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Research Report About Effect of Display Gadgets on Eyesight Quality (Computer Vision Syndrome) of M.Sc.(CSIT) Students In Tribhuvan University

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Abstract

The aim of the study was to analyze the effects that gadgets have on eyesight quality (also known as Computer Vision Syndrome). A Questionnaire & survey study was conducted on Ashad,2075 on 46 students, with a mean age of 25.13 years( with standard deviation 1.50) from Central Department of CSIT TU. The Students Characteristic is observed. A questionnaire was also distributed, which contained 8 questions that highlighted the gadget’s impact on the eyesight. The use of different gadgets, such as TV, computer, laptops, projectors, mobile phones or other displays become part of our everyday life and people experience a variety of ocular symptoms or vision problems related to these. Computer Vision Syndrome (CVS) represents a group of visual and extra ocular symptoms associated with sustained use of visual display terminals. Eye Strain, Dry Eye, and Red Eye are the most frequent manifestations determined by the long time use of gadgets. Television, Mobile phones and laptops are the most frequently used gadgets. People who use gadgets for a long time in a day have more CVS symptoms than that who use less. A small amount of refractive errors (especially myopic shift) was objectively obtained by this study on near work. Dry eye syndrome could also be identified, and an improvement of visual comfort could be observed after the instillation of artificial tears drops. Computer Vision Syndrome is still under-diagnosed, and people should be made aware of the bad effects the prolonged use of gadgets has on eyesight. The prevalence of symptoms of CVS (one or more) was found to be 80.4%; the most disturbing symptom was Eyestrain (15.2%) followed by Tired Eye (13.2%). Students who used VDT Display Gadgets for more than 4 hours per day experienced significantly more symptoms of CVS. Average hours using Computer as well as mobiles using per day, wearing eyeglass & Using preventive Measures, were significantly associated with present of CVS While CVS symptoms were not associated with Gender, Duration of wearing Eyeglass and duration (years) of using Electronic gadgets.
International Journal of Scientific and Engineering Research (IJSER) Volume 9, Issue 8, August 2018
ISSN 2229-5518
i
A Research Report About Effect Of Display
Gadgets On Eyesight Quality (Computer Vision
Syndrome) Of M.Sc.(CSIT) Students In
Tribhuvan University
Sudip Poudel
Abstract
The aim of the study was to analyze the effects that gadgets have on eyesight quality (also known as Computer Vision Syndrome).
A Questionnaire & survey study was conducted on Ashad, 2075 on 46 students, with a mean age of 25.13 years (with standard
deviation 1.50) from Central Department of CSIT TU.
The Students Characteristic is observed. A questionnaire was also distributed, which contained 8 questions that highlighted the
gadget’s impact on the eyesight. The use of different gadgets, such as TV, computer, laptops, projectors, mobile phones or other
displays become part of our everyday life and people experience a variety of ocular symptoms or vision problems related to these.
Computer Vision Syndrome (CVS) represents a group of visual and extra ocular symptoms associated with sustained use of visual
display terminals. Eye Strain, Dry Eye, and Red Eye are the most frequent manifestations determined by the long time use of
gadgets.
Television, Mobile phones and laptops are the most frequently used gadgets. People who use gadgets for a long time in a day
have more CVS symptoms than that who use less.
A small amount of refractive errors (especially myopic shift) was objectively obtained by this study on near work.Dry eye
syndrome could also be identified, and an improvement of visual comfort could be observed after the instillation of artificial tears
drops.
Computer Vision Syndrome is still under-diagnosed, and people should be made aware of the bad effects the prolonged use of
gadgets has on eyesight.
The prevalence of symptoms of CVS (one or more) was found to be 80.4%; the most disturbing symptom was Eyestrain (15.2%)
followed by Tired Eye (13.2%). Students who used VDT Display Gadgets for more than 4 hours per day experienced significantly
more symptoms of CVS.
Average hours using Computer as well as mobiles using per day, wearing eyeglass & Using preventive Measures, were
significantly associated with present of CVS While CVS symptoms were not associated with Gender, Duration of wearing Eyeglass
and duration (years) of using Electronic gadgets.
