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Research article
Prevalence and determinants of internet addiction among adults during the
COVID-19 pandemic in Bangladesh: An online cross-sectional study
Poly Rani Biswas
a
, Benojir Ahammed
a
,
*
, Md. Shiafur Rahman
a
, Byazid Mahin Nirob
a
,
Md. Tanvir Hossain
b
a
Statistics Discipline, Science, Engineering &Technology School, Khulna University, Khulna 9208, Bangladesh
b
Sociology Discipline, Social Science School, Khulna University, Khulna 9208, Bangladesh
ARTICLE INFO
Keywords:
COVID-19
Internet addiction
Prevalence
Adult
Bangladesh
ABSTRACT
Background: Globally, internet use has increased significantly during the COVID-19 pandemic, and internet
addiction (IA) has become a severe public health issue. Therefore, this study aimed to assess IA prevalence among
adults and identify its determinants during the COVID-19 pandemic in Bangladesh.
Methods: Using a cross-sectional design, this study recruited 608 participants through a self-administered online-
based e-questionnaire. Young’s internet addiction test (YIAT) of 20 items was used to assess the prevalence of IA
among adults in Bangladesh. Bivariate and binary logistic regression analyses explored the factors influencing IA.
Results: The overall prevalence of IA was 29.4% among adults during the COVID-19 pandemic. However, the
addiction rate was 34.7% among participants under 20 years old. Tobacco smoking (AOR ¼1.88, 95% CI
1.15–3.07) and spending more time on the internet during the COVID-19 pandemic (AOR ¼2.06, 95% CI
1.08–3.94) were likely the reasons for IA among Bangladeshi adults. Participants aged over 24 years (AOR ¼0.39,
95% CI 0.17–0.91), living in rural areas (AOR ¼0.51, 95% CI 0.32–0.81), living away from family (AOR ¼0.45,
95% CI 0.26–0.79), attached to physical activity (AOR ¼0.35, 95% CI 0.24–0.52), and sleeping less than or equal
6 hours (AOR ¼0.63, 95% CI 0.42–0.93) had a lower chance of IA during the COVID-19 pandemic.
Conclusion: This study has shown that the prevalence of IA was comparatively higher among younger participants
during the COVID-19 pandemic. Smoking, long-time use of the internet, physical activity status, and sleeping
duration were the most significant determinants of IA. Thus, raising awareness among the younger generation is
the most important strategy to reduce IA. The findings of this study can be used to support health and educational
organizations to design their programs, which will help prevent IA in Bangladesh during the COVID-19 pandemic.
1. Introduction
Internet addiction (IA) refers to an unhealthy and poorly regulated
preoccupation with the internet resulting in impulsive behaviors and
psychiatric impairments (Shaw and Black, 2008). The concept of IA was
brought to light by Griffiths (1996); however, Young (1998) successfully
characterized IA as an ‘impulse-control disorder’free of intoxication. Due
to the realization of the potential adverse impacts, it can have on the
behavioral and functional aspects of an individual, IA has been included
as a non-substance addictive disorder in the DSM-5 (American Psychi-
atric Association, 2013). IA may cause difficulties in personal and social
life (Diomidous et al., 2016), and its harmful effects may include
compulsive behavior, poor sleep quality, reduced food consumption,
attention deficit, resistance towards family and academic obligations,
and decreased academic grades, as well as psychological problems, such
as depression and anxiety (Alam et al., 2014;American Psychiatric As-
sociation, 2013;Bener et al., 2019;Young, 1998).
Despite posing a substantial threat to significant life domains,
including interpersonal and intrapersonal relations and physical and
mental health (Alam et al., 2014;Young, 1998), reliance on the internet
has been increasing worldwide at a dramatic rate. Globally, for example,
64% of people were using the internet in 2020, with a penetration rate of
64.2%. Although Asia has the highest number of internet users in the
world (2.7 billion), North America has the highest penetration rate
(89.9%) (Internet World Statistics, 2021). This growing internet use
among people, particularly the younger population (Zenebe et al., 2021),
has contributed to IA. For instance, a meta-analysis comprising 164
studies (N¼89.281) from seven world regions estimated a global
* Corresponding author.
