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Self-Esteem, Daily Internet Use and Social Media Addiction as Predictors of Depression among Turkish Adolescents

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Abstract

In this study, direct and indirect effects of self-esteem, daily internet use and social media addiction to depression levels of adolescents have been investigated by testing a model. This descriptive study was conducted with 1130 students aged between 12 and 18 who are enrolled at different schools in southern region of Aegean. In order to collect data, " Children's Depression Inventory " , " Rosenberg Self-esteem Scale " and " Social Media Addiction Scale " have been used. In order to test the hypotheses Pearson's correlation and structural equation modeling were performed. The findings revealed that self-esteem and social media addiction predict %20 of the daily internet use. Furthermore, while depression was associated with self-esteem and daily internet use directly, social media addiction was affecting depression indirectly. Tested model was able to predict %28 of the depression among adolescents.
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Self-Esteem, Daily Internet Use and Social Media Addiction as
Predictors of Depression among Turkish Adolescents
Kağan Kırcaburun
Duzce University, Faculty of Education, Computer Education and Instructional Technology
Abstract
In this study, direct and indirect effects of self-esteem, daily internet use and social media addiction to depression
levels of adolescents have been investigated by testing a model. This descriptive study was conducted with 1130
students aged between 12 and 18 who are enrolled at different schools in southern region of Aegean. In order to
collect data, “Children's Depression Inventory”, “Rosenberg Self-esteem Scale” and “Social Media Addiction
Scale” have been used. In order to test the hypotheses Pearson's correlation and structural equation modeling were
performed. The findings revealed that self-esteem and social media addiction predict %20 of the daily internet use.
Furthermore, while depression was associated with self-esteem and daily internet use directly, social media
addiction was affecting depression indirectly. Tested model was able to predict %28 of the depression among
adolescents.
Keywords: depression, self-esteem, daily internet use, social media addiction, structural equation modeling
1. Introduction
Depression is one of the major health problems among modern society. Research conducted by World Health
Organization (WHO) in 2016 revealed that depression is affecting approximately 350 million people from all
around the World. Different from general mood change and short term emotional reactions against daily struggles,
depression becomes a very dangerous and serious health problem especially when intense depressive feelings and
symptoms are shown for extended period of time. It is a common and serious psychological disorder and affects
individuals’ daily routine activities and abilities such as thinking, feeling, sleeping, eating, working and studying
(NIMH, 2016). Duran (1999) defined depression as a syndrome that includes symptoms of retardation and
fuzziness in speech and movement; worthlessness, pettiness, weakness and reluctance; pessimistic emotions,
thoughts and psychological states.
Depression is a mental illness that also affects adolescents prevalently. While depressive symptoms can
be seen among children uncommonly, beginning from early stage of adolescence, symptoms are escalating acutely
(Fleming & Offord, 1990). Major depressive illnesses are usually commencing in adolescence and because of their
chronic and repetitive character there is a high probability of iteration in adulthood (Jacob et al., 2008). Kim-Cohen
et al. (2003) reported that 75% of the adults that are going through major depressive disorder have experienced
their first depressive episode in childhood or adolescence.
It was reported that 2.8 million American adolescents who are between ages of 12 to 17 have gone through
at least one major depressive episode in 2014. This was the 11.4% of the total population of age of 12-17
adolescents. In recent years, these numbers have been going up regularly (Abuse, 2014). Depression has been seen
among Turkish adolescents as well. A study conducted by Eskin et al. (2008) has shown that among high school
students, 61.5% of the participants were having mental health problems. In other research, Toros et al. (2005)
conducted a study with the students aged between 10 and 20; findings revealed that 12.5% of the participants had
high levels of depression.
There is number of psychical, social and psychological factors thought to be effective on depression. One
of them is self-esteem which expresses the individuals’ respect towards themselves. Self-esteem is self-
appreciation and self-approval which originated from self-assessment (Yavuzer, 2003; as cited in Sarıkaya, 2015).
Individuals who are lack of self-liking and seeing themselves lower than actually who they are, feel and perceive
themselves inadequate against their surroundings. They tend to be more sensitive against criticism and rather focus
on how people see them. As a result of this, they avoid taking risks, they usually demonstrate self-enclosed
behavior and they feel alone and left-off (Rosenberg & Owens, 2001; as cited in Sowislo & Orth, 2013).