Keywords: eyesight quality, refractive errors, gadgets, Computer Vision Syndrome
Acronyms:
DV: Dioptric Value VA: Visual Acuity TU: Tribhuvan University
BV: Binocular Vision TV: Television CVS: Computer Vision Syndrome
VDT: Video Display Terminal CDS: Central Department of Statistics SPSS: Statistical Package
for Social Sciences
CSIT: Computer Science & Information Technology
International Journal of Scientific and Engineering Research (IJSER) Volume 9, Issue 8, August 2018
ISSN 2229-5518
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1.1 Introduction:
Computer vision syndrome (CVS) is a condition in which a
person experiences one or more of eye symptoms as a result
of prolonged working on a computer or using other display
gadgets.
It was conducted a questionnaire survey in students
studying in Tribhuvan university (central department of
statistics) Nepal. This was a research project of students as
part of the project work for semester III (statistics) Tribhuvan
University.
1.2 Literature Review:
Technological advances have made an impact in almost
every aspect of our lives (office work, accounting, designing,
medical facilities, database management, experimental work
and daily tasks) after the availability of computers.
A personal computer and electronic gadgets are the common
items now-a-days in offices, colleges, universities and home.
Its use has increased efficiency in easy access to information,
writing articles, and communicating to others. Millions of
people including children, college students are using
computers for prolonged hours. A video display terminal
(VDT) is also known as computer screen.
The symptoms reported were eyestrain, tired eyes,
headache, blurred vision, irritation, burning sensation,
redness, double vision, neck pain, and backache which
might be caused by combination of individual visual
problems, poor workplace conditions and improper work
habits (Cole et al, 1996; Collins et al, 1998). However, eye
related symptoms were reported as the most common health
problem among VDT users (Shaeedy, 1992; Costanza, 1994;
Thomson, 1998).
The condition of a person experiencing one or more of these
eye symptoms as a result of operating a computer is
generally referred as computer vision syndrome (CVS); and
the symptoms have been divided broadly into four
categories:
(i) asthenopic eye strain, tired eyes, sore
eyes,
(ii) ocular surface related watering,
irritation, dry eye,
(iii) visual blurred vision, slowness of focus
change, double vision, and
(iv) Extra ocular neck pain, back ache,
shoulder pain,
(Blehm et al, 2005).
Now-a-days, large numbers of university students are using
audio visual equipments for studies and for research work.
In addition, computers are used by them for seeing movies,
playing computer games and online chatting.
We can divide the eye problem in two categories such as:
1.2.1Common vision problems:
The most common vision problems are refractive errors,
more commonly known as nearsightedness, farsightedness,
astigmatism and presbyopia. Refractive errors occur when
the shape of the eye prevents light from focusing directly on
the retina. The length of the eyeball (either longer or shorter),
changes in the shape of the cornea, or aging of the lens can
cause refractive errors. Most people have one or more of
these conditions.
Fig. 2 Normal Eye
The cornea and lens bend (refract) incoming light rays so
they focus precisely on the retina at the back of the eye.
Refraction is the bending of light as it passes through one
object to another. Vision occurs when light rays are bent
(refracted) as they pass through the cornea and the lens.The
light is then focused on the retina. The retina converts the
light-rays into messages that are sent through the optic nerve
to the brain. The brain interprets these messages into the
images we see. The most common types of refractive errors
are nearsightedness, farsightedness, astigmatism
and presbyopia.
Refractive errors can be corrected with eyeglasses, contact
lenses, or surgery.
International Journal of Scientific and Engineering Research (IJSER) Volume 9, Issue 8, August 2018
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1.2.2Computer vision syndrome (CVS):
Computer vision syndrome (CVS) is a condition in which a
person experiences one or more of eye symptoms as a result
of prolonged working on a computer or using other display
gadgets.
Display Gadgets are the electronic devices including Mobile
Phones, Tablets, Television, Computers, Projectors and other
audio visual equipments
2.1 Objectives of the Study
The objectives of this study are as follows:
i. To determine the prevalence of CVS
symptoms, knowledge and practices of
computer use in students studying in TU CSIT.
ii. To evaluate the association of various factors in
computer/mobile use with the occurrence of
Computer Vision symptoms.
iii. To determine the types of CVS Symptoms
among MSc. CSIT students.
iv. To determine the average time of uses of
electronic device per day.
v. To identify the minor eye problems.
2.2 Limitations of the Study:
This study may be limited through the use of a
questionnaire as a data collection instrument.
Because questionnaires must generally be brief, all
medical information may not have been included in
the questionnaire.
The research is based on only department of CSIT
so the result may not be generalized to the all
students of this university.
