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Introduction
Ever since its introduction, social networking sites
(SNSs) have become a phenomenon that has taken
the world by storm, with its usage growing
exponentially over the years.1-3 Social networking sites
are defined as “Web-based services allowing individuals
to create a public or semi-public profile within a limited
system, which articulates a list of other similar users
whom they share a connection and interest with, and
at the same time view and traverse their list of
connections and those made by others within the
system”.1,4 Examples of current social networking
sites frequently used by people worldwide include
Facebook, Twitter, LinkedIn, Google+, YouTube,
Instagram, Pinterest, Tumblr, Reddit, and Flickr.
People of all ages use social networking sites, but
adolescents are the most avid users, with the
prevalence of social networking sites increasing over
the years.3,5 About 46.4% to 96.8% of the world
adolescents were found to have accessed or engaged
in social networking sites. However, these statistics
varied and may be underestimated.2,6-10 Various
theories, such as the Uses and Gratification (U & G)
theory, examined adolescents’ needs and motives
for social networking sites consumption. The
Prototype Willingness Model, which predicted the
adolescents’ willingness to engage in risky online
activities, and the planned behaviour theory, which
described the usage of social networking sites by
the adolescents as positive behaviour, have been
linked to the phenomenon of social networking sites
usage by the adolescents.2 Social networking sites’
usage is a double-edged sword, as their usage was
assistive from certain aspects but detrimental from
other aspects.
Addiction Among Adolescents to Social Networking Sites in
Malaysia: A Hierarchical Multiple Linear Regression Analysis
Wong Khung Ying, Md Mizanur Rahman, Andrew Kiyu
Faculty of Medicine and Health Sciences, Universiti Malaysia, Sarawak, Malaysia
Abstract
Background: Social networking sites (SNSs) have changed the ways that we interact with each other. The
use of social networking sites by adolescents is addictive, with numerous negative consequences. Various
factors influence social networking sites addiction among adolescents.
Objective: We aimed to determine the prevalence of gender-specific social networking sites addiction among
adolescents and the factors influence social networking sites addiction.
Methods: A quantitative, cross-sectional community-based research was conducted by face-to-face interviews
among adolescents in all 11 administrative divisions of Sarawak, Malaysia. The multistage cluster sampling
technique was followed, with an adolescent selected systematically from each household. An adapted and
validated questionnaire, which included 20 items of social networking sites addiction, was used to collect data.
We analysed 1344 adolescent’s data using IBM SPSS Version 22.0. A partial least square structural path with
mediation analysis was done using WarpPLS version 7.0.
Results: Three-quarters of the adolescents (76.2%) used social networking sites, but only two-fifths of them
(40.4%) were addicted, with 15% having moderate-severe addiction to social networking sites. The most
frequently used social networking sites was YouTube (77.9%), followed by Facebook (75.2%) and Instagram
(59.0%). Self-esteem had a negative correlation, while adolescent risk behaviours directly affected social
networking sites addiction (p<0.001). The most potent predictors for social networking sites addiction were
YouTube, Instagram, and Pinterest (p<0.05).
Conclusion: Tackling risk behaviours and enhancing adolescents’ self-esteem would reduce the tendency to
be addicted to social networking sites.
Keywords: Adolescents, Addiction, Social networking sites, Social media
DOI: https://doi.org/10.3329/bmrcb.v48i1.60655
Bangladesh Med Res Counc Bull 2022; 48: 10-20
RESEARCH PAPER
*Correspondence: Md Mizanur Rahman
Faculty of Medicine and Health Sciences, Universiti Malaysia
Sarawak, 94300 Kota, Samarahan, Sarawak, Malaysia.