Vulnerability model is one of the models that was developed to define the relationship between depression
and self-esteem. According to this model, lower self-esteem is a serious risk factor for future depression (Orth,
Robins ve Roberts, 2008). Individuals with low self-esteem usually are in a need for constant approval from their
friends and loved ones in order to feel valuable and precious. This situation is lifting the probability of being
rejected by their close friends and consequently the probability of being depressed (Joiner, Alfano & Metalsky,
1992). In many research, relationship between depression and low self-esteem have been revealed (Burwell &
Shirk, 2006; Conti, Adams & Kisler, 2014; Erözkan, 2009; Eskin et al., 2008; Kernis et al., 1998; Li et al., 2015;
Lin, 2015; Orth et al., 2008; Orth et al., 2014; Orth et al.,2016; Steiger, Fend & Allemand, 2015; Wouters et al.,
2013).
For individuals who are having difficulties in expressing themselves, feeling alone and left-off, it may be
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Vol.7, No.24, 2016
65
thought that since virtual platforms such as internet and social media allow individuals to be anonymous by
disguising their identity, they can act as a person they are not and express themselves more comfortably (Kurtalan,
2008). In a recent study, it was reported that, over 7.3 million people are living in the world, 3.4 million of them
are using internet and 2.3 million of them are active social media users. These results show that number of internet
and active social media users were up 10% compared to 2015 results (Chaffey, 2016).
Statistics suggest that majority of internet users are also social media users. Social media enable
individuals to communicate with one another through internet. It also contains communion platforms such as
Facebook, Twitter and YouTube that provides availability to online interactions (Corbeil & Corbeil, 2011). Using
social media platforms such as Facebook and Twitter have become widespread among adolescents. According to
recent study conducted with American students aged between 13 and 17, while 90% of them were social media
users, 75% of them were using social networking sites and nearly 35% of them were logging in to their social
media profiles several times a day (Rideout, 2012). As a result of their study with the students aged between 13
and 19, Kırık et al. (2015) also reported that social media was effective on students’ lives and social media use and
addiction levels were increasing among adolescents.
Social media is the most commonly used platform on the internet and it is becoming rapidly the most
important communication and interaction tool. Number of users of social networking platforms is growing in
accordance with the increasing use of internet (Çam & İşbulan, 2012). However, although social media enables
individuals to interact with a wide range of people, these superficial and artificial interactions stay inadequate for
replacing the face-to-face communications. Excessive use of internet and social networking platforms could
weaken the connections between individuals and their families, friends and loved ones. As a result of that,
individuals may feel lonelier and depressed (Pantic, 2014; Yellowless & Marks, 2007).
When the literature reviewed, number of research regarding subjects of depression, self-esteem, excessive
internet use and social media addiction have been noticed. As a result of their study with adolescents and teenagers
aged between 15 and 21, Orth et al. (2008) concluded that low self-esteem was causing depression. This finding
supports the vulnerability model that suggests lower self-esteem is significant predictor of depression. Another
finding that supports this model was found by Kernis et al. (1998). According to this study, unstable self-esteem
causes vulnerable feelings of self-worthiness and this leads to depressive symptoms. In other study, Erözkan (2009)
who has investigated the predictors of depression among 8 graders reported that low self-esteem was an important
predictor of depression. In a similar study, Eskin et al. (2008) found out that low self-esteem was causing
depression among high school students. In a meta-analysis conducted by Chen, Chiu & Huang (2013), 50 studies
containing more than 32,000 participants were examined. As a result of the study, findings revealed that there was
a moderate but significant relationship between self-esteem and depression. Aside from these studies, Shrier et al.
(2001) conducted a research with 6,583 adolescent students who were in grades of 7th to 12th. As a result of the
study it was stated that there was no significant relationship between depressive syndrome and self-esteem.
In the literature, it can be seen that there is number of studies which have investigated the relationships
between daily internet use, pathological internet use, internet addiction and depression. For instance, according to
Sanders et al. (2000), increase on internet use was causing weakening effect on social relations, however that
wasn’t affecting the depression levels of the students significantly. In similar studies, Banjanin et al. (2015) and
Tan et al. (2016) stated that there was a significant positive correlation between internet use and depression.
According to them, as the time spent online increased depression level of individual was rising. In another study,
Ayas & Horzum (2013) investigated the relations between internet addiction, loneliness, self-esteem and
depression among high school students. Findings revealed that while there was a significant positive relationship
between depression and internet addiction, no relations have been found between self-esteem and internet
addiction. In a recent study, Budak et al. (2015) stated that internet addiction levels of the university students were
causing elevation on psychopathological symptoms and drop on their self-esteem.