E-mail addresses: benojirstat@gmail.com,benojirstat@ku.ac.bd (B. Ahammed).
Contents lists available at ScienceDirect
Heliyon
journal homepage: www.cell.com/heliyon
https://doi.org/10.1016/j.heliyon.2022.e09967
Received 23 June 2021; Received in revised form 26 June 2021; Accepted 12 July 2022
2405-8440/©2022 The Author(s). 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/).
Heliyon 8 (2022) e09967
prevalence of 6% for IA, with the highest prevalence reported in the
Middle East (10.9%), followed by North America (8%) and Asia (7.1%)
(Cheng and Li, 2014). Like other countries, Bangladesh has been expe-
riencing IA, especially among its younger population, as they are more
exposed to internet-related activities than their older counterparts.
Studies suggest that young men, primarily students from economically
well-off families living in urban areas, who spend more hours on the
internet for academic or non-academic purposes, are more susceptible to
IA (Afrin et al., 2017;Hassan et al., 2020).
However, the world may have witnessed an unprecedented spike in
IA due to the ongoing novel coronavirus disease of 2019 (COVID-19)
pandemic, which originated in Wuhan, in the Hubei province of China
(Forster et al., 2020). Unlike its predecessors –severe acute respiratory
syndrome (SARS) in 2002 and the Middle East respiratory syndrome
(MERS) in 2012 –which had a high-case fatality rate (Deng and Peng,
2020), COVID-19 has an exceptionally high human-to-human trans-
mission rate, thus, compelling the global public health watchdog –the
World Health Organization (WHO) –to declare a global pandemic on 11
March 2020 (World Health Organization, 2020). In the absence of spe-
cific antidotes or vaccines, it became a global challenge during 2020 for
national and international public health agencies to curb the spread and
loss of lives. By April 2021, 140 million people were infected with
COVID-19, and it had killed over three million people worldwide (World
Health Organization, 2021a); there were over 0.7 million confirmed
COVID-19 cases in Bangladesh, with around 11,000 resulting deaths
(World Health Organization, 2021b). Therefore, the global community
implemented a wide range of non-therapeutic measures, including
restricting the travel of foreign nationals, closing entire transit systems as
well as public spaces, and shutting down educational institutions (Ahmed
et al., 2020;Cao et al., 2020) as well as more stringent steps like
country-wide lockdowns (Chen and Yuan, 2020;Cohen and Kupfersch-
midt, 2020). Like other countries, Bangladesh suspended all forms of
academic activities from 18 March following the first confirmed case of
the COVID-19 on 8 March 2020 and implemented a lockdown in the
guise of ‘general holidays’from 26 March 2020, and this was extended at
regular intervals until early September 2020 (Jahid, 2020). This pro-
longed ‘home confinement’significantly affected the mental well-being
of different cohorts of people, causing intensified anxiety, depression,
stress, fear, worsening sleep quality, and increasing substance abuse
(Ahammed et al., 2021;Cao et al., 2020;Hossain et al., 2022a;Islam,
Barna, Raihan, Khan and Hossain, 2020a;Shovo et al., 2021).
Subsequently, people turned to the internet and other technology-
based mechanisms to ‘alleviate negative feelings’(Kardefelt-Winther,
2014) and cope with the ‘new normal’by supporting their work,
communication, and academic activities (Ela et al., 2021;Hossain et al.,
2022b). Exposure to social and mass media through the internet allowed
people to receive daily updates on the pandemic situation, which
improved public awareness and encouraged ‘social distancing’and ‘home
staying’(Sakya et al., 2021). However, the sense of loneliness during the
prolonged lockdown (Li et al., 2021), together with COVID-19-related
anxiety and depression, were significantly associated with over-
consumption of the internet and smartphone use (Elhai et al., 2020). This
‘over-exposure’evidently led to growing anxiety and depression,
particularly among the younger population (Hammad and Alqarni, 2021;
Hossain et al., 2020).
