Prevalence and factor associated work-related musculoskeletal disorders of students in virtual classroom

Abstract

Objective:
This study examined the prevalence of musculoskeletal disorders (MSDs) and their associated factors among 1st to 4th-year students at Walailak University who attended virtual classrooms for 1 week, 1 month, and 3 months.

Method:
A cross-sectional study was conducted among 382 students aged 18-23 years with no history of musculoskeletal disease or psychiatric disorder who had at least three months of virtual classroom learning. Statistical analysis was performed using chi-squared and Fisher's exact tests.

Results:
Most musculoskeletal abnormalities occurred in the shoulders, head and neck, and lower back at 1 week, 1 month, and 3 months, respectively. At one week and one month in virtual classrooms, the occurrence of MSDs among the students was correlated with psychosocial factors (p < 0.05), and at three months, MSDs were associated with personal factors such as body mass index and psychosocial factors (p < 0.05).

Conclusion:
Stress management for students should be implemented in virtual classrooms to prevent MSDs.

Full text

Heliyon 9 (2023) e18461
Available online 20 July 2023
2405-8440/© 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Prevalence and factor associated work-related musculoskeletal
disorders of students in virtual classroom
Phatcharawadee Srirug
a
,
b
, Khemika Jongjit
a
, Orawanya Muansri
a
, Yanisa Somton
a
,
Nutthida Kongbankhong
a
, Praphatson Sengsoon
a
,
b
,
*
a
Department of Physical Therapy, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat, Thailand
b
Movement Sciences and Exercise Research Center, Walailak University (MoveSE-WU), Nakhon Si Thammarat, Thailand
ARTICLE INFO
Keywords:
Prevalence
Work-related musculoskeletal disorders
Virtual classroom
ABSTRACT
Objective: This study examined the prevalence of musculoskeletal disorders (MSDs) and their
associated factors among 1st to 4th-year students at Walailak University who attended virtual
classrooms for 1 week, 1 month, and 3 months.
Method: A cross-sectional study was conducted among 382 students aged 18–23 years with no
history of musculoskeletal disease or psychiatric disorder who had at least three months of virtual
classroom learning. Statistical analysis was performed using chi-squared and Fisher’s exact tests.
Results: Most musculoskeletal abnormalities occurred in the shoulders, head and neck, and lower
back at 1 week, 1 month, and 3 months, respectively. At one week and one month in virtual
classrooms, the occurrence of MSDs among the students was correlated with psychosocial factors
(p <0.05), and at three months, MSDs were associated with personal factors such as body mass
index and psychosocial factors (p <0.05).
Conclusion: Stress management for students should be implemented in virtual classrooms to
prevent MSDs.
1. Introduction
Work-related musculoskeletal disorders (WMSDs) are injuries and discomfort caused by repetitive behaviors that involve per-
forming the same activities for a long period, which increases the risk of disease. The disease area with the highest prevalence of MSDs
was the lower back, with the most prevalent condition in 134 of the 204 countries analyzed [1].
From 2019 to 2020, the UK Department of Labor Statistics found 480,000 people with WMSDs and an incidence rate of 1420 per
100,000. Workers in many occupations lost more than 8.9 million working days in a year, accounting for 30.00% of cases of WMSDs
and 27.00% lost days at work [2]. The statistics of occupational musculoskeletal diseases reported by the Health Data Center (HDC)
system in Thailand show a high yearly morbidity rate, reecting occupational diseases among the working age. The most common
occupational musculoskeletal diseases among the working age include lower back pain, tendinitis, and myofascial pain syndrome [3].
Moodley et al. have assessed WMSDs among undergraduate nursing students at the University of Johannesburg, and it was found that
the prevalence of musculoskeletal disorders among students was 83.00% out of 125 students, most of whom had lower back pain (LBP)
* Corresponding author. Physical Therapy Department, School of Allied Health Sciences, Walailak University, Nakhon Si Thammarat 80160,
Thailand.
E-mail address: praphatson.kl@wu.ac.th (P. Sengsoon).
Contents lists available at ScienceDirect
Heliyon
journal homepage: www.cell.com/heliyon
https://doi.org/10.1016/j.heliyon.2023.e18461
Received 19 January 2023; Received in revised form 15 July 2023; Accepted 18 July 2023

