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Internet Addiction Among Adolescents With Attention-Deficit/Hyperactivity Disorder
MAKALE #22463 © Yazan Dr.Melek Gözde LUŞ | Yayın Temmuz 2021 | 452 Okuyucu
Cukurova Medical Journal Cukurova Med J 2019;44(Suppl 1):140-147
ÇUKUROVA ÜNİVERSİTESİ TIP FAKÜLTESİ DOI: 10.17826/cumj.551351
Yazışma Adresi/Address for Correspondence: Dr. Melek Gözde Luş, Haydarpaşa Numune Training and Research
Hospital, University of Health Science, Department of Child and Adolescent Psychiatry. Istanbul, Turkey
E-mail: gozdelus@yahoo.com
Geliş tarihi/Received: 09.04.2019 Kabul tarihi/Accepted: 05.07.2019 Çevrimiçi yayın/Published online: 24.09.2019
ARAŞTIRMA / RESEARCH
Internet addiction among adolescents with attention-deficit/hyperactivity disorder
Dikkat eksikliği/hiperaktivite bozukluğu olan ergenlerde internet bağımlılığı
Melek Gözde Luş1, Meliha Zengin Eroğlu2
1Haydarpaşa Numune Training and Research Hospital, University of Health Science, Child and Adolescent Psychiatrist, Department of Child and Adolescent Psychiatry. 2Department of Psychiatry. Istanbul, Turkey
Cukurova Medical Journal 2019;44(Suppl 1):140-147.
Abstract
Öz
Purpose: The aim of the present study was to evaluate the relationship between Internet addiction (IA) and attention-deficit/hyperactivity disorder (ADHD) among adolescents.
Materials and Methods: The study was conducted with adolescents aged 12–17; ADHD group consisted of 100 children were diagnosed with ADHD and the control group of the study consisted of 95 children who did not have any psychiatric diagnosis. A total of 195 adolescents completed the Young Internet Addiction Scale (YIAS) and were assessed for ADHD symptoms. Personal Information Questionnaire was used to obtain information about characteristics of internet usage.
Results: The average YIAS score of ADHD group is 30.97±17.74 and found to be significantly higher than the control group. The most preferred website by the ADHD group is computer game sites (35%). ADHD group prefer to play adventure games mostly (27%)There is no statistically significant difference between the groups in terms of parent’s control rate of internet usage, disrupting effect of internet usage on daily activity, rate of negative effects of internet usage on family relations and friendship relations and effects of internet usage on eating and sleeping habits.
Conclusion: As we know from previous studies, the association between IA and reward deficiency is also related with the high frequency of comorbid ADHD but our results are incompatible with the literature related to internet addiction and excessive use of the internet. It is considered that prospective longitudinal studies with larger groups are needed.
Amaç: Bu çalışmanın amacı, ergenler arasında İnternet bağımlılığı (IA) ile dikkat eksikliği/hiperaktivite bozukluğu (DEHB) arasındaki ilişkiyi değerlendirmektir.
Gereç ve Yöntem: Çalışma 12-17 yaş arası ergenler ile yapıldı; DEHB grubu 100 çocuktan, DEHB tanısı almış, çalışmanın kontrol grubu ise herhangi bir psikiyatrik tanı konmamış 95 çocuktan oluşmaktadır. Toplam 195 Ergen Genç İnternet Bağımlılığı Ölçeğini (YIAS) tamamlamış ve DEHB belirtileri için değerlendirilmiştir. İnternet kullanımının özellikleri hakkında bilgi edinmek için Kişisel Bilgi Anketi kullanılmıştır.
Bulgular: DEHB grubunun ortalama YIAS skoru 30.97 ± 17.74 olup kontrol grubundan anlamlı olarak yüksek bulundu. DEHB grubunun en çok tercih ettiği internet sitesi bilgisayar oyun siteleridir (% 35). DEHB grubu çoğunlukla macera oyunu oynamayı tercih etmektedir (% 27). Gruplar arasında ebeveynlerin internet kullanımı kontrol oranı, internet kullanımının günlük aktivite üzerindeki etkisinin bozulması, internet kullanımının aile ve arkadaş ilişkileri üzerindeki olumsuz etkisi açısından istatistiksel olarak anlamlı bir fark yoktur. Aynı şekilde internet kullanımının yeme ve uyku alışkanlıkları üzerinde de olumsuz bir etkisi saptanmamıştır.
