J Child Adolesc Psychiatr Nurs. 2019;32:139–148. wileyonlinelibrary.com/journal/jcap © 2019 Wiley Periodicals, Inc.
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139O R I G I N A L A R T I C L E
Virtual behaviors affecting adolescent mental health: The
usage of Internet and mobile phone and cyberbullying
Pelin Calpbinici RN, MSc,
1Research Assistant
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Fatma Tas Arslan RN, PhD,
2Professor
1
Department of Nursing, Semra and Vefa Kucuk Health College, Nevsehir Haci Bektas Veli University, Nevsehir, Turkey
2
Department of Nursing, Faculty Health Sciences, Selçuk University, Konya, Turkey
Correspondence
Pelin Calpbinici, Semra and Vefa Kucuk Health College, Nevsehir Haci Bektas Veli University, 2000 Evler District, Zubeyde Hanım Street, 50300 Nevsehir, Turkey.
Email: [email protected]
Abstract
Problem: An important environmental factor affecting adolescents today is
undoubtedly technological tools. This descriptive and cross
‐sectional study was
conducted to evaluate the relationship of adolescents
’ Internet and mobile phone
usage, cyberbullying behaviors, and their self
‐reported mental health.
Methods: The sample of the study consisted of a total of 426 students including 215
male students and 211 female students. A questionnaire was prepared by the
researcher to determine the sociodemographic and personal characteristics and
virtual behavioral characteristics of individuals. The Brief Symptom Inventory was
used to determine the participants
’ mental status.
Findings: It was found that adolescents
’ daily Internet usage duration, Internet usage
purpose, the place where they use Internet, cyberbullying, and exposure to
cyberbullying were related to the adolescents
’ self‐reported mental health (p < .05).
Conclusion: Several aspects of the virtual behaviors of the adolescents were
associated with their sense of mental health issues. In this context, the school health
nurse should raise awareness among adolescents about the use of technology and
how it might impact their mental wellbeing.
K E Y W O R D S
adolescent, mental health, virtual behavior
Adolescents’ mental health problems have increased over the last 20–30 years such that it is now seen as a public health problem that needs to be addressed (Dean, Britt, Bell, Stanley, & Collings, 2016; Kieling et al., 2011; UNİCEF, 2011). Even though adolescents are generally perceived as a healthy age group, mental health problems in all societies constitute a great part of the illness burden among this age group. According to WHO (2017), depression is the third leading cause of illness and disability in adolescents and suicide is the third cause of death in adolescents. A UNICEF report (2011) documented that 20% of adolescents in the world experience mental health or behavior problems.
Adolescence is a period in which mental health problems and various health‐threatening behaviors tend to occur (Sampasa‐Kanyinga
& Hamilton, 2015). Many factors are seen to affect the adolescent’s mental health in this period (Patel, Flisher, Hetrick, & McGorry, 2007). Studies have demonstrated that inappropriate use of technological tools by the adolescents such as mobile phones, computers, and the Internet negatively affects their mental health (Pantic et al., 2012; Sampasa‐Kanyinga & Lewis, 2015). Computer, Internet, and mobile phone have a place in the lives of adolescents and indeed adolescents use these technological tools intensively (Gallimberti et al., 2016; Lenhart, 2015; Muñoz‐Miralles et al., 2016; Sinkkonen, Puhakka, & Meriläinen, 2014). However, adolescents’ uncontrolled and improper use of these technological tools is found to be associated with negative mental and behavioral problems such as Internet addiction (Mueller et al., 2017), inappropriate online behaviors (Lau & Yuen, 2013), decreased face‐to‐face communication and social anxiety (Selfhout, Branje, Delsing, ter Bogt, & Meeus, 2009), loneliness (Ostovar et al., 2016; Yao & Zhong, 2014), depression and suicidal ideation A part of this study was presented at the 5th National and 2nd International Mediterranean
(Kim et al., 2006; Lam & Peng, 2010; Pantic et al., 2012), narcissistic personality disorder, and low self‐esteem (Mehdizadeh, 2010).