Studies during the COVID-19 pandemic found heightened IA among
people of different age cohorts worldwide and linked it with a wide range
of factors. For example, Sarıalio
glu et al. (2022) noted that more than
80% of Turkish adolescents were using the internet for more than 6 hours
a day during the pandemic; this was significantly influenced by parental
education, habit of internet use, sense of loneliness, and family income,
with the latter showing a negative relationship with internet use. A study
in Taiwan noted a 24.4% prevalence of IA among junior high school
students; this was significantly associated with increased impulsivity and
alexithymia, low subjective well-being, and family function, especially
among older students (Lin, 2020). An Indonesian study showed that the
prevalence of IA among the adult population during COVID-19 was
14.4%; this was significantly influenced by increased duration of online
use for a specific application, including gaming, information seeking,
entertainment, and social media usage (Siste et al., 2020). Li et al. (2021)
found that the overall prevalence of IA among the general population in
China was 36.7% during the COVID-19 pandemic; the associated risk
factors were duration of internet use, lack of social support, growing
mental stress and pressure, and addiction to videogames.
In Bangladesh, a few studies addressed IA and related issues in the
pre-COVID-19 period (Afrin et al., 2017;Islam and Hossin, 2016;Jahan
et al., 2019;Mamun et al., 2019); however, there has only been a single
study conducted by Islam et al. (2020b), that has addressed problematic
internet use (PIU) during the COVID-19 pandemic. They observed that an
individual’s sociodemographic and lifestyle factors, such as online be-
haviors, significantly determine the presence and absence of PIU. For
example, people who are younger, highly educated, living with families,
engaging in low or no physical exercise, and with a habit of playing
online games or use of social media for recreation are positively associ-
ated with PIU (Islam et al., 2020b). However, the authors did not esti-
mate the prevalence rate of PIU among the citizenry of Bangladesh.
Hence, this cross-sectional web-based study aimed to estimate the
prevalence of IA among the adult population in Bangladesh and to
identify the risk factors associated with it during the COVID-19
pandemic.
2. Materials and methods
2.1. Study design and participants
This study was web-based and cross-sectional in nature, and the data
were collected online over a period of around one month, starting on 1
January 2021 and ending on 8 February 2021. It is important to note that
exposure to social media has increased substantially during the COVID-
19 pandemic in Bangladesh, especially among the population between
18 and 30 years in age (Hossain et al., 2020). Among the popular social
media platforms, Facebook has been widely used by a mammoth 47.2
million people in Bangladesh, of which 21.2 million users were between
18 and 24 years of age (Prothom Alo, 2021). As such, the participants
were recruited randomly through existing social media –i.e., Facebook –
and were invited to respond to a self-administered e-questionnaire
developed using Google Form. The e-questionnaire contained three
separate but interrelated modules, including questions on
socio-demographic information, IA measurement, and information
relating to the internet and other behavioral issues during the COVID-19
pandemic. The study set out the response range for maximum questions
and encouraged the participants to answer intelligently through the
e-questionnaire descriptions in order to ensure the survey’s quality. This
study considered only adults aged 18 years or above and recorded the
participants’consent during the data collection. A total of 608 responses
were recorded, all of which were retained in this study after week-long
scrutiny.
2.2. Ethical clearance
The Khulna University Ethical Clearance Committee (KUECC)
approved this study (Reference No. –KUECC-2021/04/17). The partic-
ipants were informed about their anonymity and the non-commercial use
of information by an informed consent form attached to the e-question-
naire. Moreover, the participants were able to decline the e-survey
without any prior justification. They were also assured of their right to
retract the provided information within a stipulated timeline.