Sonuç: Daha önceki çalışmalardan da bildiğimiz gibi, IA ile ödül eksikliği arasındaki ilişki de yüksek eşlik eden DEHB sıklığı ile ilişkilidir ancak sonuçlarımız internet bağımlılığı ve aşırı internet kullanımı ile ilgili literatürle uyumlu değildir
Keywords: Attention deficit/hyperactivity disorder, Internet addiction, adolescent, comorbidity
Anahtar kelimeler: Dikkat eksikliği / hiperaktivite bozukluğu, İnternet bağımlılığı, ergen, komorbidite.
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INTRODUCTION
Problematic internet use or internet addiction (IA) are terms most commonly used when referring to loss of control over or maladaptive patterns of internet use leading to clinically significant impairment or distress1,2. The high heterogenity makes it difficult to define these behaviors and other terms have been used to describe this phenomenon include ‘compulsive internet use’, ‘pathological internet use’ and ‘internet dependency’3. Studies suggest that overall prevalence of IA in adolescents ranges between 2% and 18%4,5. There is significant association between IA and Attention Deficit and Hyperactivity Disorder (ADHD) symptoms in adolescents6. Furthermore, IA is frequently related to psychiatric disorders and ADHD is the most common psychiatric disorder among adolescents with IA7. The presence of psychiatric comorbidities may have negative impact on psychosocial functioning and treatment outcome for IA. Several researchers have tried to construct diagnostic criteria for IA. There was no consensus on IA diagnostic criteria until the American Psychiatric Association (APA) proposed the Internet Gaming Disorder (IGD) in Section III of DSM-5 in 2013 as a condition for further study8. Heterogenity of internet use includes a variety of activities such as gaming, cybersex, downloading, social networking and gambling. Addiction to specific internet activities make it difficult to identify a distinct pathophysiology and it has been claimed that the term ‘internet addiction’ should be replaced by addictions to specific internet activities9. DSM-5 proposed the diagnostic criteria of IGD to define addiction to Internet gaming but it should be considered that IGD is different concepts from IA8. According to the lack of reward hypothesis, individuals who do not provide enough satisfaction with natural rewards (water, food, sexuality) turn to the substances and behaviors that stimulate the reward path10. It is known that internet use is a quick reward with a short delay providing more reward seeking and behavioral motivation wich impulsivity is seen as a risk factor. Impulsivity can be seen as a major factor contributing to substance use disorder as in ADHD and it has been proposed that impulsivity is involved in vulnerability to substance addiction among individuals with ADHD11, 12, 13,14. In terms of IA and ADHD coexistence the adverse influence of ADHD on social relationships that persist into adolescence and internet use can provide social support. Some researchers argued that there is a relationship between social skills deficits and IA in adolescents with ADHD15. In the light of increasing evidence of strong relationship between IA and ADHD, and both previous cross-sectional and prospective studies, it can be said that adolescents diagnosed with ADHD are under a higher risk of IA than those without ADHD.
In our study, we aimed to investigate whether there is a significant difference between the levels of computer game addiction in children with and without diagnosis of ADHD. The presence of psychiatric comorbidities may have further impact on psychosocial functioning and treatment outcome for IA and this highly heterogeneous spectrum of addictive behavior related to internet activities deserves further research.
MATERIALS AND METHODS
Participants
Participants were recruited from a clinical sample of adolescents aged 12–17 years who were consecutively referred to our Child and Adolescent Psychiatry outpatient clinic in Haydarpaşa Numune Training and Research Hospital. The study sample for the ADHD group was consisted of 100 children diagnosed with ADHD for first time and free from any psychiatric treatment. Adolescents with comorbid any psychiatric disorders like depression, anxiety disorders, bipolar and related disorders, obsessive and compulsive disorders and related disorders, schizophrenia, autism spectrum disorder and the related diagnosis of social communication disorder, mental retardation and substance addiction were excluded from the study. The control group of the study consisted of 95 children aged between 12 and 17 years who consecutively referred to the same clinic with any psychiatric complaints and decided that they have any significant psychiatric diagnosis after psychiatric examination.
Procedure
Comprehensive information obtained from a clinical examination which included interviews with both youth and parent. Written informed consent about the study was signed by parent for each adolescent. Adolescents and their families were informed that they have the right to withdraw from the study if
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they wanted to do so. All participants examined by same child and adolescent psychiatrist. ADHD diagnose was based on the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V; APA, 2013) criteria (18). The personal information questionnaire developed for this research and Young’s Internet Addiction Scale were applied to all 195 adolescents.