As the use of social media and social networking sites widened rapidly, studies that were investigating
the effects of this increase to depression have been conducted. Pantic et al. (2012) reported that daily time spent
on social media was causing adjuvant effect on depression levels of the high school students. Steers, Wicham &
Acitelli (2014) have reported a similar result to the findings of Pantic et al. (2012). According to this study, staying
longer on Facebook was making students more depressed. In contrast to the finding of Pantic et al. (2012),
Jelenchick, Eickhoff & Moreno (2013) stated that there was no significant relationship between daily time spent
on social networking platforms and depression among university students. In other study, De Choudhury, Counts
& Horvitz (2013) have developed a model that was aiming to analyse the tweets of individuals in order to determine
their depression levels. As a result of the study, it was reported that social media platforms such as Twitter could
be consistent, reliable sources for measuring the depression levels of the individuals. It was also stated that
detecting any sign of depression at early stages would enable specialists to prevent and intervene symptoms before
escalating. Another study, that has investigated the Facebook status updates of the university students, revealed
that 25% of the students were showing depressive symptoms and 2.5% of them were determined as in a major
depressive episode.
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Despite there is a number of research that have investigated the effects of self-esteem, internet use and
social media addiction on the depression levels of the individuals, number of studies conducted with Turkish
adolescents thought to be inadequate. Therefore, this study was seemed to be needed in order to study the effects
of psychological and technological factors on the depression levels of Turkish adolescents. Furthermore,
contributions of the studies which are investigating the effects of excessive use of internet and social media on
individuals’ psychology considered to be beneficial to the literature.
Hypotheses of this research are:
1- There is a positive association between depression and daily internet use.
2- There is a positive association between depression and social media addiction.
3- There is a negative association between depression and self-esteem.
4- There is a positive association between daily internet use and social media addiction.
5- There is a negative association between daily internet use and self-esteem.
2. Method
2.1 Research Design
In this study, relational survey design has been used. Relational survey design enables researchers to investigate
the change and the level of the variation of two or more variables together (Karasar, 2015). In order to determine
the relationship between depression, self-esteem, daily internet use and social media addiction, structural equation
modeling analysis have been utilized.
2.2 Participants
Adolescents aged between 12 and 18 constitute the population of the study. Purposeful sampling method was used
in order to choose the participants. 1130 students who are in grades between 6 to 11 in secondary and high schools
in southern region of Aegean had participated in this study. Demographic features of the participants are shown in
Table 1.
Table 1
Characteristics of the Participants
n %
Gender Female 659 58.7
Male 463 41.3
Grade Level
6
th
grade 154 13.6
7
th
grade 201 17.8
8
th
grade 143 12.7
9
th
grade 294 26
10
th
grade 177 15.7
11
th
grade 161 14.2
Age
12 137 12.1
13 224 19.8
14 143 12.7
15 212 18.8
16 228 20.2
17 154 13.6
18 32 2.8
Online via Mobile Yes 865 80.5
No 210 19.5
Daily Internet Use
Less than 1 Hour 384 34
Between 1-3 Hours 467 41.3
More than 3 Hours 279 24.7
2.3 Instruments
Children’s Depression Inventory (CDI): The CDI consists of 27 items labeled from A to Z. For every item there
are 3 possible statements which are given points between 0 and 2. 13 of the items are reverse coded. Highest total
score that can be taken from the scale is 54 and pathologic cutpoint is 19. The scale was developed by Kovacs in
1981. Adaptation into Turkish of the scale was conducted by Öy (1991). As a result of reliability test, Cronbach
Alfa co-efficient was found .86. In this study, calculated reliability co-efficient alpha was .85.
Rosenberg Self-esteem Scale (RSES): The scale was developed by Rosenberg (1965). Adaptation into
Turkish of the scale was conducted by Çuhadaroğlu (1986). Scale consists of 10 items on a 4-point likert scale. 5
of the items are reverse scored. Consistency of the scale was .71. In this study, reliability co-efficient was found .78.
Daily Internet Use: Daily internet use was one of the variables in this study. In order to identify the
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characteristics of internet usage among participants, personal information form was used. Participants have chosen
between 3 items which are "Less than 1 hour", "Between 1 to 3 hours" and "More than 3 hours".
Social Media Addiction Scale: In this study, addiction factor of “Social Networking Status Scale” was
used. The scale was developed by Arslan & Kırık (2013). Scale consists of 25 items on a 5-point likert scale such
as “I lose track of time while i am on Facebook”, “I prefer social media over Tv.” and “From the early times of
the day i feel desire to log in to social networking sites”. Calculated Cronbach Alfa reliability co-efficient for this
scale was .93. In this study, consistency of the scale was .94.