Heliyon 9 (2023) e18461
2
(81.10%). Fifty-nine (47.2%) nursing students spent under 10 h per week sitting in the classroom. Time spent sitting in the classroom
showed a statistically signicant effect on the prevalence of MSDs [4].
The factors associated with MSDs can be divided into three main categories: individual, physical, and psychosocial factors [5].
Concerning individual or personal factors, a previous study showed that females were more at risk than males [6], older men were at
higher risk than younger men [7], persons with an overweight body mass index (BMI) were at a higher risk than those with an un-
derweight BMI [8], non-exercisers were at a higher risk than exercisers, and smokers were at a higher risk than non-smokers [9].
Physical factors are often related to improper equipment and workstations, work posture, work experience, work time, and break time
[10]. A previous study found that an overly high keyboard position was associated with the occurrence of thoracic symptoms among
students in their higher undergraduate years of study. Computer use for >3 h/day is related to the occurrence of lumbar symptoms
[11]. Psychosocial factors such as work demands, job control, and social support at work are of concern and can increase work-related
risk factors that cause or exacerbate MSDs [12].
Due to the worldwide spread of COVID-19, social distancing has been implemented to reduce its spread. Many universities have
modied teaching using e-learning systems conducted on digital platforms [13]. Virtual classrooms refer to learning experiences
facilitated through the Internet or online with computers used for teaching through electronic media systems, which has become a new
form of education in a world without borders [14]. Various types of electronic devices have been used for learning, such as desktop
computers, notebook computers, tablets, and smartphones, which are accompanied by risk factors such as poor working posture,
device design, and workstations that result in MSDs [15]. In 2021, the use of notebook computers for online learning among children
was 40.60%, and the use of smartphones for online learning was 61.70% [16]. Desktop computers, notebook computers, and
smartphones are essential learning tools in today’s virtual classrooms. The advantage is that learning can occur anywhere, including
outside the classroom. However, there may be disadvantages, such as sitting for a long period, inappropriate ergonomic posture, and
inappropriate workstations.
No studies have investigated the incidence of WMSDs among students enrolled in virtual classrooms. Therefore, this research aimed
to study the prevalence of and factors associated with MSDs among students in virtual classrooms. The results of this study can help
identify methods to prevent WMSDs among students in virtual classroom settings.
2. Materials and methods
2.1. Ethical consideration
The Human Research Ethics Committee of Walailak University, Thailand, approved the study protocol (Reference Number: WUEC-
22-066-01).
2.2. Study population
A cross-sectional study using convenience sampling was conducted between March and April 2022. The participants included 382
students studying at Walailak University in Thailand, selected by convenience sampling. A Google Forms questionnaire was created
and sent to the undergraduate students. All participants were informed of the study protocol and signed a consent form before
participating.
A total of 382 participants (100%) were divided according to their years of study as a percentage of the total number of students.
There were 127 1st-year students (33.12%), 101 2nd-year students (26.56%), 68 3rd-year students (17.74%), and 86 4th-year students
(22.58%). All participants were 18–23 years old, studying in virtual classrooms (learning experience through the inter/online with
computers in an asynchronous classroom where students interacted with instructors and other students and were not dependent on
their physical location for participating in this online learning experience) for more than three months and had never received a
medical diagnosis or physical therapy for bone diseases or muscles that could affect the use of electronic devices in virtual classrooms.
The participants were not menstruating or pregnant, not clinically diagnosed with psychiatric disorders, and had never been injured by
exercise or playing sports. In addition, the participants were never involved in any accidents that could have affected their use of
electronic devices in the virtual classrooms during the 3-month study period. Moreover, the participants did not engage in supple-
mentary occupations/activities that could affect muscles and exacerbate orthopedic injuries and had not undergone other forms of
learning, such as internships or cooperative education.
2.3. Procedure
The questionnaire used in this study consisted of two parts. Part I consisted of a questionnaire on prevalence, including questions
that assess the symptoms and duration of musculoskeletal pain over the past 1 week, 1 month, and 3 months. The collected data were
derived from three main aspects. Part II consisted of a questionnaire on personal, physical, and psychosocial factors. Personal factors
included sex, age, BMI, exercise, and smoking status. Physical factors included using electronic devices, posture, workstation, online
learning experience, and study duration and rest. Psychosocial factors included psychological distress, which was classied according
to the measured stress level (developed by Suanprung Hospital, Ministry of Public Health, Thailand). The Suanprung Stress Test-20
(SPST-20) was shown to have an overall Cronbach’s alpha greater than 0.7 [17] and consisted of 20 items, each of which had a
scoring criterion ranging from 1 (slightly stressed) to 5 (most stressed). The total score was no more than 100, where a score of 0–23
points indicated a low level of stress, a score of 24–41 points indicated a moderate level of stress, a score of 42–61 points indicated a
P. Srirug et al.