2.3. Internet addiction test
The IA of the participants was measured by Young’s internet addic-
tion test (YIAT) (Young, 1998). The YIAT –the most commonly and
P.R. Biswas et al. Heliyon 8 (2022) e09967
2
frequently used scale measuring the internet addiction of adults –com-
prises 20 items scored on a 5-point Likert scale ranging from ‘not appli-
cable’(0) to ‘always’(5) with a maximum score of 100. Based on the
scoring, participants were classified into ‘not internet addicted’(0–59)
and ‘internet addicted’(60–100) (Mamun et al., 2019). The Cronbach’s
alpha (
α
) for YIAT in this study was 0.965, reflecting an excellent internal
consistency.
2.4. Socio-demographic and behavioral characteristics
In this study, a group of socio-demographic and behavioral factors
was considered as explanatory variables, based on previous research, to
measure effects on IA. Socio-demographic information including gender,
age, occupational status, place of residence, educational qualification,
and living arrangements (Prakash et al., 2020;Hassan et al., 2020) was
collected. Furthermore, to ascertain fundamental behavioral factors, the
survey included a few questions relating to lifestyle. The participants
were asked if they smoked cigarettes and whether they were involved in
physical activities such as exercise, walking, sports, cycling, or any other
activities lasting at least 30 min per day (Hassan et al., 2020) during the
COVID-19 pandemic. Participants were also asked to report their
average, typical sleep duration during the ongoing pandemic as either
short or long (Mamun et al., 2019). They were then asked how long they
spent online per day, the device they used to access the internet, duration
of internet use (Hassan et al., 2020), and status of internet use during the
COVID-19 pandemic.
2.5. Statistical analysis
Descriptive analyses were conducted in order to describe the socio-
demographic and behavioral characteristics of the participants. The
prevalence of IA was stratified by age, gender, educational qualification,
occupation, place of residence, living arrangement, smoking status,
physical activity status, sleep duration, the device of internet use, length
of internet use, status of internet use during the COVID-19 pandemic, and
daily internet use duration; Chi-square (
χ
2) test was used to compare the
differences between the groups at a 5% level of significance. Finally,
considering the statistically significant factors from the Chi-square (
χ
2)
test, a multivariable binary logistic regression model was conducted in
order to explore the potential determinants of IA. The results were shown
using the adjusted odds ratio (AOR) with 95% confidence intervals (95%
CI). The statistical package for the social sciences (SPSS) version 20 (SPSS
Inc., Chicago, IL, USA) was used to organize and analyze the data.
3. Results
3.1. Socio-demographic and behavioral characteristics of study
participants
Table 1 shows the characteristics of the participants. Of the 608
participants, 419 (68.9%) were male and 189 (31.1%) were female.
Among the participants, 58.1% were aged 20–24 years, 78.8% were
students, and three out of five participants (66.4%) had completed un-
dergraduate or postgraduate education. Four out of five participants
(79.3%) resided with their families, and 66.0% lived in urban areas
during the pandemic. Around 80% of participants were non-smokers, and
more than half were engaged in regular physical activities (54.9%) and
slept less than or equal 6 hours a day (55.3%). Among the participants,
66.4% spent more than 3 hours per day on the internet, and 69.1%
admitted that their internet use had increased during the pandemic.
3.2. Prevalence of internet addiction
Table 1 also shows the prevalence (95% CI) of IA in relation to a range
of socio-demographic and behavioral characteristics. The overall preva-
lence of IA was 29.4%. The findings indicate that participants with
distinct characteristics, such as younger people, men, those without un-
dergraduate education, students, those living in urban areas, those living
with families, smokers, those who did not engage in any physical activity,
and those sleeping more than 6 hours, were more likely to show IA. In
addition, Table 1 also shows the association of IA with various explan-
atory factors using a Chi-square (
χ
2
) test of independence. The findings
indicate that age (p¼0.007), education qualification (p¼0.039), place
of residence (p¼0.009), living arrangement (p¼0.001), smoking status
(p¼0.001), physical activity (p<0.001), sleep duration (p¼0.001),
status of internet use (p¼0.001), and duration of daily internet use (p¼
0.005) were significantly associated with IA.