2.4 Data Analysis
In the analyses, descriptive statistics, Pearson correlation test and structural equation modeling was used. Structural
equation modeling is an extensive statistical approach that is used to test models which consist of hypotheses about
direct and indirect associations between observed and latent variables (Hoyle, 1995). Analyses were conducted by
using Amos 23.0 and Spss 23.0 package programs.
3. Results
3.1 Descriptive Statistics and Inter-correlations
Significant relationships between depression, self-esteem, daily internet use and social media addiction have been
observed. While depression was negatively but moderately associated with self-esteem, it was positively but
weakly correlated with daily internet use and social media addiction.
Table 2
Mean Scores, Standard Deviations and Correlation Co-efficients of The Variables
Variables X Sd 1 2 3 4
1.Depression 16.61 8.37 .
2.Self-Esteem 29.28 5.39 -.50** .
3.Daily Internet Use 1.90 .76 .27** -17**
4.Social Media Addiction 75.12 22.32 .13** -09** ..44** .
**p<.001
3.2 Structural Equation Model
Good fit, acceptable values (Hu & Bentler, 1999) and model results are given in Table 3.
According to Table 3., χ2/df and RMSEA results are at acceptable levels and SRMR, GFI, NFI, NNFI,
CFI, IFI, AGFI results are at good fit levels. These results suggest that model is accepted.
Table 3
Model Indexes
Indexes Model Results Good Fit Acceptable Values
X
2
/df 4.35 X
2
/df < 2 X
2
/df < 5
RMSEA
.05 RMSEA <. 05 .05 < RMSEA <. 08
SRMR .03 SRMR < .05 .05 < SRMR < .10
GFI .99 .95 < GFI < 1 .90 < GFI < .95
CFI .99 .95 < CFI < 1 .90 < CFI < .95
NFI .99 .95 < NFI < 1 .90 < NFI < .95
IFI .99 .95 < IFI < 1 .90 < IFI < .95
AGFI .98 .90 < AGFI < 1 .85 < AGFI < .90
NNFI .97 .95 < NNFI < 1 .90 < NNFI < .95
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Chi-square= 8.69, df= 2, p-value= .013, RMSEA= .054
Figure 1. Standardized Values Between Variables
As the t values and standardized values of the variables were examined, it was found that while social
media addiction was positively affecting daily internet use (t=16.18, standardized=.43); daily interent use was
negatively associated with self-esteem (t=-4.93, standardized= -.13). Furthermore, depression was affected by self-
esteem negatively (t=-18.5, standardized= -.47) and it was predicted by daily internet use positively (t=7.39,
standardized=.19). Structural equations and R
2
values are presented in Table 4.
Table 4
Structural Equations and R
2
Values
Structural Equation R
2
Daily Internet Use = .43*SocialMediaAddiction - .13*SelfEsteem .20
Depression = .08*SocialMediaAddiction + .19*DailyInternetUse - .50*SelfEsteem .28
Social media addiction and self-esteem were predicting %20 of the daily internet use and %28 of the
depression among adolescents was predicted by social media addiction, daily internet use and self-esteem. In the
model, daily internet use and self-esteem was affecting depression directly and social media addiction indirectly.
4. Discussion
In this study, variables that are thought to be effective on depression levels of the adolescents have been examined
by using correlation analysis and structural equation modeling. Findings revealed that there were significant
correlations between depression, self-esteem, daily internet use and social media addiction. It was also found that
depression was directly negatively associated with self-esteem and positively with daily internet use. Social media
addiction was affecting depression levels of adolescents indirectly (positively).
According to results, self-esteem was affecting daily internet use of adolescents negatively. This finding
coincides with some studies (Aydm & San, 2011; Bahrainian et al., 2014; Kim et al., 2016; Mei et al., 2016;
Zhang, 2015), as well as it contradicts the other ones (Ayas & Horzum, 2013; Reisoğlu, Gedik & Göktaş, 2013).
This result may be explained by that individuals who have low self-esteem are avoiding real interactions and
escape to virtual world where they can behave anonymously and act as whoever they want.
