Introduction

“Problematic Internet Use (PIU)” is characterized as the individual’s inability to control internet use, resulting in feelings of distress and functional impairment in daily activities.¹ It has also been reported that adolescents are the most at-risk group for PIU. This may be because adolescents are more prone to risky behaviors and resort to addictive applications to cope with anxiety, disappointment, and failure, to satisfy the need for excitement or the feeling of invincibility, or because the internet offers adolescents the opportunity to distance themselves from their own identities and feel free.²

Studies reporting the prevalence of PIU have shown marked differences around the world.³ According to the results of a recent meta-analysis, the global prevalence of PIU exhibits substantial variation across geographical regions and demonstrates a progressive increase over time. The highest prevalence rates were reported in the World Health Organization African Region (34.53%) and Eastern Mediterranean Region (30.11%), whereas the lowest rates were observed in the Americas Region (11.06%) and the European Region (11.06%). In the same meta-analysis, the prevalence of PIU among adolescents was reported to range from 10.60% to 13.70%.⁴

As the prevalence of PIU has increased, its effect on health-related behaviors has become more prominent.⁵ Kim et al.⁶ demonstrated an association between PIU and negative dietary behaviors such as skipping meals, snacking, inadequate fruit and vegetable intakes, consumption of carbonated soft drinks and fast food and negative lifestyle habits such as decreased physical activity. Koças et al.⁷ reported that internet addiction was associated with worsening sleep quality among high school students. Previous studies also reported lower rates of PIU among those who engaged in more physical activity and found an association between PIU and poor physical health.^8,9

The number of studies simultaneously investigating the relationship between sleep patterns, physical activity, and nutritional habits in conjunction with PIU remains limited. The present study aimed to assess the associations between these three health-related daily behaviors and PIU, as well as to determine the prevalence of PIU among high school students residing in the Inner Aegean Region of Türkiye.

Materials and Methods

Study design

This cross-sectional study was conducted in high schools between October 01, 2019 and March 13, 2020. Permission to carry out the study was approved by the local ethics committee. All study procedures were performed in accordance with the Declaration of Helsinki.

Sample size and selection

The minimum sample size was calculated as 886 with a 99.9% confidence interval (CI) using “OpenEpi (https://www.openepi.com/SampleSize/SSPropor.htm) calculator” according to n = [DEFF*Np(1-p)]/ [(d²/Z²_1-α/2*(N-1)+p*(1-p)] equation. Among the parameters, N (Total number of high school students living in Afyonkarahisar province) was accepted as 13862; p as 12±5% (previously reported percentage frequency of internet addiction risk among high school students);¹⁰ d (confidence limit) as 1%; DEFF (design effect) as 2 and Z²_1-α/2 as 1.96. Taking into account the 20% non-participation margin, a total of 1051 students were planned to be included in the study. After determining the schools with different socioeconomic levels in cooperation with the Research and Development unit of the National Education Directorate, the schools were selected using the cluster sampling method. A total of 6 schools were randomly identified: one private school with a high socioeconomic level, two schools with a medium socioeconomic level, and three schools with a low socioeconomic level. In order to reach 175 students from each school, two classes from the 9th, 10th, 11th and 12th grades were selected. Students who agreed to participate in the research after obtaining parental and student consent, were included in the study. Students whose parents or themselves did not agree to participate in the research, those without internet access and those who had a history of chronic mental illness (such as obsessive-compulsive disease, anxiety disorder) or physical illness (such as diabetes, cardiac diseases) that could affect daily health-related habits such as diatary habits and physical activity were excluded from the study.

Data collection

After explaining the purpose and procedure of the research, written consent forms for adolescents and parents were distributed to students who verbally agreed to participate. The next day, the students, whose consent was obtained, were asked to fill out the survey form and a scale to test PIU.

