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STUDY OF DEPRESSION, ANXIETY, AND SOCIAL MEDIA ADDICTION AMONG UNDERGRADUATE STUDENTS

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  • Universitas Muhammadiyah Kalimantan Timur

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This paper studies the connection between social media addiction and mental disorder from the existing investigation among undergraduate students. A comprehensive document search was conducted by using six electronic databases, including PubMed, Scopus, ScienceDirect, Web of Science, JSTOR, ProQuest Education to identify articles published before November 21st, 2019. All collected papers focused on studying social media addiction and psychosis. Two reviewers individualistically evaluated the quality of the study by using the Joanna Briggs Institute’s approach. Five articles were filtered out through the screening process and included in the review. The high prevalence of social addiction among college students (9.7% ∼ 41%) has been clarified. The association between social media addiction and mental disorders is positive for student health. This article contributes to raising awareness and finding solutions to these risk problems. The study also confirms the connection between online shopping addiction and eating disorders among social addicts. We also discuss the causes and harms of social media addiction. © 2020, Journal of Management Information and Decision Sciences. All Rights Reserved
Content may be subject to copyright.
Journal of Management Information and Decision Sciences Volume 23, Issue 4, 2020
257 1532-5806-23-4-201
Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
STUDY OF DEPRESSION, ANXIETY, AND SOCIAL
MEDIA ADDICTION AMONG UNDERGRADUATE
STUDENTS
Tuan Hai Nguyen, Asia University; Bac Lieu University
Kuan-Han Lin, Asia University, Taiwan
Ferry Fadzlul Rahman, Asia University; Universitas Muhammadiyah
Kalimantan Timur
Jenho-Peter Ou, Asia University
Wing-Keung Wong, Asia University; China Medical University Hospital; The
Hang Seng University of Hong Kong
ABSTRACT
This paper studies the connection between social media addiction and mental disorder
from the existing investigation among undergraduate students. A comprehensive document search
was conducted by using six electronic databases, including PubMed, Scopus, ScienceDirect, Web
of Science, JSTOR, ProQuest Education to identify articles published before November 21st, 2019.
All collected papers focused on studying social media addiction and psychosis. Two reviewers
individualistically evaluated the quality of the study by using the Joanna Briggs Institute’s
approach. Five articles were filtered out through the screening process and included in the review.
The high prevalence of social addiction among college students (9.7% ~ 41%) has been clarified.
The association between social media addiction and mental disorders is positive for student health.
This article contributes to raising awareness and finding solutions to these risk problems. The
study also confirms the connection between online shopping addiction and eating disorders among
social addicts. We also discuss the causes and harms of social media addiction.
Keywords: Social Media Addiction, Mental Disorder, Undergraduate Student, Prisma Chart,
Systematic Analysis.
JEL. Classification: I1 Health, I12 Health Behavior, I23 Higher Education.
INTRODUCTION
Social media addiction (or problematic social media use) classified into DSM V is a
proposed form of psychological or behavioural dependence on social media platforms (Casale &
Banchi, 2020). Meanwhile, mental disorders (or mental illnesses) are conditions that affect your
thinking, feeling, mood, and behaviour (Medlineplus, 2020). It is hard for physicians to diagnose
the disease if the addict does not report his or her problem. In previous studies on social media
addiction, most studies focused on social media addiction used questionnaires/surveys to assess
this behavioural addiction without a clinical diagnosis. Young people and students considered to
be most vulnerable to problematic internet use (Ioannidis et al., 2018; Kuss et al., 2013; Kuss &
Lopez-Fernandez, 2016). A study in India showed that the rate of social media addiction was
36.9% of 1389 social media users who were Pre-University college students (Ramesh et al., 2018).
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Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
Furthermore, the problem of social media use in children and young people are often allied with
mental disorders symptoms, for example, anxiety and depression (Hoge et al., 2017). In the US,
approximately 25% of college students surveyed showed signs of depression when using Facebook
(Moreno et al., 2011). A survey in 2013 from American Psychological Association found that
psychological problems are increasing among college students with the ratio, such as anxiety
(41.6%), depression (36.4%), and relationship problems (35.8%) (American psychological
association, 2013).
When individuals practice their time appropriately for social media, it gives users a good
consequence. In some situations, social media can help improve mood and boost health promotion
(Hoge et al., 2017). During the time the whole world was fighting the coronavirus, social media’s
strength contributes to a significant part of Vietnam’s successful anti-COVID-19 epidemic (La et
al., 2020). When diagnosing Facebook addiction symptoms, clinicians can consider a person’s
relationship with parents or peers (Badenes-Ribera et al., 2019). The reason is that antidepressants
do not help much improve patients with anxiety and depression (Kelly et al., 2012). In contrast,
social media also increases the negative aspects of youth activities because of their popularity in
the activities of people today. The more time people spend on social media, the more likely they
are to suffer from depression ( Lin et al., 2016; Boers et al., 2019). Fear of missing out can reduce
the happiness of young people (Fabris et al., 2020).
Previous studies have inspected the association between social media addiction and mental
disorders. First of all, one article in 2014 shows the association between SNS and mental health
issues: depressive symptoms, changes in self-esteem, and Internet addiction (Pantic, 2014).
Another article also concluded that Facebook use is associated with six results: addiction, anxiety,
depression, body image, alcohol use, and other problems (Frost & Rickwood, 2017). Problematic
social media use among young Americans largely explains the connection between social media
use and depressive symptoms (Shensa et al., 2017). A meta-analysis of random effects has
confirmed a positive correlation between problematic Facebook use and psychological distress
(Marino et al., 2018). Another meta-analysis also confirmed the relation between Facebook’s
application and the depressive symptoms but on a small scale (Yoon et al., 2019). Finally, there is
a link between social media use and mental health issues (Keles et al., 2020). However, the studies
mentioned above do not focus on a specific age group, so the difference between this article and
previous assessments is that this study only focuses on college students.