In the structured model, most significant predictor of depression was self-esteem. According to this, as
the self-esteem levels of students decreased, probability of showing depressive symptoms were going up. Although
there is a large number of studies supporting this finding (Burwell & Shirk, 2006; Conti, Adams & Kisler, 2014;
Erözkan, 2009; Eskin et al., 2008; Kernis et al., 1998; Li et al., 2015; Lin, 2015; Orth et al., 2008; Orth et al., 2014;
Orth et al., 2016; Steiger, Fend & Allemand, 2015; Wouters et al., 2013), some researchers reported different
results (Gana et al., 2015; Shrier et al., 2001).
There are various models in the literature that are trying to illuminate the relationship between depression
and self-esteem. One of them is vulnerability model which claims low self-esteem is leading individuals to
depression. Different from that, scar model asserts that depressive episodes leave certain scars on individuals'
psychology and this leads to lower self-esteem. In their study, Steiger, Fend & Allemand (2015) aimed to
determine which model was better at explaining the relationship between depression and self-esteem. As a result,
findings which are supporting vulnerability model was higher than the findings of scar model. In current study,
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similar results were observed as Steiger, Fend & Allemand (2015). According to this, depression was not predicting
the low self-esteem levels of adolescents, however, low self-esteem was a significant risk factor and was leading
individuals to depression. This may be explained by that individuals with low self-esteem are more sensitive and
fragile to negativity around their surroundings. Because of that, this may lead to psychological and emotional
damage on person’s life by having permanent bad mood.
Another important result of the study is that depression was affected by daily internet use positively.
Students who have stayed longer on the internet had higher scores on depression inventory. While this finding is
parallel with the result of some studies (Banjanin et al., 2015; Morrison & Gore, 2010; Ostovar et al,. 2016; Tan
et al., 2016), it differs from some other studies (Cotton et al., 2014; Moreno, Jelenchick & Breland, 2015; Sanders
et al., 2000). As a result of their research that has investigated the association between depression, social isolation
and internet use, Sanders et al. (2000) reported that while increased time spent online was weakening the social
relations, it was not significantly affecting the depression levels of adolescents. Opposing to Sanders et al. (2000),
findings of this study suggest that daily time spent online was predicting depression weakly but significantly. This
may be interpreted by that the more students stay away from real life and interactions, the more they get lonely
and depressed. As much as there is online communication with other people, since human beings also need physical
interactions, these artificial and superficial relations might not be enough to feel fulfilled and satisfied emotionally
and psychologically.
Parallel to daily internet use, social media addiction was also positively correlated with depression and
analyses revealed that depression levels of adolescents was associated with social media addiction indirectly. It
means as the time spent on social media increases, risk of depression is going up. As some studies resulted similarly
(Pantic et al., 2012; Sagioglou et al., 2014; Sidani et al., 2016; Woods & Scott, 2016), some of them did not
(Banjanin et al., 2015; Jelenchick et al., 2013; Tandoc, Ferrucci & Duffy, 2015). These diversified results suggest
that more studies may be needed to shed light on the relationship between social media addiction and depression.
Finding of this study suggest that social media addiction causes increased time spent online and as a result of it,
there is a higher probability for depressive symptoms to be seen.
As a result of this study, it may be concluded that self-esteem, daily internet use and social media
addiction are significant predictors of depression among Turkish adolescents. Adolescence is a transitional period
between childhood and adulthood that brings number of psychological, physiological and cognitive alterations
into the individuals' lives. In this vulnerable period, harmful factors such as depression which could affect students’
development negatively must be avoided as much as possible. Furthermore, conducting preventive studies would
be beneficial for healthy development of adolescents. In accordance with this purpose, in order to be able to prevent
possible damages, it may be suggested that other possible risk factors that can cause depression among adolescents
should be examined. Also, teachers, psychological counselors and adults should gain more consciousness about
negative factors affecting adolescents.
This study has some limitations. First limitation is that, sample of the study was consisted of students
only from a single city in southern region of Aegean. Conducting future studies with samples from various cities
and different age groups would be beneficial in order to generalize the model that was tested in this study. Another
limitation is that data was collected by using quantitative scales and self-reports. It may be suggested that new
studies may be conducted by using more detailed qualitative instruments to shed further light on these associations.
Acknowledgements
I especially thank to Ismet Kırcaburun, who have kindly contributed to data collection process.
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... An important factor in adolescents' and emerging adults' negative self-evaluation is the intensive use of, or even addiction to, social media. Numerous researchers have reported a negative correlation between daily social media use and self-esteem levels [6,7], alongside poor sleep quality, anxiety, and depression [8]. For overweight individuals, their perception of body size and volume can lead to social discomfort, shyness, low self-confidence, and an anxious posture and attitude [9]. ...