Email: aniqm@hotmail.com
ORCID: 0000-0002-0706-2920
10
Adolescents rely heavily on social networking sites
and tend to spend hours using them, with a reported
average duration spent ranging from one to ten hours
per week. However, there was a possibility of under-
reporting 3,5. The long hours spent by adolescents on
social networking sites increased their tendency to
get addicted to social networking sites.4,11 About 50%
to 90% of adolescents who used social networking
sites were reported to be addicted to some extent,
with addiction ranging from mild to severe 4,11. Social
networking sites addiction is the “Pathological use of
social networking sites, exceeding regular social
networking sites usage, where typical behavioural
addiction signs and symptoms were portrayed,
interfering in various aspects of daily life, and resulting
in negative outcomes for the concurrent and future
development of the adolescents”.3,4,12
Various factors were associated with social networking
sites addiction among adolescents, such as their age
and gender.3,4,12 Moreover, self-esteem and risk
behaviours were predictors of adolescents’ tendencies
towards social networking sites usage and addiction
4,3,12. Previous studies had established that a negative
relationship existed between social networking sites
addiction and self-esteem, where adolescents with
lower self-esteem had a higher tendency of social
networking sites addiction.3,4,12 Also, adolescents
involved in risk behaviours were more likely to be
addicted to social networking sites.3,4,12
Naturally, as social networking sites usage continues
to grow, the risk of social networking sites addiction
also continues to increase. Thus, not only is it crucial
to determine the level of social networking sites
addiction, but also the potential predictors of social
networking sites addiction among adolescents. In this
context, the study aimed to test two hypotheses,
namely:
H1: Social networking sites addiction was positively
correlated with risk behaviours and negatively
correlated with the self-esteem of the adolescents;
and
H2: Self-esteem had a mediated effect on social
networking sites addiction among adolescents.
Materials and Methods
Setting, sampling and data collection:The study was
a quantitative, cross-sectional, community-based
research conducted among the general adolescent
population from all 11 administrative divisions in
Sarawak, Malaysia. Two districts were randomly
selected from each of the divisions. Then from a list
obtained from the district office or local council, a
specific number of housing areas, villages or
longhouses were randomly selected from each of those
districts. A maximum of ten adolescents (five males
and five females) were selected from each housing
area, villages or longhouses (figure 1). The inclusion
criteria were all Malaysian adolescents between the
ages of 10 to 19 years who lived in easily accessible
housing areas, villages or longhouses with internet
access in Sarawak. However, adolescents with mental
or cognitive impairment, or those who did not
understand English, Bahasa Malaysia, or Mandarin,
and those without a paired opposite gender from the
same housing area, village or longhouse were excluded
from the study. Data were then collected from those
adolescents through face-to-face interviews in English,
Bahasa Malaysia, or Mandarin, using pre-tested and
standardised interviewer-administered questionnaires.
The questions were adopted or adapted from validated
questionnaires after permission was obtained.3,4,12
Measurements
Risk behaviours:The adolescents’ risk behaviours
were measured using a 21-item question adapted from
the Youth Risk Behaviours Surveillance System
(YRBSS) by the Centres for Disease Control and
Prevention. 13 The most appropriate answer to all 21
items was selected from a four-point Likert’s scale,
with scores ranging from 0 to 3, which corresponded
with the adolescents’ level of involvement with the
mentioned risk behaviours. The lowest score of 0
indicated ‘Never’, followed by a score of 1 that indicated
‘Within the last month’, a score of 2 that indicated
‘During the last 1-6 months’, and a score of 3 that
indicated ‘Beyond the last 6 months’. From the
summative score that ranged from 0 to 63, a weighted
mean score was calculated and using equal
percentiles based on scanned cases.13 The level of
risk behaviours was classified into no low-medium risk
and high risk.