3.3. Factors associated with internet addiction
Significant factors from the Chi-square (
χ
2
) test of independence were
retained in the multivariable binary logistic regression analysis in order
to investigate how these factors have influenced IA in Bangladesh
(Table 2). In the multivariable model, after complete adjustments, there
was robust evidence for the odds of IA being 1.88 times and 2.06 times
higher among tobacco smokers (AOR ¼1.88, 95% CI 1.15–3.07) and
intensified internet users during the COVID-19 pandemic (AOR ¼2.06,
95% CI 1.08–3.94). It is also evident that the odds of IA for older par-
ticipants (>24 years) and those living in rural areas were 0.39 times
(AOR ¼0.39, 95% CI 0.17–0.91) and 0.51 times (AOR ¼0.51, 95% CI
0.32–0.81) lower than for younger people and those living in urban
areas, respectively. The odds of IA for participants living away from
family were 0.45 times lower than for those living with family (AOR ¼
0.45, 95% CI 0.26–0.79). There was compelling evidence that the odds of
IA were 65% lower among participants who were engaged in regular
physical activities than among those who did not (AOR ¼0.35, 95% CI
0.24–0.52). Participants who slept less than or equal 6 hours a day (AOR
¼0.63, 95% CI 0.42–0.93) and those who had been exposed to internet
use for over 3 years (AOR ¼0.41, 95% CI 0.22–0.78) were less likely to
be internet addicted than those who slept longer than 6 hours a day and
those had used the internet for less than two years, respectively.
4. Discussion
This study aimed to assess the prevalence of IA and the associated risk
factors among adults in Bangladesh during the COVID-19 pandemic. The
findings indicate that the overall prevalence of IA among adults in
Bangladesh was 29.4%, which is higher than the finding of another study
(27.1%) conducted on adults during the COVID-19 pandemic (Hassan
et al., 2020). Countries other than Bangladesh have also witnessed
increased IA among adults during COVID-19. For example, a study in
Indonesia reported a 14.4% level of IA (Siste et al., 2020), while it was
36.7% in China (Li et al., 2021). This heightened IA among adults can be
attributed to their home confinement, which has led to increased use of
social and electronic media for information and entertainment (Hossain
et al., 2020;Siste et al., 2020). The higher response from young adults in
this study could also be responsible for the higher prevalence of IA. The
introduction of online education (OE), particularly in the universities of
Bangladesh in late August 2020, may have boosted the use of the internet
for academic purposes (Hossain et al., 2022b), thereby, increasing the
risks of IA among young adults.
From the binary logistic regression, it is apparent that age, place of
residence, living arrangement, tobacco smoking, regular physical activ-
ities, sleep duration, internet use, and duration of internet use during the
COVID-19 pandemic significantly influenced IA, while tobacco smoking
and internet use during the COVID-19 pandemic were positively associ-
ated with IA. In this study, it was observed that older people were less
likely to be addicted to the internet than younger people. Because older
adults in Bangladesh were more engaged in securing necessities for their
family members, despite the imposition of social distancing (Hossain
et al., 2021), they had relatively fewer chances to become entangled with
the internet. In contrast, younger adults have experienced a rapid
P.R. Biswas et al. Heliyon 8 (2022) e09967
3
increase in internet use for academic purposes (Ela et al., 2021;Hossain
et al., 2022b) as well as for entertainment, including gaming, gambling,
and pornography viewing (Gjoneska et al., 2022), due to prolonged home
confinement. Hence, age-specific intervention programs should be
implemented to reduce the burden of IA among the younger population
in Bangladesh.