Heliyon 9 (2023) e18461
3
high level of stress, and a score of 62 points indicated severe stress. SPST-20 was used to assess participants’ stress levels after studying
virtual classroom events. The questionnaire used in this study was answered by ten Walailak University students who were part of the
sample group. This test was conducted to test the clarity and suitability of the questions. The characteristics of the sample group
followed the same criteria as those of the participants. The questionnaire was then improved to clarify the questions that were unclear,
following which the researcher handed this questionnaire to three musculoskeletal experts (experience in musculoskeletal diseases >5
years) who assessed and assigned a content validity score of ≥0.50 (IOC: Index of item objective congruence).
The researcher corrected the questions in the questionnaire following the advice of the experts. The nal version of the ques-
tionnaire was answered by 30 students to test its clarity and suitability. The completed questionnaire was used to create an online
questionnaire to collect data from Walailak University students in Thailand. Subsequently, information obtained from the inquiry was
collected, and the data were statistically analyzed.
2.4. Sample size calculation
The required sample size was estimated by using the Taro Yamane formula as shown in Equation (1).
n=N
1+NE2(1)
where N represents the population size (1st to 4th-year students at Walailak University), n represents the sample size, and E represents
the signicance level (0.05). Therefore, the required sample size was 382.
2.5. Statistical analysis
Data were analyzed using SPSS Version 26.0. Statistical signicance was set at P <0.05. Descriptive statistics were used to analyze
the frequency and percentage of personal, physical, and psychosocial factors. The relationships between personal, physical, and
psychosocial factors and WMSDs at 1 week, 1 month, and 3 months were analyzed using chi-squared and Fisher’s exact tests.
3. Results
3.1. Prevalence of musculoskeletal disorders among students in virtual classrooms at 1 week, 1 month, and 3 months
The prevalence of MSDs in nine body parts, including the head and neck, shoulders, arms, elbows, wrists and hands, upper back,
lower back, hips and thighs, knees, ankles, and feet. The most common MSDs found at one week among the 382 participants, with a
100% response rate, the most common MSDs found at 1 week are shown in Table 1. At 1 week, the most common areas with MSDs were
the shoulders of 237 participants (62.04%), head and neck of 233 participants (60.99%), and lower back of 225 participants (58.90%).
At one month, the most common areas with MSDs were the head and neck (223 participants, 58.38%), arms and elbows (205 par-
ticipants, 53.66%), and shoulders (180 participants, 47.12%). At 3 months, the most common areas with MSDs were the shoulders
(190 participants, 49.74%), head and neck (185 participants, 48.43%), and lower back (174 participants, 45.55%).3.2 Frequency and
percentage of personal, physical, and psychosocial factors.
3.1.1. Personal factors
From the survey of the prevalence and factors associated with MSDs among students in virtual classrooms, most of them were
female, aged 20–21 years, had an average BMI of 21.76 ±4.42 kg/m
2
, exercised regularly, and did not smoke, as shown in Table 2.
3.1.2. Physical factors
A survey of students in virtual classrooms found that the most common posture and foot placement were hunchbacks in a chair with
the chin out and feet at on the ground. Tablets were the main devices used in virtual classrooms. The Bluetooth pen was the most
popular accessory used with tablets. The workstation consisted of a table with a chair and a backrest. The participants had more than
6–9 months of virtual classroom experience. The duration of each class with no break time was 2 h. The average study duration in class
was 5–6 h per day and 5–6 days per week. The rest time between classes ranged from 1 to 15 min, as shown in Table 3.
3.1.3. Psychosocial factors
According to the Suanprung Stress Test (SPST-20), the stress level among most students in virtual classrooms was moderate, as
Table 1
Prevalence of WMSDs at 1 week, 1 month, and 3 months (n =382).
WMSDs 1 week 1 month 3 months
n (%) n (%) n (%)
No 47 (12.30) 62 (16.20) 112 (29.30)
Yes 335 (87.70) 320 (83.80) 270 (70.70)
P. Srirug et al.