Self-esteem:The adolescents’ self-esteem level was
measured using a 10-item question, which was
adopted from the Rosenberg self-esteem scale.14 The
best answer to all ten items was selected from a four-
point Likert’s scale, with scores ranging from 1 to 4,
which corresponded with the adolescents’ level of
agreement with the mentioned item. The lowest score
of 1 indicated ‘Strongly disagree’, followed by a score
Addiction to social networking sites Ying WK et al
11
Bangladesh Medical Res Counc Bull 2022; 48: 10-20
Division
1
(P)
Two
Districts
(SRS)
Housing
(SRS)
10 ppl/
housing
(1:1;
M:F)
(SyRS
10 ppl/
housing
(1:1;
M:F)
(SyRS
10 ppl/
housing
(1:1;
M:F)
(SyRS
10 ppl/
housing
(1:1;
M:F)
(SyRS
10 ppl/
housing
(1:1;
M:F)
(SyRS
10 ppl/
housing
(1:1;
M:F)
(SyRS
10 ppl/
housing
(1:1;
M:F)
(SyRS
10 ppl/
housing
(1:1;
M:F)
(SyRS
10 ppl/
housing
(1:1;
M:F)
(SyRS
10 ppl/
housing
(1:1;
M:F)
(SyRS
10 ppl/
housing
(1:1;
M:F)
(SyRS
Housing
(SRS)
Housing
(SRS)
Housing
(SRS)
Housing
(SRS)
Housing
(SRS)
Housing
(SRS)
Housing
(SRS)
Housing
(SRS)
Housing
(SRS)
Housing
(SRS)
Two
Districts
(SRS)
Two
Districts
(SRS)
Two
Districts
(SRS)
Two
Districts
(SRS)
Two
Districts
(SRS)
Two
Districts
(SRS)
Two
Districts
(SRS)
Two
Districts
(SRS)
Two
Districts
(SRS)
Two
Districts
(SRS)
Division
2
(P)
Division
3
(P)
Division
4
(P)
Division
5
(P)
Region:
Sarawak
(P)
Division
6
(P)
Division
7
(P)
Division
8
(P)
Division
9
(P)
Division
10
(P)
Division
11
(P)
of 2 that indicated ‘Disagree’, a score of 3 that
indicated ‘Agree’, and a score of 4 that indicated
‘Strongly agree’. After reversing the five reverse
responses, a summative score was calculated,
ranging from 10 to 40. A weighted mean score was
calculated using equal percentiles based on scanned
cases. 13 The adolescents’ self-esteem level was
classified into low, moderate, high and very high.
Social networking sites usage:Adolescents were
required to select the types of social networking sites
used and the duration (minutes per day) spent on
each of those sites, and the number of times a day
that they used those sites.
Social networking sites addiction:The level of addiction
among adolescents to social networking sites was
measured using a 20-item questionnaire adapted from
the questionnaire by Young.15 The word ‘Internet’ in
the study by Young was changed to ‘social networking
sites’ for this study. The best answer to all 20 items
was selected from a six-point Likert scale, with scores
ranging from 0 to 5, which corresponded with the
adolescents’ level of agreement with the mentioned
item. The lowest score of 0 indicated ‘Never’, followed
by a score of 1 for ‘Rarely’, 2 for ‘Occasionally’, 3 for
‘Frequently’, 4 for ‘Often’, and 5 for ‘Always’. Total
scores were calculated across the items to produce
a summative score ranging from 0 to 100. Based on
Young’s Internet Addiction Test, the level of the
adolescents’ addiction to social networking sites was
classified into no addiction (£30), mild addiction
(31-49), moderate addiction (50-79), and severe
addiction (80-100).13 Cronbach’s Alpha internal
reliability coefficients provided information that the test
had internal reliability, and past studies found that the
test instrument had high construct validity.16,17
Data entry and analysis:All collected data were
checked and verified manually, with immediate
correction of any inconsistencies and inaccuracies.
The completed data were then coded and entered into
the computer using Statistical Package for Social
Science (SPSS) version 22.0.18 After all the data were
cross-checked for any unusual findings, outliers, and
missing values, multiple imputation techniques were
used to impute the missing values.19 A total of 1344
responses were used for analysis. Descriptive
statistics were presented as frequency and
percentage.