Measures
Young’s Internet Addiction Scale (YIAS)
The YIAS is a self-report questionnaire composed of 20 questions with a 5-point Likert scale ranging from 1 (rarely) to 5 (always). The scale was translated and adapted to Turkish language by Bayraktar16,17. The 20 items of the YIAS are calibrated, with scores ranging from 20 to 100, with higher scores reflecting a greater tendency toward addiction. Three types of internet use were identified; IA, limited symptoms and no symptoms. The corresponding scores were; >80, 50–79 and <50, respectively. Cut-off points of the YIAS may differ from one country to another based on the internet use style of the culture. The cut-off point of the Turkish YIAS was reported as < 80. The internal consistency of the Turkish YIAS is 0.91.
Personal Information Questionnaire
The personal information form prepared by researchers, in order to learn the sociodemographic informations of the participants. The participants were asked to provide their information about the participant’s level of class, gender, family internet usage characteristics (time spent at internet, places where the internet is used, purposes of internet usage, most prefered computer games and websites they used).
Statistical analysis
IBM SPSS Statistics 22 for statistical analysis (SPSS IBM, Turkey) programs were used to analyze data. The convenience of the parameters to normal distribution was evaluated by Shapiro Wilks test. In the comparison of two groups of the parameters which are normally distributed in the comparison of the quantitative data, as well as the descriptive statistical methods (mean, standard deviation, frequency) Student t-test was used. Chi-square test, fisher exact test, fisher freeman halton test and continuity (Yates) correction were used to compare qualitative data. Significance was evaluated as p <0.05.
RESULTS
82 (42.3%) girls and 112 (57.7%) boys were included in the study. 51.3% of the participants consitituted ADHD group(n=100). The rest of 195 participants (48.7%) consisted control group(n=95). The proportion of adolescents aged 12-14 years in the ADHD group (%69.7) is higher than the control group (p=0.022). Sociodemographic variables of the sample are seen in Table 1.
Mean YIAS score of ADHD group was 30.97±17.74 points and significantly higher than control group (p=0.044). Rate of getting disciplinary punishment during the lifetime at hyperactivity group was found to be significantly higher than the control group (%32 vs %12.6 p: 40,000). There was no statistically significant difference between the groups in terms of school achievement, distribution of activities of leisure time, rates of having a mobile phone, distribution of places of residence. Rate of having an internet connection in mobile phone was significantly lower in ADHD group (%70.1 vs %83.2) (Table 1).
There was no statistically significant difference between groups in terms of having a computer at home and internet usage rates (p>0.05). Rate of using internet for 9 years and over, the rate of using internet at home and spending 5-10 hours times per week on internet were found to be statistically lower in ADHD group (p<0.05). General characteristics of computer and internet use among groups shown at Table 2.
ADHD group had a significantly higher rate of using internet “always” to play games than the control group (19% vs 4.2%) Children with ADHD are always more likely to use the internet to play games than the control group (p=0.001). The rates of using the internet mostly for non-purposeful use, using for watching videos, using for chatting, using to enter social networking sites, and using for studying / doing research are lower in the ADHD group compared to the control group (Table 3).
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Table 1. General characteristics of groups.