In the age of information technology and the internet boom today, social media addiction
is very vulnerable, specifically for young people. This article chooses to analyze social media
addiction studies of college students aged 18-24. The first reason is those college students expected
to have better future incomes than young people working in the industry after completing high
school (Jerrim, 2015). The second reason is that the degree of social media addiction is increasing
among young men and women (Aparicio-Martínez et al., 2020). A study in the US found that
social media use is associated with an increase in depression (Lin et al., 2016).
Furthermore, while the COVID-19 pandemic is still complicated over the world,
governments recommend that people should stay home and only socialize when necessary. Hence,
people have favourable conditions to spend more time on social media. Founded on data from
Statista conducted in March 2020, the percentage of longer spending on social media (e.g.,
Facebook, Instagram, Twitter, etc.) in the world is 44%, China is 50%, the United States is 32%,
and Singapore is 39% (Statista, 2020). Therefore, this study aimed to systematically examine the
prevalence of social media addiction among college students and assess the association between
Journal of Management Information and Decision Sciences Volume 23, Issue 4, 2020
259 1532-5806-23-4-201
Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
social media addiction and mental disorders for undergraduate students. The next sections of this
paper are data and methodology, content analysis, results discussion, implications, and conclusion.
DATA AND METHODOLOGY
Data
The way to collect the data from this paper was from PRISMA’s guidelines, the Preferred
Reporting Items for Systematic Reviews and Meta-analyses (Moher et al., 2009). The advantage
of this method is to summarize and analyze previous studies’ details related to the research
objectives. The Prisma statement assists the authors to improve systematic assessments. The
authors need to examine 27 listed items (see appendix A) and develop a four-phase diagram to
process and refine relevant research papers (Moher et al., 2009).
Search Strategy
Six databases were systematically searched, including ProQuest Education (1986-2019),
PubMed (2011-2019), Scopus (Scopus (2011-2019), ScienceDirect (2009-2020), Web of Science
(2009-2019), and JSTOR (1981-2016). The date to collect the database is November 21st, 2019.
The listed search keywords are made based on instructions from the PICO framed research
question (N.Y.U. libraries, 2020; Schardt et al., 2007). In this paper, the authors narrow to
population and outcome. The population was college students or university students, while the
outcome was the association between social media addiction and mental disorder. The search terms
have been used to search for the research, and the authors use synonyms of the keywords.
Undergraduate students contain college students or university students, and social media addiction
comprises social networking addiction or Facebook addiction or Instagram addiction or Twitter
addiction. Mental disorders consist of mental disorders or intellectual disorders or psychological
disorders. The first process of finding documents in this article is on the PubMed website, see
appendix B for details. Each element was searched in turn on PubMed advanced search. The
keyword sequences in PubMed was identified in the search toolbar as ((((College students OR
university students))) AND ((Social networking addiction OR Facebook addiction OR Instagram
addiction OR Twitter addiction))) AND ((mental disorder OR intellectual disorder OR
psychological disorder)). After that, the search technique for the next database was performed with
the same procedure for other data. The paper was checking the related studies during the 1981-
2020 period. As a result, 1100 articles have been compiled and screened as the information in the
PRISMA flow chart, Figure 1.
Study Selection Criteria
The inclusion and exclusion criteria were used to screen articles that matched the research
objectives of this study. First, quantitative non-interventional study designs (cross-sectional
studies, cohort study, case-control study) and studies published in English were included. Besides,
studies published in peer review journals were also comprised. But studies with non-peer reviewed
journals, proceeding letters, editorials, conference abstracts, literature review, systematic review,
and experimental design were excluded. Second, the participants that were undergraduate students
aged 18-24 were encompassed. Graduate students or high school students were omitted. Third, the
outcome of interest was the association between social media addiction and mental disorders such
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260 1532-5806-23-4-201
Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
as depression or anxiety. Social media addiction has counted in social networking addiction or
Facebook addiction or Instagram addiction or Twitter addiction or WeChat addiction; mental
disorders have identified as depression or anxiety. Two reviewers independently reviewed all
papers based on the titles and abstracts of the studies identified in the literature search and selected
eligible documents for full-text review (Tuan, Ferry). The third reviewer consulted when needed
(Kuan-Han).
FIGURE 1
PRISMA FLOW CHART
Data Extraction and Synthesis
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Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
A reviewer (Tuan) extracted the information and cross-checked with a second independent
reviewer (Ferry) for each chose to study: publication year, country of research, study design,
sample size, gender, age, exposure measurement for social networking addiction, outcome
measurement for mental disorder and findings for the association and SNS addiction. The extracted
data were recorded in Excel 2016 spreadsheet. Any differences were resolved through discussion
between two reviewers and with the participation of a third reviewer (Kuan-Han).
Quality Assessment
The critical evaluation checklist established by the Joanna Briggs Institute (JBI) and
collaborators was used to evaluate each study’s quality, including the type of study design (The
Joanna Briggs Institute, 2017). JBI’s critical assessment checklist has eight questions for cross-
sectional research. Each answer item on the list was scored as 1 for “yes” and 0 for “no, not clear,
or not applicable.” Reviewers have to discuss any disagreement to get the final decisions.
Statistical Analysis
Data were analyzed with SPSS 25.0 software (I.B.M. Corp, Armonk, NY). The Kappa
statistics and percentage agreement were calculated to evaluate the agreement between the two
reviewers on research choice and quality assessment, with a kappa value of 0.8 or higher indicating
as a great deal (Giannantonio, 2008).
