.2 ± 3.4 vs. 48.1 ± 2.7 years, p = 0.04; men, 54.0 ± 7.3 vs. 47.0 ± 3.0 years,
p = 0.36; women, 55.5 ± 3.9 vs. 50.6 ± 3.8 years, p = 0.4). The prevalence of DED was signiﬁcantly higher inwomen (p = 0.04). Tear ﬁlm breakup time was signiﬁcantly shorter (3.8 ± 2.4 vs. 8.7 ± 2.0, p = 0.04) andthe meibum score was signiﬁcantly higher (p = 0.02) among subjects with DED. Regarding the tear ﬁlm breakup
pattern, line and random breaks were most prevalent among DED. FVA showed a signiﬁcant negative correlation
with DED (r = −0.25, p = 0.047).
Conclusions: The app might motivate people to perform quick tests with the expectation of getting easy DED
screening. The number of subjects diagnosed with DED was relatively high.

1. Introduction
In 2016, the Asia Dry Eye Society announced the new deﬁnition of
DED as follows: “Dry eye is a multifactorial disease characterized byunstable tear ﬁlm causing a variety of symptoms and/or visual impairment, potentially accompanied by ocular surface damage [1].” This
new deﬁnition stresses instability of the tear ﬁlm. Since the importanceof the tear ﬁlm has increased, in 2016, “Tears' Day” was established toincrease the public's awareness of tears in Japan.
The Dry Eye Workshop II (DEWS II) reported that VDT use can beone of the main causes of DED, and especially the evaporative DED
subtype [2]. There has been a dramatic increase in work performed
using VDTs including smartphones in recent years. Ocular symptoms
reported by VDT users include eyestrain, tiredness, irritation, a burning
sensation, redness, reduced visual acuity, ocular pain, double vision,and dry eyes [3–6]. To determine whether the current working environment with increased VDT use is causing DED, a mobile application∗(app) called “You Can Know Whether You Have Dry Eye in a Minute”
was created in 2012. This app can be downloaded for free, which enables everyone to estimate the possibility of having DED by using
combined methods: functional visual acuity (FVA) measurement andfour validated DED questions [7]. FVA is an index of visual function
over time obtained by continuous measurement of the dynamics ofvisual acuity (VA). It has been reported that FVA is decreased in patients with DED despite the demonstration of normal VA in standard
testing [8–13].
The aim was to evaluate the eﬀectiveness of using an DED screening
app to predict the statuses of tears and DED among the general
Japanese population and disseminate DED information at educational
events.

Corresponding author. Department of Ophthalmology, Keio University School of Medicine 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
E-mail addresses: uchinomiki@keio.jp, uchinomiki@yahoo.co.jp (M. Uchino).

https://doi.org/10.1016/j.jtos.2018.06.002
Received 22 December 2017; Received in revised form 15 May 2018; Accepted 4 June 2018

1542-0124/ © 2018 Elsevier Inc. All rights reserved.

The Ocular Surface 16 (2018) 430–435

M. Uchino et al.

2. Methods

meibomian secretion not easily expressible, and opaque, white granularsecretion; and grade 3, meibomian seborrhea with increased sticky
secretion.
To avoid the inﬂuence of CL use, these examinations were performed at least 20 min after removal. To avoid variation among theexaminers, N.Y. performed all tear ﬁlm assessments and the MGD
evaluation was performed by two ophthalmologists (M.K. and Y.U.). All
examiners are members of the Japanese Dry Eye Society and specialize
in ocular surface disease.

2.1. Study population
This study was conducted at Kitte-marunouchi, which located in
front of Tokyo Station, Tokyo, Japan, on July 4, 2017. We randomly
asked subjects who visited the “Tears Event” to participate in this study.
Subjects who understood the use of apps underwent dry eye screening
tests including detailed dry eye examinations using a dry eye app.
Subjects with a history of refractive surgery were excluded. This crosssectional study followed the tenets of the Declaration of Helsinki. The
Institutional Review Board of Hanegino Eye Clinic, Tokyo, Japan approved the protocol prospectively. Written informed consent was obtained from all participants after an explanation of the nature andpossible consequences of the study.