ADHD group
Control group
Total
n (%)
n (%)
n (%)
YIAS Scores
30.97±17.74
26.37±13.85
28.73±16.09
Age
12-14
69 (69.7%)
51 (53.7%)
120 (61.9%)
15-17
30 (30.3%)
44 (46.3%)
74 (38.1%)
Gender
Female
21 (21.2%)
61 (64.2%)
82 (42.3%)
Male
78 (78.8%)
34 (35.8%)
112 (57.7%)
School Grade
5
4 (4%)
0 (0%)
4 (2.1%)
6
13 (13.1%)
0 (0%)
13 (6.7%)
7
15 (15.2%)
16 (16.8%)
31 (16%)
8
20 (20.2%)
33 (34.7%)
53 (27.3%)
9
22 (22.2%)
14 (14.7%)
36 (18.6%)
10
15 (15.2%)
30 (31.6%)
45 (23.2%)
11
8 (8.1%)
2 (2.1%)
10 (5.2%)
12
2 (2%)
0 (0%)
2 (%1)
Disciplinary penalty
Yes
31 (32%)
12 (12.6%)
43 (22.4%)
No
66 (68%)
83 (87.4%)
149 (77.6%)
School performance
Very good
9 (9.3%)
12 (12.6%)
21 (10.9%)
Good
30 (30.9%)
43 (45.3%)
73 (3%8)
Average
49 (50.5%)
34 (35.8%)
83 (43.2%)
Bad
6 (6.2%)
6 (6.3%)
12 (6.3%)
Very bad
3 (3.1%)
0 (0%)
3 (1.6%)
Academic achievement
Bad
9 (9.3%)
4 (4.2%)
13 (6.8%)
Average
50 (51.5%)
37 (38.9%)
87 (45.3%)
Good
30 (30.9%)
45 (47.4%)
75 (39.1%)
Very good
8 (8.2%)
9 (9.5%)
17 (8.9%)
Place of living
Public dorm
4 (4.1%)
3 (3.2%)
7 (3.6%)
Private dorm
2 (2.1%)
0 (0%)
2 (1%)
Rental House
28 (28.9%)
20 (21.1%)
48 (25%)
Parent’s own house
63 (64.9%)
72 (75.8%)
135 (70.3%)
Table 2. Characteristics of computer and internet use among groups
ADHD group
Control group
Total
n (%)
n (%)
n (%)
Having computer at home
Yes
82 (87.2%)
80 (84.2%)
162 (85.7%)
No
12 (12.8%)
15 (15.8%)
27 (14.3%)
Using internet
Yes
83 (89.2%)
92 (96.8%)
175 (93.1%)
No
10 (10.8%)
3 (3.2%)
13 (6.9%)
Internet usage rates
Less than 1 year
9 (9.8%)
2 (2.1%)
11 (5.9%)
1-2 years
20 (21.7%)
12 (12.6%)
32 (17.1%)
3-4 years
23 (25%)
19 (20%)
42 (22.5%)
5-6 years
20 (21.7%)
16 (16.8%)
36 (19.3%)
7-8 years
14 (15.2%)
18 (18.9%)
32 (17.1%)
More than 9 years
6 (6.5%)
28 (29.5%)
34 (18.2%)
Place of where internet most used
Internet cafe
6 (6.5%)
0 (0%)
6 (3.2%)
Home
73 (79.3%)
86 (90.5%)
159 (85%)
Schooll
3 (3.3%)
5 (5.3%)
8 (4.3%)
Other
6 (6.5%)
3 (3.2%)
9 (4.8%)
Both home and internet cafe
4 (4.3%)
1 (1.1%)
5 (2.7%)
The average time spent online per week
Less than 2 hours
16 (17.4%)
3 (3.2%)
19 (10.2%)
2,5-5 hours
21 (22.8%)
31 (32.6%)
52 (27.8%)
5-10 hours
24 (26.1%)
36 (37.9%)
60 (32.1%)
10-15 hours
15 (16.3%)
12 (12.6%)
27 (14.4%)
More than 15 hours
16 (17.4%)
13 (13.7%)
29 (15.5%)
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Most preferred sites on the Internet
Computer game
35 (35%)
22 (23.2%)
57 (29.2%)
Music
24 (24%)
29 (30.5%)
53 (27.2%)
Educational
10 (10%)
5 (5.3%)
15 (7.7%)
Chat
9 (9%)
16 (16.8%)
25 (12.8%)
Movie
12 (12%)
13 (13.7%)
25 (12.8%)
Spor
3 (3%)
6 (6.3%)
9 (4.6%)
Science and technology
0 (0%)
3 (3.2%)
3 (1.5%)
Other
7 (7%)
1 (1.1%)
8 (4.1%)
Most preferred computer games
Sports
17 (17%)
11 (11.6%)
28 (14.4%)
Racing
16 (16%)
21 (22.1%)
37 (19%)
Adventure
27 (27%)
15 (15.8%)
42 (21.5%)
Shooter
8 (8%)
0 (0%)
8 (4.1%)
Puzzle
7 (7%)
12 (12.6%)
19 (9.7%)
Fighting
15 (15%)
19 (20%)
34 (17.4%)
Other
10 (10%)
17 (17.9%)
27 (13.8%)
Table 3. Puposes of using internet among groups.