CONTENT ANALYSIS AND RESULTS
Study Selection
A total of 1100 articles are collected through six databases. After removing duplicate
articles and refining articles based on inclusion and exclusion criteria, five articles met the final
analysis selection. The process of screening the articles was in Table 2. The consensus between
the two independent reviewers for this research choice is excellent for both title and abstract
(Kappa = 0.865, percentage agreement = 99.1%) and full text (Kappa = 0.86, percentage agreement
= 93%). The quality of the selected article presented in Table 2. Consensus of 2 reviewers for
assessment of quality was excellent (Kappa = 0.8 percentage agreement = 94%).
Study Characteristics
The characteristics and results of the studies, including the association between social
media addiction and psychosis, are presented in Table 1. All included papers were written in
English and published since 2014 to 2019 and places of the study included China, Singapore, and
the US (Hormes et al., 2014; Tang & Koh, 2017; Montag et al., 2018; Liu & Ma, 2019; Xie &
Karan, 2019). All research methods in these studies are cross-sectional (Hormes et al., 2014; Liu
& Ma, 2019; Montag et al., 2018; Tang & Koh, 2017; Xie & Karan, 2019)
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Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and social media addiction among undergraduate students.
Journal of Management Information and Decision Sciences, 23(4), 257-276.
TABLE 1
SUMMARY OF INCLUDED STUDIES
No
Author, year
Country
Sample
size
Gender
Exposure
measurement
for social
networking
addiction
Outcome
measurement for
mental disorder
Findings
Association
Prevalence of
SNS
addiction
1
Montag et al.,
2018
China
61
34.4%
female;
65.6% male
WeChat
addiction scores
Self-report
questionnaires: trait
anxiety and
depressive
symptoms;
Higher tendencies towards
WeChat addiction were
associated with smaller gray
matter volumes of the subgenual
anterior cingulate cortex, a key
region for monitoring and
regulatory control in neural
networks underlying addictive
behaviors. Moreover, a higher
frequency of the paying function
was associated with smaller
nucleus acumen’s volumes.
Findings were robust after
controlling for levels of anxiety
and depression.
25 (41%)
2
Liu & Ma,
2019
China
463
74,3%
female,
25,7% male
Chinese Social
Media Addiction
Scale.
The Experience in
Close Relationships
Scale, the
Difficulties in
Emotion Regulation
Scale
Attachment anxiety positively
predicted SNS addiction and that
emotion regulation mediated this
link. These findings suggest that
individuals’ affective regulation
capability should be a target of
future interventions and
treatments
78 (16.8%)
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Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and social media addiction among undergraduate students.
Journal of Management Information and Decision Sciences, 23(4), 257-276.
3
Tang et al.,
2018
Singapore
1110
62.5%
females,
37.5% males
A modified
version of the 6-
item Bergen
Facebook
Addiction Scale
(BFAS) was used
to measure SNS
addiction.
Diagnostic and
Statistical Manual
of Mental Disorders
(DSM-5)
(American
Psychiatric
Association, 2013)
The comorbidity rates of SNS
addiction and affective disorder
were 21% for depression, 27.7%
for anxiety, and 26.1% for mania.
In general, females as compared
to males reported higher
comorbidity rates of SNS
addiction and affective disorder.
328 (29.5%)
4
Hormes et al.,
2014
USA
253
62.8%
female, male
37,2%
Young Internet
Addiction Test
Acceptance and
Action
Questionnaire-II,
White Bear
Suppression
Inventory and
Difficulties in
Emotion Regulation
Disordered online social
networking use was present in
9.7% [n = 23; 95% confidence
interval (5.9, 13.4)] of the sample
surveyed, and significantly and
positively associated with scores
on the Young Internet Addiction
Test (P < 0.001), greater
difficulties with emotion
regulation (P = 0.003) and
problem drinking (P = 0.03).
23 (9.7%)
5
Xie et al.,
2019
USA
526
59% Female,
41% male
Bergen Facebook
Addiction Scale
State-Trait Anxiety
Inventory (STAI;
Spielberger, 2010);
the six-item Short-
Form State Anxiety
Scale (Marteau &
Bekker, 1992)
Trait anxiety, Facebook intensity,
and broadcasting behavior on
Facebook positively predict
Facebook addiction and state
anxiety. Moreover, gender
interacts with trait anxiety, so
that the gender difference in
Facebook addiction is significant
only when trait anxiety is low.
N/A
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Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
TABLE 2
METHODOLOGICAL QUALITY OF INCLUDED STUDIES
Joanna Briggs Institute checklists
Hormes et
al., 2014
Liu & Ma,
2019
Montag et
al., 2018
Tang et al.,
2018
Xie, et al.,
2019
Cross-sectional studies
Were the criteria for inclusion in the sample clearly
defined?
1
1
1
1
1
Were the study subjects and the setting described in
detail?
1
1
1
1
1
Was the exposure measured in a valid and reliable
way?
1
1
1
1
1
Were objective, standard criteria used for
measurement of the condition?
1
1
1
1
1
Were confounding factors identified?
1
1
1
1
1
Were strategies to deal with confounding factors
stated?
1
1
1
1
1
Were the outcomes measured in a valid and reliable
way?
1
1
1
1
1
Was appropriate statistical analysis used?
1
1
1
1
1
Participants’ Characteristics
Five articles are selected out of 47 full-text articles assessed for eligibility. Besides, the
authors only choose undergraduate students, who aged from 18 to 24. The respondents were from
the US, China, and Singapore. The sample size was from 61 to 1,110 respondents, while the
number of females was higher than males, except for one study from Montag et al. (2018).