This study has revealed that place of residence has a strong negative
association with IA. The prevalence and risk of IA were significantly
lower among rural adults than among their urban counterparts. A
possible reason could be that rural people were economically hardest hit
by the imposition of regional, national, and international bans on
transporting agricultural products, which created an imbalance between
demands for daily necessities and earning opportunities (Halim et al.,
2022;Hossain et al., 2021); thus, it would have been nearly impossible
for these already marginalized rural people to spend money on the
internet over other necessities, especially food and medicine. Frequent
load shedding, together with low accessibility and poor online connec-
tivity (Hossain et al., 2022b), might also have affected the possibility of
rural people becoming addicted to the internet.
The findings further suggested that living arrangements were a
strong determinant of IA among adults in Bangladesh. A pre-COVID-19
study indicated that living with family members reduced the possi-
bilities of PIU (Hassan et al., 2020). In this study, interestingly, it was
found that the risk of IA was lower among people living away
from families during the COVID-19 pandemic; this could be because
people living away from families might have been engaged in
Table 1. Distribution of variables of the respondents by internet addiction status.
Variables n (%) Internet Addiction Chi-Square pvalue
Addicted
(>60 scores) n (%)
Non addicted
(60 scores) n (%)
Overall 608 179 (29.4) 429 (70.6)
Age
<20 years 121 (19.9) 43 (34.7) 79 (65.3) 10.01 0.007
20–24 years 353 (58.1) 112 (31.7) 241 (68.3)
>24 years 134 (22.0) 25 (18.7) 109 (81.3)
Gender
Female 189 (31.1) 46 (24.3) 143 (75.7) 3.44 0.645
Male 419 (68.9) 133 (31.7) 286 (68.3)
Education qualification
Below Undergraduate 204 (33.6) 71 (34.8) 133 (65.2) 4.25 0.039
Undergraduate and above 404 (66.4) 108 (26.7) 296 (73.3)
Occupation
Student 479 (78.8) 145 (30.3) 334 (69.7) 0.75 0.387
Job/Others 129 (21.2) 34 (26.4) 95 (73.6)
Place of residence during COVID-19
Urban 401 (66.0) 132 (32.9) 269 (67.1) 6.85 0.009
Rural 207 (34.0) 47 (22.7) 160 (77.3)
Living arrangement during COVID-19
Living with family 482 (79.3) 157 (32.6) 325 (67.4) 10.98 0.001
Living without family 126 (20.7) 22 (17.5) 104 (82.5)
Smoking status during COVID-19
No 479 (78.8) 126 (26.3) 353 (73.7) 10.68 0.001
Yes 129 (21.2) 53 (41.1) 76 (58.9)
Physical activity status during COVID-19
No 27 (45.1) 115 (42.0) 159 (58.0) 37.69 <0.001
Yes 334 (54.9) 64 (19.2) 270 (80.8)
Sleep duration during COVID-19
>6 h 272 (44.7) 102 (37.5) 170 (62.5) 15.38 0.001
≤6 h 336 (55.3) 77 (22.6) 259 (77.1)
Device of internet use during COVID-19
Mobile/Tab 353 (58.1) 107 (30.3) 246 (69.7) 0.32 0.853
Computer/Laptop 24 (3.9) 7 (29.2) 17 (70.8)
Both 231 (38.0) 65 (28.1) 166 (71.9)
Internet use experience
<2 years 82 (13.5) 28 (34.1) 54 (65.9) 1.97 0.373
2–3 years 91 (15.0) 30 (33.0) 61 (67.0)
>3 years 435 (71.5) 121 (27.8) 314 (72.2)
Status of internet use during COVID-19
Decrease 26 (4.3) 2 (7.7) 24 (92.3) 15.78 0.001
Same 162 (26.6) 34 (21.0) 128 (79.0)
Increase 420 (69.1) 143 (34.0) 277 (66.0)
Daily internet use (Hour) during COVID-19
≤3 h 204 (33.6) 45 (22.1) 159 (77.9) 8.05 0.005
>3 h 404 (66.4) 134 (33.2) 270 (66.8)
P.R. Biswas et al. Heliyon 8 (2022) e09967
4
income-generating activities (IGAs) or alternative livelihood opportu-
nities (ALOs) to survive during the hardship of the pandemic (Ela
et al., 2021;Hossain et al., 2021). Some were frustrated over the un-
certainty of life and livelihood (Ela et al., 2021), and such a mental
state might have reduced the risk of IA among adults living away from
families in Bangladesh.