2.4. Diagnosis of dry eye disease
The latest revised version of the Japanese DED diagnostic criteria
was used. Brieﬂy, the new diagnostic criteria include only two parameters: the presence of subjective dry eye symptoms and a TBUT ≤5 s.
A diagnosis of DED was made in the presence of two positive parameters [6].

2.2. Dry eye symptom questionnaire

2.5. The app “You Can Know Whether You Have Dry Eye in a minute”

The symptoms of each subject were assessed after an objective examination using the Dry Eye-Related Quality-of-Life Score (DEQS)
questionnaire [14]. The DEQS questionnaire was recently developed inJapan, and its internal consistency, test-retest reliability, discriminant
validity, and responsiveness to change have all been validated. The
DEQS consists of 15 questions that assess bothersome ocular symptoms
and their impacts on daily life. The total score ranges from 0 (best) to100 (worst) [14].
Information on age, sex, and smoking status (current smoker or not)was also obtained. Based on our previous studies [3,5,6], we assessed
the duration of VDT use (stratiﬁed, none to over 10 h in 1-h increments)
and contact lens (CL) use (yes or no). A current history of certain
common systemic diseases (hypertension, diabetes mellitus) was determined by asking participants whether their physician had ever told
them they had these conditions. We deﬁned systemic medication use as
medication prescribed only by a doctor and not over-the-counter supplements.

The app called “You Can Know Whether You Have Dry Eye in a
Minute,” which is freely available, was utilized in this study (Tsubo
Labo, Tokyo, Japan; Fig. 1). In detail, the app consists of two parts. One
is the subjective symptom questionnaire and the other is an assessmentof FVA. The questionnaire consists of four questions in total. Two arefrom the Women's Health Study [7], which are used commonly inepidemiological studies worldwide. In addition, two questions are included that are commonly used to screen for dry eye disease in Japan.
In total, the questionnaire was as follows: 1) Do you have ocular fatigue? 2) Do your eyes feel irritated? 3)Do your eyes feel dry? 4) Do you
have photophobia? The other part consisted of an FVA assessment. FVA
was measured for 30 s under daily visual correction without topicalanesthesia [17,18]. Subjects were allowed to blink naturally during themeasurement period. Patients delineated the orientation of automatically presented Landolt rings by pressing an arrow on the smartphone. FVA was deﬁned as the mean value change in VA over time
during the examination [17,18]. If the subject fails to select the correct
answer or did not provide any answer within 5 s, the Landolt rings
increase in size. On the other hand, if the subject answers correctly, theLandolt rings become smaller. The FVA test was performed before alltear function examinations. From the combination of the questionnaireand FVA results, the app automatically estimated the possibility of
having DED on a scale from 0 to 100. The algorithm to calculate the dry
eye possibility was as follows: dry eye possibility = −6.113 + 4.907 ×
FVA+ (eye fatigue is YES -1 or No +1) x 0.544+ (eye irritation is YES-1 or No +1) x 0.452 + (dry sensation is YES -1 or No +1) x 0.397+(sensitivity to bright light is YES -1 or No +1) * 0.350. Finally, the app
provides the user with information about the nearest ophthalmologicalclinic using a global positioning system. All subjects who consented toparticipating in this study tested the app ﬁrst, which was then followedby the clinical evaluation. The clinical examiner was blinded to theresults of the app test to avoid bias.