Cyberbullying is one of the virtual behaviors associated with technology that affects mental health and has potentially devastating effects on adolescents’ wellbeing (Spears, Taddeo, Daly, Stretton, & Karklins, 2015). Cyberbullying is defined as aggressive and inten-tional actions made by an individual or a group to others via e‐mail, mobile phone, short message service, and Internet sites for threatening, embarrassing, exclusion, and condescending purposes (Smith et al., 2008; Ybarra & Mitchell, 2004). Studies conducted in different countries about the prevalence of cyberbullying among adolescents have demonstrated that cyberbullying behaviors are a problem experienced at schools in an amount that cannot be ignored (Aricak et al., 2008; Khoury‐Kassabri, Mishna, & Massarwi, 2016; Mishna, Cook, Gadalla, Daciuk, & Solomon, 2010; Selkie, Fales, & Moreno, 2016; Tsitsika et al., 2015). Mental problems like depression (Landoll, La Greca, Lai, Chan, & Herge, 2015; Wang, Nansel, & Iannotti, 2011), social anxiety (Fahy et al., 2016), insomnia (Kubiszewski, Fontaine, Huré, & Rusch, 2013), suicidal ideation (Litwiller & Brausch, 2013 Schenk & Fremouw, 2012), low self‐ esteem (Brewer & Kerslake, 2015; Cénat et al., 2014), and loneliness (Larrañaga, Yubero, Ovejero, & Navarro, 2016) can be seen in adolescents exposed to cyberbullying. Conversely, adolescents who initiate cyberbullying are more prone to violence (Sari & Camadan, 2016), more aggressive (Ybarra & Michell, 2004), have low social competence and low empathy skills (Ang & Goh, 2010; Steffgen, König, Pfetsch, & Melzer, 2011), and demonstrate more antisocial behaviors (Sticca, Ruggieri, Alsaker, & Perren, 2013).
The aim of this study was to investigate the relationship of virtual behaviors of adolescents such as Internet and mobile phone usage and cyberbullying and their perceived mental health.
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M E T H O D S
This study was conducted as descriptive and cross‐sectional to assess the relationship of Internet and mobile phone usage and cyberbully-ing behaviors of adolescents on their mental health.
1.1 | Population and sample
The population of the study consisted of 8,311 high school students including 4,199 male students and 4,112 female students attending ninth–twelfth grade of public and private high schools located in Nevşehir city in Turkey in academic year of 2013–2014. Schools were determined by a stratified sampling method and then one branch from classes ninth–twelfth was selected according to the simple random sampling method. Selected cohorts who used computer, Internet, and mobile phone, and agreed to participate were included in the sample. A total of 426 students (215 male and 211 female) aged between 14 and 18 (16.05 ± 1.26) years were reached and asked to participate in the study.
1.2 | Data collection tools
A questionnaire prepared by the researcher in accordance with the literature was used to collect data (Arıcak, Kınay, & Tanrıkulu, 2012; Çiftçi, 2010; M. Şahin, Sarı, Ömer & Er, 2010; Sarak, 2010,). The questionnaire consisted of two parts: the sociodemographic characteristics of the students were in the first section and questions investigating their virtual behaviors were in the second section. The questions about virtual behaviors were organized into in three main topics areas. Questions about students’ mobile phone and Internet usage were collected in one section. Using a 3‐point Likert‐type questions (never, sometimes, often) the second section contained questions related to cyberbullying behaviors such as threat, mockery, and harassment through both Internet and mobile phone. Under the third title, 2‐point (yes/no‐type) questions assessed the cyber victimization of the adolescents and the status of exposure to behaviors like threat, mocking, and harassment through both the Internet and mobile phone.
