Use of social networking sites (SNSs) and its repercussions on sleep quality, psychosocial behavior, academic performance and circadian rhythm of humans – a brief review

Abstract

Social networking sites (SNSs) confer countless benefits to mankind through increased communication and connection between and among millions of people on the globe. Do the detrimental effects of SNSs outweigh its benefits? We have tried to answer this question through reviewing the relevant literature on the repercussions of use of SNSs on sleep quality, psychosocial behavior, academic performance and circadian rhythm in humans. Literature on the subject underscores the adverse effects of SNSs usage on sleep resulting in poor sleep quality, delayed sleep onset, shortening of sleep length, excessive daytime sleepiness (EDS), insomnia, apnea and nightmare. The students addicted to social media suffer from psychiatric distress, anxiety, depression, low self-esteem, suicidal ideation, procrastination and poor academic attainment. There is, however, a paucity of literature on the effects of overuse of SNSs on the functioning of circadian clocks in humans. It emerged that the adolescents and young adults are the most vulnerable to the ill effects of excessive use of the SNSs. We recommend that more researches on the effects of SNSs on human health should be carried out and effective awareness campaigns should be launched to educate the people about the darker side of the excessive use of SNSs.

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Use of social networking sites (SNSs) and its
repercussions on sleep quality, psychosocial
behavior, academic performance and circadian
rhythm of humans – a brief review
Rakesh Kumar Swain & Atanu Kumar Pati
To cite this article: Rakesh Kumar Swain & Atanu Kumar Pati (2019): Use of social networking
sites (SNSs) and its repercussions on sleep quality, psychosocial behavior, academic
performance and circadian rhythm of humans – a brief review, Biological Rhythm Research, DOI:
10.1080/09291016.2019.1620487
To link to this article: https://doi.org/10.1080/09291016.2019.1620487
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REVIEW ARTICLE
Use of social networking sites (SNSs) and its repercussions
on sleep quality, psychosocial behavior, academic
performance and circadian rhythm of humans –a brief
review
Rakesh Kumar Swain
a
and Atanu Kumar Pati
a,b,c
a
School of Zoology, Gangadhar Meher University, Amruta Vihar, Sambalpur, India;
b
School of Studies in
Life Science, Pandit Ravishankar Shukla University, Raipur, India;
c
Center for Translational Chronobiology,
Pandit Ravishankar Shukla University, Raipur, India
ABSTRACT
Social networking sites (SNSs) confer countless benefits to man-
kind through increased communication and connection between
and among millions of people on the globe. Do the detrimental
effects of SNSs outweigh its benefits? We have tried to answer this
question through reviewing the relevant literature on the reper-
cussions of use of SNSs on sleep quality, psychosocial behavior,
academic performance and circadian rhythm in humans. Literature
on the subject underscores the adverse effects of SNSs usage on
sleep resulting in poor sleep quality, delayed sleep onset, short-
ening of sleep length, excessive daytime sleepiness (EDS), insom-
nia, apnea and nightmare. The students addicted to social media
suffer from psychiatric distress, anxiety, depression, low self-
esteem, suicidal ideation, procrastination and poor academic
attainment. There is, however, a paucity of literature on the effects
of overuse of SNSs on the functioning of circadian clocks in
humans. It emerged that the adolescents and young adults are
the most vulnerable to the ill effects of excessive use of the SNSs.
We recommend that more researches on the effects of SNSs on
human health should be carried out and effective awareness
campaigns should be launched to educate the people about the
darker side of the excessive use of SNSs.
ARTICLE HISTORY
Received 15 May 2019
Accepted 2 September 2019
KEYWORDS
Social networking sites;
sleep quality; academic
performance; circadian
rhythm; chronotype
1. Introduction
The Homo sapiens are innovators. They developed various tools and techniques for
themselves and also for the welfare of society. All tools and techniques are collectively
called as technology. The lifestyle of today’s man is technology dependent. The tech-
nologies play an important role in several sectors, such as industry, health care, educa-
tion, business, trade and day-to-day life of an individual. One of the technologies, the
“Internet”was developed just a few years back. It started playing a crucial role in human
life and at this moment it solves many of their problems. The smartphone is one of the
CONTACT Atanu Kumar Pati akpati19@gmail.com Gangadhar Meher University, Amruta Vihar, Sambalpur,
Odisha, India
BIOLOGICAL RHYTHM RESEARCH
https://doi.org/10.1080/09291016.2019.1620487
© 2019 Informa UK Limited, trading as Taylor & Francis Group

greatest inventions of the contemporary century. The people get instant access to the
Internet through these phones. One can have information on any subject and of any-
thing almost instantly using the smartphones.
There were about 4.4 billion active Internet users worldwide until April 2019 (Statista;
www.statista.com). China, India and the United States together have the maximum
number of Internet users. The Internet has penetrated deep into human life as
a source of information, trade and communication (Sahin 2018). That is why the 21st
century is also called as the “Era of the Internet”. The Internet facilitates people’s
participation in social networking sites (SNSs) and online trading sites. It has dramatically
changed the way of communication among the peoples (Sahin 2018).
The SNSs allow their registered members to interact with each other. The members
send and exchange messages, pictures and videos to others and among themselves.
Instant interaction is possible between any two individuals or among a group of
individuals located anywhere in the world (Ryan et al. 2014; Vashishtha et al. 2017).
These SNSs include Facebook, YouTube, WhatsApp, Facebook Messenger, WeChat,
Instagram, QQ, QZone, Douyin/Tik Tok, Sina Weibo, Reddit, Twitter, Douban, LinkedIn,
Baidu Tieba, Skype, Snapchat, Viber, Pinterest, Discord and so on. Figure 1 depicts the
top 12 social media as of April 2019. Of those, the Facebook is the most widely used SNS;
it has about 2.2 billion monthly active users till this time (Figure 2;https://dustn.tv/
social-media-statistics/). In 2010, there were 0.97 billion SNSs users. This number is
expected to rise to 3.02 billion in 2021 (www.statista.com). This amounts to almost 211-
fold increase in the number of SNSs users a little over a decade. India has the maximum
number of FB users in the world; the number of Indian users touched 260 million mark
Figure 1. The statistics cards of 12 top social media (Reproduced with permission from https://dustn.
tv/social-media-statistics/).
2R.KUMARSWAINANDA.K.PATI

as of April 2019 (Figure 3;www.statista.com). In another estimates, India is likely to have
627 million Internet users by the end of 2019 (Kantar IMRB ICUBE report - Internet in
India 2019).
Smart features, attractive backgrounds or themes, symbols and functional buttons on
SNSs, such as in LINE, WhatsApp and others attract the young and adolescents to spend
more time on playing games, chatting and messaging activities (Luke and Evelina 2017).
0
0.5
1
1.5
2
2.5
Monthly Active Users (in Billion)
Figure 2. Monthly active users (expressed in billion) in top 10 social media (based on the statistics
cards shown in Figure 1).
Figure 3. Leading countries apropos number of Facebook users as of April 2019 (in millions). Open
source; downloaded from https://www.statista.com/on 12 May 2019.
BIOLOGICAL RHYTHM RESEARCH 3

These social networking apps enable users to share information, images, videos, photos,
ideas and greetings. The users can also make voice and video calls. They can create
groups consisting of friends and like-minded people and communicate among the
members of the group. Nowadays, it is observed that most of the young adults are
using SNSs without any inhibition as these sites provide a platform where they can
connect to their peers without adult surveillance (Livingstone 2008). With the help of
smartphones and portable devices, most of the students stay online throughout day and
night due to the ubiquity of Wi-Fi and 4G technology (Rosen et al. 2013; Leep et al. 2015;
Terry 2015). These young pupils are highly skilled in using any form of social media and
technical media; one can say that they are multitaskers, social networkers and they are
the first to rush into any new technology (Rosen et al. 2010).
Excessive use of social media makes the users addicted to the Internet (Kuss and Ve
Griffiths 2012). Sometimes the users of the SNSs due to their excessive indulgence in
Internet browsing forget to discharge their work and social responsibilities. Addicted
individuals become covertly restless if they do not get access to the SNSs. In recent
times, social media addiction has become a very problematic issue among teens and
adolescents.
However, it has also been argued that moderate social media usage alleviate stress,
loneliness or depression in an individual. But, excessive use of the SNSs may create
problems and is likely to exacerbate unnecessary mental states in an individual (Xu and
Tan 2012). The social media use may incite aggression, personality disorder, an unwho-
lesome diet, early sexuality, and tobacco/alcohol abuse in the young populace (Brown
and Bobkowski 2011).
Humans are basically sociable. The extent of socialization may vary. Most of the
humans prefer not to stay in isolation. Humans always have the desire to stay
connected and networked with others. In the advent of the Internet, the people
got an excellent opportunity to become socially active through SNSs. There are
numerous SNSs platforms that people use to make new relationships. In these SNSs
platforms, there is no need for a personal handshake or face-to-face meeting. The
SNSs have grown in numbers by leaps and bounds (https://makeawebsitehub.com/
social-media-sites/). The negative aspects of SNSs cannot be ignored that encourage
negative behavior in teens, such as an increase in procrastination and a rise in drugs/
alcohol abuse (Sahill 2011).
Health organizations nowadays prefer social media as the best platform to com-
municate, share information regarding health and educate people about health-
related issues (Moreno 2013; Valle et al. 2013; Menon et al. 2014;Riceetal.2014;
Laranjo et al. 2015). The SNSs provide a platform for many adolescents where they
express their feelings, and they like/dislike what they post on social media. Through
SNSs, they express their views to known and unknown recipients, and in addition,
they get the feedback which stimulates them to be engaged more and more in the
social media.
It appears that SNSs confer countless benefits to mankind through increased com-
munication and connection between and among millions of people on the globe. Do
the detrimental effects of SNSs outweigh its benefits? We have tried to answer this
question through reviewing the relevant literature on the repercussions of use of SNSs
4R.KUMARSWAINANDA.K.PATI