Measures

Questions regarding internet usage habits and lifestyle habits were prepared based on previous studies^6,7,11 and the lifetime status of habits was questioned in terms of their presence/absence or frequency. The following questions were asked in the questionnaire: (i) Demographic characteristics of students and their families (age, sex, residence, education level of parents). The age variable was evaluated as under or over 15 years, and a distinction was made between 9th-10th grades and 11th-12th grades. (ii) Internet usage characteristics (year of internet use, average daily internet usage time on weekdays and weekends, presence or absence of usage of internet cafe) (iii) Sleep characteristics (daily sleep duration; according to the recommendations of the US National Sleep Foundation, the short sleep duration limit was considered to be <8 hours¹² and presence or absence of sleep problems; difficulty falling asleep, frequent interruption of sleep, difficulty waking up in the morning, feeling sleepy in the morning) (iv) Using a mobile phone other than an alarm for the first time after waking up in the morning (v) Regular sports habit (regularly participating in licensed or unlicensed individual or team sports) and regular physical activity status (exercise for at least one hour a day, on certain days of the week), and (vi) Nutritional characteristics (how many days per week they skipped breakfast, skipped meals, consumed salty or sugary snacks, consumed sugary sodas and, whether they consumed caffeinated beverages and energy drinks). The adequacy of the questions was checked with a preliminary study with 20 high school students and the questionnaire was given its final form.

In our research, Youth Internet Addiction Test-Short Form (YIAT-SF) was used to test PIU. The original form of the “Internet Addiction Test (IAT)” was developed by Young¹³ converted into a short form by Pawlikowski et al.¹⁴ and adapted into Turkish by Kutlu et al.¹⁵ YIAT-SF consists of 12 items and is a five-point Likert (1 = Never, to 5 = Very often) type scale. The Turkish version of the YIAT-SF has been previously shown to be reliable and valid for adolescents.¹⁵ There is no reverse scored items in the scale. High scores from the scale indicate a high level of internet addiction. To calculate the frequency of internet addiction among participants, the cutoff score was accepted as 36, as recommended in the literature.^14,16 Scores of 36 and above indicated that the students had PIU.

Statistical analysis

IBM-SPSS 26.0 (SPSS Inc., Chicago, IL, USA) program was used for statistical analysis. Normal distribution of the data was evaluated with the Shapiro-Wilk test. Categorical variables were expressed as n (%) and normally distributed data from continuous variables were expressed as mean ± standard deviation. All variables were first tested with bivariate analysis. Participants were analyzed in two groups according to the presence or absence of PIU. Chi-square test or Fisher’s exact test was used to compare the percentage distributions of categorical data between groups. Then multiple logistic regression analysis was performed to test the relations of the risk of PIU with internet and health variables by adjusting for age, sex, maternal education status, paternal education status and residence. Variables with a p value <0.05 in the univariate analyses were included in the multiple logistic regression backward step model. Multiple logistic regression results are reported as adjusted odds ratios (AOR) with 95% CI. A p<0.05 level was considered significant.

Results

A total of 1051 students participated in the study. Data from a total of 951 participants were analyzed by excluding students with chronic diseases (n=32) and incompletely filled out questionnaires (n=68). The mean age of the students was 15.3±1.0 years. Of the students, 42.3% (n=402) were female. The prevalence of PIU among participants was determined as 12.1%. Table I shows the distribution of participants’ demographic and internet usage characteristics according to PIU status. The proportion of more than >5 years of internet use (p=0.001), daily internet usage time more than 2 hours per week on weekdays (p<0.001) and weekends (p<0.001), use of internet cafes (p=0.015) were significantly higher in participants with PIU.

Table II shows the comparison of participants’ health-related daily habits with PIU. The frequency of having at least one type of sleep problem (p<0.001), use of a mobile phone other than an alarm within the first hour after waking up (p<0.001), skipping breakfast (p<0.001) or other daily meals (p<0.001), eating sugary snacks (p=0.004) and salty snacks (p<0.001), consuming sugary-carbonated drinks (p<0.001), caffeinated drinks (p=0.015), and energy drinks (p=0.001) were significantly higher in participants with PIU.