The Brief Symptom Inventory (BSI) was used for self‐report of the adolescents. The Brief Symptom Inventory (BSI) is a Likert‐type self‐assessment inventory developed by Derogatis (1992) for the purpose of screening mental health symptoms. The BSI comprises nine subscales; somatization, obsession compulsion, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism (Derogatis, 1992). The validity and reliability study of the scale in turkish adolescents was carried out by N. H. Şahin and Durak (1994). N. H. Şahin and Durak (1994) reported that five subscales (anxiety, depression, negative self‐ esteem, somatization, and hostility) was more suitable for student group. High total scores obtained from the scale indicates the frequency of the symptoms experienced by the individual. In each subscale, an individual can obtain maximum four and minimum zero points. Mean scores that approach four reflect severe symptoms; scores that approach zero reflect low symptom profiles. The Cronbach’s α reliability coefficient of the BIS was .94 in the Turkish version. In this study Cronbach’s α coefficient of the scale was calculated as .96.
1.3 | Data collection
Before starting to the study, the data collection form was trailed by the researcher with 10 adolescents studying in another high school outside the region where the study was conducted. As a result of the preliminary application, no changes were made in the data collection form. A brief explanation was provided to the students by the researcher and then verbal consents were obtained from the students who agreed to participate in the study. The data collection tools were distributed to the students by the researchers. A researcher stayed in the class during the completion of the forms to ensure that there is no interaction between the students. The standard instruction and procedure was repeated by the researcher in all student groups. All forms were completed within one course hour.
1.4 | Data analysis
The data obtained in the study were analyzed using the SPSS/20.0 (Statistical Package for the Social Sciences) program. While the obtained data were evaluated using descriptive statistics (mean, standard deviation, percentage), the data showing normal distribu-tion were evaluated by using one‐way analysis of variance and independent samples t test. Significance level was accepted as p < .05.
1.5 | Ethical considerations
Before starting the study, ethics committee approval from Non-invasive Clinical Trials Ethics Committee and written permission from the schools where the study was conducted were obtained. In addition, permission was obtained from the authors for the availability of the scale. Consents of the individuals participating in the study were obtained by reading the consent form to the students; their voluntary participations were ensured.
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R E S U L T S
2.1 | Virtual behaviors of the adolescents
It was found that 77% of the adolescents had computers in their homes, 46% had their own computers and 60% started to use computer between the ages of 8–11. Adolescents use computers daily on average approximately 49 min and Internet with a daily average of 139.94 min. It was also determined that 76% of the adolescents used the Internet at home, 16% used it in an Internet café, and 8% used Internet in the school.
When their distributions of the adolescents according to the purposes of Internet use were examined, it was determined that the majority of the adolescents (80%) used Internet for social media (Facebook/Skype/Twitter, etc.), 75% for studying, and 51% for gaming. When the rules established by the family about the Internet usage were questioned, it was found that 47% had rules established by the family about using the Internet.
Eighty seven percent of the adolescents had their own mobile phone and they used the mobile phones mostly for communication (talking and messaging; 63%) followed by social media use (50%) and game playing (32%), respectively. Adolescents were on the phone with an average of 53 min/d, received an average of 40 messages, and send an average of 41 messages.
When cyberbullying behaviors of the adolescents were evalu-ated; about half (49%) of the students stated that they had engaged in cyberbullying behaviors, 8% said that they sometimes sent messages with virus to the other people on the Internet, 20% expressed that they sometimes mocked other people via mobile phone or Internet, 8% said that they sometimes published the name or the photos of a person they wanted to harm without his/her permission on different sites. In addition 12% stated that they sometimes introduced themselves as someone else, 12% stated that they sent insulting messages via mobile phone or Internet to other
people or friends, 19% stated that they sometimes disturbed other people from the mobile phone a private number, 9% stated that they sometimes sent threatening messages to the other people via mobile phone or Internet, and 11% said that they sometimes distributed the negative information obtained about someone through Internet (Facebook/Skype/Twitter). Fifty percent of the students performing cyberbullying used these behaviors for entertainment, 26% for revenge, and 24% used them when they were bored.