Table 1. Literature on the relationship between use of social networking sites (SNSs) and sleep quality, psychosocial variables, academic performance and
circadian rhythm.
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Sleep quality
Facebook addiction
and depression
300 (184 M,
116 F)
Students BFAS and PHQ9 Bangladesh 39.7% had FA, less physical activity,
sleep problems and showed
depression symptoms.
Al Mamun and
Griffiths 2019
Impact of SNS on sleep
quality
286 (182 M,
104 F)
Average:
22.1 ± 1.6
y
Medical
students
PSQI and Questionnaire Saudi Arabia Females used WhatsApp and
Twitter at a significantly higher
rate than males and had poor
sleep quality.
Asiri et al. 2018
FB use and sleep
quality
21 F 18–23 y UG students PSQI The UK Light emitted from I-pad before
sleep had a significant impact on
sleep quality of subjects.
Bowler and
Bourke 2018
WhatsApp use and
sleep disturbances
306 >30 y Doctors and
nurses
PSS-10, WhatsApp
Usage Characteristics
Questionnaire
Malaysia Compared to males, female workers
showed higher excessive day
time sleepiness disorder and
poor sleep quality.
Ganasegeran et al.
2017
Media exposure and
health related
quality of life
300 (150 M,
150 F)
18–22 y Students PSQI and SF-36v2 Pakistan Found actively engaged in
watching TV, using FB, other
media at late night. They
exhibited symptoms, like
getting day time sleepiness, and
sleeping late in light. Aging, poor
sleep quality and media
exposure were found to be
significant predictors of sleep
disturbances.
Muazzam and
Ahmad 2017
Pattern of sleep and
sleep hygiene
353 (218 M,
135 F)
15.89 ± 1.93
y
Students BEARS Nigeria 42.8% adolescents engaged in
social media and used it till ˂1
h before bedtime. Watching TV,
playing video games and using
social media induced
disturbances in their sleep habit.
They reported suboptimal sleep.
Peter et al. 2017
(Continued)
BIOLOGICAL RHYTHM RESEARCH 5

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Internet use and its
relationship with
sleep disorder and
excessive day time
sleepiness
727 (53% M,
47% F)
13 ± 0.9 y 7th- and 8th-
grade
students
IAT-Scale Portugal Students addicted to Internet
showed sleep disorder, mild
insomnia, excessive day time
sleepiness and circadian rhythm
desynchronization.
Ferreira et al. 2017
WhatsApp addiction
personality disorder
01 A lady (house
wife)
Psychological test and
Counseling
India The subject suffered from bipolar
disorder, aggressiveness and
sleep disturbance.
Faye et al. 2016
Internet use at work
place
250 (70% M,
30% F)
30.4 y Employees Back ground data sheet India Employee spent 1.55 h in SNSs
surfing during work place. 42%
acknowledged that their work
postponed due to consumption
of most of their time in Internet
activity. 64% reported that their
work efficiency affected due to
nonwork-related Internet surfing.
Reported 1.6-h-delayed sleep at
night.
Shrivastava et al.
2016
An association
between social
media use and sleep
disturbance
1788
(49.7% M,
50.3% F)
19–32 y Young adults Pew Internet Research
Questionnaire,
PROMIS
The USA Authors reported social media
addiction leading to sleep
disorders.
Levenson et al.
2016
The impact of
technology on
adolescence sleep
259 13–21 y Adolescents ESS The USA Technology produced impact on
night time sleep and daytime
dysfunction among adolescence.
Johansson et al.
2016
Prebedtime behaviors
and Actigraphy
assessed sleep
146 16.2 ± 1.0 y Students Actigraphy, PBBQ and
MEQ
Australia Playing video games and online
SNS use led to shorter sleep.
Harbard et al.
2016
Monitoring the life
style and behavior
1654
(46.7% M,
53.3% F)
13–20 y Students from
8th to 12th
grade
Self-questionnaire Elbasan, central
Albania
FB users played violent online
videogames, and used cold
weapons, stayed more time at
bar and stayed awake till late.
Cela et al. 2014
(Continued)
6R.KUMARSWAINANDA.K.PATI

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Facebook addiction
among university
postgraduate
students
9 (6 M, 3 F) 25–30 y Postgraduates
students of
Universiti
Putra
Semistructured
interview
Malaysia FB addicts experienced disturbed
daily routine. They avoided social
relationship, and ignored offline
responsibilities, and suffered
from sleep disorders.
Zaremohzzabieh
et al. 2014
Link between
Facebook
dependence and
poor sleep quality
418 respondents
(96 M, 322 F)
Average: 20.1 y Undergraduate
students
PSQI, Questionnaire of Internet
Addiction
Peru
Subjects addicted to
Facebook use
reported disturbed
sleep, and daytime
dysfunction.
Wolniczak
et al. 2013
Internet and social
media usage and
the QoL among HD
patients
134 HD
patients
(73 M, 61
F)
53 ± 13.4 y HD patients of
the state
hospital
Short Form of Medical
Outcomes Study (SF-
36), BDI, SMMSE,
PSQI
Konya, Turkey Most of the patients had Facebook
account. SNS produced
a beneficial effect on their sleep
quality. They had less depression
and better cognitive function.
Afsar 2013
Sleep patterns and
electronic media
470 14 ± 0.8 y SSHS, EMFQ Israel Exhibited late bed times, short
sleep duration and fatigue due
to electronic media usage
Shochat et al.
2010
Internet overuse and
EDS
2336
(1343 M,
993 F)
16.7 ± 1.0 y Students YIAT, ESS South Korea Most of the subjects suffered from
insomnia, nightmare, apnea and
reported EDS due to IA
Choi et al. 2009
Relationship of sleep
with television/
gaming/social
media
2546
(54.2% M)
Students Self-administered
questionnaire
Belgium Spent considerable time on
television/surfing Internet and
had less sleep on weekdays and
felt higher level of tiredness.
Den Bulck 2004
Psychosocial behavior
Negative aspects of FB
use
27,867
(59.22% F)
23.94 y Mixed BFAS, IAT and
Problematic
Facebook Use Scale
Western countries
and Africa
The authors noticed a positive
association between time spent
online and problematic FB use.
The latter had a negative
association with self-esteem.
Marino et al.
2018a
(Continued)
BIOLOGICAL RHYTHM RESEARCH 7

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
The reliability and
validity study of
SMAS-SF
998 (432 M,
566F)
18–58 y Secondary
school, high
school and
university
students
SMAS-SF Turkey Social networking sites deeply
affected the daily lives of
students.
Sahin 2018
SNS addiction and
psychosomatic
problems
511 (64.6%
F)
20–35 y English
speaking
social
networking
site users
Bergen Social Media
Addiction Scale,
Problematic Internet
Use Scale-2, Chinese
Maladaptive
Cognition Scale and
DERS-SF
Australia, Greece and
the UK
Participants exhibited SNS
addiction and showed FoMo,
maladaptivecognition,
psychiatric distress and POSI.
Pontes et al. 2018
Problematic Facebook
use with
psychological
distress and well
being
13,929 16–32 y Mixed FIQ and BFAS Western countries,
two Asian countries
and two African
countries.
The problematic FB use was found
to be associated with
psychological distress, anxiety
and depression.
Marino et al.
2018b
Effects of smartphone
usage
1824 15 y Middle school
students
Smartphone Addiction
Scale
South Korea Smartphone users were prone to
anger, depression and lethargic
behavior. This was attributed to
excessive SNSs use.
Cha and Seo 2018
The big five of
personality and
Instagram addiction
752 18–24 y University
students
IAS, BFI and Self-Liking
Scale
Turkey Instagram addiction resulted in
lower agreeableness and
conscientiousness through self-
liking.
Kircaburun and
Griffiths 2018
Social media and
recession
132 (41 M, 91
F)
20.44 y UG students Self-made 12-item
questionnaire
Involvement in PSMU was found to
be positively associated with
depressed mood, attention
deficit, loneliness, fatigue and
feeling inferior.
Aalbers et al. 2018
Relationship of social
media with
addictive behavior,
suicidal ideation and
depression
374 (M
41.4%,
F 58.6%)
20.01 y Students Social Network
Addiction
Questionnaire, CES-
D, Positive and
Negative Suicidal
Inventory
Mexico Students showed addictive
behavior toward SNS use and
that led to depression and
suicidal ideation. 36.1% subjects
had suicidal thoughts.
Jasso-Medrano
and López-
Rosales 2018
(Continued)
8R.KUMARSWAINANDA.K.PATI