Heliyon 9 (2023) e18461
4
shown in Table 4.
3.2. Association between personal, physical, and psychosocial factors and musculoskeletal disorders at 1 week, 1 month, and 3 months
Personal factors associated with MSDs at 3 months were signicantly associated with BMI and musculoskeletal disorders. The
statistical signicance level of the association was high in the same direction (phi =0.158, p <0.05).
Psychosocial factors were signicantly associated with MSDs at 1 week at a very high level and in the same direction (phi =0.289,
p <0.05). At one month, there was a statistically signicant association with MSDs at a high level and in the same direction (phi =
0.297, p <0.05). At three months, there was a statistically signicant association with MSDs at a high level and in the same direction
(phi =0.247, p <0.05), as shown in Table 5.
4. Discussion
This study assessed MSDs among Walailak University students attending virtual classrooms over one week, one month, and three
months and found that most students tended to have an awkward posture owing to the choice of tablets (76.18%) and smartphones
(54.97%) as their main devices. During the study period, these devices resulted in a hunchbacked sitting posture and a protruding neck
(43.19%). Body discomfort and disorders were observed in the shoulders (62.04%), head and neck (60.99%), and lower back
(58.90%). In the United States, the prevalence of symptoms during device use is 67.9%. Most symptoms were reported in the neck
(84.6%), upper back/shoulder areas (65.4%) [18]. In Thailand, a few studies have surveyed the prevalence of WMSDs among uni-
versity students and ofce workers and found that WMSDs were prevalent in the neck, shoulders, and lower back areas [19–21]. This
may be due to inappropriate ergonomic posture, prolonged awkward posture, long working hours, or inadequate resting time.
Moreover, a study on the prevalence and risk factors of musculoskeletal disorders among smartphone users also found that the
common areas of WMSDs were in the upper part of the body, where factors that affected the risk of MSDs included posture during
smartphone use, duration of smartphone use, and characteristics of smartphone use [22].
BMI and psychosocial factors were signicantly associated with MSDs at a signicance level of 0.05. Factors that were not related to
MSDs with statistically signicant at the 0.05 level were sex, age, physical activity, smoking, and physical factors. This study found that
most participants’ BMI was within the normal range (18.50–22.90 kg/m
2
) at 51.30%. However, previous studies have mentioned that
even with a well-proportioned body or normal BMI, people who sat for long hours in bad posture developed imbalanced muscle
function, thereby leading to musculoskeletal disorders [7,22].
In addition, regarding age, a previous study found that younger people using a computer for more than 3 months developed re-
petitive movements, thereby leading to cumulative trauma disorder (CTD) [23] and pain symptoms from abnormal muscle function.
Some of the main theories have linked stress-induced physiological changes to MSDs. These physiological changes include
increased blood pressure, uid pressure, reduced growth function, decreased sensitivity to pain, pupil dilation, increased muscle
tension, and the body’s heightened sensitivity. Psychosocial factors are associated with MSDs [24]. A previous study examined the
association between psychosocial risk factors and musculoskeletal disorders in Indian IT professionals. The prevalence of existing pain
(shoulders, neck, and lower back) was signicantly associated with high psychosocial risk factors [25]. Moreover, an Occupational
Safety and Health Administration (OSHA) report on ergonomics found that work-related stress accumulated over prolonged periods of