Of the adolescents, 61% reported that they were exposed to cyberbullying 31% said that they received messages with viruses, 21% said that they were mocked through mobile phone or Internet (Facebook/Twitter/Skype), 13% said that their photos were pub-lished without their permissions, 15% said that they received threatening messages from mobile phone or Internet, 42% stated that they were bothered with a private number on their mobile phone, and 19% stated that unpleasant and untrue rumors were published in the Internet (Facebook/Twitter/Skype) about them. Of the students who were exposed to cyberbullying, 48% stated that they felt anger, 27% stated that they were sad, 23% stated that they wanted revenge, and 16% stated the they were afraid.
2.2 | BSI mean scores and virtual behaviors
of the adolescents
The mean scores obtained by the adolescents from the Brief Symptom Inventory (BSI) were found as 1.03 ± 0.76 for anxiety, 1.27 ± 0.96 for depression; 0.96 ± 0.76 for negative self‐esteem; 0.74 ± 0.68 for somatization; and 1.33 ± 0.78 for hostility. No statistically significant difference was found between the age of starting to the computer, having their own computer, having rules established by their families for the Internet usage, the daily speaking duration with the mobile phone of the adolescents and the subscale mean scores of the Brief Symptom Inventory (p > .05; see Table 1).
Comparing the daily Internet usage duration and BSI mean scores of the adolescents, it was found that the anxiety (1.18 ± 0.79), depression (1.44 ± 0.87), negative self‐esteem (1.11 ± 0.79), somatization (0.86 ± 0.72), hostility (1.49 ± 0.77) subscale mean scores of the adolescents who used Internet for >1 hour in a day were higher than the adolescents who never used Internet and those who used Internet for ≤1 hr and this difference was statistically significant (p < .001; Table 1).
When the Internet usage purpose of the adolescents and their BSI subscale mean scores were compared, it was found that BSI all subscale mean scores of adolescents who did not use Internet for studying were higher than those who used Internet for studying. All BSI subscale mean scores of the adolescents who used Internet for social media (Facebook/Skype/Twitter, etc.) were higher than those who did not use it for social media and this result was statistically significant (p < .05). Anxiety (1.13 ± 0.76), negative self‐esteem (1.04 ± 0.74), somatization (0.84 ± 0.68), and hostility (1.44 ± 0.78) mean scores of the adolescents who used the Internet for playing games were determined to be higher and statistically significant
T A B L E 1 Comparing The Brief Symptom Inventory mean scores and virtual behaviors of the adolescents Mental symptoms
Characteristic Anxiety X ±SD Depression X ± SD Negative self‐esteem X ± SD Somatization X ± SD Hostility X ± SD The age of starting to the computer use
≤7 years 1.17 ± 0.73 1.38 ± 0.73 1.07 ± 0.69 0.79 ± 0.66 1.49 ± 0.77 8–11 years 1.01 ± 0.73 1.24 ± 0.87 0.95 ± 0.76 0.71 ± 0.66 1.30 ± 0.72 ≥12 years 1.01 ± 0.83 1.28 ± 0.89 0.90 ± 0.78 0.74 ± 0.76 1.29 ± 0.89
F 1.195 0.684 1.011 0.537 1.488
p .304 .505 .365 .585 .227
Having their own computer
Yes 1.04 ± 0.75 1.23 ± 0.85 0.95 ± 0.74 0.70 ± 0.66 1.39 ± 0.80 No 1.02 ± 0.76 1.30 ± 0.86 0.96 ± 0.77 0.77 ± 0.70 1.27 ± 0.75
t 0.259 −0.876 −0.112 −0.938 1.546
p .796 .382 .911 .349 .123
The daily Internet usage duration
None 0.64 ± 0.40 0.87 ± 0.42 0.56 ± 0.39 0.44 ± 0.36 0.93 ± 0.69 ≤1 hr 0.86 ± 0.69 1.07 ± 0.80 0.78 ± 0.69 0.59 ± 0.62 1.13 ± 0.74 >1 hr 1.18 ± 0.79 1.44 ± 0.87 1.11 ± 0.79 0.86 ± 0.72 1.49 ± 0.77
F 11.484 11.707 11.987 9.754 14.012
p <.001*,** <.001*,** <.001*,** <.001*,** <.001*,**
The Internet usage purpose
Studying Yes 0.96 ± 0.69 1.19 ± 0.82 0.88 ± 0.69 0.69 ± 0.63 1.25 ± 0.71 No 1.25 ± 0.88 1.48 ± 0.93 1.15 ± 0.89 0.89 ± 0.81 1.57 ± 0.90
t −3.445 −3.080 −2.789 −2.415 −3.344
p .001 .002 .006 .017 .001
Social media (Facebook/ Skype/Twitter, etc.)