By adjusting the age, sex, maternal education, paternal education and residence, risk of PIU presence according to internet-related (Year of internet use >5 vs. ≤5 years, daily internet usage time [weekdays] ≥2 vs. <2 hours, daily internet usage time [weekend] ≥2 vs. <2 hours, usage of internet cafe) and health-related variables (having at least one type of sleep problem, time of mobile phone use after waking up in the morning ≤1 vs. >1 hour, having breakfast <3 vs. ≥3 days/week, skipping daily meals ≥3 vs. <3 days/week, eating sugary snacks ≥3 vs. <3 days/week, eating salty snacks ≥3 vs. <3 days/week, consuming sugary-carbonated drinks ≥3 vs. <3 days/week), consuming caffeinated drinks, consuming energy drinks) was tested with multiple logistic regression analysis with backward stepwise model (Table III). Having daily internet usage time ≥2 hours on weekdays (adjusted odds ratio [AOR]: 3.45, 95% CI: 2.17-5.51), having at least one type of sleep problem (AOR: 2.04, 95% CI: 1.29-3.25), having breakfast less than 3 days per week (AOR: 2.22, 95% CI: 1.45-3.40), eating salty snacks ≥3 days per week (AOR: 1.98, 95% CI: 1.27-3.10), consuming sugary-carbonated drinks ≥3 days per week (AOR: 1.70, 95% CI: 1.06-2.61) were associated with PIU.

Discussion

This study showed that the prevalence of PIU among high school students is 12.1%. This is consistent with the worldwide prevalence of PIU for adolescents ranging from 10.60% to 13.70% reported by Meng et al.⁴ However, it is slightly below the prevalence reported as 21.1% in the Black Sea region and 18.5% in the Marmara region in Türkiye.^8,9 The difference in the prevalence of PIU among high school students living in different geographical regions in Türkiye may be due to the variability in the ability of families with different sociocultural norms to cope with excessive use of the internet. It may also be due to the use of different scales to detect PIU in these studies. However, Burkauskas et al.¹⁷ reported that although the same instrument (IAT) and cutoff score (≥50) were used, the prevalence of PIU differed even in studies from the same country or region. Regional differences in prevalence can be assessed more clearly with a national, multicenter, longitudinal study using more robust measurement tools that test the diagnosis of internet addiction.

In our study, we found that the frequency of PIU did not change with age and sex. In previous studies, findings regarding the association between age, sex and PIU have varied. Some recent studies have reported that older high school students are more likely to have PIU.^3,18 However, in the study of Seyrek et al.¹⁹ no significant association was found between internet addiction and age and sex. Khan et al.²⁰ found that internet addiction in medical school students did not differ between sexes. Cam et al.⁸ also reported no significant correlation between PIU severity and sex. Dafour et al. showed that boys spent significantly more time online than girls, that a greater proportion of girls used social networks intensively, while boys used multiplayer online role-playing games, and that there was no significant difference between sexes in terms of internet addiction risk.²¹ However, some previous studies also determined that the internet addiction rate was significantly higher in males.^3,22-24

In this study, the ratio of PIU was found to be significantly higher in participants who used the internet for more than two hours on weekdays, but no similar finding was found for weekends. In a study conducted in South Africa in 2019, Salubi et al.²⁵ showed that 34.8% of the participants used the internet for more than ten hours a day, and the time spent on the internet was associated with internet addiction. In a study conducted among university students in India in 2020, Jain et al.²⁶ examined the association between internet addiction and the time spent on the internet per day. Internet use of two hours or more per day was found to be significantly associated with internet addiction. Şaşmaz et al.²² also reported that internet addiction was related to the duration of daily computer use.