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
SNS and mental
disorders
200
(51.0% M,
49.0% F)
21.6 y Medical
students
STAI, BDI and
Structured
Questionnaire
India 80% respondents spent ≥4hin
SNSs per day. 24% students
experienced depression and
68.5% felt anxiety. Woke up early
and went to bed late night to
spend more time on SNSs.
Barman et al. 2018
Social media behavior
and its relationship
with major
depressive disorder
504
(11.4% M,
82.1% F)
20.4 y UG students Social Media Intensity
Scale, BFAS, PHQ-9
Texas Social media addiction and social
comparison through social media
led to major depressive disorder.
But social interaction by social
media had reduced MDD.
Robinson et al.
2019
Social media and
depression
212 (116 M,
96 F)
18–35 y Students Enrique Echeburua
Questionnaire and
BDI
Peru Excessive use of SNS, like
Instagram, Twitter led to
depression. 62.5% Twitter users
had depression.
Jeri-Yabar et al.
2018
SNSs addiction and
psychological well
being
3945 12–15 y Secondary
school
students
CIUS, UCLA-10 item
Loneliness Scale,
SLSS, Rosenberg’s
Self-esteem Scale
The Netherlands The school students, who spent
more time online, exhibited
depressive mood, anxiety,
negative self-esteem, and low life
satisfaction.
van Rooij et al.
2017
WhatsApp use and its
relationship with
personality and
anxiety
272 12–17 y Mixed Questionnaire of
Anxiety (STAIC),
Questionnaire of
Personality (TIPI),
Questionnaire of
Problematic
WhatsApp (CERW,
CERM)
Spain Both males and females suffered
from anxiety due to WhatsApp
usage.
Tresáncoras et al.
2017
Behavior of WhatsApp
users
150 UG students BFAS, WhatsApp Use
Pattern
Questionnaire
India WA-dependent students exhibited
WA addiction in all dimensions,
such as tolerance, salience,
withdrawal, mood modification,
relapse and conflict.
Sampath et al.
2017
(Continued)
BIOLOGICAL RHYTHM RESEARCH 9

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Pitfalls of SNSs use 5961
(2931 M,
3030 F)
15–22 y 9th- and 10th-
grade
students
BSMAS, CES-D, RSES-HU
and
Sociodemographics
Questionnaire
Hungary Students addicted to social media
showed reduced self-esteem and
higher level of depression.
Banyai et al. 2017
Excessive use of
mobile phone,
Insomnia and
depression
295 (173 M,
122 F)
15–19 y Students Athene Insomnia Scale
and CES-D
Japan Mobile phone extreme usage led to
sleep interruption and insomnia.
Usually surfing social media and
engagement with online chats
led to depression.
Tamura et al. 2017
Social media use and
mental health
226 (55 M,
51 F and 7
unreported) 14–17 y Adolescents and
parents
DSM Checklist, FoMo Survey, UCLA
Loneliness Scale and Social
Media Survey Parent Version
The USA
Higher social media
uses led to higher
FoMo, anxiety,
depression and
loneliness
Barry et al.
2017
Role of SNS and its
association with
emotional
functioning
440 11–19 y adolescent
20–29 y
adults
211 adolescents, 229
young adults
PSS, BAI and BDI-II Iran Twitter users
showed anxiety,
stress and
depression.
Prevalence of
anxiety was
more among
females.
Khodarahimi and Fathi
2017
FoMo and Internet use
expectancies and
symptoms of ICD
270 (80 M,
190 F)
17–39 y 153 from
Germany,
117 from
Spain
s-IAT-ICD, FoMo Scale
and IUES
Germany and Spain Psychopathological disorder
predicted fear of missing out
(FoMo).
Wegmann et al.
2017
Use of Twitter and
other social media
in the detection of
opioid addiction
2312 twitter
users
Teenagers,
young
people
Auto DOA, Web
Crawling tool
The USA Auto DOA effectively detected
opioid addiction. Authors
reported 1132 addicts.
Fan et al. 2017
(Continued)
10 R.KUMARSWAINANDA.K.PATI

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Problematic social
media use and
depressive
symptoms
1749
(49.9% M,
50.1% F)
19–32 y Mixed PROMIS-S, BFAS The United States Subjects developed depressive
symptoms due to problematic
social media use.
Shensa et al. 2017
Association between
screen time and
unhealthy behaviors
2625 13–18 y Adolescents Satisfaction with Life
Scale, Middle School
Student Mental
Health Scale,
Rosenberg Self-
esteem Scale
China SNSs had a significant relationship
with anxiety and physical activity
that led to poor quality of life.
However, SNS use did not
produce any effect on academic
performance.
Yan et al. 2017
SNSs use-based
disorders and
coping abilities
485 (125 M,
358 F)
14–55 y Students,
married
person and
job holders
s-IAT-com, IUES, TICS
and Self-esteem
Scale
Germany Social isolation led to ICD. Wegmann and
Brand 2016
Information-seeking
behavior and smart
phone
209 13–68 y Young students
of schools,
universities,
and old
people
66-item questionnaire Israel Young generation used more SNS,
like WhatsApp than older
generation. They also showed
higher neuroticism, extroversion
and less conscientiousness.
Zhitomirsky-Geffet
and Blau 2017
The validity and
psychometric
properties of SMDS
1325 10–17 y Teenagers SMDS The Netherlands Social media addiction led to
mental problem, depression and
attention deficit disorder.
van Den RJJM
et al. 2016
SNS use and its
association with
sleep quality,
anxiety, depression
467 11–17 y Adolescents PSQI, HADS, RES, and
Social Media Use
Integration Scale
Scotland Social media usage led to anxiety,
depression. Poorer sleep quality
was also reported.
Woods and Scott
2016
SNS and poor
psychological
functioning
753 14.1 y Students Kessler Psychological
Distress Scale
Canada Girls and high school students
spent more time in SNSs than
boys and middle school students.
Experienced high level of
psychological distress and
suicidal ideation.
Sampasa-Kanyinga
and Lewis 2015
Characteristic of social
network gamers
through online
survey
370 (356 M,
14 F)
38.9 y Working
employees,
and students
IAT, TAS-26, BDI-II, SCL-
90-R, and WHOQOL-
BREF
The USA, The UK,
Canada, Germany,
Australia and other
countries
Internet addiction led to
alexithymia, depression, and
poor QoL among 16.2%
participants.
Geisel et al. 2015
(Continued)
BIOLOGICAL RHYTHM RESEARCH 11

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Internet use and
depression
338 (116 M,
222 F)
18 y Students IAT and CES-DC Belgrade, Serbia Authors found a positive
association between Internet
addiction and depression.
Banjanin et al.
2015
SNS and cyber bullying
victimization
5126 (48% F) 11–20 y School students Kessler Psychological
Distress Scale
Canada Use of SNS led to cyber bullying
victimization. Psychological
distress, suicidal ideation and
attempts reported.
Sampasa-Kanyinga
and Hamilton
2015a
Facebook use and
psychological
stressors
44 (17 M, 27
F)
19–52 y Taking classes
at
Midwestern
University
IAT, Parental Bonding
Instrument,
Personality Disorder
Questionnaire, and
CES-DC
Asian, Asian-
American,
European,
European-American
FB users were found to be under
stress when they did not get an
access to their FB account.
Fox and Moreland
2015
Comparisons of
performance
between students
using electronic
device and students
focusing on lectures
during class
26 (8 M, 18
F)
3rd-year
students of
dental
courses of
Harvard
School of
Dental
Medicine
Questionnaire Boston, the US Both distracted and nondistracted
students performed equally.
Unlike males, the distracted
females gave 50% correct
answers.
Nalliah and
Allareddy 2014
Facebook users:
addiction and
psychosocial issues
241 Students Rosenberg’s Self-
esteem Scale, Lai’s
Personality test and
FAS
Taiwan FB addiction led to depression, and
self-inferiority
Hong et al. 2014
FB addiction and
students’resistance
119
(50.4% M)
23.5 y Undergraduate
psychology
students
BFAS America Although students were not
addicted to Facebook, yet they
showed a positive relationship
toward salience, withdrawal,
relapse, conflict, tolerance and
mood modification.
Akter 2014
Symptoms of excessive
Internet usage
69 (66 M, 03
F)
18 y Students of
Missouri
University of
Science and
Technology
IRPS India The users of Internet exhibited
symptoms, like withdrawal,
craving, tolerance to Internet and
introversion.
Vishwanathan
2014
(Continued)
12 R.KUMARSWAINANDA.K.PATI