2.3. Tear function and ocular surface evaluation
Ophthalmic examinations included assessments of conjunctival andcorneal vital staining with ﬂuorescein. Tear stability was assessed by
the standard tear ﬁlm breakup time (TBUT) measurement before theevaluation of keratoconjunctival epithelial damage. To determine the
TBUT, ﬂuorescein vital staining was performed, and patients wereasked to blink three times to ensure adequate mixing of the ﬂuorescein
dye with tears. The time interval between the last complete blink andthe appearance of the ﬁrst corneal dark spot was measured with astopwatch, with the mean of three measurements regarded as the TBUT
in this study. Corneal and conjunctival epithelial damage were assessed
separately by ﬂuorescein staining. The eye was categorized into threeequal parts representing the temporal conjunctiva, nasal conjunctiva,
and cornea. All three parts were scored separately with a maximum
staining score of 3 points. Overall epithelial staining severity was scoredon a scale of 0–9 points. The tear ﬁlm breakup pattern (TBUP) was
categorized using Yokoi's classiﬁcation [15]. Brieﬂy, this classiﬁcation
includes ﬁve TBUPs as follows: area, spot, line, dimple, and random
breaks. Area and line breaks were considered aqueous tear deﬁciencies;
on the other hand, spot, dimple, and random breaks corresponded tothe short TBUT type of DED.
Meibomian gland dysfunction (MGD) grading was performed according to a modiﬁed Bron's classiﬁcation [16] as follows: grade 0, no
glandular dropout and easy meibum expressibility with clear transparent meibomian secretion; grade 1, glandular dropout in one-third of
the eyelid length with acinar cluster visibility in the remaining eyelid,
granular secretion, diﬃcult expressibility, and turbid, non-sticky secretion; grade 2, glandular dropout in one-third of the eyelid with lossof acinar cluster visibility but with observable yellow stripes,

2.6. Satisfaction questionnaire
The satisfaction questionnaire was distributed to subjects whocompleted the DED screening. The questionnaire consisted of twoquestions as follows: 1) Do you think that the dry eye testing was
useful? and 2) After seeing the results, do you intend to visit an ophthalmology clinic? The possible answers were yes, no, or unknown for
all questions.
2.7. The educational approach to disseminate the importance of the tearﬁlm and dry eye disease
To educate subjects about the importance of the tear ﬁlm, a 12-page431

The Ocular Surface 16 (2018) 430–435

M. Uchino et al.

Fig. 1. The mobile application “You Can Know Whether You Have Dry Eye in a Minute”.
The smartphone application enables subjects to measure functional visual acuity at anytime and anywhere.

subjects with and without DED (p = 0.03). The most prevalent dry eye
pattern was impaired wettability of the corneal surface at the breakup
spot caused by tear ﬁlm instability. The DED group showed higher MGD
and meibum grades (p = 0.06 and 0.02, respectively). Among subjects
diagnosed with DED, one-quarter had MGD scores of 2 or greater.
However, we did not observe a signiﬁcant diﬀerence in the relationshipbetween the TBUP and meibum grade (p = 0.46). In detail, among
subjects with a line break, 75% were MGD grade 0, 12.5% were MGD
grade 1, and 12.5% were MGD grade 2. Among those with a spot break,
100% were MGD grade 0; additionally, 93.3% of subjects with arandom break were grade 0. Lastly, regarding subjects with a dimple
break, 40% were MGD grade 0, 20% were MGD grade 1, and the remaining 40% were MGD grade 2. The presence of conjunctivochalasis
did not show signiﬁcance, and no subject with or without DED had lid
wiper epitheliopathy (p = 0.2 and 1.0, respectively). For subjective
DED symptoms related to QOL, the DED group showed worse scoresthan the non-DED group; however, there was no statistical diﬀerence(Table 3; 16.9 ± 2.1 vs. 12.1 ± 1.8, p = 0.14). DED prediction results
using the app did not show statistical signiﬁcance between subjects
with and without DED (82.5 ± 2.6 vs. 76.9 ± 4.6, p = 0.26). The FVA
maintenance ratio measured by the app showed a signiﬁcant diﬀerence
between subjects with and without DED (0.76 ± 0.04 vs. 0.91 ± 0.55,
p < 0.0047). There were signiﬁcant associations between the app's
DED evaluation and the total DEQS score (r = 0.39, p = 0.002) andbetween the app's DED evaluation and the TBUT result (r = −0.30,
p = 0.018).
On the satisfaction questionnaire, 69% of subjects felt the evaluation was useful and 47% felt the need to visit an ophthalmologist fortreatment.