Further analysis in the form of hierarchical multiple
regression analysis was done in which the score of
social networking sites addiction was used as a
continuous dependent variable. Hierarchical
regression is a model-building technique in regression
model, which builds successive linear regression
models, with the addition of more predictors.20 Then,
a partial least square structural path analysis was
done using WarpPls version 7.0 to test the effect of
P = Purposive; SRS = Simple random sampling; SyRS = Systematic random sampling; M = Male; F = Female:
Figure 1: Flowchart of the sampling procedure
12 Bangladesh Medical Res Counc Bull 2022; 48: 10-20
Ying WK et al Addiction to social networking sites
adolescent risk behaviours and self-esteem on social
networking sites addiction.21 Finally, the direct and
indirect effects of adolescent risk behaviours and self-
esteem were interpreted using Cohen’s guideline.22
Ethical issues: The respondent information sheet was
provided in English, Bahasa Malaysia and Mandarin.
Written informed consent was then obtained from both
the parent or guardian and the adolescents if the
respondent was less than 18 years old or only if the
respondent was 18 or 19 years old. Participation was
voluntary, with the respondents having no obligation
to participate in the study. All participants were
assured of anonymity, privacy and data confidentiality.
Results
Characteristics of the adolescents: The mean (SD)
age of the male and female adolescents were
respectively 14.95 (2.5) years and 15.09 (2.7) years
(table I). Gender-stratified analysis of all the
adolescents’ characteristics showed no statistically
Table I: Socio-demographic characteristics of the adolescents
Characteristics Gender †p-value
Male Female Total
(n=672) (n=672) (n=1344)
n%n%n%
Age (years)
Mean (SD) (years) 14.95 (2.54) 15.09 (2.66) 15.02 (2.60) -
Ethnicity
Chinese 194 28.9 199 29.6 393 29.2 p>0.05
Malay 191 28.4 158 23.5 349 26.0
Iban 171 25.4 167 24.9 338 25.1
Bidayuh 40 6.0 54 8.0 94 7.0
Orang Ulu 42 6.3 45 6.7 87 6.5
Melanau 34 5.1 49 7.3 83 6.2
Religion
Christian 373 55.5 401 59.7 774 57.6 p>0.05
Islam 234 34.8 212 31.5 446 33.2
Buddhist 48 7.1 45 6.7 93 6.9
No religion 12 1.8 11 1.6 23 1.7
aOthers 50.7 30.4 80.6
Marital status
Single 663 98.7 661 98.4 1324 98.5 p>0.05
Married 91.3 81.2 17 1.3
aOthers 00.0 30.4 30.2
Occupation
Student 639 95.1 638 94.9 1277 95.0 p>0.05
Unemployed 91.3 10 1.5 19 1.4
Housewife 00.0 30.4 30.2
Employed 24 3.6 21 3.1 45 3.3
Highest level of education
No formal education 20.3 20.3 40.3 p>0.05
Kindergarten 10.1 20.3 30.2
Primary 150 22.3 140 20.8 290 21.6
Secondary 451 67.1 439 65.3 890 66.2
Pre-university 53 7.9 71 10.6 124 9.2
Vocational 81.2 14 2.1 22 1.6
Diploma 71.0 40.6 11 0.8
Average pocket money each day (MYR)
Mean (SD) (MYR) 7.25 (8.37) 7.38 (8.06) 7.31 (8.21) -
Median (MYR) 5.00 5.00 5.00
aEngaged, Divorced
†p-value reached from Chi-square test of independence
*p<0.05; **p<0.01; ***p<0.001
Addiction to social networking sites Ying WK et al
13
Bangladesh Medical Res Counc Bull 2022; 48: 10-20
significant differences between males and females
(p>0.05).
Social networking sites usage:More than three-
quarters of the adolescents (76.2%; n=1024),
comprising 74.4% of the males and 78% of the
females, used social networking sites (table II).