Tobacco smoking has been found to be an important indicator of IA.
This study revealed that smoking was positively associated with IA.
Studies conducted during COVID-19 suggested an increase in substance
abuse, including tobacco smoking, among working and nonworking
adults as a means of coping or self-medication when dealing with quar-
antine, leading to emotional disturbance and exhaustion (Gritsenko et al.,
2020;Hanafiet al., 2021). Generally, smokers suffer from different
psychological problems, and they are more likely to be addicted to the
internet due to attempts to relieve their mental stress through virtual
entertainment.
This study found that IA was significantly lower among adults
involved in regular physical activity. A Brazilian research has suggested
that when individuals spent more time on physical activity, including
walking, jogging, or running, to keep fit or stay healthy during the
COVID-19 pandemic, they experienced fewer mental health issues such
as anxiety and depression (Puccinelli et al., 2021), as they were
pre-occupied with the activity. Moreover, regular physical activity im-
proves self-control, which may reduce the risk of IA (Park et al., 2016).
The findings further suggested that the prevalence and risk of IA were
lower among adults who slept for less than or equal 6 hours per day. A
Table 2. Multiple logistic regression analysis of variables associated with internet addiction in Bangladesh.
Variables Coefficient βOdds ratio, Exp (β) 95% CI pvalue
Lower Upper
Age
<20 years
RC
1.00
20–24 years -0.12 0.89 0.50 1.58 0.694
>24 years -0.92 0.39 0.17 0.91 0.030
Gender
Female
RC
1.00
Male 0.39 1.48 0.94 2.32 0.088
Education qualification
Below Undergraduate
RC
1.00
Undergraduate and above -0.02 0.97 0.62 1.52 0.902
Occupation
Student
RC
1.00
Job/Others 0.45 1.56 0.85 2.89 0. 154
Place of residence during COVID-19
Urban
RC
1.00
Rural -0.68 0.51 0.32 0.81 0.004
Living arrangement during COVID-19
Living with family
RC
1.00
Living without family -0.79 0.45 0.26 0.79 0.005
Smoking status during COVID-19
No
RC
1.00
Yes 0.63 1.88 1.15 3.07 0.012
Physical activity status during COVID-19
No
RC
1.00
Yes -1.05 0.35 0.24 0.52 <0.001
Sleep duration during COVID-19
>6h
RC
1.00
≤6 h -0.47 0.63 0.42 0.93 0.020
Device of internet use during COVID-19
Mobile/Tab
RC
1.00
Computer/Laptop -0.37 0.69 0.24 1.96 0.485
Both -0.19 0.83 0.52 1.31 0.421
Internet use experience during COVID-19
<2 years
RC
1.00
2–3 years -0.31 0.74 0.38 1.45 0.374
>3 years -0.89 0.41 0.22 0.78 0.007
Status of internet use during COVID-19
Decrease
RC
1.00
Same 0.06 1.05 0.50 2.22 0.883
Increase 0.72 2.0 6 1.08 3.94 0.029
Daily internet use (Hour) during COVID-19
≤3h
RC
1.00
>3 h 0.34 1.39 0.85 2.30 0.186
Note:
RC.
Reference category.
P.R. Biswas et al. Heliyon 8 (2022) e09967
5
previous study on university students in Bangladesh documented a strong
association between mental health conditions with poor sleep quality
during the COVID-19 pandemic (Ahammed et al., 2021). Uncertainty
over academic and professional life (Cao et al., 2020;Ela et al., 2021)
together with engagement in IGAs or ALOs (Ela et al., 2021;Hossain
et al., 2021) to meet the demands for daily necessities (Halim et al.,
2022) might have affected the sleep quality and prevent the Bangladeshi
adults from becoming addicted to the internet.