brochure was created, and 1000 copies were distributed among Kittemarunouchi visitors on Tears Day. In addition, 712 members of theJapanese Dry Eye Society, 2245 members of the Tokyo Association ofOphthalmologists, and almost all clinics in Japan received brochures to
educate patients. In addition to education regarding tears, we had two
30-min lectures about tears by M.U. and one talk show featuring acelebrity and T.K. The audience numbered approximately 100 in total.
Moreover, an online educational lecture targeting ophthalmologists inJapan was performed by Y.H.
2.8. Statistical analysis
Fisher's exact test, the U test, and t-test were used to compare
parameters between subjects in the DED and non-DED groups. All statistical analyses were performed using SAS software (version 9.4; SAS
Inc., Cary, NC, USA). A p-value < 0.05 was considered statisticallysigniﬁcant.
3. Results
Among the 63 subjects who consented, all completed the study,
including 25 men (39.7%) and 38 women (60.3%) aged between 24 and84 years (50.8 ± 15.9 years, average ± standard deviation [SD];
Table 1). No diﬀerence was observed between the sexes in CL or
medication use (p = 0.7 and 0.67, respectively). However, men reported signiﬁcantly longer VDT working hours than did women(7.5 ± 3.5 vs. 3.1 ± 3.3 h, p ≤ 0.001). There was a signiﬁcant sex
diﬀerence between subjects in the DED and non-DED groups(p = 0.04). Women had a higher prevalence of DED (61.9%) comparedwith men (42.9%, p = 0.04). However, CL and systemic medication use
did not show any signiﬁcant diﬀerence between subjects in the DED and
non-DED groups (p = 0.1 and 0.9, respectively).
Regarding ocular ﬁndings, subjects with DED had signiﬁcantly
shorter TBUTs than did subjects without DED (3.8 ± 2.4 vs.
8.7 ± 2.0, p = 0.04; Table 2). Almost all subjects had no ocularﬂuorescein staining in either group (0.07 ± 0.3 vs. 0, p = 0.33). In the
DED group, random and line breaks were the top two TBUPs (44.7%
and 36.8%) followed by dimple breaks (13.2%) and spot breaks (5.3%).
No subject demonstrated an area break in this study. Almost half of the
non-DED group showed no breakup within 10 s (57.1%); the remainderof the subjects who had TBUTs within 10 s all showed a random break(100%). Signiﬁcant diﬀerences in TBUPs were observed between

4. Discussion
Recently, smartphones have become used widely and smartphonebased apps are available anywhere; thus, there is an increased need forapps that can easily evaluate health conditions. In resource-poor
countries, the diagnosis of certain diseases such as cattle diseases has
been performed using a smartphone-based app and was shown to be
useful [19]. In the ﬁeld of ophthalmology, an application supporting
primary care physicians in diagnosing ocular disease has been developed, but there is no application that a patient can use to estimate theirocular conditions. Among eye diseases, DED is one of the most prevalent for which patients seek eye care, and there is an increased need
432

The Ocular Surface 16 (2018) 430–435

M. Uchino et al.

Fig. 2. A representative functional visual acuity result. a: The functional visual acuity of a subject with dry eye disease; functional visual acuity is maintained. b: Thefunctional visual acuity of a subject without dry eye disease; functional visual acuity decreases as time elapses.
Table 1
Characteristics of the study population.

Table 2
Associations between dry eye disease and demographic characteristics.