However, gender-wise, there was no statistically
significant differences in the use of social networking
sites (p>0.05). The social networking sites used most
by the adolescents was YouTube (77.9%), followed
by Facebook (75.2%) and Instagram (59.0%), while
the least frequently used social networking sites were
others for Weibo, Bebo, and Google+ (2.9%). Bivariate
analysis revealed that the proportion of social
networking sites usage among the male and female
adolescents was similar for all the different social
networking sites, except for Instagram (p<0.001;
Cramer’s V = 0.119). The mean (SD) duration that the
adolescents spent on social networking sites per day
were 298.93 (241.31) minutes, with a minimum of ten
minutes and a maximum of 960 minutes (16 hours).
On average, the adolescents spent the most extended
amount of time per day on YouTube with a mean(SD)
of 113.4 (118.5) minutes, followed by Facebook with
a mean(SD) of 84.6 (111.7) minutes and Instagram
with a mean (SD) of 61.8(90.7) minutes.
Social networking sites addiction: Only two-fifths of
the adolescents (40.4%) who used social networking
sites were addicted to social networking sites, with
15% having moderate-severe addiction to social
networking sites. Although male adolescents (44%)
were found to be more addicted to social networking
sites compared to their females counterparts (37%),
the gender differences was not statistically significant
(p>0.05) (figure 2).
Factors associated with social networking sites
addiction:Hierarchical multiple linear regression
analysis:A hierarchical multiple linear regression
analysis was done to determine the factors associated
with social networking sites addiction among
adolescents. Social networking sites addiction, which
was in the form of continuous data, was the dependent
variable. Gender was dummy-coded with male gender
as ‘1’ and female gender as ‘0’. Exploratory data
analysis was done to determine the potential outliers
and skewed data. Univariate and multivariate outliers
were determined using Mahalanobis distance.23 A total
of 347 data were removed due to outliers. There was
no potential multi-collinearity as variance inflation
factors (VIF) was less than three.24 Two variables,
namely age in years and gender were entered into
the model and was subsequently followed by other
variables such as self-esteem, risk behaviours,
Facebook, Twitter, YouTube, Instagram, Pinterest,
Reddit, Swarm, Tumblr, Snapchat, other social
networking sites, time spent on social networking sites
(minutes) and duration of using social networking sites
(days). In the first model, age and gender had no
potential impact on addiction to social networking sites
with adjusted R-square = 0.006 though ANOVA
Table II: Gender-stratified percentage distribution of types of social networking sites used
Social networking sites Gender †p-value
Male Female Total
(n=500) (n=524) (n=1024)
n%n%n%
YouTube 399 79.8 399 76.1 798 77.9 p>0.05
Facebook 386 77.2 384 73.3 770 75.2 p>0.05
Instagram 265 53.0 339 64.7 604 59.0 p<0.001
Twitter 107 21.4 120 22.9 227 22.2 p>0.05
Snapchat 45 9.0 82 15.6 127 12.4 p>0.05
Pinterest 48 9.6 46 8.8 94 9.2 p>0.05
Tumblr 21 4.2 22 4.2 43 4.2 p>0.05
Reddit 23 4.6 15 2.9 38 3.7 p>0.05
Swarm 19 3.8 12 2.3 31 3.0 p>0.05
Others (Weibo, Bebo, 18 3.6 12 2.3 30 2.9 p>0.05
Google+)
*p<0.05, **p<0.01; ***p<0.001;
†p-value reached from Chi-square test of independence
14 Bangladesh Medical Res Counc Bull 2022; 48: 10-20
Ying WK et al Addiction to social networking sites
showed a statistically significant model [F(df)=
3.173(2,674); p<0.05)]. However, after the inclusion
of other variables, the model significantly improved at
21.2% (p<0.001) with adjusted R-square = 0.202. The
ANOVA table of the second model was also
statistically significant [F(df)= 11.726(16,660);
p<0.001].