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Online social
networking sites
and poor emotion
regulation skills
253 (62.8%
F)
19.68 y UG students Modified DSM-IV-TR,
PACS-FB, YIAT,
AUDIT, AAQ-II, DERS,
WBSI, CAGE-FB
The United States Women had more craving for FB
usage than men. They deviated
from ambition, avoided
emotional responses and
exhibited poor impulse control.
Hormes et al. 2014
Designing of scale to
quantify FB use
withdrawal
26 Facebook users BFAS and FWS 11 FB addicts on withdrawal
experienced anxiety, annoyance,
increased appetite, difficulties in
concentrating, hostility,
impatience and memory lapses.
Parlak and
Eckhardt 2014
FB usage and
technology-related
anxiety and
attitudes
1143 participants
(460 M, 683
F)
18–65 y Students and normal
people
MCMI-III Southern
California
FB users suffered from
bipolar mania,
narcissism,
dysthymia and
histrionic
personality disorder.
Rosen et al.
2013aa
FB addiction and
subjective vitality
and happiness
297 (47% M,
53% F)
18–25 y UG students BFAS, SVS and SHS Turkey Facebook addiction had a negative
relationship with the subjective
happiness and subjective vitality.
Uysal et al. 2013
Facebook use and life
style of medical
university students
1000 (400 M,
600 F)
18–25 y MBBS students Self-administered
questionnaire
Pakistan Medical students, using FB, had
headache, eye problems,
decreased work efficiency,
depression, mood swing and
backache.
Farooqi et al. 2013
Effects of Internet
addiction
3105
(1501 M,
1604 F)
11–19 y Dutch students CIUS and QBF The Netherlands Highly addictive Internet users
showed aggressive behavior.
Kuss et al. 2013
Facebook addiction
among Turkish
college students
447 (347 M,
100 F)
18–30 y Students of
technical
education
college
GHQ, FAS and FUS Turkey Students addicted to FB
experienced anxiety, depression
and insomnia.
Koc and Gulyagci
2013
(Continued)
BIOLOGICAL RHYTHM RESEARCH 13

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Use of Happy Farm
Facebook
application and
behavior
18–24 y University
students
Self-questionnaire Taiwan More materialistic students were
found to be addicted to online
games and had less interpersonal
relation.
Wu 2013
Interpersonal
relationship and
Internet addiction
444 (199 M,
245 F)
University
students
Questionnaire Taiwan Internet addiction reduced
interpersonal relationship.
Lai et al. 2013
Reasons behind the
nonuse of social
net-working sites by
university students
20 (9 M, 11
F)
18–25 y Students of two
universities
Semistructured
interview
Easternand north-
easternTurkey
Students thought that using SNSs is
a waste of time and might lead
to addiction, virtual relationship
lacking trustworthiness.
Turan et al. 2013
FB use and subjective
well-being
82 (M 29, 53
F)
19.52 y Peoples SWLS, BDI, RSES and
Social Provision Scale
Michigan FB undermined subjective well
being.
Kross et al. 2013
Problems associated
with use of the SNS
221
(4.62% M,
95.38% F)
15–49 y Mixed Authors self-
questionnaire
Poland Excessive SNS use led to
disturbances in sleep, anxiety
and depression.
Szczegielniak et al.
2013
SNSs and job
performance
193 (90 M,
103 F)
27 y Employee Through online
questionnaires
Texas, the USA Using SNSs among the employees
enhanced their level of job
satisfaction. Increased job
satisfaction led a positive impact
on job performance.
Moqbel et al. 2013
SNSs usage and
depression
160 (51 M,
109 F)
18 High school
students
BDI-II-II Central Serbia Students, who spent more time on
SNS, had depression as well as
obesity.
Pantic et al. 2012
SNSs usage and
narcissism
233 (144 F,
89 M)
19 UG students Questionnaire Asia and Africa Facebook induced openness more
and Twitter increased narcissism.
McKinney et al.
2012
Predictors of SNSs use 201 (46 M,
153 F)
17–24 y Students from
Australian
University
Five Factor Inventory,
Coopersmith Self-
esteem Inventory,
Addictive Tendencies
Scale
Australia Participants, who used SNS had less
conscientiousness, higher
extroversion and were more
prone to addiction.
Wilson et al. 2010
(Continued)
14 R.KUMARSWAINANDA.K.PATI

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Cause and effect of PIU 635 (42% M,
58% F)
UG students UCLA Loneliness Scale,
Self-monitoring Scale
Midwestern
Universities
Individuals suffered from loneliness
and showed a positive
relationship with compulsive
Internet use. Poor work output
was observed owing to
indulgence in SNSs.
Kim and LaRose
2009
WhatsApp
enchantment and
its impact
78 PG and 77
UG
students
(91 M, 64
F)
Veterinary
students
Self-prepared
questionnaire
Punjab, India Both positive and negative
impacts were observed.
Malhotra and
Bansal 2017
Online social
networking (OSNs)
addictions
15 18–19 y Students of two
universities
Semistructured
questionnaire
Indonesia Young females were found to be
more addictive to OSNs.
Luke and Evelina
2017
Social media use and
health
895 (366 M,
484 F)
10.4–17 y School students KIDSCREEN-52
questionnaire,
MPPUS-10
questionnaire
Central Switzerland
and Basel
Students who used SNSs more
frequently had unsatisfactory
health-related quality of life
(HRQoL).
Foerster and
Röösli 2017
Social media use and
health-related
problems
21,053 14.4 y Secondary
school
students
CIUS and 25-item SDQ The Netherlands Males had problematic gaming
addiction, while females showed
problematic social media uses,
suicidal thoughts and
hyperactivity.
Mérelle et al. 2017
Negative
consequences of
SNS use
1468 (377 M,
1091 F)
16–18 y Spanish
speaking
Latin-
American
social media
users
HADS, FoMo Scale, and
CERM Questionnaire
Argentina Bolivia,
Chile, Colombia,
Peru, Mexico,
Guatemala,
Ecuador, Honduras,
Uruguay, Venezuela
and Nicaragua
Fear of Missing out led to
Smartphone addiction. Females
showed depression due to
Facebook usage, and males had
anxiety.
Oberst et al. 2016
Internet use and
addictive behavior
255 19.18 y Young and
educated
middle class
37-item Likert Scale Turkey The addicted subjects avoided
problems and showed
withdrawal symptoms.
Kurtulus et al.
2016
(Continued)
BIOLOGICAL RHYTHM RESEARCH 15

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Frequency of Internet
addiction through
online survey
534 (233 M,
301 F)
Medical
students
IAT Questionnaire Greece Of the participants, Twitter users
were more than the Facebook
users. Internet addiction was
attributed to playing online
games.
Tsimtsiou et al.
2015
FB usage and health 311 (132 M,
179 F)
18–32 y Students BFAS, SHS, SVS, SWLS,
Flourishing Scale
Turkey Problematic FB use lowered well
being, but did not hamper life
satisfaction, flourishing,
subjective happiness and vitality.
Satici and Uysal
2015
SNS addiction among
health science
students
81 mixed
gender
20–25 y Medical and
laboratory
science
students
Six-item Electronic Self-
reporting Survey Part
of-BFAS
Muscat, Oman Addiction to SNSs, such as
Facebook, Twitter was evident.
Masters 2015
Dominance of Internet
addiction among
school children
553 (62.7%
F)
Average:
15.6 y
Elementary and
high school
students
Young’s Diagnostic
Questionnaire
Novi Sad, Serbia 18.7% were found to be addicted
to Internet. Most of them used
FB and compared to boys, the
girls visited FB more frequently.
Ač-Nikolićet al.
2015
A double-edged sword
effect of Facebook
upon the users life
satisfaction and
empathetic skills
515 18–26 y College
students
SWLS and Empathy
Quotient Scale
Hong Kong Strongly addicted adult FB users
showed weakening empathetic
responses to others.
Chan 2014
Instant messaging
services and mental
health
105 (49 M,
56 F)
21 y IM users at
Midwestern
University
YIAT and ASRS-V1.1 China and the USA Extreme Internet uses deteriorated
their mental health leading to
Internet addiction and
expression of symptoms for
ADHD.
Rosenbaum and
Wong 2012
Academic Performance
Electronic gadgets and
its effect on the
behavior, and
academic
performance
240 12–16 y 6th–10th grade
students
Questionnaire Karnataka, India 67% students spent more time in
SNS. Reported headache in early
morning along with eye
irritation, and changes in their
behavior.
Hegde et al. 2019
(Continued)
16 R.KUMARSWAINANDA.K.PATI