Prevalence and Measures of Social Media Addiction
Prevalence of social media addiction
The figures in Table 1 display that the prevalence of SNS addiction in Asia countries like
Singapore and China is greater than that of the US The high percentage of college students addicted
to social networking sites in Asia countries once again confirmed the validity of previous studies.
The figure is consistent with earlier studies that the prevalence of social media addiction among
Asian students than other continents ( Kuss & Griffiths, 2011; Andreassen et al., 2012; Tang &
Koh, 2017; Tang et al., 2018). In two studies in China, one identified 78 of the 463 students
surveyed were reported as social media addicts or 16.8% (Liu & Ma, 2019); Another study, 21 out
of 61 students addicted to WeChat social networking (or 41%) were announced (Montag et al.,
2018). A study in Singapore declared 328 out of 1110 (29.5%) of the students surveyed identified
Journal of Management Information and Decision Sciences Volume 23, Issue 4, 2020
265 1532-5806-23-4-201
Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
Facebook addiction (Tang & Koh, 2017). In two studies in the US, one study found that 23 out of
253 surveyed students (9.7%) addicted to social networks (Hormes et al., 2014); Another study
did not specify the prevalence of social media Facebook (Xie & Karan, 2019).
Measures of social media addiction
Previous studies have used numerous approaches to measure social media addiction. First
of all, the young internet addiction test encompasses 20 items for measuring symptoms associated
with excessive internet use, assessing salience and anticipation of use, unreasonable use, and lack
of control overuse and neglect of work and social life (Hormes et al., 2014). Difficulties in Emotion
Regulation Scale (DERS) comprises 36 items that are separated into six self-report measure of
increasing in emotion regulation (Hormes et al., 2014). Additionally, SNS addiction could coincide
with food addiction and shopping addiction (Tang & Koh, 2017). SNS addicts are meeting the
pressure to access the sites frequently due to the fear of missing out and keeping up with demands
on relationship maintenance, constant social comparison with others, relationship turbulence with
the public nature of conflict on the SNS, and frequent violation of privacy ( Kuss et al., 2013; Fox
& Moreland, 2015; Tang & Koh, 2017).
Moreover, social networking addiction can be anticipated based on the low gray matter
volumes in the ventral (subgenual) anterior cingulate volume (Montag et al., 2018). The nucleus
accumbens could estimate frequent usage (Montag et al., 2018). Furthermore, updating status and
sharing photos and videos predicts Facebook addiction actively, but wall activities such as “liking”
or commenting are not related to Facebook addiction (Xie & Karan, 2019). Finally, Facebook
addiction can be predicted based on two characteristics, such as gender and anxiety (Xie & Karan,
2019). For more specific, among the low level of trait anxiety, women had a higher level of
Facebook addiction than men (Xie & Karan, 2019). A high level of character anxiety can lead to
stress when users disconnected from SNS (Xie & Karan, 2019).
Measures of mental disorder
There were various outcome measures used for mental disorders in the selected studies.
The first measure is DERS (Hormes et al., 2014) that was a 36-item, six-factor self-report measure
of difficulties, assessing (1) awareness of emotional responses; (2) lack of clarity of emotional
responses; (3) non-acceptance of emotional responses; (4) limited access to emotion regulation
strategies perceived as useful; (5) difficulties controlling impulses when experiencing negative
emotions; and (6) difficulties engaging in goal-directed behaviours when experiencing negative
emotion. The second measure is ECR-SV (Liu & Ma, 2019), including a twelve-item test for
evaluating adult attachment. The scale comprised of two six-item subscales: anxiety and
avoidance. Each item rated on a 7-point Likert scale ranging from 1 = strongly disagree to 7 =
strongly agree. Another measure of depression, anxiety, and mania were DSM-5 (Tang & Koh,
2017). They were scoring at least 5 of the nine items on the depression scale during the same two-
week period for classifying depression. Scoring 3 (or more) of the six symptoms on the anxiety
scale was to sort anxiety. Scoring 3 (or more) of the seven traits in the mania scale has classified
mania. The six-item Short-Form State Anxiety Scale (Xie & Karan, 2019) was used to measure
state anxiety. Finally, the authors (Montag et al., 2018) aimed to characterize the addictive
potential of communication applications based on their measure for the brain.
The Association between Social Media Addiction and Mental Disorder
Journal of Management Information and Decision Sciences Volume 23, Issue 4, 2020
266 1532-5806-23-4-201
Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
The use of online social networking sites has caused many emotional regulatory issues
such as more experiential avoidance, lack of acceptance of emotional responses, limited access to
emotion regulation strategies, poor impulse control, and clever engaging in goal-directed
behaviours (Hormes et al., 2014). People with a higher level of trait anxiety are more likely to feel
anxious when separated from SNS, and gender difference does not exist with a high level of trait
anxiety (Xie & Karan, 2019). People who use Facebook more intensively are more addicted to
Facebook and report the senior level of state anxiety without Facebook (Xie & Karan, 2019).
Besides, emotional disorders partly mediated in the relationship between stress and social media
addiction (Liu & Ma, 2019). Attached anxiety has recognized as a predictor of SNS addiction, but
there is no relationship between avoidance attachment and SNS addiction (Liu & Ma, 2019).
Higher levels of self-reported addiction symptoms and more frequent practice (of the paying
service) were related to lower gray matter volumes in the ventral (subgenual) anterior cingulate
and the nucleus accumbens (Montag et al., 2018). In addition to this, structural alterations in the
frontostriatal-limbic circuitry characterize a common denominator across different categories of
digital addiction, including Internet Communication Disorder (Montag et al., 2018).