Yes 1.11 ± 0.77 1.34 ± 0.87 1.03 ± 0.78 080 ± 0.71 1.41 ± 0.98 No 0.70 ± 0.61 0.98 ± 0.70 0.66 ± 0.58 0.47 ± 0.45 0.78 ± 0.65
t 5.124 3.953 4.909 5.340 4.593
p <.001 <.001 <.001 <.001 <.001 Playing game Yes 1.13 ± 0.76 1.31 ± 0.83 1.04 ± 0.74 0.84 ± 0.68 1.44 ± 0.78
No 0.92 ± 0.74 1.23 ± 0.89 0.86 ± 0.77 0.63 ± 0.67 1.21 ± 0.76
t 2.896 0.998 2.505 3.282 3.009
p .004 .319 .013 .001 .003
The place where they used the Internet
Home 1.03 ± 0.75 1.27 ± 0.84 0.95 ± 0.73 0.75 ± 0.68 1.34 ± 0.77 Internet cafe 1.17 ± 0.87 1.35 ± 0.99 1.09 ± 0.92 0.82 ± 0.78 1.33 ± 0.88
School 0.75 ± 0.55 1.13 ± 0.72 0.79 ± 0.59 0.44 ± 0.39 1.17 ± 0.61
F 3.483 0.758 1.910 3.957 0.824
p .032***,**** 4.69 .149 .020***,**** .440
The rules established by the family about the Internet usage
Yes 1.04 ± 0.78 1.27 ± 0.86 0.99 ± 0.77 0.79 ± 0.74 1.31 ± 0.80 No 1.02 ± 0.74 1.27 ± 0.86 0.93 ± 0.75 0.69 ± 0.63 1.34 ± 0.75
t 0.182 0.114 0.870 1.392 −0.449
p .856 .909 .385 .165 .654
Having their own mobile phones
Yes 1.04 ± 0.76 1.29 ± 0.86 0.97 ± 0.75 0.73 ± 0.68 1.36 ± 0.79 No 0.97 ± 0.76 1.10 ± 0.81 0.88 ± 0.79 0.77 ± 0.69 1.14 ± 0.64
t 0.723 1.691 0.876 −0.444 2.082
compared to the adolescents who did not use Internet for playing game (p < .05; Table 1).
A significant difference was found between the anxiety and somatization subscale mean scores of the adolescents and the place where they used the Internet (p < .05). The anxiety and somatization subscale mean scores were lower in the students who used Internet at school compared to the adolescents who used Internet at home and in Internet cafes and this was found to be statistically significant (p < .05; Table 1). Hostility subscale mean scores of the adolescents who had their own mobile phones (1.36 ± 0.79) were found to be
higher and statistically significant compared to the adolescents who had no personal mobile phone (1.14 ± 0.64; p < .05; Table 1).