ADHD group
Control group
Total
n (%)
n (%)
n (%)
Aimlessly Surfing
Always
14 (14%)
7 (7.4%)
21 (10.8%)
Mostly
18 (18%)
34 (35.8%)
52 (26.7%)
Sometimes
28 (28%)
30 (31.6%)
58 (29.7%)
Very rare
24 (24%)
13 (13.7%)
37 (19%)
Never
16 (16%)
11 (11.6%)
27 (13.8%)
Watching video
Always
27 (27%)
12 (12.6%)
39 (20%)
Mostly
31 (31%)
49 (51.6%)
80 (41%)
Sometimes
22 (22%)
25 (26.3%)
47 (24.1%)
Very rare
16 (16%)
9 (9.5%)
25 (12.8%)
Never
4 (4%)
0 (0%)
4 (2.1%)
Chatting
Always
21 (21%)
13 (13.7%)
34 (17.4%)
Mostly
15 (15%)
39 (41.1%)
54 (27.7%)
Sometimes
24 (24%)
27 (28.4%)
51 (26.2%)
Very rare
30 (30%)
12 (12.6%)
42 (21.5%)
Never
10 (10%)
4 (4.2%)
14 (7.2%)
Studying / doing research
Always
19 (19%)
11 (11.6%)
30 (15.4%)
Mostly
20 (20%)
30 (31.6%)
50 (25.6%)
Sometimes
29 (29%)
43 (45.3%)
72 (36.9%)
Very rare
28 (28%)
9 (9.5%)
37 (19%)
Never
4 (4%)
2 (2.1%)
6 (3.1%)
Gaming
Always
19 (19%)
4 (4.2%)
23 (11.8%)
Mostly
26 (26%)
21 (22.1%)
47 (24.1%)
Sometimes
21 (21%)
32 (33.7%)
53 (27.2%)
Very rare
23 (23%)
14 (14.7%)
37 (19%)
Never
11 (11%)
24 (25.3%)
35 (17.9%)
Using social networking sites
Always
16 (16%)
15 (15.8%)
31 (15.9%)
Mostly
17 (17%)
41 (43.2%)
58 (29.7%)
Sometimes
24 (24%)
26 (27.4%)
50 (25.6%)
Very rare
31 (31%)
10 (10.5%)
41 (21%)
Never
12 (12%)
3 (3.2%)
15 (7.7%)
Table 4 shows that, there is no statistically significant difference between the groups in terms of rates of having a mobile phone however, the rate of having an internet connection in mobile phone in ADHD group is significantly lower than the control group (p=0.049). There is no statistically significant difference between the groups in terms of parent’s control rate of internet usage (p=0.221), disrupting
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effect of internet usage on daily activity (p=0.094), rate of negative effects of internet usage on family relations (p=0.280) and friendship relations (p=0.924) and effects of internet usage on eating (p=0.145) and sleeping habits (p=0.311).
Table 4. Other parameters between groups.
ADHD group
Control group
Total
n (%)
n (%)
n (%)
Having mobile phone
Yes
77 (79.4%)
85 (89.5%)
162 (84.4%)
No
20 (20.6%)
10 (10.5%)
30 (15.6%)
Having internet connection on mobile phone
Yes
68 (70.1%)
79 (83.2%)
147 (76.6%)
No
29 (29.9%)
16 (16.8%)
45 (23.4%)
Parental control of Internet usage
Yes
64 (69.6%)
57 (60%)
121 (64.7%)
No
28 (30.4%)
38 (40%)
66 (35.3%)
Disrupting effect of internet usage on daily activity
Yes
34 (34%)
22 (23.2%)
56 (28.7%)
No
66 (66%)
73 (76.8%)
139 (71.3%)
Negative effects of internet usage on family relations
Yes
30 (30%)
22 (23.2%)
52 (26.7%)
No
70 (70%)
73 (76.8%)
143 (73.3%)
Negative effects of internet usage on friendship relations
Yes
6 (6%)
7 (7.4%)
13 (6.7%)
No
94 (94%)
88 (92.6%)
182 (93.3%)
Affecting relationships with teachers
Yes
8 (8%)
4 (4.2%)
12 (6.2%)
No
92 (92%)
91 (95.8%)
183 (93.8%)
Effects of internet usage on sleeping habits
Yes
32 (32%)
37 (38.9%)
69 (35.4%)
No
68 (68%)
58 (61.1%)
126 (64.6%)
Effects of internet usage on eating habits
Yes
15 (15%)
7 (7.4%)
22 (11.3%)
No
85 (85%)
88 (92.6%)
173 (88.7%)
DISCUSSION
The previous studies about IA report high rates of comorbidity with ADHD. Beside this, it has also been reported that severity of ADHD symptoms predict the severity of IA symptoms7,18,19,20. In the present study, we found that adolescents with ADHD had significantly higher YIAS score than control group. The average YIAS score of ADHD group was 30.97±17.74 in our study. So according to cut off points they have no symptoms about IA. Enagandula R et al. (2018) found mean YIAT score of 50 children with ADHD was 50 and of 50 normal children was 3021.They showed that, in the ADHD group, children having higher scores on YIAT also have higher mean duration of internet usage.In contrast, we found the rate of using internet for 9 years and over, the rate of using internet at home and spending 5-10 hours times per week on internet were statistically lower in ADHD group than the control group. Considering the relationship between internet addiction and impulsivity with ADHD and behavioral disregulation the incidence of IA in adolescence may