Selected articles confirmed the association between social media addiction and mental
disorder. One report confirmed SNS addiction predictions through attachment anxiety (Liu & Ma,
2019), and another article anticipated addiction to Facebook through trait anxiety, Facebook
intensity, and broadcasting behaviour (Xie & Karan, 2019). In statistical analysis, among the
students addicted to social networks, the proportion of food addiction is 3%, and shopping
addiction is 5% (Tang & Koh, 2017). Moreover, 9.7% of social media addicts had a positive
relationship with the young internet addiction test scores, difficulty regulating emotions, and
problematic drinking (Hormes et al., 2014).
FINDINGS AND IMPLICATIONS
The Findings
This study summarizes articles related to social media addiction and mental disorders
among college students systematically. To do so, a total of five articles have been compiled and
analyzed. The objectives of the study was to clarify that (1) The high prevalence of social addiction
among college students (9.7% ~ 41%) has been stated; (2) confirms positive relationship between
social media addiction and mental disorders by reviewing previous studies.
Theoretical Contributions
The paper contributes to the theory of mental disorders and social media addiction by
taking some effective preventive measures to understand the community better and our findings
are consistent with (Fusar-Poli et al., 2019). Our paper contributes to theories of online customer
behaviour, social media marketing (Chen & Lin, 2019; Vanhala et al., 2020), and contributes to
the theory of customers' need for uniqueness (Abosag et al., 2019) by determining the impact of
mental health and behavioural addiction of consumers on emotions, cognitions, entertainment,
online attitudes and purchase intentions in the online shopping behaviour models. Furthermore,
the paper has the potential to influence public relations implemented by any organization through
social media (Namisango & Kang, 2019). It also stimulates the idea that managers build an
organizational culture through social media (Ravasi & Schultz, 2006) in the context of
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Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
globalization and multicultural exchanges (Chu et al., 2020). Lastly, the paper also improves the
understanding of companies operating in the tourism sector to effectively launch tourism
marketing campaigns by considerate customer psychology and visitor activity on social media
(Zeng & Gerritsen, 2014).
The Practical Implications
Facebook is a useful tool to meet the lives of modern society because it supports Maslow's
needs-based hierarchy (Houghton et al., 2020). It meets the needs of Maslow's scale, such as safety,
belonging, self-esteem, social connection (Houghton et al., 2020). Although Facebook has been
criticized for its data and privacy policies, users continue to use the social network due to the
satisfaction of Facebook on life (Houghton et al., 2020). It is used to get rid of problems or manage
loneliness (Menon et al., 2014). Therefore, the most popular global social network today is
Facebook among many social networks worldwide (Clement, 2020). However, to lessen stress and
anxiety from graphic imagery and worrisome messages, individuals should control the amount of
time on the internet, particularly during the COVID-19 pandemic outbreak (Amsalem et al., 2020).
Academics and practitioners could apply our approach to study many aspects related to
social media behaviour. For example, the method can flexibly apply to the connection between the
exchange rate and the economy (Batai et al., 2017) and the relationship between capital structure
and profitability (Chang et al., 2019). Furthermore, it also assists analyzing online consumer
behavior (Raphaeli et al., 2017), new fashion trends from generation Y in e-commerce (Ladhari et
al., 2019), social media marketing in the Small and Medium Enterprises (Chatterjee & Kumar Kar,
2020). Meanwhile, extensions could include applying our approach to study education (Hau et al.,
2019; 2020), agriculture (Moslehpour et al., 2018), transportation (Thipwong et al., 2020a),
tourism (Thipwong et al., 2020b), and environment (Tran et al., 2019). Extensions could include
many other exciting issues, and readers may refer to (Chang et al., 2017) for more information.
The Cause And Severity Of The Association Between Social Media Addiction And Mental
Disorder
The causes
Four causes of social media overuse may be listed as follows (1) The increase in depression
symptoms have occurred in tandem with the rise of smartphones since 2007 (Twenge et al., 2017).
(2) Young people, especially Generation Z, spend less time connecting with friends, but they spend
more time connecting digital content. They quickly lose focus at work or study because they spend
a lot of time watching others’ lives in an age of information explosion. (3) Another theory of an
increase in depression is low self-esteem when they feel negative on SNS comparing to those who
are more beautiful, thinner, more famous, and wealthier (Primack et al., 2017). Thus, social media
users might become less emotionally satisfied, making them feel socially isolated (Primack et al.,
2017). (4) Studying pressure and increasing homework load may be the cause of mental problems
for students (Twenge et al., 2017), thereby promoting the matching of social media addiction and
psychiatric disorders.
The severity
Journal of Management Information and Decision Sciences Volume 23, Issue 4, 2020
268 1532-5806-23-4-201
Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
Depression symptoms and suicide rates have increased for young people since 2010,
especially dangerous for girls (Twenge et al., 2017). Screen time in using social networking
applications might have a more significant impact on the mental health of girls than boys (Twenge
et al., 2017). Depressive symptoms and suicidal outcomes from television viewing have decreased
since 2010, although television viewing correlated positively with depression symptoms and
suicidal outcomes (Twenge et al., 2017). The popularity of the internet, smartphones, social
networking sites, though part of modern life, has contributed to the rise of depressive and suicidal
symptoms in young people. Therefore, measures to prevent harm, such as depression or suicide
among young people, should be discussed and offered to all stakeholders.
Proposed Solutions
As for the solution to social media addiction’s problem, on the user’s side, everyone adjusts
his or her behaviour using social networks or social media. It is highly recommended to change
social networking users’ time to about 30 minutes per day to improve mental health and well-being
(Hunt et al., 2018). Control of social media usage time is primarily the user’s responsibility and
then the influence of relatives or friends. Therefore, self-awareness of how much time spent on
social networks needs to be the best plan to avoid addiction and positively affect users’ work.