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
SNS, social well being
and academic
performance
366 (F) Students DEMATEL Malaysia Engagement in SNS had a positive
influence on students well being
and also enhanced their learning
performance.
Samad et al. 2019
SNS and academic
performance
380 (184 M,
196 F)
Students ASSIST, Persian Version
of SNS Usage
Questionnaire
Iran 70.3% were Instagram users where
as 24.7% were WA users. SNS
had a negative effect on the
study habit of students. Spent
several hours in Internet surfing.
Rostaminezhad
et al. 2018
WA and memory
performance
64 (24 M, 40
F)
12–17 Pupils The Personal
Information
Questionnaire,
Execution
Assessment Q
Israel Students felt difficulties and got
distracted from reading
obligations. WA use induced
a decline in learning abilities and
students reported reduced
memory efficacy.
Aharony and Zion
2018
Social network sites: its
impact on academic
performance
273 (21% M,
79% F)
Students from
two
universities
CIAS Qatar Students addicted to Instagram and
Snapchat felt tired at morning,
slept less than 4 h and had very
poor academic performance.
Al-Yafiet al. 2018
Social media impact
on academic
performance and
behavior
345 (192 M,
152 F)
18–26 y Students Self-structured
questionnaire
Bangladesh 72% respondents used FB followed
by YouTube, Instagram, etc.
Spent nearly 2.03 h in FB. As
a result got few hours for their
study, showed procrastination in
the submission of assignment,
and were poor in academic
performance.
Nahar Mim et al.
2018
Applying social
networks to
engineering
education
62 Two groups
with 31
students in
each group
Questionnaire Turkey Education through SNS tools
showed a positive relationship
with academic performance
among engineering students.
Doğan et al. 2018
SNS relationship with
academic and
nonacademic
performances
331 (107 M,
224 F)
21–30 y Students Self-administered
questionnaire
East Malaysia SNSs usage enhanced both
academic performance and
nonacademic engagements.
Abdurahman et al.
2018
(Continued)
BIOLOGICAL RHYTHM RESEARCH 17

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Adverse health effect
and SNS use
300
(28.3% M,
71.7% F)
18, 18–27,
>27
Medical
students
Self-administered
questionnaire
India Majority of respondents spent 4–5
h per day in SNSs. Subjects
experienced musculoskeletal
pain, eye irritation and headache.
They exhibited unhealthy
behavior, like holding urine,
skipping meals, etc.
Deogade et al.
2018
Mobile SNSs and
academic
performance
505 (242 M,
263 F)
<30 Students Questionnaire China Excessive use of mobile SNSs
caused a cognitive-emotional
preoccupation. It also led to
techno exhaustion, life invasion
and privacy-invasion. These
factors influenced academic
performance.
Cao et al. 2018
SNS and academic
performance
longitudinal study
71 (45 M, 26
F)
18.24 Students Questionnaire Quebec, Canada There was no significant
relationship between SNS and
academic performance.
Doleck et al. 2018
Impact of FAD on
study habits and
academic
achievements
200 (100 M,
100 F)
15–18 y Secondary
school
students
BFAS and Study Habit
Inventory
India Adolescents spent more time on
Facebook, which affected their
study habits and showed poor
academic performance.
Vashishtha et al.
2017
Social media use and
academic
performances
234 ≥18 y Students Self-reported
questionnaire
The USA 71% respondents were distracted
due to usage of SM during
class hour and 80% respondents
experienced that they were
disturbed by the users those who
used SM in class hour. Female
users were more compared to
male. SM uses in classes
disturbed their study and might
have a detrimental effect on
their study especially among girl
students.
Leyrer-Jackson
and Wilson
2017
Social media and
cognitive behavior
50 Dental
graduates
Authors’own
questionnaire
Chennai, India Social media decreased efficiency
and productivity, and had an
adverse effect on education.
Deepika and
Lakshmi 2017
(Continued)
18 R.KUMARSWAINANDA.K.PATI

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
SNS and classroom
performance
122 (40 M,
82 F)
16–25 y UG students Multiple choice
questions
Turkey Multitasking abilities in Social
media during lecture
deteriorated their grading points.
Cognitive perceptions were also
disrupted.
Demirbilek and
Talan 2017
Implications of using
SNS in university
30 Academic and
nonacademic
staffs from
two
universities
Questionnaire Indonesia Both academic and nonacademic
staffs showed a positive
relationship with the use of SNSs.
They preferred using WA, and FB
for sharing information, and was
the best tool for learning
process.
Luke and Meranga
2017
Effects of WhatsApp
use
201
(55.7% M,
44.3% F)
18–23 y Medical
students
Self-prepared
questionnaire
India About 45.8% respondents was
unable to concentrate during
their study, 33.3% felt that it
reduced their physical activities,
and 12.9% students reported
decline in their academic
performance since they have
started using WA.
Shettigar and
Karinagannanavar
2016
Facebook use and its
effects on life of
health science
students
452 (224 M,
228 F)
20.2 ± 1.2 y Medical, dental
and nursing
students
Self-administered
questionnaire
Bharatpur, Nepal Of the FB users, 67% participants
declared a negative impact on
their studies; 21% felt burning
sensation in their eyes, had
disturbed sleep (19%), and
headache (16%).
Jha et al. 2016
Association between
procrastination with
Facebook intrusion
and intensity
954 18–58 y High school
and
university
students
General Procrastination
Scale, Facebook
Intrusion
Questionnaire,
Decisional
Procrastination Scale
Poland Liklihood of FB intrusion depended
upon intensity of FB usage
among procrastinators.
Przepiorka et al.
2016
(Continued)
BIOLOGICAL RHYTHM RESEARCH 19

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Social media and its
influence on
academic
performance
526 (244 M,
282 F)
Students from
four
senior schools
Questionnaire Ghana Females used WhatsApp more
frequently. They had poor
academic performance and
committed spelling and
grammar errors.
Mingle and Adams
2015
Usage of social media
by medical and
dental students
162 (M 107,
F 55)
Students Self-administered
questionnaire
Pakistan 87% respondents had SNS
membership actively. Majority of
them used FB and YouTube. SNS
had a positive effect on academic
performance.
Javed and Bhatti
2015
SNS and its effect on
academic
performance
209 (83 M,
126 F)
18–24 y UG and
Graduate
students
BIG Five Inventory, IAT China Male students with low
agreeableness had spent more
time in problematic social
networking use. As a result their
academic performance also
hampered.
Glass et al. 2015
Influence of social
media use on
academic
performance
1578 participants Polytechnique
students
Self-questionnaire developed by
researchers
Ghana
Time spent on Facebook
had a positive
association with the
poor academic
performance.
Acheaw and
Larson
2015
Perception of students
toward SNS with
reference to
academic purposes
480 Students Self-administered
questionnaire
Bangladesh Compared to female students,
prevalence of SNS use were more
in male students. Very few
proportions of students used it
for academic purposes.
Shohrowardhy
and Hassan
2014
(Continued)
20 R.KUMARSWAINANDA.K.PATI

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Investigation on the
motives of Facebook
use and effects on
addiction to FB
327 (283 M,
44 F)
21–40 y Somali youth Facebook Addiction
Scale
Somalia Social interaction, political news,
entertainment were the motives
to use FB. Females used more
than males, became bored if not
logged in, and neglected
responsibilities leading to poor
grades.
Dhaha and Igale
2014
Online SNS and
pattern of use in six
European countries
10,930
(5211 M,
5719 F)
14–17 y Adolescents Online Communication
Tools, Youth Self
Report Scale
Greece, Spain, Poland,
the Netherlands,
Romania and
Iceland
40% users spent 2 or more than 2
h on SNS, larger proportions of
girls spent more time in SNS
than boys. Heavier users had
lower academic performance,
poor offline activities and more
internalizing problems.
Tsitsika et al. 2014
SNS use among
students
6358 UG and PG
students
35-item questionnaire
provided through
online survey
Malaysia Most of the respondents used SNS
as a learning tool and did not
agree that its usage had any
impact on their academic
performance.
Hamat et al. 2012
Role of YouTube in
education
91 Medical
students
Self-assessment
questions
UAE YouTube acted as an effective tool
for HAE study and highly used by
medical students.
Jaffar 2012
SNS –Its impact on
academic
performance
340 (48% M,
52% F)
26.73 y UG students Questionnaire The USA OSN had a negative impact on
academic performance.
Participants showed higher
attention deficit due to higher
usage of OSN.
Paul et al. 2012
(Continued)
BIOLOGICAL RHYTHM RESEARCH 21