Participating adults with internet use experience of more than two
years had a significantly lower risk of being internet addicted. Similar
findings appeared in a previous study conducted in Ethiopia (Zenebe
et al., 2021). The reason could be that long-time internet users may be
busy with online-based work (Hassan et al., 2020). Participants whose
internet use had increased during the COVID-19 pandemic were found to
have high IA. Social media use has increased during the COVID-19
pandemic (Hossain et al., 2020), people have also been using the
internet to pass time and watch different entertainment programs, which
may have led to internet addiction.
4.1. Strengths and limitation
This study focused on the prevalence of IA and its determinants
among Bangladeshi adults during the COVID-19 epidemic. The target
population was young adults from both urban and rural areas of
Bangladesh. Our study also included a high number of socioeconomic
and demographic variables; this is a characteristic of people-based
research in Bangladesh. The present research advances our understand-
ing of the issue under study and has practical implications. Some limi-
tations should be mentioned regarding the generalizability of the present
study’sfindings. The survey was performed online, as online surveys are
a popular and effective tool for a quick evaluation of a particular situation
such as the COVID-19 pandemic. The data was self-reported; therefore,
there was a risk of response-related bias. The selection biases might also
have influenced the outcomes. Moreover, the study did not cover a na-
tionally representative sample, as most of the participants were from the
southwestern region of Bangladesh. The cross-sectional nature of the
study might mean that it does not accurately explain the causal rela-
tionship between explanatory variables and internet addiction. The study
assessed the presence of internet addiction among people during a sud-
den emergency without considering their level of internet addiction in
pre-COVID-19 conditions. Despite selecting all factors influencing IA
among people in an emergency, there may have been some other con-
founding issues that remained unattended.
5. Conclusion
There is a high prevalence of IA among adults in Bangladesh,
especially since the start of the COVID-19 pandemic. IA was found to be
strongly linked to socioeconomic factors, such as age, place of residence,
and living arrangements, as well as behavioral factors, such as smoking
status, physical activity, sleep duration, use of the internet during the
pandemic, and duration of daily internet use. This type of study is
critical in countries like Bangladesh, where internet use is growing
faster than socio-economic development, and it becomes more necessary
during unanticipated situations such as the COVID-19 pandemic. The
findings of this study have substantiated the necessity and imple-
mentation of effective intervention programs. It may assist policymakers
in identifying excessive internet users and reducing their overuse of the
internet. Appropriate preventive measures, such as teaching students
and the public about safe internet use, and counseling those already
addicted to the internet, are recommended. More interventions should
strengthen self-control, build positive core self-evaluations, and opti-
mize social adjustment, especially during emergencies. Finally, to
properly assess IA in Bangladesh, more research is encouraged, partic-
ularly a nationally representative sample, in order to minimize non-
substance addiction.
Declarations
Author contribution statement
Poly Rani Biswas: Conceived and designed the experiments; Per-
formed the experiments; Analyzed and interpreted the data; Contributed
reagents, materials, analysis tools or data; Wrote the paper.
Benojir Ahammed: Conceived and designed the experiments;
Analyzed and interpreted the data; Contributed reagents, materials,
analysis tools or data; Wrote the paper.
Md. Shiafur Rahman; Byazid Mahin Nirob: Performed the experi-
ments; Contributed reagents, materials, analysis tools or data.
Md. Tanvir Hossain: Analyzed and interpreted the data; Wrote the
paper.
Funding statement
This research did not receive any specific grant from funding agencies
in the public, commercial, or not-for-profit sectors.
Data availability statement
Data will be made available on request.
Declaration of interest’s statement
The authors declare no conflict of interest.
Additional information
No additional information is available for this paper.
Acknowledgements
We appreciate all the participants as well as the anonymous
reviewers.
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