Cognitive-behavioural therapy should consider as an effective intervention in the short-term for
behavioural addiction (Stevens et al., 2019). Instead of wasting time on social networking, there
are many activities for students to minimize the negative impacts of S.N.S. First, students should
increase face-to-face connections with friends with physical activities such as exercise or playing
sports, and so on. In strengthening family connection, one option for parents to manage their
children’s time at home by teaching them to do housework; another choice is sharing the important
information from students from watching television, reading books, or newspapers.
From the social media manufacturer and the government’s administration, legal documents
to support anti-social network addiction or social media need to be discussed and put into
implementation laws to protect users. A bill, the Social Media Addiction Reduction Technology
(SMART) from US Senator Josh Hawley (Mettler, 2019), is suggested to address social media
addiction’s negative issues. For the 18-24 age group of college students, parents can still strongly
influence these students’ consciousness and psychology. Many signs of social network addiction
were explained. The children may show signs of social media addiction, such as spending time on
social media, fear of losing connection with friends on social media, frequently posting
information online, and shopping addiction or eating disorders. When parents see those signs, they
should control the social media usage time of their children. Besides, they may coordinate with
the legislature by building and updating the laws for those who are social media addiction. Finally,
home-school coordination is a crucial factor in regulating student consciousness and behaviour.
CONCLUDING REMARKS
Compared with similar research (Frost & Rickwood, 2017; Keles et al., 2020; Marino et
al., 2018; Pantic, 2014; Shensa et al., 2017; Yoon et al., 2019), our findings are consistent with the
findings from some existing literature, including (1) Symptoms of depression and anxiety are
associated with excessive social media use. (2) People who have a passive lifestyle are at a higher
risk of depression. (3) Excessive social media usage time, over three hours, is a significant risk to
users' anxiety and depression. (4) Social comparison habits are likely to cause depression and
psychological disorders because users often feel lost when others share their good experiences. In
Journal of Management Information and Decision Sciences Volume 23, Issue 4, 2020
269 1532-5806-23-4-201
Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
contrast, the difference between this article and others is to focus on a specific age group
(undergraduate students aged 17 to 24), discuss the causes, severity, and proposed solutions to the
association among social media addiction, depression, and anxiety.
In contrast, compared with divergent research, some of our findings are contradict with
some findings from some existing literature. For example, social media use moderated had positive
relationships with job performance, job satisfaction, work engagement, and work-life conflict
(Chu, 2020). Internal social media is an effective way to increase employee engagement through
the level of perceived transparency of the organization and organizational identification (Men et
al., 2020). Besides, individuals can use social media to make appropriate connections to achieve
their fundamental goal orientation (Brinkman et al., 2020). Consequently, social media is the
driving force behind shopping and positive word-of-mouth commitment for customers (Ryu &
Park, 2020).
From this study, the authors recommend that people use social media for no more than
three hours a day to avoid the risk of social media addiction. Besides, people with mental disorders,
anxiety disorders, stress, depression need to strictly control the time spent using social media and
especially restrict the posting or discussion of issues that can cause mental impairment.
Furthermore, people in good health should create an excellent social environment, even in
cyberspace by offering useful information and do not spread negative comments or discussions on
social media. People who are vulnerable to mental illness should be supervised and shared from
family, friends, and relatives for negative issues stemming from social media. Moreover, when
developing regulations on the use of social networking sites, leaders should make specific
provisions towards building a positive communication culture of all members on the digital
technology platform. Finally, when treating patients with symptoms of psychosis and depression,
psychologists and psychiatrists should pay attention to the appearance of behavioural addiction,
including social media addiction.
During the COVID-19 pandemic, it was understandable that students will increase their
time spent by using social media at home. However, by doing so, it will increase the potential risk
of social network addiction, social anxiety, and depression in the era of digital technology boom
today, especially research has found out that there is a positive relationship between social media
addiction and mental disorders among college students. A popular measure of social media
addiction in recent years is the Bergen Facebook Addiction Scale as used in some research articles.
The article also points out the connection between online shopping addiction and eating disorders
among social addicts. On the other hand, the authors have listed signs of social media addiction so
individuals can control their social network usage. From this fact, this article contributes to raising
awareness and finding out solutions to solve the risk problems.
The study had some limitations that the outcomes should examine thoughtfully. The
primary limitation is the small number of qualified studies being screening from the existing
research papers. The paper examined only five articles to study the relationship between social
media addiction and mental disorder and focuses mainly on college students. Additionally, there
was a high risk of language bias because the authors only reviewed studies published in English
and reputable peer-reviewed journals. Other limitations include heterogeneity in study design,
methodology, sample size, and outcome measures that could be improved. Finally, including
articles studying in advanced and good developing countries with strong economies like the United
States, China, and Singapore could improve the results. Future research related to social media
addiction could include studying different levels of depression and anxiety. The theoretical
framework for social addiction should also be improved. Last, the connection between social
Journal of Management Information and Decision Sciences Volume 23, Issue 4, 2020
270 1532-5806-23-4-201
Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
media addiction and mental disorder should also be examined and be paid attention to the treatment
of related pathologies as well as follow-up studies.
ACKNOWLEDGEMENT
The fifth author would like to thank Robert B. Miller and Howard E. Thompson for their
continuous guidance and encouragement. This research has been supported by Asia University,
Bac Lieu University, Universitas Muhammadiyah Kalimantan Timur, China Medical University
Hospital, The Hang Seng University of Hong Kong, Research Grants Council (RGC) of Hong
Kong (project number 12500915), and Ministry of Science and Technology (MOST, Project
Numbers 106-2410-H-468-002 and 107-2410-H-468-002-MY3), Taiwan.