The analysis revealed that self-esteem, which was
negatively correlated with social networking sites
addiction (p<0.001), had the highest contribution
(20.8%) in the model, followed by risk behaviours
involvement (12.2% contribution), which was positively
correlated with social networking sites addiction
(p<0.001). The other related variables that contributed
to the model were social networking sites usage
(14.9% contribution, p<0.001), duration spent on
social networking sites per day (8% contribution,
p<0.05), YouTube (7.9% contribution, p<0.05),
Instagram (8.2% contribution, p<0.05) and Pinterest
(7.3% contribution, p<0.05). Otherwise, other
variables, such as Facebook, Twitter, Reddit, Swarm,
Tumblr, and Snapchat, had no potential effect on social
networking sites addiction (table III).
Figure 2: Gender-stratified level of social networking
sites addiction (n=1024)
56
27.4
14.4
2.2
63
24.4
11.5
1.1
0
10
20
30
40
50
60
70
No Mild Moderate Severe
Percentage
Male
Female
Table III: Factors affecting social networking sites addiction: Hierarchical multiple linear regression analysis
Model/Variables Unstandardized B Std. Standardized 95% CI for B Contribution
Error Beta LL UL to model
1(Constant) 18.824*** 5.120 8.770 28.877
Age (years) .556 .323 .066 -.078 1.190 .066
Gender 3.007 1.701 .068 -.332 6.347 .068
2(Constant) 39.672*** 6.717 26.482 52.861
Age (years) -.105 .336 -.012 -.765 .555 -.011
Gender 1.790 1.592 .040 -1.336 4.916 .039
Self-esteem -10.670*** 1.764 -.216 -14.134 -7.206 -.208
Risk behaviour .531*** .150 .129 .238 .825 .122
Facebook 1.626 1.071 .059 -.478 3.729 .052
Twitter .897 1.199 .028 -1.457 3.251 .026
YouTube 2.432* 1.060 .092 .351 4.514 .079
Instagram 2.451* 1.023 .096 .442 4.461 .082
Pinterest 3.901* 1.825 .084 .318 7.484 .073
Reddit -1.944 4.289 -.024 -10.365 6.477 -.016
Swarm -6.042 4.935 -.069 -15.732 3.648 -.042
Tumblr 2.876 3.223 .043 -3.452 9.204 .031
Snapchat -2.506 1.603 -.060 -5.653 .642 -.054
Other SNSs 4.149 2.901 .052 -1.548 9.846 .049
Time spent on SNSs (min) .010* .004 .117 .002 .018 .080
Duration of using SNSs (days) .004*** .001 .167 .002 .006 .149
*p<0.05, **p<0.01; ***p<0.001;
LL=Lower limit of 95% CI and UL=Upper limit of 95% CI
15
Bangladesh Medical Res Counc Bull 2022; 48: 10-20
Addiction to social networking sites Ying WK et al
Structural path and mediation analysis:To understand
the mediated effect of self-esteem, a mediation analysis
was done.21,25 Model fitting information revealed average
adjusted R2 = 0.119 (p<0.001) and average VIF = 1.041,
which indicated no potential multi-collinearity. The
Tenenhaus Goodness of Fit was 0.349, which was
acceptable (small ³0.1, medium ³0.25, large ³0.36).
The analysis revealed that social networking sites
addiction was negatively correlated with self-esteem
with small effect (b=-0.243; p<0.001; ES=0.069).
However, risk behaviours directly affect social networking
sites addiction (b=0.176; p<0.05; ES=0.040) with small
effect. Self-esteem was negatively correlated with risk
behaviours (b=-0.097; p<0.001; ES=0.009), but the
effect was very weak. Moreover, the analysis also
showed that the duration spent on social networking
sites per day and the total duration of social networking
sites usage (b=-0.185; p<0.001; ES=0.077) had a direct
effect on social networking sites addiction (b=-0.240;
p<0.001; ES=0.048) (table IV).