Somatization mean score (0.68 ± 0.63) of the adolescents who used mobile phone for communication purpose was determined to be lower and statistically significant compared to the adolescents who did not use it for communication purpose (0.84 ± 0.77; p < .05). BSI subscale mean scores of the adolescents who used their mobile phones for social media (Facebook/Skype/Twitter, etc.) were higher and statistically significant compared to those who did not use it for social media (p < .001). No significant difference was found between T A B L E 1 (Continued)
Mental symptoms
Characteristic Anxiety X ±SD Depression X ± SD Negative self‐esteem X ± SD Somatization X ± SD Hostility X ± SD
p .470 .092 .381 .657 .038
The daily speaking duration with the mobile phone
None 1.00 ± 0.79 1.24 ± 0.90 0.92 ± 0.79 0.76 ± 0.78 1.24 ± 0.74 ≤1 hr 0.99 ± 0.73 1.22 ± 0.82 0.94 ± 0.76 0.68 ± 0.64 1.30 ± 0.76 >1 hr 1.17 ± 0.79 1.45 ± 0.89 1.03 ± 0.72 0.89 ± 0.68 1.51 ± 0.84
F 1.597 2.275 0.540 2.982 2.910
p .204 .104 .583 .052 .056
The mobile phone usage purpose Communication (talking and messaging)
Yes 0.98 ± 0.71 1.22 ± 0.81 0.91 ± 0.69 0.68 ± 0.63 1.34 ± 0.76 No 1.12 ± 0.83 1.36 ± 0.92 1.04 ± 0.85 0.84 ± 0.77 1.32 ± 0.81
t −1.721 −1.679 −1.641 −2.183 0.243
p .086 .094 .102 .030 .808
Social media (Facebook/ Skype/Twitter, etc.)
Yes 1.17 ± 0.81 1.41 ± 0.88 1.07 ± 0.76 0.85 ± 0.75 1.45 ± 0.82 No 0.89 ± 0.67 1.12 ± 0.80 0.84 ± 0.74 0.62 ± 0.59 1.20 ± 0.70
t 3.798 3.580 3.296 3.500 3.406
p <.001 <.001 .001 .001 .001
Playing game Yes 1.12 ± 0.76 1.38 ± 0.84 1.04 ± 0.76 0.81 ± 0.70 1.40 ± 0.79
No 0.99 ± 0.75 1.22 ± 0.86 0.91 ± 0.76 0.70 ± 0.67 1.29 ± 0.77 t 1.744 1.787 1.625 1.575 1.452 p .082 .075 .105 .116 .147 Cyberbullying Yes 1.27 ± 0.82 1.45 ± 0.91 1.17 ± 0.83 0.89 ± 0.76 1.57 ± 0.83 No 0.79 ± 0.61 1.09 ± 0.76 0.75 ± 0.61 0.58 ± 0.57 1.09 ± 0.64 t 6.746 4.346 5.883 4.906 6.530 p <.001 <.001 <.001 <.001 <.001 Exposed to cyberbullying Yes 1.22 ± 0.82 1.44 ± 0.91 1.13 ± 0.82 0.88 ± 0.76 1.52 ± 0.79 No 0.74 ± 0.53 1.01 ± 0.69 0.68 ± 0.56 0.52 ± 0.49 1.04 ± 0.65 t 7.451 5.575 6.775 5.913 6.703 p <.001 <.001 <.001 <.001 <.001
Abbreviation: SD, standard deviation. *p < .05 (none vs. >1 hr).
**p < .05 (≤1 vs. >1 hr). ***p < .05 (home vs. school). ****p < .05 (Internet cafe vs. home).
the BSI subscale mean scores of adolescents using their mobile phones for gaming (p > .05; Table 1).
A significant correlation was found between the all subscale scores of adolescents and their status of performing cyberbullying (p < .001). Anxiety (1.27 ± 0.82), depression (1.45 ± 0.91), negative self‐esteem (1.17 ± 0.83), somatization (0.89 ± 0.76), and hostility (1.57 ± 0.83) mean scores of the adolescents stating that they performed cyberbullying were higher than the adolescents stating that they did not perform any cyberbullying and this difference was determined to be statistically significant (p < .001; Table 1).
Anxiety (1.22 ± 0.82), depression (1.44 ± 0.91), negative self‐ esteem (1.13 ± 0.82), somatization (0.88 ± 0.76), and hostility (1.52 ± 0.79) subscale mean scores of the adolescents who stated that they were exposed to cyberbullying were higher than the adolescents who stated that they were not exposed to cyberbullying and this difference was statistically significant (p < .001; Table 1).