Sex

Male

FemaleTotal

Number25 (%)

38 (%)

63

Age, years ( ± the SD)
VDT working hours
CL useMedication use

48.1 ± 13.7
7.5 ± 3.5
7 (28.0)
7 (29.2)

52.5 ± 17.1
3.1 ± 3.3
9 (23.7)
9 (24.3)

50.8 ± 15.9
4.8 ± 3.9
16 (25.4)
16 (26.2)

P-value

Number

0.29< 0.001
0.7
0.67

Age, years ( ± the SD)
The female sex
VDT working hours
CL useMedication use

Dry EyeNon Dry Eye

42 (%)

21 (%)

53.7 ± 15.9
29 (61.9)
4.1 ± 4.0
8 (19.1)
11 (26.8)

44.9 ± 10.8
9 (42.9)
6.2 ± 3.88 (38.1)
5 (25.0)

P value

0.04
0.04
0.04
0.1
0.9

SD: standard deviation, VDT: visual display terminal, CL: contact lens.
SD: standard deviation, VDT: visual display terminal, CL: contact lens.

for applications that can evaluate the ocular condition including TBUT.
This study evaluated the eﬀectiveness of using an app called “You Can
Know Whether You Have Dry Eye in a Minute.” This application does
not directly evaluate the status of the cornea including the TBUT;
however, it enables patients to calculate their FVAs. FVA is well known
to have a statistically negative correlation among DED subjects [9], andthe measurement of FVA can be an alternate method to screen for DED.
In this study, we found a signiﬁcant reduction in FVA among subjects
with DED. Subjects without DED had higher VA maintenance ratios,
which imply stable VAs over 30 s (0.91 ± 0.55%). On the other hand,subjects with DED had lower VA maintenance ratios and unstable VAs
433

The Ocular Surface 16 (2018) 430–435

M. Uchino et al.

found that among subjects without DED, 12 did not show any tear ﬁlm
breakup until 10 s (Fig. 3). Among the remaining nine subjects who
showed TBUTs of 5–10 s, all showed the random-type TBUP. On theother hand, random and line breaks were most prevalent among subjects with DED (44.7% and 36.8%, respectively).
Yokoi et al. reported that a random break was considered the resultof increased evaporation of aqueous tears [15]. A line break has been
demonstrated to have decreased aqueous tear thickness at the lower
cornea from the uptake of water by the low meniscus, and also from the
upward drag of aqueous tears by the tear ﬁlm lipid layer. This study
revealed that subjects without DED had complete establishment of atear ﬁlm, which then showed breakup after 5 s of eye opening. The
relationship between area breaks and tear volume was not clear in thisstudy. Since we did not measure tear secretions using the Schirmer I testor another measurement system, we could not evaluate factors inﬂuencing TBUPs and tear secretion.
Interestingly, this study showed a high satisfaction rate for the DED
evaluation. A campaign or educational event such as the one in thisstudy might play an important role in determining ocular surface
conditions. In addition, almost half of the subjects felt the need for DED
treatment at a clinic. To reduce disease, prevention using screening
tools and increasing the patient's understanding of the condition areimportant. This screening app might provide important information toevaluate daily FVA and maintain their current condition.
The results of this study may provide guidance for speciﬁc precautions such as brief periods of rest during VDT work, the provision of
information and guidance on dry eye related problems, and the adoption of relevant policies in workplaces to prevent ophthalmic disorders
such as DED during VDT work.
We acknowledge several limitations to this study. Less than 100
subjects participated in this study. To evaluate the true prevalence of
DED in an urban setting, we need to establish a population-based study
enrolling thousands of subjects. Second, this study was performed at acelebration of Tears Day, so this location might have included a greater
proportion of subjects who were interested in tears than in the general
population, which may have induced a selection bias. A decrease in
FVA from other types of ocular disease has been reported previously;
however, we did not consider this factor in the present study. Moreover,the symptomatology questionnaire that is included in the app should be
modiﬁed to make the diagnosis more accurate. In the near future, weneed to establish a study that takes ocular comorbidities and FVA into
account by using a diﬀerent symptomatology questionnaire to understand false-positive results.