be expected to increase with ADHD22,23,24. But in our study, the number of adolescents aged 12-14 years in the ADHD group is higher than the control group. So this age range factor may effect on our results. It is thought that large-scale and long-term studies are needed on this subject. Kahraman Ö. et al. (2018) conducted a study with 111 patients with ADHD aged 12-18 and 108 healthy contols. They found that internet access at home was significantly higher in control group when compared to ADHD group25. In our study, there was no statistically significant difference between groups in terms of having a computer at home and internet usage rates, while the rate of having an internet connection in mobile phone in ADHD group was significantly lower than the control group.
Internet use for gaming was higher in ADHD group in the study before mentioned and these results are consistent with our study. As a result of the studies in the literature, it can be said that ADHD diagnosis also provides a predisposition to gaming addiction26,27. Impulsivity and its association with IGD could make adolescents vulnerabile to the rewarding effects of gaming and to IGD28. Similarly, in our study adolescents with ADHD are always more likely to use the internet to play games than
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the control group. But as opposed to impulsivity and behavioral dysregulation with ADHD, the rates of using the internet mostly for non-purposeful use, using for watching videos, using for chatting, using to enter social networking sites are lower in the ADHD group compared to the control group. As far as we know, there is little literature about the types of computer games played by children with ADHD. Our ADHD group prefer to play adventure games the most from internet games. Considering that playing a computer game is associated with the dopaminergic system in the brain and stimulates the brain's reward mechanism, it seems likely that adventure games are more attractive for the children with ADHD29.
Another important point is that, there is no statistically significant difference between the groups in terms of disrupting effect of daily use of internet on rutine activity, rate of negative effects of internet usage on family relations, friendship relations, internet usage on eating and sleeping habits. As we know from previous studies, association between IA and reward deficincy is also related with the high frequency of comorbid ADHD30,31. Our results are incompatible with the literature related to internet addiction and excessive use of the internet. These results are interpreted as there is a need for longitudinal studies in ADHD groups.
This study is a cross-sectional study and conducted with a narrow group. Besides, the scale used in the study is a self-report questionnaire which may compromise the validity of diagnosis, especially considering that adolescents would minimize their problems with internet. Prospective longitudinal studies with larger groups are needed.
Yazar Katkıları: Çalışma konsepti/Tasarımı: MGL, MZE; Veri toplama: MGL; Veri analizi ve yorumlama: MGL, MZE; Yazı taslağı: MGL, MZE; İçeriğin eleştirel incelenmesi: MZE; Son onay ve sorumluluk: MZE, MGL; Teknik ve malzeme desteği: MGL; Süpervizyon: MZE; Fon sağlama (mevcut ise): yok.
Bilgilendirilmiş Onam: Katılımcılardan yazılı onam alınmıştır.
Hakem Değerlendirmesi: Dış bağımsız.
Çıkar Çatışması: Yazarlar çıkar çatışması beyan etmemişlerdir.
Finansal Destek: Yazarlar finansal destek beyan etmemişlerdir.
Author Contributions: Concept/Design : MGL, MZE; Data acquisition: MGL; Data analysis and interpretation: MGL, MZE; Drafting manuscript: MGL, MZE; Critical revision of manuscript: MZE; Final approval and accountability: MZE, MGL; Technical or material support: MGL; Supervision: MZE; Securing funding (if available): n/a.
Informed Consent: Written consent was obtained from the participants.
Peer-review: Externally peer-reviewed.
Conflict of Interest: Authors declared no conflict of interest.
Financial Disclosure: Authors declared no financial support
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