time and developed increased MSDs [26].
Physical factors, including changing posture and taking breaks between sessions in virtual classrooms, were not correlated with
musculoskeletal disorders. A study by Dagne et al. found that people who worked in the same position for long periods of time without
Table 2
Personal factors data (n =382).
Personal factors n (%)
Sex
Male 78 (20.40)
Female 304 (79.60)
Age (years)
18–19 116 (30.40)
20–21 173 (45.30)
22–23 93 (24.30)
BMI (kg/m
2
)
<18.50 87 (22.80)
18.50–22.90 196 (51.30)
23–24.90 40 (10.50)
25–29.90 30 (7.90)
>30 29 (7.60)
Exercise
No 128 (33.51)
Yes 254 (66.49)
Smoking
No 376 (98.43)
Yes 6 (1.57)
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Heliyon 9 (2023) e18461
5
breaks were three times more likely to develop musculoskeletal injuries [27].
The most common sitting posture and foot placement were sitting hunchback on a chair with the neck forward and feet at on the
ground (21.20%). In addition, most participants were aged 18–23 years, exercised regularly, did not smoke, and had a suitable
Table 3
Physical factors data (n =382).
Physical factors n (%)
Posture
Sit on chair with straight back look forward and feet above oor 3 (0.79)
Sit on oor with straight back and look forward 7 (1.83)
Sit on chair with straight back neck exion and feet above oor 22 (5.76)
Sit on chair with straight back neck exion and feet on oor 28 (7.33)
Sit on chair with straight back look forward and feet on oor 28 (7.33)
Prone with back extension 52 (13.61)
Sit on oor with hunch back and chin out 77 (20.16)
Sit on chair with hunch back chin out and feet above oor 81 (21.20)
Sit on chair with hunch back chin out and feet on oor 84 (21.99)
Number of use the main device
Use 2 devices together 347 (90.84)
Use 1 device 35 (9.16)
Main device
Desktop computer 35 (9.16)
Notebook computer 193 (50.52)
Tablet 291 (76.18)
Smartphone 210 (54.97)
Accessory device
Microphone 28 (7.33)
Keyboard 75 (19.63)
Mouse 156 (40.84)
Earphone 258 (67.54)
Bluetooth pen 304 (79.58)
Workstation
Table and chair without backrest 7 (1.80)
Sofa and oor 12 (3.10)
Computer desk and adjustable chair sitting 38 (9.90)
Bed 57 (14.90)
Low folding table and oor 66 (17.30)
Table and chair with backrest 202 (52.90)
Virtual classroom learning experience
>3–6 months 106 (27.70)
>6–9 months 113 (29.60)
>9–12 months 62 (16.20)
>1 year 101 (26.40)
Duration of study in class per a day
1–2 h 30 (7.90)
3–4 h 104 (27.20)
5–6 h 129 (33.80)
7–8 h 100 (26.20)
>8 h 19 (5.00)
Frequency of study in class per a week
1–2 days 42 (11.00)
3–4 days 113 (29.60)
5–6 days 173 (45.30)
1 week 54 (14.10)
Resting time between classes
1–15 min 237 (62.00)
16–30 min 29 (7.60)
31–45 min 26 (6.80)
46–60 min 60 (15.70)
>1 h 30 (7.90)
Table 4
Psychosocial factors data (n =382).
Psychosocial factors n (%)
Mild stress 34 (8.90)
Moderate stress 137 (35.90)
High stress 133 (34.80)
Severe stress 78 (20.40)
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Heliyon 9 (2023) e18461
6
workstation that could reduce the risk of accumulating musculoskeletal injuries. A study by Mehrparvar et al. found that people with
ergonomic knowledge could adjust their behavior at work and workstations and implement appropriate regular exercise. This could
reduce the risk of developing WMSDs [28]. For these reasons, students can be instructed to maintain the correct posture while studying
in virtual classrooms, and teachers can be required to add some interactive links in the teaching method to make students properly
active rather than passively listening for a long period of time. Teachers can increase recess and shorten the time of each class to