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APPENDIX A
Section/topic
#
Checklist item
TITLE
Title
1
Identify the report as a systematic review, meta-analysis, or
both.
ABSTRACT
Structured summary
2
Provide a structured summary including, as applicable:
background; objectives; data sources; study eligibility
criteria, participants, and interventions; study appraisal and
synthesis methods; results; limitations; conclusions and
implications of key findings; systematic review registration
number.
INTRODUCTION
Rationale
3
Describe the rationale for the review in the context of what
is already known.
Objectives
4
Provide an explicit statement of questions being addressed
with reference to participants, interventions, comparisons,
outcomes, and study design (PICOS).
METHODS
Protocol and registration
5
Indicate if a review protocol exists, if and where it can be
accessed (e.g., Web address), and, if available, provide
registration information including registration number.
Eligibility criteria
6
Specify study characteristics (e.g., PICOS, length of follow-
up) and report characteristics (e.g., years considered,
language, publication status) used as criteria for eligibility,
giving rationale.
Information sources
7
Describe all information sources (e.g., databases with dates
of coverage, contact with study authors to identify additional
studies) in the search and date last searched.
Journal of Management Information and Decision Sciences Volume 23, Issue 4, 2020
274 1532-5806-23-4-201
Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
Search
8
Present full electronic search strategy for at least one
database, including any limits used, such that it could be
repeated.
Study selection
9
State the process for selecting studies (i.e., screening,
eligibility, included in systematic review, and, if applicable,
included in the meta-analysis).
Data collection process
10
Describe method of data extraction from reports (e.g.,
piloted forms, independently, in duplicate) and any
processes for obtaining and confirming data from
investigators.
Data items
11
List and define all variables for which data were sought
(e.g., PICOS, funding sources) and any assumptions and
simplifications made.
Risk of bias in individual studies
12
Describe methods used for assessing risk of bias of
individual studies (including specification of whether this
was done at the study or outcome level), and how this
information is to be used in any data synthesis.
Summary measures
13
State the principal summary measures (e.g., risk ratio,
difference in means).
Synthesis of results
14
Describe the methods of handling data and combining
results of studies, if done, including measures of consistency
(e.g., I2) for each meta-analysis.
Risk of bias across studies
15
Specify any assessment of risk of bias that may affect the
cumulative evidence (e.g., publication bias, selective
reporting within studies).
Additional analyses
16
Describe methods of additional analyses (e.g., sensitivity or
subgroup analyses, meta-regression), if done, indicating
which were pre-specified.
RESULTS
Study selection
17
Give numbers of studies screened, assessed for eligibility,
and included in the review, with reasons for exclusions at
each stage, ideally with a flow diagram.
Study characteristics
18
For each study, present characteristics for which data were
extracted (e.g., study size, PICOS, follow-up period) and
provide the citations.
Risk of bias within studies
19
Present data on risk of bias of each study and, if available,
any outcome level assessment (see item 12).
Results of individual studies
20
For all outcomes considered (benefits or harms), present, for
each study: (a) simple summary data for each intervention
group (b) effect estimates and confidence intervals, ideally
with a forest plot.
Synthesis of results
21
Present results of each meta-analysis done, including
confidence intervals and measures of consistency.
Risk of bias across studies
22
Present results of any assessment of risk of bias across
studies (see Item 15).
Additional analysis
23
Give results of additional analyses, if done (e.g., sensitivity
or subgroup analyses, meta-regression [see Item 16]).
DISCUSSION
Summary of evidence
24
Summarize the main findings including the strength of
evidence for each main outcome; consider their relevance to
key groups (e.g., healthcare providers, users, and policy
makers).
Limitations
25
Discuss limitations at study and outcome level (e.g., risk of
bias), and at review-level (e.g., incomplete retrieval of
identified research, reporting bias).
Journal of Management Information and Decision Sciences Volume 23, Issue 4, 2020
275 1532-5806-23-4-201
Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
Conclusions
26
Provide a general interpretation of the results in the context
of other evidence, and implications for future research.
FUNDING
Funding
27
Describe sources of funding for the systematic review and
other support (e.g., supply of data); role of funders for the
systematic review.
APPENDIX B
The Procedure to Use Keywords in the Search Tools
The first process of finding documents in this article is used on the PubMed website. Each
element in the order in Table 1 will be searched in turn on PubMed advanced search, then all
documents will be aggregated in search engines with AND links. The authors search for related
articles in the PubMed advanced search tools step by step as follow:
Step 1: Visit web link https://www.ncbi.nlm.nih.gov/pubmed/advanced
Step 2: Copy each component in Table 1 into the advanced search section. The web page
interface will look when performing the same operation seen in Figure 2.
TABLE 1
THE KEYWORDS IN THE SEARCH TOOLS
No
Keywords in the search tools
Criteria
1
College students OR university students
People
2
Social networking addiction OR Facebook addiction OR Instagram addiction OR
Twitter addiction
Exposure
3
Mental disorder OR intellectual disorder OR psychological disorder
Outcome
4
All components
FIGURE
KEYWORD SEQUENCES IN PUBMED ADVANCED SEARCH BUILDER
Journal of Management Information and Decision Sciences Volume 23, Issue 4, 2020
276 1532-5806-23-4-201
Citation Information: Nguyen, T. H., Lin, K-H., Rahman, F. F., Ou, J-P., & Wong, W-K. (2020). Study of depression, anxiety, and
social media addiction among undergraduate students. Journal of Management Information and Decision Sciences, 23(4), 257-276.