(The study may also be limited over the first and
third semester students of the central
department of CSIT.)
The sample of Students for the study was chosen
from present students in class and may not be
representative of the total population of Students in
TU (if some representative students were absent
under the time period of data collection).
The use of simple statistical techniques may
introduce an element of subjectivity into the
interpretation and analysis of the data.
All attempts have been made to minimize the effects of these
limitations on the study.
3.1 Coverage:
The study area of the research is Students of Central
Department of Computer Science & Information
Technology, Tribhuvan University.
3.2 Methodology (Materials and Methods)
The study was a prospective observational one, conducted
from Ashad 2075, on 46 students, of central department of
CSIT with a mean age of 25.13 years (with standard
deviation 1.50).
A research questionnaire was prepared after reviewing the
articles available on computer vision syndrome and effect of
electronic gadgets. Then the questionnaire was used to
collect data regarding the gadget’s impact on eyesight. We
were particularly interested in the types of display used, the
amount of time spent in front of the device per day and
Power of eyeglasses.
Data were statistically analyzed in SPSS 20.0 by using
Independent Student’s t-test (statistically significant at p
0.05), fisher exact test (for two categorical variables χ2 cell
having less than 5 number in one or two cell) & other
descriptive statistical methods using Kobo Toolbox,
Microsoft Excel.
A complete enumeration of present students in class was
conducted among 46 students of First & Third semester of
Central Department of CSIT from Tribhuvan University and
the questionnaire was edited for easy understanding by the
respondents. After making sure that the respondents were
using the computer daily for one hour or more over a period
of some months/years, the students were explained about
the, Objectives of the research project; confidentiality of the
data collected; and verbal consent was taken for their
willingness to participate in the study. All the students
agreed for participation in the study and hence, all of them
were taken as sample for this study.
All the students present in the class at the time of giving the
questionnaire were included in the study as per the inclusion
criteria. After collecting the filled up pro formas from the
students, they were checked for the responses in all the
sections. The pro formas from the students with insufficient
data were excluded from the study as per the exclusion
criteria.
International Journal of Scientific and Engineering Research (IJSER) Volume 9, Issue 8, August 2018
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The data was collected in a Kobo collect Of Kobo toolkit
software (The set of questionnaire included in KoboToolbox
application is in Appendix-1) and downloaded. And edited
in Microsoft Excel & analyzed using SPSS version 20.0
program.
3.3 Decision Criteria:
If the student had experienced at least one symptom
during/following use of computer, he/she was considered to
be having symptom of CVS. Some of them might have
experienced more than one symptom. Therefore, to
determine the association of various factors with the
presence or absence of symptoms, all the symptoms were
added together (cumulated number) for statistical purpose.
Thus, the total numbers of symptoms are much more than
the number of students.
Independent t- test was used to evaluate the significance of
symptoms with various factors during computer use. &
fisher exact test (for two categorical variables χ2 cell having
less than 5 number in one or two cell) & other descriptive
statistical methods A p value (0.05 i.e. 5% level of
significance) was taken as statistically significant.
4.1 Results and Conclusions:
A total of 46 students were recruited in this study. All of
them responded the questionnaire correctly. Male students
were more (39, 84.78%) than females (7, 15.22%).The mean
age of students was 25.13 years (with σ = 1.50). out of 46
students 21 (54.34%) were wearing eyeglasses and 1 student
was wearing contact lens. 19 students were myopias and 2
students were hyperopia.
The mean duration of daily computer use per day was 4.96
hours (with σ = 2.347) & daily use of mobile (for
internet/video/games) was 3.10 hours (with σ =2.332).
Majority of students (87%) were aware of the bad effects of
prolonged use of computer on the eye. The mean total
duration of computer use (by all students) was 8.72 years
(with σ =3.526) & mean total duration of Android/IOS mobile
use was 6.09 years (with σ = 1.736) . Thirty seven (80.4%)
students had one or more symptoms of CVS, while 9 (19.6%)
did not have any symptoms. The most disturbing symptom
was Eye strain (15.2%) followed by Tired Eye (13.2%)
4.1.1 Descriptive Statistics (Tables & Figures):
Table-1 Most Disturbing Symptoms:
Symptoms
Frequency
Percent
Cumulative
Percent
2
4.3
4.3
1
2.2
6.5
1
2.2
8.7
4
8.7
17.4
7
15.2
32.6
2
4.3
37.0
2
4.3
41.3
11
23.9
65.2
5
10.9
76.1
1
2.2
78.3
6
13.0
91.3
4
8.7
100.0
46
100.0
International Journal of Scientific and Engineering Research (IJSER) Volume 9, Issue 8, August 2018
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Fig.3 Most Disturbing CVS Symptoms
The most disturbing symptom was Eye strain (15.2%)
followed by Tired Eye (13.2%), while 9 (19.6%) did not have
any symptoms.