Analysis of the indirect and total effect of different
parameters indicated that the total effect of self-
esteem on social networking sites addiction was
statistically significant (p<0.001), but had a minimal
effect on risk behaviours (p>0.05). Risk behaviours
had a direct effect on social networking sites addiction
(p<0.001). The other two control variables, namely
duration spent on social networking sites per day and
the total duration of social networking sites usage
had a direct effect on social networking sites addiction
(p<0.001) (table V, figure 3). However, all the effect
sizes were very weak (less than 0.15).22
Table IV: Structural path analysis of social networking sites addiction
Hypothesis Parameters Coefficient SE ES Acceptance
H1SNSs addiction <-Risk behaviour 0.176*** 0.037 0.040 Accepted
H2SNSs addiction <- Self-esteem -0.243*** 0.038 0.069 Accepted
H3Risk behaviour <- Self-esteem -0.097*** 0.038 0.009 Accepted
Control variables
1SNSs addiction <- Duration of use 0.240*** 0.037 0.048 Accepted
of SNSs per day
2SNSs addiction <- Duration of use of SNSs 0.185** 0.038 0.077 Accepted
Table V: Indirect and total effect on social networking sites addiction
Parameters Indirect effect p-value ES Total effect p-value ES
SNSs addiction <- Self-esteem -0.017 0.265 0.005 -0.260 0.001 0.075ø
SNSs Addiction <- Risk behaviour - - - 0.176 0.001 0.040ø
Risk behaviour <- Self-esteem - - - -0.097 0.01 0.009ø
SNSs addiction <- Use of SNSs per day -0.240 0.001 0.077ø
SNSs addiction <- Duration of SNSs use - - - 0.185 0.001 0.048ø
*p<0.05, **p<0.01; ***p<0.001
ES= Effect size.
Ø=Small (0.02); øø=Medium (0.15); øøø=Large (0.35)
16 Bangladesh Medical Res Counc Bull 2022; 48: 10-20
Ying WK et al Addiction to social networking sites
Discussion
Adolescents’ social networking sites usage may be
explained by different theories, such as Uses and
Gratification (U&G), Prototype Willingness Model, and
planned behaviour.26-28 Different theories
demonstrated the various factors that affected social
networking sites usage and addiction among
adolescents. Thus, different studies reported different
prevalence of social networking sites usage among
the adolescents, where the prevalence ranged from
46.4% to 96.8%, with this study reporting a percentage
of 76.2%.28 However, although there was no significant
gender difference in social networking sites among
adolescents, female adolescents tend to use more
social networking sites compared to their male
counterparts.28
Various studies showed that the most frequently used
social networking sites was Facebook.28 However, in
this study, YouTube was the most frequently used
social networking sites, followed by Facebook and
Instagram, and this preference was also demonstrated
in another study among Malaysian adolescents.28
These different preferences of social networking sites
types demonstrated the personal preferences of
adolescents.
On average, the adolescents spent about 228 minutes
per day on social networking sites, which amounted
to about four hours per day or 27 hours per week.
Nevertheless, most adolescents spent between 30
minutes to two hours a day on social networking sites,
with more than one-fifth of the adolescents spending
more than two hours a day on social networking
sites.29,30 The different times spent on social
networking sites in other studies demonstrated the
adolescents’ subjective reporting on the amount of
time they spent using social networking sites. The
duration of time spent on social networking sites would
be more accurate if the adolescents counted the exact
time spent using timing counters.
Although Internet addiction had been the focus of
experts and researchers over the past two decades
with the 20-item Internet Addiction Test tool by Young
frequently used, internet addiction had not been
included in the official classification of mental illness
and disorder.31 Only Internet gaming disorder had been
classified as a psychiatric disorder in the International
Classification of Disease and Related Health Problems
(ICD-11), which would be implemented on 1 January
2022.31 However, among adolescents, who were the
most avid users of social networking sites, the issue
of social networking sites addiction was a more
pressing issue, which had only started to be mentioned
in recent years.3,5
About two-fifths of the adolescents were addicted to
social networking sites, within the range of prevalence
of social networking sites addiction among
adolescents reported, ranging from 1.6% to 90% in
other studies.29,30 The vast range in prevalence may
be attributed to the country and the population involved
in the research. Age was not associated with social
networking sites addiction among the adolescents,
which corresponded with the findings of some studies,
but contradicted with others that reported older
adolescents to more likely to be addicted to social
networking.29-31 Furthermore, although not significant,
male adolescents were more likely to be addicted to
social networking sites than female adolescents,
especially under the moderate-severe addiction
category.11,32 Also, adolescents who spent more time
using social networking sites were more likely to be
addicted to them.33,34
Among all the mentioned social networking sites,
YouTube, Instagram, and Pinterest were the most
potent predictors of social networking sites addiction.