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Effect of social
networking on
study efficiency
48 (26 M, 22
F)
Undergraduate
and
graduate
students of
Johnson and
Wales
University
Anonymous
questionnaire
The USA SNS use led to poor grade. Wang et al. 2011
SNS usage in higher
education
105 (68% F) 19–32 y Students Questionnaire Spain 88% respondents believed that
SNSs act as the best tool for
learning. It motivated and also
provided better time
management for their study.
Arquero and
Romero-Frías
2013
Tweets by teacher and
learning mechanism
86 Students Online tweets The USA Students using Twitter for
interacting with their teachers
showed a positive result toward
learning purposes compared to
non Twitter users.
Van Vooren and
Bess 2013
Technology usage
during sleep –Its
impact on sleep,
attention and
academic
performance
446 (201 M,
228 F)
13–16 y School students Adolescent Technology
Usage Survey,
Working Memory
Scale
Western New York High levels of technology usage led
to less sleep duration. Low
technology users had better GPA
than high technology users.
Dehmler 2009
Circadian rhythm and chronotype
CR activity of mixed
human population
on SNS
15 young
members
(8 M and 7
F), 13
senior
citizens
(10 M and
3F)
Young
students:
22–33 y;
senior
citizens:
60–62 y
Consisting of
two groups,
respectively
with young
subjects and
senior
citizens
PSQI, MCTQ, MEQ,
Facebook Intrusion
Questionnaire,
Cosinor Analysis
India Members of young groups were
active during evening, whereas
members of the senior citizens’
group were active during
morning.
Agrawal and Pati
2018
(Continued)
22 R.KUMARSWAINANDA.K.PATI

Table 1. (Continued).
S. no. Area of research
Subject and
gender Age Subject type Method/variable used Location Result Reference
Facebook association
with the levels of
cortisol
88 (41 M, 47
F)
12–17 y Users of
Facebook
Psychological
Questionnaire, CDI
and SEQ
Canada A positive association between the
number of FB friends and the
production of diurnal cortisol
level was discerned. This led to
elevation of stress.
Morin-Major et al.
2016
Facebook use and
chronotype
663 (64.1%
F)
15–45 y Users of
Facebook
Facebook Intensity
Scale, Facebook
Intrusion
Questionnaire, CSM
Poland Chronotype had negative
association with FB usage, and
intensity of Facebook use was
found more among the ET.
Blachino et al.
2015
AAQ-II
Acceptance and Action Questionnaire-II;
ADHD
Attention Deficit Hyperactivity Disorder;
ASRS-V1.1
ADHD Self Report Scale V1.1;
ASSIST
Approaches and Study Skills Inventory for Students;
AUDIT
Alcohol Use Disorders Identification Test;
BAI
Beck Anxiety Inventory;
BDI
Beck Depression Inventory;
BEARS
B = Bedtime Issues, E = Excessive Daytime Sleepiness, A = Night Awakenings, R = Regularity and Duration of Sleep, S = Snoring;
BFAS
Bergen Facebook
Addiction Scale;
BFI
BIG Five inventory;
BSMAS
Bergen Social Media Addiction Scale;
CAGE-FB
Cut-down, Annoyed, Guilt, Eye-opener- Facebook;
CDI
Child Depression Inventory;
CERM
Cuestionario
de Experiencias Relacionadas con el Móvil;
CES-D
Centre for Epidemiological Studies Depression Scale;
CES-DC
Center for Epidemiologic Studies of Depression Scale for Children;
CIAS
Chen’s
Internet Addiction Scale;
CIUS
Compulsive Internet Use Scale;
CSM
Composite Scale of Morningness;
DEMATEL
Decision Making Trial and Evaluation Laboratory;
DERS
Difficulties in Emotion
Regulation Scale;
DERS-SF
Difficulties in Emotion Regulation Scale-Short form;
Auto DOA
Automatically Detect Opioid Addicts;
DSM
Diagnostic and Statistical Manual of Mental Disorders;
DSM-IV-TR
Diagnostic and Statistical Manual of Mental Disorders: Text Revision (edited IV version);
EDS
Excessive Daytime Sleepiness;
EMFQ
Electronic Media and Fatigue Questionnaire;
ESS
Epworth
Sleepiness Scale;
ET
Evening type;
EAQ
Execution Assessment Questionnaire;
F
Female;
FA
Facebook Addiction;
FAD
Facebook Addiction Disorder;
FAS
Facebook Addiction Scale;
FB
Facebook;
FIQ
Facebook Intrusion Questionnaire;
FoMo
Fear of Missing out;
FUS
Facebook Usage Scale;
FWS
Facebook Withdrawal Scale;
GHQ
General Health Questionnaire;
GPA
Grade Point Average;
HADS
Hospital Anxiety and Depression Scale;
HAE
Human Anatomy Education;
HD
Hemodialysis;
HRQoL
Health Related Quality of Life;
IA
Internet Addiction;
IAS
Instagram Addiction Scale;
IAT
Internet
Addiction Test Scale;
ICD
Internet Communication Disorder;
IRPS
Internet Related Problem Scale;
IUES
Internet Use Expectancies Scale;
M
Male;
MCMI-III
Million Multiaxial Clinical Inventory-III;
MCTQ
Munich Chronotype Questionnaire;
MDD
Major Depressive Disorder;
MEQ
Morningness-Eveningness Questionnaire;
MPPUS−10
Mobile Phone Problem Use Scale (10 item);
OSN
Online Social
Networking;
PACS-FB
Penn Alcohol Craving Scale-FB;
PBBQ
The Prebedtime Behavior Questionnaire;
PG
Post graduate;
PHQ9
Patient Health Questionnaire;
PIQ
Personal Information Questionnaire;
PIU
Problematic Internet use;
POSI
Preference for Online Social Interaction;
PROMIS
Patient-Reported Outcomes Measurement Information System;
PROMIS-S
Patient-Reported Outcomes
Measurement Information System Scale;
PSMU
Passive Social Media Use;
PSQI
Pittsburgh Sleep Quality Index;
PSS
Perceived Stress Scale;
QBF
Quick Big Five Inventory;
QoL
Quality of Life;
RSES
Rosenberg Self-Esteem Scale;
RSES-HU
Rosenberg’s Self-Esteem Scale-Hungarian Version;
SCL−90-R
Symptom Check List-90-R;
SDQ
Strengths and Difficulties Questionnaire;
SEQ
Self-Esteem
Questionnaire;
SF−36v2
36-Item Short Form Survey (Version 2.0);
SHS
Subjective Happiness Scale;
s-IAT-com
Short Internet Addiction Test for online communication;
s-IAT-ICD
Short Internet
Addiction Test for Internet Communication Disorder;
SMAS-SF
Social Media Addiction Scale-Students Form;
SMDS
Social Media Disorder Scale;
SMMSE
Standardized Mini Mental State Examination;
SNS
Social Networking Site;
SSHS
School Sleep Habits Survey;
STAI
State-Trait Anxiety Inventory;
STAIC
State-Trait Anxiety Inventory for children;
SVS
Subjective Vitality Scale;
SWLS
Satisfaction With
Life Scale;
TAS−26
Toronto Alexithymia Scale (26 item);
TICS
Trier Inventory of Chronic Stress;
TIPI
Ten Item Personality Inventory;
UCLA
University California Los Angeles;
UG
Under graduate;
WA
WhatsApp;
WBSI
White Bear Suppression Inventory;
WHOQOL
World Health Organization Quality of Life Measurement;
y
Year;
YIAT
Young Internet Addiction Test.
BIOLOGICAL RHYTHM RESEARCH 23

on sleep quality, psychosocial behavior, academic performance, and circadian rhythm in
humans (Table 1).
2. Sleep quality
It has been reported that there is a steady decline in sleep duration among adolescents
(Iglowstein et al. 2003; Keyes et al. 2015). This recent phenomenon has been ascribed to
multiple factors, such as biological, environmental, societal and so forth (Calamaro et al.
2009; Pallesen et al. 2011; Bartel et al. 2015). The screen media usage (SMU) in the 21st
century has been identified as one of the major culprits. Adolescents engage themselves
in surfing the Internet and playing games for a longer time in cell phone before
bedtime. This behavior leads to a reduction in their sleep length and increases in the
excessive day time sleepiness (Eggermont and Van Den Bulck 2006; Fossum et al. 2014).
Insufficient sleep also leads to the development of negative physiological consequences,
including an increased risk of obesity and metabolic dysfunction. Anxiety, depression,
mood disturbances, suicidal ideation and drug/alcohol abuse have also been reported
among the adolescents due to insufficient sleep (Gupta et al. 2002; Chen et al. 2008;
Lowry et al. 2012). Adolescents with poor sleep quality exhibit poor judgment, lack of
motivation and decreased life quality (Pilcher et al. 1997; Wolfson and Carskadon 1998;
Gradisar et al. 2008; Owens 2014). This phenomenon has been observed to be gender
neutral, however (Thomée et al. 2007).
According to the National Science Foundation, USA sleep requirements of individuals
vary as a function of their age (National Sleep Foundation (NSF) 2015). For example,
children in the age range between 6 and 13 years should have 9–11 h of sleep; while
adolescents aged 14–17 should have 8–10 h of sleep whereas young adults ranging
18–25 years should have 7–9 h of sleep. A study conducted earlier revealed that about
45% of adolescents reported 8-h sleep per night (National Sleep Foundation (NSF) 2015).
It has been observed that the adolescents experience a shift in their biological rhythm
and they wake up later in the morning and stay more alert at night (Carskadon 2011;
National Sleep Foundation (NSF) 2015). If they wake up before 7.00 AM they experience
uneasiness and fail to concentrate on their work (Burke 2016). Spending more time in
SNSs, before and after going to bed, results in greater sleep latency and subsequent
sleep interruptions (Cain and Gradisar 2010). Overuse of technology has a negative
impact on both sleep quality and quantity (National Sleep Foundation (NSF) 2011). It
has been reported that exposure to bright light in the evening causes a delay in the
initiation of melatonin secretion thereby leading to delay in the onset of drowsiness or
sleep among the individuals (Cajochen et al. 2011; Chang et al. 2014).
The young and adolescents consider SNSs platforms as the most attractive and
precious. They tend to become highly addicted to these sites and exhibit various
symptoms, like changes in their sleep behavior, or cognitive behavior, and several health
consequences. Xanidis and Brignell (2016) performed a study on 334 randomly selected
subjects, including 101 males and 231 females aged between 18 and 58 years. They
concluded that SNS dependency leads to poor sleep quality among its users.
Exposure of 8th and 9th-grade students to electronic media declines their average
sleep duration. They consume a lot of time in weekdays apropos their engagement with
the electronic media and consequently get very few hours to sleep, invariably less than 7
24 R.KUMARSWAINANDA.K.PATI