Table-2 Level Of Computer Screen:
Frequency
Percent
Above Eye Level
12
26.1
At Eye Level
21
45.7
Below Eye Level
13
28.3
Total
46
100.0
Fig.4 Level Of Computer Screen
Most of the students(45.7%) use computer at the eye level
followed by below eye leavel(28.3%) & above eye level
(26.1%).
Table-3 Preventive Measures Applied (Multiple
Response)
Frequency
Percent
Cumulative
Percent
No Response
4
8.7
8.7
Looking Far Objects
6
13.0
21.7
Taking Break
22
47.8
69.6
Taking
Break/Looking Far
Objects
3
6.5
76.1
Taking Break /Use
Eye Drops
6
13.0
89.1
Use Eye Drops
3
6.5
95.7
Use radiation filter
on screen
2
4.3
100.0
Total
46
100.0
International Journal of Scientific and Engineering Research (IJSER) Volume 9, Issue 8, August 2018
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Fig.5 Preventive Measure Applied
Taking Break, Looking Far Objects & Using Eye Drops,
were the frequently used preventive measures among MSc
CSIT Students.
Symptoms of Computer Vision Syndrome after Continuous
Use of Gadgets are shown in the pie chart below :( this
chart is based on multiple response)
International Journal of Scientific and Engineering Research (IJSER) Volume 9, Issue 8, August 2018
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Fig.6 Symptoms after prolonged use of Gadgets.
Table-4 Lighting Of Room/Workplace
Frequency
Percent
Cumulative
Percent
Fluorescent
12
26.1
26.1
LED
29
63.0
89.1
Natural
5
10.9
100.0
Total
46
100.0
Fig.7 Lighting Of Room
Most Of the Students Used LED Light (63%) followed By
Fluorescent Light (26.1%) & Natural Light (10.9%) while
using Computer at their Room/workplace.
4.1.2 Statistical Tests:
Let us set the null and alternative hypothesis to
analyze the data statistically.
[where variable* indicates: Gender, Using Eyeglasses, Using
preventive measures, Duration of wearing eyeglasses, Using
computer from(years),average hours computer using daily,
Mobile/android/ios using from(years) and average hours
mobile using per day.]
Null Hypothesis (H0) :
There is no significant impact on CVS Symptoms by the
respective variable*
Alternative Hypothesis (H1) :
There is significant impact of variable* On CVS
Symptoms.
Independent t test for various Scale variables with Presence of CVS
Group Statistics
Presenc
e Of
CVS
No Of
Student
s
Mea
n
Std.
Deviatio
n
Std.
Error
Mea
n
Duration
wearing glass
(Years)
No
1
2.00
.
.
Yes
19
7.95
4.336
0.995
Using
Computer(Year
s)
No
9
10.44
3.432
1.144
Yes
37
8.30
3.463
0.569
Hrs Computer
using(1 Day)
No
9
3.22
1.563
0.521
Yes
37
5.38
2.326
0.382
Using
IOS/android
from
(Years)
No
9
6.56
1.740
0.580
Yes
37
5.97
1.740
0.286
Mobile Using
Hrs(1 Day)
No
9
1.67
1.000
0.333
Yes
37
3.45
2.438
0.401
Using More
Than 4 Hours
No
4
4.50
0.577
0.289
Yes
37
4.35
1.513
0.249
Above data are statistically analyzed using independent t-
tests (presence of CVS vs. other scale variables at 5% level
of significance)
The t-statistic table as follows:
Independent Samples Test
Levene's
Test for
Equality of
σ 2
t-test for
Equality of
Means
F
Sig.
t
DF
Sig.
Wearing
Eyeglass (Yrs)
Equal σ2
assumed
-
-
-
1.337
18
0.198
International Journal of Scientific and Engineering Research (IJSER) Volume 9, Issue 8, August 2018
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Equal σ2
not
assumed
-
-
.