YouTube was an essential part of adolescents’ lives,
where a high number of them used the social
networking site for a long period.8 At the same time,
Instagram and Pinterest had the most reciprocity with
YouTube, and thus the adolescents tend to spend a
long time using them.35 Naturally, the adolescents
who spent more time using social networking sites
were more likely to be addicted to them.35
Figure 3: Structural path analysis of social networking
sites addiction
S_esteem
(R)1i
Risk
(R)1i
Time
(R)1i
Addict
(R)1i
Duration
(R)1i
b=0.10
(P<.01) b=0.18
(P<.01)
b=0.24
(P<.01) b=0.18
(P<.01)
b=0.24
(P<.01)
R2=0.01
R2=0.23
17
Bangladesh Medical Res Counc Bull 2022; 48: 10-20
Addiction to social networking sites Ying WK et al
Self-esteem was inversely related to social networking
sites addiction. Higher self-esteem was a protective
factor for social networking sites addiction, while lower
self-esteem was a risk factor for social networking
sites addiction. 3,33,36-39 Risk behaviours were
positively related to social networking sites addiction.
The adolescents who were more involved in risk
behaviours were more likely to be addicted to social
networking sites.40
This study was generalisable to the whole of Sarawak,
given the adolescents’ diversity and the large sample
size involved. Baseline evidence was also provided
regarding the adolescents’ addiction to social
networking sites and the determining factors, such
as risk behaviours and self-esteem, which could be
used to plan and develop suitable policies to tackle
social networking sites addiction among adolescents.
However, the limitation of the study was the possibility
of response and recall bias, where data collection was
based on self-reports, with face-to-face interviews
involving adolescent-adult interactions. Although other
factors may affect social networking sites addiction,
such as family dysfunction and parental monitoring
and general psychiatric status, this study only took
into account a few factors. Moreover, this study was
done from the adolescent’s perspective, when it would
be worthwhile to get their parents’ perspective on
behavioural indicators. Furthermore, being a cross-
sectional study, this study could only guide the
possible factors determining social networking sites
addiction. This study was also conducted to screen
for the severity of social networking sites addiction,
where further assessment would be required to confirm
the presence of social networking sites addiction
among adolescents.
Conclusion
The study was to test the relationship between
Facebook, Instagram, Twitter, and Snapchat use by
adolescents and social networking sites addiction,
risk behaviours and self-esteem. Risk behaviours and
self-esteem were important predictors of social
networking sites addiction. Thus, by preventing
adolescents from being involved in risk behaviours and
enhancing their level of self-esteem through education
and involvement in motivational programes,
adolescents’ tendency to be addicted to social
networking sites would be reduced. Although further
research would be required to demonstrate the causal
relationship between the variables, the study’s findings
provided a basis for further studies.
Acknowledgements
The authors would like to express their gratitude to all
involved district offices, local councils, longhouse
chiefs and village heads for their permission to conduct
the research in their areas. The authors would also
like to thank those whose questionnaires were adopted
or adapted, as well as to all the adolescents who had
participated in the research.
Conflict of interest: The authors declared that there
is no conflicts of interest
Funding: Partially funded by Faculty of Medicine
and Health Sciences, Universiti Malaysia Sarawak
Ethical approval: Ethics Committee of Universiti
Malaysia Sarawak. [UNIMAS/NC-21.02/03-02
Jld.2 (64)]
Submitted: 16 August 2021
Final revision received: 10 March 2022
Accepted: 20 March 2022
Published: 01 April 2022
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