h. It has also been reported that they suffer from day time sleepiness and experience
problematic sleep pattern and fatigue attributed to improper sleep hours in weekdays
compared to a weekend (Shochat et al. 2010). Use of SNSs not only makes the users
addicted to, but it also enslaves and emancipates the users. It has also been concluded
that SNS addiction acts as an antecedent for cell phone addiction (Salehan and
Negahban 2013).
Participants with overuse of SNSs have poor sleep quality as compared to the
nondependent users. It has been estimated that they had 1.3 times poorer sleep quality
(Wolniczak et al. 2013). The adolescents who frequently use social media develop
a sense of urgency and very high expectations of instant responses apropos their
feelings and needs (Barish 2015). All of these factors together may contribute to delayed
sleep, sleep interruption and less sleep. According to Choi et al. (2009), high school
seniors with Internet addiction (IA) and overuse of SNSs reported day time sleepiness.
They suffer from headache, insomnia, nightmare, teeth grinding in addition to
excessive day time sleepiness.
Sleep deprivation is one of the leading causes of circadian rhythm misalignment and
has been reported to disturb metabolic, endocrine and immune responses (Adams et al.
2013). Consequences of sleep deprivation are reflected in weight gain, insulin resistance
and hypertension (Laposky et al. 2008; AlDabal and BaHammam 2011). While it induces
an increase in the levels of circulating cortisol and systemic inflammation, it also
compromises the immune response (Laposky et al. 2008; AlDabal and BaHammam
2011). They also discovered a relationship between sleep deprivation and negative
behavior that prominently includes alcohol/drug abuse, increased sexual behavior and
the overuse of drowsiness suppressants (Carskadon 1990; Irwin et al. 1996; Patel and Hu
2008; AlDabal and BaHammam 2011).
3. Psychosocial behavior
Use of SNSs has been shown to have ample influences on large number of psychosocial
behaviors. It has been reported that excessive use of social media lead to psychiatric
distress (Sampasa-Kanyinga and Lewis 2015; Pontes et al. 2018; Marino et al. 2018b),
depression (Pantic et al. 2012; Afsar 2013; Farooqi et al. 2013; Koc and Gulyagci 2013;
Szczegielniak et al. 2013; Hong et al. 2014; Geisel et al. 2015; Banjanin et al. 2015; van
Den RJJM et al. 2016; Woods and Scott 2016; Oberst et al. 2016; Banyai et al. 2017;
Tamura et al. 2017; Barry et al. 2017; Khodarahimi and Fathi 2017; Cha and Seo 2018;
Jasso-Medrano and López-Rosales 2018; Barman et al. 2018; Jeri-Yabar et al. 2018;
Marino et al. 2018b; Al Mamun and Griffiths 2019), anxiety (Marino et al. 2018b;
Barman et al. 2018; van Rooij et al. 2017; Tresáncoras et al. 2017; Barry et al. 2017;
Khodarahimi and Fathi 2017; Yan et al. 2017; Woods and Scott 2016; Parlak and Eckhardt
2014; Rosen et al. 2013a; Koc and Gulyagci 2013; Szczegielniak et al. 2013; Oberst et al.
2016) and low self-esteem (Wilson et al. 2010; Hong et al. 2014; Wegmann and Brand
2016; Banyai et al. 2017; Yan et al. 2017) among student population. Incidences of
lethargic behavior (Cha and Seo 2018), suicidal ideation (Sampasa-Kanyinga and Lewis
2015;Sampasa-Kanyinga and Hamilton 2015a; Mérelle et al. 2017; Jasso-Medrano and
López-Rosales 2018) and procrastination (Przepiorka et al. 2016; Nahar Mim et al. 2018)
have been attributed to excessive use of SNSs.
BIOLOGICAL RHYTHM RESEARCH 25

Subjects using excessive SNSs suffer from poor cognitive abilities (Pontes et al. 2018).
They also exhibit mood swings and attention deficit (Paul et al. 2012; van Den RJJM et al.
2016; Aalbers et al. 2018). Use of SNSs also induces feeling of loneliness (Kim and LaRose
2009; van Rooij et al. 2017; Barry et al. 2017; Aalbers et al. 2018) and subjective fatigue
(Shochat et al. 2010; Aalbers et al. 2018). Many addicted individuals show fear of missing
out (FoMo), when they are deprived of opportunities to use social media (Oberst et al.
2016; Barry et al. 2017; Wegmann et al. 2017; Pontes et al. 2018). Excessive use of SNSs
also leads to opioid addiction (Fan et al. 2017). It has been demonstrated that data
mining from social media uses, such as in Twitter could be used to detect opioid
addicted subjects through using AutoDOA. This technique could also be used for
prevention and treatment of opioid addiction (Fan et al. 2017). It has been reported
that in older individuals social information seeking behavior has a link with the higher
neuroticism and extroversion (Wilson et al. 2010; Zhitomirsky-Geffet and Blau 2017).
Many adolescents spent their day by checking posts in the SNS media. The young
adults begin and end their day by frequently visiting the SNSs. The SNSs disrupt their
solitary activities and reduces their face-to-face interaction (Spies Shapiro and Margolin
2014). Many researchers have highlighted the negative psychological effects of
Facebook (Elgan 2015; Chowdhry 2016; Lewis 2016; Tordesillas 2016). Rosen et al.
(2013a) reported that those who spend more time in social media and actively engage
themselves in Facebook have major depression symptoms. It has also been reported
that spending more time in SNSs deteriorates the social relationship, weakens the
relationship with family and increases loneliness and depression. In a few case studies,
it has been observed that excessive SNSs users often seek clinical evaluation and
treatment (Karaiskos et al. 2010; Griffiths et al. 2014). Excessive SNSs use has been
found to be associated with mental health problems, like depressive symptoms and
suicidal behaviors (Sampasa-Kanyinga and Lewis 2015; Sampasa-Kanyinga and Hamilton
2015a; Seabrook et al. 2016). Unhealthy lifestyle behaviors that include physical inactiv-
ity, poor eating behavior and substance use have been attributed to screen media use
(Sampasa-Kanyinga et al. 2015,2016; Sampasa-Kanyinga and Hamilton 2015b; Sampasa-
Kanyinga and Chaput 2016a,2016b). On account of excessive SMU the adolescents
confront with a host of other complications, such as lack of cognitive flexibility (Dong
et al. 2014), poor decision making (D’Hondt et al. 2015), anxiety (Wegmann et al. 2015),
procrastination (Chóliz and Marco 2012), poor working memory (Dong et al. 2012) and
concentration conflicts (Rücker et al. 2015).
4. Academic performance
Excessive usage of SNSs has been shown to compromise the academic performance of
students. Instead of using textbooks, children or adolescents pay more attention to
these SNSs, resulting in the production of harmful impacts on their learning environ-
ment (Cela et al. 2014).
Cha and Seo (2018) conducted research on the smartphone addiction amongst the
middle school students in 17 cities of South Korea. The study involved 1824 middle
school students with a mean age of about 15.6 years. The authors and trained inter-
viewers conducted face-to-face interviews using a designated scale to determine the
intensity of addiction to smartphone among the participants. Out of 1824 participants,
26 R.KUMARSWAINANDA.K.PATI