manage effective study time, as stated by Saumya et al. who found that college students’ increased screen time on electronic devices
during COVID-19 led to a high prevalence of musculoskeletal disorders [29]. Activities can also be designed specically for students to
lead them in exercises during recess in order to reduce the incidence of musculoskeletal diseases.
5. Conclusion
This study found that musculoskeletal disorders among students in virtual classrooms were at their highest prevalence at one week.
These disorders commonly occur in the shoulders, head and neck, and lower back. Among the factors affecting musculoskeletal dis-
orders, including personal, physical, and psychosocial factors, only psychosocial factors were associated with MSDs among students in
virtual classrooms at 1 week and 1 month. BMI in personal factors, along with psychosocial factors, was associated with MSDs among
students in virtual classrooms at 3 months of age.
The results of this study may persuade students to recognize and pay attention to the occurrence of MSDs. Moreover, the infor-
mation from this study can be used to identify ways to encourage effective learning in virtual classrooms. The basic information
obtained can also be used as guidelines for further in-depth studies.
6. Limitations of the study
The data used in this study were obtained from the students at Walailak University. Therefore, the results can possibly be applied
only to universities or colleges that provide teaching and learning similar to Walailak University, such as 5–6 h per day for the duration
of study in class, 5–6 days per week for the frequency of study in class. In addition, this study used convenience sampling techniques, in
which variables such as learning style and the psychological state of the faculty might have had potential effects on student responses.
The use of stratied sampling techniques is recommended for future studies.
Author contribution statement
Phatcharawadee Srirug: Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis
tools or data; Wrote the paper.
Khemika Jongjit, Orawanya Muansri, Yanisa Somton and Nutthida Kongbankhong: Performed the experiments; Analyzed and
interpreted the data; Wrote the paper.
Praphatson Sengsoon: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data;
Contributed reagents, materials, analysis tools or data; Wrote the paper.
Table 5
Association between factors and work-related musculoskeletal disorders (WMSDs) (n =382).
Factors WMSDs (p-value)
1 week 1 month 3 months
Personal factors
Sex 0.588 0.645 0.552
Age 0.661 0.503 0.971
BMI 0.621
a
0.321 0.048* (Phi =0.158)
Exercise 0.093 0.939 0.200
Smoking 0.452
a
0.343
a
0.763
a
Physical factors
Main device 0.473
a
0.886
a
0.818
a
Posture 0.094
a
0.220
a
0.184
Workstation 0.980
a
0.910 0.227
a
Experience 0.608 0.996 0.641
Average duration of study in class 0.100 0.954 0.359
Duration of study in class per a day 0.340 0.092 0.889
Duration of study in class per a week 0.102 0.530 0.810
Rest time between classes 0.567
a
0.863
a
0.768
Psychosocial factors 0.000* 0.000* 0.000*
Mild stress (Phi =0.289) (Phi =0.297) (Phi =0.247)
Moderate stress
High stress
Severe stress
Note: * Statistically signicant.
a
Fisher’s exact test.
P. Srirug et al.

Heliyon 9 (2023) e18461
7
Data availability statement
No data was used for the research described in the article.
Supplementary content related to this article has been published online at [URL].
Declaration of competing interest
The authors declare that they have no known competing nancial interests or personal relationships that could have appeared to
inuence the work reported in this paper.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.org/10.1016/j.heliyon.2023.e18461.
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