Table 3
Associations between dry eye disease and ocular ﬁndings.
Number

TBUT
Fluorescein staining
MGD
0
1
2
3
MeibumChalasis
Lid Wiper
Total DEQS score

Dry EyeNon Dry Eye

P value4221

3.8 ± 2.4
0.07 ± 0.3

8.7 ± 2.0
0

0.04
0.33

1 (2.4)30 (71.4)
8 (19.1)
3 (7.1)0.45 ± 0.1
0.28 ± 0.1
016.9 ± 2.1

21 (100)0000.10 ± 0.1
0.10 ± 0.1
012.1 ± 1.8

0.06

0.02
0.2
1
0.14

SD: standard deviation; TBUT: tear ﬁlm breakup time; MGD: meibomian gland
dysfunction; DEQS: Dry Eye-Related Quality-of-Life Score.

(0.76 ± 0.04%, p = 0.0047). Kaido et al. reported using a discriminantequation obtained using FVA measurements combined with symptoms
and stated that it can be a screening method for DED [11]. They used
standard FVA measurements in the clinic rather than app-based FVA
measurements. It used to be diﬃcult for subjects to measure their FVAs
at anytime and anywhere. A screening instrument is ideal if it is demonstrably simple, quick to administer, and easy to use. In this light,
our app is a useful tool that can measure FVA at anytime as long as
there is a smartphone available.
The app also showed the possibility of detecting DED based on ascore ranging from 0–100. Interestingly, our results show that subjects
with DED had a higher probability of having DED according to the app;however, there was no statistical signiﬁcance (82.5 ± 2.6 vs.
76.9 ± 4.6, r = −0.24, p = 0.26). The reasons for the lack of signiﬁcance remain unknown; however, it is possible that the questions
included in the app might not be adequate to detect Japanese dry eye
symptomatology. In addition, the revised Japanese criteria include only
the TBUT and a questionnaire; therefore, it might lack speciﬁcity inevaluating DED. There was a signiﬁcant association between the app's
evaluation and the total DEQS score (p = 0.002). Interestingly, we also
found an association between the result from the app and the TBUT
(p = 0.018). The app itself might similarly detect and measure TBUT in
addition to providing an evaluation of DED for users worldwide.
Other than the utilization of an app, this is the ﬁrst study evaluating
TBUPs among the general population including non-DED subjects. We

Fig. 3. Distributions of tear breakup patterns among the subjects. All subjects without dry eye disease show random breaks. In subjects with dry eye disease, line andrandom breaks are more prevalent.
434

The Ocular Surface 16 (2018) 430–435

M. Uchino et al.

In conclusion, DED App might motivate people to perform quick
tests with the expectation of getting easy DED screening. By utilizing
this app, subjects might be able to discern their dry eye status based onJapanese criteria anytime and anywhere without visiting an eye clinic.
The features of DED in the Japanese population showed a low TBUT
and higher prevalence among women. Although further studies areneeded to increase our understanding of the importance of this publichealth problem, the results of this study may increase the awareness of
methods to evaluate DED easily.