Using Computer
(Yrs)
Equal σ2
assumed
0.075
0.786
1.671
44
0.102
Equal σ2
not
assumed
-
1.680
12.29
0.118
Hrs Computer
Using
(Per Day)
Equal σ2
assumed
3.747
0.059
-
2.629
44
0.012*
Equal σ2
not
assumed
-
-
3.336
17.78
0.004
Using
IOS/android
from(Yrs)
Equal σ2
assumed
0.202
0.656
0.901
44
0.373
Equal σ2
not
assumed
-
0.901
12.20
0.385
Mobile Using
Hrs(1 Day)
Equal σ2
assumed
3.284
0.077
-
2.132
44
0.039*
Equal σ2
not
assumed
-
-
3.414
32.67
0.002
Using Gadgets(>
4 Hrs)
Equal σ2
assumed
Equal σ2
not
assumed
1.674
-
0.023
0.193
0.390
39
8.71
0.048
0.006*
*indicates significant.
From above independent t-test we found that average hours
using computer per day (p = 0.012), average hours using
Mobile per day (p = 0.039) have a significant impact to the
appearance of CVS.
Using Display gadgets more than 4 hours (p = 0.006) has high
chance of appearance of CVS.
But there is not significant impact on appearance of CVS
Symptom by, Duration of Wearing eyeglasses (p = 0.198),
Time duration of using computer (p = 0.102) and Time
duration of using mobile (p = 0.373).
χ 2 /Fisher Exact Test for Categorical variables With Presence of
CVS
Cross-tabulation [Gender Vs Presence of CVS]
Count
Presence Of CVS
Total
No
Yes
Gender
Female
1
6
7
Male
8
31
39
Total
9
37
46
Chi-Square with Fisher’s Exact Test
Value
Df
Asymp.
Sig. (2-
sided)
Exact
Sig. (2-
sided)
Exact
Sig. (1-
sided)
Pearson Chi-
Square
.146
1
0.702
Fisher's
Exact Test
1.000
0.583
N of Valid
Cases
46
From above fisher exact test it was found that There is not
significant association (p=0.583) between gender and
presence of CVS Symptoms.
Cross-tabulation [Wearing Eyeglass Vs Presence of CVS]
Count
Presence Of CVS
Total
No
Yes
Wearing
Eyeglass
No
8
17
25
Yes
1
20
21
Total
9
37
46
Chi-Square with Fisher’s Exact Test
Value
Df
Asymp.
Sig. (2-
sided)
Exact
Sig. (2-
sided)
Exact
Sig. (1-
sided)
Pearson Chi-
Square
5.381
1
0.020
Fisher's
Exact Test
0.027*
0.022*
N of Valid
Cases
46
.
From above fisher exact test It was found that there is a
significant association (p= 0.027) between wearing eyeglass
and presence of CVS Symptoms.
International Journal of Scientific and Engineering Research (IJSER) Volume 9, Issue 8, August 2018
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Cross-tabulation [Using Preventive Measure Vs Presence
Of CVS]
Count
Presence Of CVS
Total
No
Yes
Using Preventive
Measure
No
4
0
4
Yes
5
37
42
Total
9
37
46
Chi-Square with Fisher’s Exact Test
Value
DF
Asymp.
Sig. (2-
sided)
Exact
Sig. (2-
sided)
Exact
Sig. (1-
sided)
Pearson
Chi-
Square
18.011
1
0.000
Fisher's
Exact Test
0.001*
0.001*
N of Valid
Cases
46
*indicates significant
From above fisher exact test It was found that there is
highly significant association (p= 0.001) between wearing
using preventive measures and presence of CVS
Symptoms.
4.2 Recommendations:
students should be aware about of bad effect of
prolonged use of video display gadgets on eyes
If possible, students should not use
computer/mobile more than 4 hour continuously in
a day.
If it is necessary to use computer/mobile many
hours in a day then preventive measure must be
applied continuously.[ For example taking break,
looking for objects, using radiation filter in screen
etc.]
If students have other ocular problems (myopia,
hyperpiesia) Continuous use of display gadgets
should be avoided.
Acknowledgement
First and foremost, I would like to express my sincere
and profound gratitude to Prof.Dr Tika Ram Aryal for
continuous guidance, help, encouragement, guidance
and practical suggestions & feedback extended to
complete this project.
I am also grateful to all respondents from MSc 1st
and 3rd Semesters students from central Department of
Computer Science and Information Technology
(CDCSIT) and others from the study areas for their
support in providing information for this study.