... Sjamsoedin, dkk (2015) menyatakan bahwa individu dalam penggunaan internet dengan jangka waktu yang lama dapat menyebabkan insomnia, hal ini dimulai dari insomnia ringan hingga insomnia berat. Efek negatif yang dialami oleh kecanduan internet adalah menjadikan pengguna mengalami push hingga depresi (Kircaburun, 2016). Selain itu menurut Young, dkk (2000) memiliki beberapa indikator kecanduan internet yang mana beranggapan bahwa internet merupakan jalan keluar dari masalah pribadi, tidak beradaptasi dengan kehidupan nyata, menarik diri dari kehidupan, insomnia, kenaikan berat badan, serta tidak dapat mencegah diri dalam mengakses internet walau telah mengetahui hal yang tidak diinginkan. ...
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... In the international literature; excessive use of social media and usage practices of these platforms (Balcı & Gölcü, 2013;Savcı & Aysan, 2017;Griffiths et al., 2012) give way to self-esteem (Balcı et al., 2020b;Buran Köse and Doğan, 2017;Eroğlu and Bayraktar, 2017;De Cock et al., 2014;Hawi and Samaha, 2016;Kırcaburun, 2016), loneliness (Baltacı, 2019;Yavich, Davidovitch Frenkel, 2019;Tok and Arslan Aldemir, 2023), and depression (Aydın et al., 2021;Balcı and Baloğlu, 2018;Haand and Shuwang, 2020). ...
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... Orang yang memiliki harga diri yang rendah tidak akan mengalami kecanduan smartphone. Mereka biasanya lebih banyak membutuhkan dukungan dari teman atau orang-orang di sekitar mereka untuk membuat mereka merasa lebih dihargai (Kircaburun, 2016). Hasil penelitian ini sejalan dengan temuan beberapa penelitian lain yang meneliti hubungan antara selfesteem dan takut kehilangan. ...
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... Now in young adults, the addiction to media users excessively has increased and became a habit whether it is good or bad (Schou et al., & Zaremohzzabieh et al., 2015. A study conducted in 2016, showed that addiction to Twitter is higher in males as compared to females (Kircaburun, 2016) but another study highlighted the fact that female students use Facebook excessively as compared to their male counterparts (Biernatowska, A., Balcerowska, J. M., & Pianka, L. ,2017). As Andreassen et al., (2017) explore that females are one of the most significant elements of social networking site addiction. ...
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... The health-orientation of the reviewed papers is also indicated by the analysis of author keywords visualized in Table 7 and Fig. 4. While the results from articles produced by scholars within health-oriented fields have brought attention to the possible impacts of social media use on childrens and adolescents' mental and physical health, with studies exploring the relationship between social media use and sleeping patterns (such as in [36,[36][37][38][39][40][41][42][43] and [44]), attention deficit hyperactivity disorder (ADHD) symptoms (such as in [45,46]) and anxiety and depression [21,[47][48][49][50], this perspective and the common objectives, research questions and findings of these studies only covers some aspects of what constitutes social media use and the impact it might have on user health and well-being. To fully understand the impact social media use might have on children's and adolescents' health and well-being, we must first strive to gain a fuller understanding of their situated social media use, the social practices involved and the meaning these practices have to them, which most certainly require additional studies from a additional disciplines. ...
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... An adequate development of selfesteem is crucial for mental health and quality of life (Boyd et al., 2014). Low scores in self-esteem are related to more time spent online (Kircaburun, 2016). A study including youth adult participants from three different European countries discovered that high self-esteem was not only related to less daily internet use time, but it also was a protective factor against internet addiction (Błachnio et al., 2016). ...
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The present study aimed to analyse if self-control, self-esteem and self-efficacy are related to the use of artificial intelligence tools. These tools are being incorporated to educational practices, but there is a lack of empirical evidence about the relation between artificial intelligence use by students and their personal and psychological characteristics. Drawing a profile of students concerning their use of artificial intelligence is imperative in order to design effective learning strategies. This was a cross-sectional study including 1 761 undergraduate students enrolled in different degrees related to education and psychology. Data collection was conducted using validated self-reports that showed appropriate psychometric properties. According to linear regression analyses, low levels of self-control were related to a higher frequency of artificial intelligence use. Logistic regression analyses showed that self-control and self-efficacy were associated with using artificial intelligence to solve daily doubts, due to the need of interacting with someone and to do academic tasks instead of the student. Moreover, higher scores in self-esteem decreased the odds of using artificial intelligence due to the need of interacting with someone. Educators should take into account these findings when implementing the use of artificial intelligence in their educational strategies with university students.