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D I S C U S S I O N
Adolescent mental health is affected by ever changing and developing mental, physical and social competences, critical periods, and environmental factors (Yılmaz & Türkleş, 2015). An important environmental factor affecting young people today is technological tools. In this study Internet and mobile phone usage was a very common behavior among adolescents. Almost half of the adolescents (49%) who participated in the study performed cyberbullying behaviors, and more than half of them (61%) were exposed to cyberbullying. These results were much higher than the level of cyberbullying reported in previous studies (Lee & Shin, 2017; Ortega Ruiz, Calmaestra Villén & Mora Merchán, 2008; Schenk & Fremouw, 2012; Smith et al., 2008). However, there are also studies that support the rates reported in this study (Arıcak, 2009; Calvete, Orue, Estévez, Villardón, & Padilla, 2010; Juvonen & Gross, 2008). The high rate of cyberbullying in the present study could be related to the timing of this study. As new technologies emerge and access of adolescents to the technological tools increases, the possibility of being exposed to more cyberbullying also increases; as such cyberbullying behavior becomes a more common problem (Brewer & Kerslake, 2015; Calvete et al., 2010; Cénat et al., 2014; Schenk & Fremouw, 2012).
Even though the development of the Internet is a largely positive impact, the use of Internet for prolonged periods without leaving your place or using Internet so that you neglect or delay the activities related to everyday life brings a number of problems (Ceyhan, 2008). In the present study, anxiety, depression, negative self‐esteem, somatization and hostility mean scores were found to be higher in the adolescents using Internet for more than 1 hour a day compared to the adolescents using Internet for an hour or less in a day. Studies support these results and demonstrate that there is a significant correlation between the mental health and Internet usage (Choi, Park, & Cha, 2017; Lai et al., 2015; Ying & Zhang, 2015). In the previous studies,
excessive Internet use of adolescents was found to be associated with depression (Ho et al., 2014), hostility (Alpaslan, Avcı, Soylu & Guzel, 2014), anxiety (Ho et al., 2014), somatization (Cerutti, Presaghi, Spensieri, Valastro, & Guidetti, 2016), attention‐deficit hyperactivity disorder (Yen, Ko, Yen, Wu, & Yang, 2007), and suicidal ideation (Alpaslan et al., 2014; I. H. Lin et al., 2014). Messias, Castro, Saini, Usman, and Peeples (2011) found that the sadness, suicidal ideation, and suicide attempts of young people were significantly higher in adolescents who played Internet or video games for 5 hr or more in a day. Although the Internet offers different advantages to the adolescents such as updating themselves, helping them in their works, solving their problems and establishing good relationships with others (Rayan et al., 2017), there is a risk of being affected by its unsupervised use especially for the individuals with low psychological health (Rayan et al., 2017) and adolescents (Kuss, van Rooij, Shorter, Griffiths & van de Mheen, 2013).
In the study, it was found that anxiety, depression, negative self‐esteem, somatization and hostility mean scores were high for the adolescents using Internet for social media and or who used Internet to play games. Researchers have reported that the use of social networks such as Facebook, Twitter, or Instagram, and playing game on the Internet are associated with mental health problems of adolescents such as depression, psychological distress, and suicidal ideation (Mentzoni et al., 2011; Pantic et al., 2012; Sampasa‐Kanyinga & Lewis, 2015; L. Y. Lin et al., 2016). On the contrary, there are studies showing that social media use is related with less loneliness, higher self‐esteem, and life satisfaction (Pittman & Reich, 2016; Seabrook, Kern, & Rickard, 2016). Playing games on the Internet also increases cooperation and decreases aggressiveness (Gentile, 2009; Greitemeyer, Agthe, Turner, & Gschwendtner, 2012). However, it should be kept in mind that for young people with lower psychological health, use social media in the search for interaction or support may increase their risk of cyber victimization (Sampasa‐Kanyinga & Hamilton, 2015).