Last but not the least, I wish to thank all others who
directly or indirectly assisted me towards the
completion of this study.
Sudip Poudel, M.Sc 3rd semester, CDS, TU,Nepal
References:
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study. Optom Vis Sci; 73:512-528
Jaschninski W, Heuer H, Kylian H (1998).Preferred
position of visual displays relative to the eyes:A field
study of visual strain and individual differences,
Ergonomics; 41: 1034-1049.
Sheedy JE (1992). Vision problems at video display
terminals: A survey of optometrists. J Am Optom Assoc;
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Poudel, S. and Khanal, S. (2020) “Magnitude and
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International Journal of Scientific and Engineering Research (IJSER) Volume 9, Issue 8, August 2018
1ISSN 2229-5518
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Bhanderi DJ,Choudhary S, Doshi VG (2008).A
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Supplementary resources (2)

... They have been facing complications of mental health, such as stress, depression and anxiety, during the COVID-19 pandemic [75]. On a different note, the deterioration of physical health is also caused by the prolonged use of electronic devices, such as computers, tablets, and smartphones, that expose students to further radiation released from the screen [76,77], especially during the afternoon virtual learning session [78]. In addition to the prolonged use of electronic devices, other physical health problems occurred, such as major vision problems including eye strain, red eye, dried eyes [76], itchiness in vision, bleary eyes and seeing double, and other related risks such as headaches [79]. ...
... On a different note, the deterioration of physical health is also caused by the prolonged use of electronic devices, such as computers, tablets, and smartphones, that expose students to further radiation released from the screen [76,77], especially during the afternoon virtual learning session [78]. In addition to the prolonged use of electronic devices, other physical health problems occurred, such as major vision problems including eye strain, red eye, dried eyes [76], itchiness in vision, bleary eyes and seeing double, and other related risks such as headaches [79]. Excessive exposure to radiation over an extended period also risks causing cancer and tumors [78]. ...
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Amid the outbreak of the COVID-19 pandemic in the year 2020, educational platforms have been forced to change and adapt from conventional physical learning to virtual learning. Nearly all higher learning institutions worldwide are forced to follow the new educational setting through virtual platforms. Sabah is one of the poorest states in Malaysia with the poorest infrastructure, with the technology and communication facilities in the state remaining inept. With the changes in virtual platforms in all higher education institutions in Malaysia, higher learning institutions in Sabah are expected to follow the lead, despite the state lagging in its development. This has certainly impacted the overall productivity and performance of students in Sabah. Therefore, this study aims to explore the challenges of the implementation of virtual learning among students in Sabah. More specifically, this study seeks to identify vulnerable groups among students based on their geographical location. To achieve the objective of this study, a survey has been conducted on a total of 1,371 students in both private and public higher learning institutions in Sabah. The sample selection for this study was determined using a purposive sampling technique. Based on Principal Component Analysis (PCA), it was found that there are five challenges in virtual learning faced by students in higher learning institutions in Sabah. These are the unconducive learning environment (var(X) = 20.12%), the deterioration of physical health (var(X) = 13.40%), the decline of mental health (var(X) = 12.10%), the limited educational facilities (var(X) = 10.14%) and social isolation (var(X) = 7.47%). The K-Means Clustering analysis found that there are six student clusters in Sabah (Cluster A, B, C, D, E & F), each of which faces different challenges in participating in virtual learning. Based on the assessment of location, almost half of the total number of districts in Sabah are dominated by students from Cluster A (9 districts) and Cluster B (4 districts). More worryingly, both Cluster A and Cluster B are classified as highly vulnerable groups in relation to the implementation of virtual learning. The results of this study can be used by the local authorities and policymakers in Malaysia to improve the implementation of virtual learning in Sabah so that the education system can be more effective and systematic. Additionally, the improvement and empowerment of the learning environment are crucial to ensuring education is accessible and inclusive for all societies, in line with the fourth of the Sustainable Development Goals (SDG-4).
... After that, it is advisable to move to distant viewing or to look at green objects. Staring at a computer screen for a long period of time can affect brain development [2] and may cause visual impairment [3]. Some signs of fatigue due to spending too much time in front of a computer are face and eye fatigue or the computer vision syndrome (CVS) [4], which may start to appear after two hours. ...
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  • S C Reddy
Reddy SC et al Computer vision syndrome Nepal J Ophthalmol 2013; 5 (10): 161-16