... One is the vulnerability model, which contends that depression is caused by poor self-esteem, and the other is the scarring model, which contends that trauma brought on by depression causes low self-esteem to develop. In order to research how sadness and low self-esteem are related, Kırcaburun recruited 1130 students aged 12 to 18 years from different schools in the Southern Aegean region, and Relevant scales such as the Child Depression Questionnaire were used as a source of data for the study, which will be used to analyze the relationship between depression in adolescents and factors such as self-esteem [14]. The results of the study said that the research supporting the fragile model is much more than the scarred model. ...
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Social media has grown in popularity at an alarming rate over the past few years, from simple forms of communication such as text messaging and phone calls to the use of messaging and calling apps, to the rise of short videos, video or photo-sharing platforms, and social network sites. The forms of social media communication have become more diversified and complex. As the cost of communication, media becomes less expensive and more acceptable to the general public. It has also become common for youth to access social media. Social media use (SMU) is now ingrained in adolescent culture. With the influence of Internet Celebrities (ICs), a derivative born along with the growth of social media, adolescents behavioral changes should not be underestimated due to the high degree of freedom in their communication and the extremely low threshold of the industry. Much of the earlier research has concentrated on the benefits that social media use provides to adolescents, and very little has been explored about the possible effects of SMU and its derivatives (i.e., IC) on adolescents behavior. A better understanding of the impact of SMU on adolescents behavior can help families and schools with intervention planning. This review may provide inspiration for future research on factors influencing adolescents behavior from a social media perspective.
... WHO has researched that melancholy is the maximum common reason of disability nowadays. More than 264 million people worldwide suffer from it [1]. Depression becomes a very dangerous and serious health problem especially when intense depressive feelings and symptoms are exhibited for a long period of time [2]. ...
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BACKGROUND; : Melancholy is one of the major fitness issues in modern society. WHO has researched that melancholy is the maximum common reason of disability nowadays. It ‘s far a common and extreme mental disorder that affects someone's each day ordinary activities and capabilities consisting of questioning, feeling, sound asleep, eating, working and analyzing. In our research, we want to show the connection between social media use and depression in medical students. . Research studies have shown that excessive use of social media affects students' mental health. Social media use can increase depression among users. OBJECTIVE; To determine if a relationship exists between social media and depression among medical students of Peshawar METHODOLOGY: A cross-sectional study was carried out among the students of private medical colleges of Hayatabad Peshawar. An online questionnaire was designed using Google forms and was sent to the participants via WhatsApp. The questionnaire was filled out by 282 participants. Data analysis was done using SPSS version 20 and MS EXCEL was used to make graphs and figures. RESULTS: The age of participants was between 18 and 27 years. 56.7% were using social media for personal needs and interest, 10.6%were using it for educational purposes and only 2.5% were used for professional purposes. We found that 40.1% were using social media more than 10 times per day, 36.9% use 2 to 5 times a day and 5.7% were using only 7(2.5%) out of 282 participants, according to the scale have an addiction and 275(97.5%) have no addiction. 193(68.4%) participants out of 282 were at risk of clinical depression and 89(31.6%) have no clinical depression. CONCLUSION; According to this study, social media does not necessarily cause depression. It was concluded that depression may be due to other causes like stressful life, unemployment, family problems, and low socioeconomic status.