Step 3: Pressing Search button and then the result will appear with the number of articles
related to the keyword. PubMed keyword sequences will be identified in the search toolbar as
((((College students OR university students))) AND ((Social networking addiction OR Facebook
addiction OR Instagram addiction OR Twitter addiction))) AND ((mental disorder OR intellectual
disorder OR psychological disorder)).
CORRESPONDING AUTHOR
Wing-Keung Wong
Chair Professor
Department of Finance and Big Data Research Center, Asia University, Taiwan
Department of Medical Research, China Medical University Hospital, Taiwan
Adjunct Professor
Department of Economics and Finance, The Hang Seng University of Hong Kong,
Hong Kong
Email: wong@asia.edu.tw
... It is becoming increasingly clear that social media addiction, which shares characteristics with other behavioral addictions, can have a detrimental impact on mental health. By modifying the brain's front striatal-limbic circuitry, social media use can contribute to the development of depression, stress, and anxiety (Nguyen et al., 2020;Zubair et al., 2023). A number of studies have similarly demonstrated a correlation between social media addiction and an increased likelihood of depression, anxiety, and depression among various demographic groups Nguyen et al., 2020;Şentürk et al., 2021). ...
... By modifying the brain's front striatal-limbic circuitry, social media use can contribute to the development of depression, stress, and anxiety (Nguyen et al., 2020;Zubair et al., 2023). A number of studies have similarly demonstrated a correlation between social media addiction and an increased likelihood of depression, anxiety, and depression among various demographic groups Nguyen et al., 2020;Şentürk et al., 2021). ...
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... Meskipun demikian, hal ini dapat mengarah pada pembenaran penggunaan ponsel pintar untuk belajar, tetapi pada akhirnya digunakan untuk media sosial, sehingga menyebabkan tingkat keterlibatan yang tinggi di media sosial dan berpotensi meningkatkan risiko masalah kesehatan mental (Nguyen et al., 2020). ...
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... Studies by Orsal et al. (2013) also found significant differences in daily internet usage time and frequency in terms of PIU severity. In relation to PSMU, it has been found that the level of PSMU increases with the increase in daily internet usage time (Nguyen et al., 2020;Aydin et al., 2021). Parlak Sert et al. (2023) conducted a study during the COVID-19 pandemic and found that as students' daily time spent on social media increased, the level of PSMU also increased. ...
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The ChatGPT (Chat Generative Pre-Trained Transformer) has been rapidly developing with a growing number of users. The potential for problematic use/dependence caused by the use of ChatGPT urgently needs to be explored. This study recruited a sample of 1040 Taiwanese adults to develop the Problematic ChatGPT use Scale (PCUS) and investigate the relationships between ChatGPT problematic use and related factors such as age, gender, demographic categories, usage time, user satisfaction rating, and depression. The results of exploratory and confirmatory factor analysis verified that the PCUS had good factorial/construct validity. Additionally, the PCUS showed high internal consistency and test-retest reliability. Among the factors related to the PCUS scores, usage time and depression showed a positive correlation with PCUS scores. Furthermore, male PCUS scores were significantly higher than female PCUS scores. The PCUS scores showed no significant relationship with age, demographic categories (undergraduate students, graduate students, and working professionals), and various satisfaction evaluations. Limitations and recommendations for future research were also discussed.
... As in the case of previous studies (e.g., Hussain & Griffiths, 2021;Keles et al., 2020), psychopathological symptoms were positively associated with SNS addiction (confirmation of Hypothesis 1). Those results correspond with the assumption that people with enhanced levels of depression and anxiety often engage in intensive SNS use to escape their negative emotional states (Malaeb et al., 2021;Nguyen et al., 2020). In the short-term perspective, they find some relief online (Shensa et al., 2020). ...
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Psychopathological symptoms, especially depression and anxiety, can contribute to the development of addictive tendencies offline and online. The present cross-national study aims to verify whether Fear of Missing Out (FoMO) and Preference for Online Social Interactions (POSI) could explain the relationship between psychopathological symptoms (i.e., depression and anxiety symptoms) and Social Networking Sites (SNS) addiction. We tested our hypothesis in two samples from Poland (N = 1163) and Germany (N = 781) using self-report measures of psychopathological symptoms, FoMO, POSI, and SNS addiction. In both countries, we found the same result pattern. Depression and anxiety symptoms were positively related to SNS addiction. Moreover, FoMO and POSI partially mediated the relationship between psychopathological symptoms and addictive SNS use. Notably, the relationship between psychopathological symptoms is significantly more robust via FoMO as it is an essential predictor of SNS addiction in both countries. Our findings show that ineffective emotional regulation, as well as maladaptive thoughts and beliefs about one’s Internet use among persons with psychopathological symptoms, might increase the risk for SNS addiction.
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Fear of missing out (FoMO) is known to be associated with a decrease in emotional well-being in adolescents. However, few studies have investigated the possible mediating factors between FoMO and emotional symptoms. In this study, we studied the relationship between FoMO and emotional symptoms in a sample of 472 Italian adolescents aged 11-19. In particular, the study investigated the possible mediating role of perceived stress associated with experiences of neglect and negative reactions by other social media users, and social media addiction. Self-report measures were used. Results show that FoMO directly and indirectly predicts emotional symptoms. Additionally, FoMO is associated with increased sensitivity to stress associated with experiences of neglect and negative reactions by online peers, and social media addiction. Sensitivity to stress associated with neglect (but not to negative reactions) by online peers is found to mediate the relationship between FoMO and social media addiction, which, in turn, mediates the relationship with emotional symptoms. In general, the study shows that FoMO is a factor in experiencing higher sensitivity to stress associated with neglect by online peers, which in turn my act as a trigger for social media addiction, and ultimately showing a negative impact on emotional well-being of adolescents. Limits and future directions for research are discussed.