[3] Uchino M, Schaumberg DA, Dogru M, et al. Prevalence of dry eye disease among
Japanese visual display terminal users. Ophthalmology 2008;115:1982–8.
[4] Thomson WD. Eye problems and visual display terminals–the facts and the fallacies.
Ophthalmic Physiol Optic: J. Br. Coll. Ophthalmic Opticians (Optometrists)
1998;18:111–9.
[5] Uchino M, Schaumberg DA. Dry eye disease: impact on quality of life and vision.
Curr. Ophthalmol. Rep. 2013;1:51–7.
[6] Uchino M, Uchino Y, Dogru M, et al. Dry-eye disease and work productivity loss invisual display users: the Osaka study. Am. J. Ophthalmol. 2014;157:294–300.
[7] Schaumberg DA, Dana R, Buring JE, Sullivan DA. Prevalence of dry eye disease
among US men: estimates from the Physicians' Health Studies. Arch Ophthalmol
2009;127:763–8.
[8] Ishida R, Kojima T, Dogru M, et al. The application of a new continuous functional
visual acuity measurement system in dry eye syndromes. Am. J. Ophthalmol.
2005;139:253–8.
[9] Kaido M, Ishida R, Dogru M, Tsubota K. The relation of functional visual acuity
measurement methodology to tear functions and ocular surface status. Jpn J
Ophthalmol 2011;55:451–9.
[10] Kaido M, Matsumoto Y, Shigeno Y, Ishida R, Dogru M, Tsubota K. Corneal ﬂuorescein staining correlates with visual function in dry eye patients. Invest.
Ophthalmol. Visual sci. 2011;52:9516–22.
[11] Kaido M, Uchino M, Yokoi N, et al. Dry-eye screening by using a functional visualacuity measurement system: the Osaka study. Invest. Ophthalmol Vis. Sci.
2014;55(5):3275–81.
[12] Kaido M, Yamada M, Sotozono C, et al. The relation between visual performanceand clinical ocular manifestations in Stevens-Johnson syndrome. Am. J.
Ophthalmol. 2012;154. 499–511.e491.
[13] Kaido M, Uchino M, Kojima T, Dogru M, Tsubota K. Eﬀects of diquafosol tetrasodium administration on visual function in short break-up time dry eye. J Ocul
Pharmacol Therapeut: Oﬀ. J. Assoc. Ocular Pharmacol. Therapeut.
2013;29:595–603.
[14] Sakane Y, Yamaguchi M, Yokoi N, et al. Development and validation of the dry eyerelated quality-of-life score questionnaire. JAMA Ophthalmol. 2013;131:1331–8.
[15] Yokoi N, Georgiev GA, Kato H, et al. Classiﬁcation of ﬂuorescein breakup patterns: a
novel method of diﬀerential diagnosis for dry eye. Am. J. Ophthalmol.
2017;180:72–85.
[16] Bron AJ, Benjamin L, Snibson GR. Meibomian gland disease. Classiﬁcation andgrading of lid changes. Eye 1991;5(Pt 4):395–411.
[17] Kaido M, Dogru M, Yamada M, et al. Functional visual acuity in Stevens-Johnson
syndrome. Am. J. Ophthalmol. 2006;142:917–22.
[18] Kaido M, Dogru M, Ishida R, Tsubota K. Concept of functional visual acuity and its
applications. Cornea 2007;26:S29–35.
[19] Beyene TJ, Eshetu A, Abdu A, et al. Assisting diﬀerential clinical diagnosis of cattle
diseases using smartphone-based technology in low resource settings: a pilot study.
BMC Vet Res 2017;13:323.

Funding
This study was a collaborative investigation of the Dry Eye Society,
Tokyo.
Conﬂicts of interest
Miki Uchino, Motoko Kawashima, Yuichi Uchino, Hiroto Mitamura,
Miki Mizuno, and Natume Sizuki declare that they have no conﬂicts ofinterest.
Yuichi Hori: Consultant and research funding from Santen
Pharmaceutical Co., Ltd. and Otsuka Pharmaceutical Co., Ltd.
Norihiko Yokoi: Consultant for Kissei Co, Ltd, Alcon Japan Ltd., andRohto Co, Ltd.
Kazuo Tsubota: Consultant and research funding received fromSanten Pharmaceutical Co., Ltd., research funding received from Kowa
Company, and holds the patent rights for the method and the apparatus
used for the measurement of functional visual acuity (US patent no:7470026). Founder of Tsubo Labo, Tokyo, Japan.
References[1] Tsubota K, Yokoi N, Shimazaki J, et al. New perspectives on dry eye deﬁnition anddiagnosis: a consensus report by the Asia dry eye society. Ocul. Surf.
2017;15:65–76.
[2] Stapleton F, Alves M, Bunya VY, et al. TFOS DEWS II epidemiology report. Ocul.
Surf. 2017;15:334–65.

435