563 (30.9%) were found to be addicted to the smartphone. They observed that addiction
leads to angriness, depression and lethargic behavior. A study on 1578 polytechnique
students of Ghana revealed that the students engaged in excessive use of SNSs had
poor academic grades (Acheaw and Larson 2015). Students, who were multitasking
between social networking use and home assignments, had 20% lower grades as
compared with the students without accounts in SNS platforms. Students who browsed
through pages of SNS on their computer screen lost their grasping efficiency during
their designated study hour and scored low grade subsequently (Enriquez 2010).
The Nielson Media Research reported that students spend 25% of their total time on
social media (Jacobsen and Forste 2011). The American Educational Research
Association in 2009 at the annual conference in San Diego, California declared that
users of social media study less and get low scores (Asif-ur-Rahman et al. 2015).
According to Englander et al. (2010), higher the Internet usages among the students
lower are their academic scores. They explained this phenomenon as the outcome of the
distracted or disruptive aspect of Internet use.
Cela et al. (2014) reported that the new generation teens do not take an interest in
reading books; instead, they spend a lot of time on social media. They stay awake until
late at night and go on chatting with friends till early morning. This altered behavior
might take a toll on their health and academic performance. School teachers admit that
students fall asleep during classes and unable to pay adequate attention to the lectures
(Cela et al. 2014). The habit of late night awakening is likely to deteriorate their health
leading to aggressive or inappropriate behaviors. Inadequate sleep has been linked to
diabetes, hypertension, obesity and depression (Danielsson et al. 2013).
Many parents and guardians of school and college going students think that their
words are not devoting adequate time for their studies as they spend a lot of time on
SNSs. It is also believed that “Internet”is one of the key factors, which might influence
the grade or study of students adversely (Kist 2008; Choney 2010; Jacobsen and Forste
2011; Meh Mood and Taswir 2013).
San Miguel (2009) reported an association between FB usage time and students’
performance at an academic level. He discovered a negative association between the
time spent on FB and grades. A GPA of 3.0–3.5 was reported among average FB users,
whereas non-FB-users secured a GPA of 3.5–4.0. Facebook users devoted 1–5hto
studies, whereas non-FB-users spent 11–15 h on studies in a week (Enriquez 2010). It
was observed that poor academic performance is attributed to excessive indulgence in
Internet browsing as addicted individuals tend to neglect their personal as well as
academic responsibilities (Nalwa and Ananad 2003).
It has been observed that IA users have poor academic performance and less inter-
action with their teachers (Ying-Fang and Peng 2008; Frangos et al. 2009). Skipping
meals, late night sleep, being obese and hypersomnic are other consequences devel-
oped among IA users. Facebook users confessed that they get diverted from their
studies for several hours when compared with non-Facebook users (Kirschner and
Karpinski 2010).
According to Bowman et al. (2012), students who engaged themselves in social media
and instant messengers invariably fail to complete their task than those who do
not engage in it. Students’deficits have been attributed to online-social networking
(OSN) usage during study periods (Paul et al. 2012).
BIOLOGICAL RHYTHM RESEARCH 27

There are many reports that have highlighted the brighter side of the SNSs use. Afsar
(2013) categorically demonstrated that SNS use is beneficial for the HD patients. These
patients had less depression and better cognitive function. A study conducted on female
students in Malaysia revealed that the SNS use produces positive effect on their well
beings and improves their academic performance (Samad et al. 2019). The SNS use has
been reported to improve academic performance and nonacademic engagement
among students of east Malaysia (Abdurahman et al. 2018). In contrast, there are
number of reports that did not reveal any negative effects of SNS use on the academic
performance (Hamat et al. 2012; Satici and Uysal 2015; Yan et al. 2017; Doleck et al.
2018). In many educational institutions, the social media platforms are used to maximize
the teaching efficiency of the teachers and learning abilities of the students (Jaffar 2012;
Arquero and Romero-Frías 2013). On the contrary, the student participants in a study
conducted in Turkey opined that use of SNS is a complete waste of time (Turan et al.
2013). They believed that SNS use might lead to addiction and instilment of trustworthi-
ness among its users. It appears that there are conflicting reports apropos the effects of
SNSs use on the academic performance. Therefore, more intensive research should be
carried out to resolve this controversy.
5. Chronotype and circadian rhythm
Chronotype is an individual’s preference with regard to going to bedtime and wake up
time. An individual does not remain active throughout the 24 h, rather beginning and
end of its active period remain restricted to a particular time period of the day. On the
basis of their activeness, he/she can be categorized into either “Morning type”(MT) or
“Lark type”. The MT remains active in the morning hour; whereas the “Evening type”(ET)
or “Owl type”remains active during evening time. There is yet another category called
“Neither type”(NT) or “Intermediate type (IT)”; in this case, the individual is neither active
at morning nor at evening. The diversity based on personalities is collectively termed as
“chronotype”(Agrawal and Pati 2018). Both sleep and orderly circadian functioning are
essential for good health. Findings emanating from few studies on teenagers and
adolescents revealed that excessive social media use can modulate the chronotype of
an individual. The youngsters are spending a lot of time accessing SNSs; as a result, their
circadian rhythms get compromised and bring in changes in their daily activities,
behaviors and academic performances. Persons spending lots of time in online video
gaming might develop social isolation and loneliness leading to sleep fragmentation
(Schmit et al. 2011). There is categorical evidence that suggests a possible association
between Internet usage and chronotype. Invariably the ET-people are found to be
Internet-dependent (Randler et al. 2014). They suffer from insomnia on account of
their excessive indulgence in surfing the Internet in the late evening and early morning
(Fossum et al. 2014).
The light emitted from any electronic gadgets could interrupt the circadian rhythm.
Melatonin induces sleep in humans. The light emitted from electronic gadgets disrupts
its secretion and interfere in its regulatory role on the sleep-wake cycle (Loughran 2015).
The light emitted from these devices reinforces the message to the brain to stay active
and awake (Levenson et al. 2016). Insomnia and scores of late chronotype have
a positive relationship with the in-bed usage of computer and mobile phone prior to
28 R.KUMARSWAINANDA.K.PATI

the initiation of actual sleep (Fossum et al. 2014). In one of our recent studies, we
reported for the first time that the timings of the social media messages could be used
to gauge the status of the endogenous circadian clock of the SNSs users (Swain and Pati
2019). More extensive studies are underway in our laboratory to elucidate circadian
rhythm in the pattern of SNSs usage among human population.
6. Conclusions and future research direction
This review summarizes information on the use of SNS and its effects on human
population. It underscores the adverse effects of SNSs usage on various variables/
components associated with sleep, such as sleep quality, delayed sleep onset, short-
ening of sleep length, excessive daytime sleepiness (EDS), insomnia, apnea and night-
mare (Figure 4). It has already been accepted unequivocally that use of SNSs produces
alterations in number of psychosocial behaviors. Literature review revealed that in
general, students addicted to social media suffer from psychiatric distress, anxiety,
depression, low self-esteem, suicidal ideation and procrastination (Figure 4). In addition,
there are many studies that have attempted to establish a relationship between SNSs
usage and academic performance, especially among the student population (Figure 4).
One important recommendation that emerges from this review of literature is that the
clinicians, counselors and health care professionals should be more sensitive and should
remain aware of the possibility of the problematic Internet or social media use in
Sleep
• Poor quality
• Delayed sleep onset
• Shortening of sleep
length
• EDS
• Insomnia
• Apnea
•Nightmare
Psychosocial
behavior
• Psychiatric distress
•Anxiety
• Depression
• Low self-esteem
• Lethargic behavior
• Suicidal ideation
• Procrastination
Circadian
rhythm
• Rhythm misalignment
• Age asymmetry in peak
usage time
Academic
performance
•Reduced memory efficacy
•Poor academic performance
•Reduced cognitive perceptions
Figure 4. Cartoon diagram depicts negative effects of social networking sites on various components
of sleep, psychosocial behavior, academic performance and circadian rhythm. Conceptualized based
on information reported in various scholarly articles cited in Scopus.
BIOLOGICAL RHYTHM RESEARCH 29

adolescents and young adults. Additionally, it is recommended that counselors and
health care workers should develop effective school/institution-based prevention, edu-
cation and intervention programs to address problematic Internet and social media
usage among adolescents and young adults. There is, however, a paucity of literature
on the effects of overuse of SNSs on the functioning of circadian clocks in humans.
Acknowledgments
The authors are obliged to the Head of the Department, School of Zoology, Gangadhar Meher
University, Amruta Vihar, Sambalpur –768 004, Odisha, India for extending all facilities during the
study and the preparation of this manuscript.
Author contribution
RKS conducted the literature survey.
AKP conceptualized the theme and wrote the article.
Disclosure statement
No potential conflict of interest was reported by the authors.
Funding
This work is a part of the PhD program of one of the authors (RKS). The authors did not receive any
financial support from any extra-mural funding agency, except the routine facilities that were
extended to the authors by the Gangadhar Meher University, Amruta Vihar, Sambalpur 768004,
Odisha, India.
ORCID
Rakesh Kumar Swain http://orcid.org/0000-0002-1818-304X
Atanu Kumar Pati http://orcid.org/0000-0002-4618-017X
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