In the present study, it was found that the place where the adolescents used the Internet was associated with their self‐ reported mental health. The somatization and anxiety mean scores of the adolescents using Internet at school was lower than the adolescents using Internet at home or in Internet café. In this context, the use of Internet under the supervision of teacher at school or the family at home seems related to less self‐reported mental distress among the study participants. Perhaps adolescents avoided risky virtual behaviors because of measures taken by schools such as the presence of programs performing the Internet access, school policies around computer use, and the supervision of all classroom computers. In the study by Çınkır and Tan (2010), the possibility of using computer games and programs containing harmful contents such as violence or pornography was reported to be higher in Internet cafes with no supervision. In this context, to eliminate these negative virtual behaviors, it is important to provide education to families and
students around safe Internet usage. Families should guide their children about this issue and establish rules about Internet usage. Another important issue is mobile phone usage. Mobile phones can be used for communication everywhere and adolescent can be online at any time. Mobile phones are used by adolescents to communicate, message with each other, play games, take pictures, and connect to the Internet (Tavakolizadeh, Atarodi, Ahmadpour, & Pourgheisar, 2014). Along with the benefits of using mobile phones, there are concerns about their overuse (Vacaru, Shepherd, & Sheridan, 2014). Recently, the problematic use of mobile phones has attracted the attention of researchers and to some, is considered equivalent to drug addiction (Nikhita, Jadhav, & Ajinkya, 2015). Researchers have shown that the use of uncontrolled mobile phone is associated with loneliness (Tan, Pamuk, & Dönder, 2013), anxiety, depression (Tavakolizadeh et al., 2014), aggressive behaviors, insomnia, smoking, suicidality, and low self‐esteem (Yang, Yen, Ko, Cheng, & Yen, 2010). The present study supports these findings: the hostility subscale mean score of the adolescents who have their own mobile phones was found to be high, whereas the anxiety, depression, negative self‐esteem, somatization, and hostility mean scores were found to be high in adolescents using their mobile phones for social media.
Cyberbullying is one of the virtual behaviors associated with technology that has potentially devastating effects on the wellbeing of adolescents and affect their mental health (Spears et al., 2015). In the present study, anxiety, depression, negative self‐esteem, soma-tization, and hostility subscale mean scores were found to be high for the adolescents who enacted cyberbullying and those who were exposed to cyberbullying. The results of the study support the literature and cyberbullying negatively affects the mental health of adolescents (Fahy et al., 2016; Holfeld & Sukhawathanakul, 2017; Landoll et al., 2015; Sari & Camadan, 2016; Ybarra & Michell, 2004; Vieno et al., 2014; Wang et al., 2011).
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L I M I T A T I O N S
There were several limitations in this study. First, the cross‐sectional research design of this study limited our ability to draw conclusions regarding causal relationships between mental health and certain correlates examined in this study. Second, the data were provided by adolescent participants. Thus, the possible problem of shared method variance resulting from a sole data source requires careful consideration. Third, cyberbullying behaviors were self‐report with-out the use of structured assessment tools. In future research, the use of structured data collection form will provide objective data about cyberbullying behaviors.
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N U R S I N G I M P L I C A T I O N S
School health nurses are obligated to ensure the safety of adolescents from vulnerable groups, as well as balancing the
response they give to the negative consequences of technology usage. For this reason, it is very important to determine early the psychological and behavioral problems which are the result of the adolescent’s virtual behaviors and to plan to care for them.
A C K N O W L E D G M E N T
The researchers express their sincere appreciation to the partici-pants who generously shared their experiences and took time to complete the survey.
C O N F L I C T O F I N T E R E S T S
The authors declare that there are no conflict of interests.
O R C I D
Pelin Calpbinici http://orcid.org/0000-0001-8242-2773
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How to cite this article: Calpbinici P, Tas Arslan F. Virtual behaviors affecting adolescent mental health: The usage of Internet and mobile phone and cyberbullying. J Child Adolesc Psychiatr Nurs. 2019;32:139–148.