Article
Purpose The study was conducted to determine the relationship between social media addiction and perceived stress in adolescents. Method The study was conducted in a descriptive and cross‐sectional design between September and December 2022 in secondary education institutions of the Provincial Directorate of National Education in a city center in eastern Turkey. The sample of the study consisted of a total of 716 adolescents who were studying in the ninth grade (145), 10th grade (198), 11th grade (216), and 12th grade (157) who met the inclusion criteria of the study at the time the study was conducted. The sample comprised individuals with diverse sociodemographic characteristics, including ages, genders, school success levels, parents’ education levels, parents’ job status, socioeconomic status, time spent on daily social media, and purposes of social media use of the adolescents. The “Sociodemographic Characteristics Form,” “Social Media Addiction Scale for Adolescents (SMASA),” and “Perceived Stress Scale (PSS)” were used as the data collection tools. Ethical principles were fulfilled in the study. Results It was found that the average age of the adolescents who participated in the study was 15.71 ± 1.22, 58.1% were females, 41.1% had good school success, 90.5% had a mobile phone, 90.2% used WhatsApp, 56.8% said that their daily social media use time was between 1 and 3 h, and 64% said that their purpose of using social media was for entertainment and leisure. The mean SMASA score was 18.49 ± 6.98, and the mean PSS score was 42.11 ± 7.54. It was found in the study that the mother's employment status, phone ownership status, use of Instagram, Facebook, Twitter, WhatsApp, Snapchat, YouTube, TikTok, and LinkedIn accounts, daily social media use, time and purposes of using social media affected the mean SMASA score. Age, gender, school success, use of Instagram and Snapchat accounts, daily social media use time, and purposes of using social media affected the mean PSS score ( p < 0.05). As a result of the study, a positive and low‐level significant relationship was detected between social media addiction and perceived stress levels ( p < 0.01). Conclusion As the levels of social media addiction increase in adolescents, the perceived stress levels also increase. It was also found that some variables affected the social media addiction and perceived stress levels of adolescents.
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This study examined how social media use related to sleep quality, self-esteem, anxiety and depression in 467 Scottish adolescents. We measured overall social media use, nighttime-specific social media use, emotional investment in social media, sleep quality, self-esteem and levels of anxiety and depression. Adolescents who used social media more – both overall and at night – and those who were more emotionally invested in social media experienced poorer sleep quality, lower self-esteem and higher levels of anxiety and depression. Nighttime-specific social media use predicted poorer sleep quality after controlling for anxiety, depression and self-esteem. These findings contribute to the growing body of evidence that social media use is related to various aspects of wellbeing in adolescents. In addition, our results indicate that nighttime-specific social media use and emotional investment in social media are two important factors that merit further investigation in relation to adolescent sleep and wellbeing.
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Given the prevalence of Internet use among youth, there is concern that a subset of Internet-using youth may exhibit problematic or addictive patterns of Internet use. The present study examines the association between problematic Internet use (PIU), demographic variables, and health-related measures among Chinese adolescents. Survey data from 1552 adolescents (male = 653, mean age = 15.43 years) from Jilin Province, China, were collected. According to the Young Diagnostic Questionnaire for Internet Addiction (YDQ), 77.8% (n = 1207), 16.8% (n = 260), and 5.5% (n = 85) showed adaptive, maladaptive, and problematic Internet use, respectively. Multinomial logistic regression analysis revealed that gender and family income per month differed between youth showing problematic and adaptive patterns of Internet use. Well-being, self-esteem, and self-control were related to severity of problematic Internet use, with greater severity typically associated with poorer measures in each domain. The findings that severity of problematic Internet use is associated with specific socio-demographic features and temperamental and well-being measures suggest that specific groups of youth may be particularly vulnerable to developing problematic Internet use. Early prevention/intervention programs targeting at-risk groups may help improve public health.
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The primary aim of this study was to examine associations between problematic Internet use, depression and sleep disturbance, and explore whether there were differential effects of problematic Internet use and depression on sleep disturbance. A total of 1772 adolescents who participated in the Shantou Adolescent Mental Health Survey were recruited in 2012 in Shantou, China. The Chinese version of the Internet Addiction Test (IAT) was used to evaluate the prevalence and severity of Internet addiction. The Chinese version of the Pittsburgh Sleep Quality Index (PSQI), a 10-item version of the Center for Epidemiologic Studies Depression Scale (CESD-10), and other socio-demographic measures were also completed. Multiple regression analysis was used to test the mediating effect of problematic Internet use and depression on sleep disturbance. Among the participants, 17.2% of adolescents met the criteria for problematic Internet use, 40.0% were also classified as suffering from sleep disturbance, and 54.4% of students had depressive symptoms. Problematic Internet use was significantly associated with depressive symptoms and sleep disturbance. The correlation between depressive symptoms and sleep disturbance was highly significant. Both problematic Internet use (β = 0.014; Sobel test Z = 12.7, p < 0.001) and depression (β = 0.232; Sobel test Z = 3.39, p < 0.001) had partially mediating effects on sleep disturbance and depression was of greater importance for sleep disturbance than problematic Internet use. There is a high prevalence of problematic Internet use, depression and sleep disturbance among high school students in southern China, and problematic Internet use and depressive symptoms are strongly associated with sleep disturbance. This study provides evidence that problematic Internet use and depression have partially mediating effects on sleep disturbance. These results are important for clinicians and policy makers with useful information for prevention and intervention efforts.
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