The present study determined that students with PIU were more likely to have at least one type of sleep problem such as difficulty falling asleep, frequent interruption of sleep, difficulty waking up in the morning, and feeling sleepy in the morning, but it was shown that the frequency of PIU did not change with sleep duration. Kojima et al.⁵ examined the association between health-related behaviors and internet use in Japanese adolescents and found a significant association between PIU and sleeping after midnight. Park et al.²⁷ investigated the association between depressive symptoms and PIU and sleep problems and reported that sleep-wake behavior problems, insomnia, and excessive daytime sleepiness increased as IAT scores increased in the non-depressed group. In their study examining the association between sleep habits and problems and internet addiction in Japanese adolescents, Kawabe et al.²⁸ showed that night sleep time was shorter, bedtime and morning waking time were later in the addicted group. Yang et al.²⁹ examined PIU and accompanying sleep problems in adolescents and showed that the risk of sleep disorders increased in the presence of PIU. It is known that excessive internet use undermines the time devoted to sleep and other life habits and therefore causes sleep problems. Yang et al.²⁹ also referred to “Time displacement theory” to clarify the association between PIU and sleep problems, which is used to explain that internet use generally reduces the time devoted to other activities.

Findings from previous studies examining the association between physical activity and PIU vary. Khan et al.²⁰ showed that medical students with low physical activity had a higher frequency of internet addiction than students with regular physical activity. It was also reported that physically active students are less likely to be problematic internet users among South Korean adolescents.³⁰ On the other hand, Dang et al.¹¹ reported that physical activity had no significant association with internet addiction in Vietnamese youth and adolescents. Similar to the present study, Haripriya et al.³¹ showed that there was an association between smartphone addiction and sleep quality, but not with physical activity. In our study, we did not find a relationship between PIU and students’ regular sports and regular physical activity habits. This may be due to the fact that students use the internet in their remaining free time, even if they do regular sports or physical activity. It may also be due to the confounding effects of other variables that affect physical activity habits, such as family income level, suitability of school and home environment for physical activity, and excessive school workload.

This study found that poorer breakfast habits, consuming more salty snacks and sugary-carbonated drinks were associated with PIU. A recent study observed a positive correlation between PIU and disordered eating attitudes³² and a meta-analysis study identified internet addiction as a determinant of eating disorders.³³ Gür et al.³⁴ found a significant association between internet addiction scores and physical behavior problems (going to bed late, skipping meals, eating in front of the computer) in secondary school students. Kojima et al.⁵ also found a significant association between PIU and skipping breakfast. Kim et al.⁶ found a higher frequency of skipping dinner and consuming frequent snacks in high-risk internet users. They did not show any significant difference in favorite snacks according to the level of internet addiction. Similarly, a previous study found that use of social networking sites was associated with an increased likelihood of skipping breakfast and consuming sugar-sweetened beverages and energy drinks.³⁵ The reasons for the association between PIU and unhealthy eating habits may be due to increased exposure to unhealthy food advertisements via the internet, easier consumption of unhealthy snacks such as sugary drinks or chips while on the internet, and missing healthy meal times because of excessive time spent on the internet. Prospective studies are needed to elucidate the mechanisms of this relationship.

A key strength of this study is the simultaneous investigation of the associations between sleep patterns, physical activity, dietary habits, and PIU within a relatively large sample. By including these variables in the same model and applying logistic regression analysis, potential confounding effects were controlled, allowing a clearer delineation of their independent relationships with PIU.

There are also some limitations in our study that should be taken into account. The first limitation is that the study was conducted in a single province and therefore the results are not generalizable. The second limitation of this study is that we did not use validated scales to test sleep, physical or sports activity, and dietary habits. Additionally, this study only measured general internet addiction. Specific addictions that may vary by gender, such as online gaming and problematic use of social media, were not measured, which constitutes a third limitation of the study. Future studies should examine the source of the problem, such as for what purposes adolescents use the internet, what their motivations are for using the internet, and how addictive devices such as game consoles or smartphones affect the total duration of internet use.

Conclusion

In this study, we determined that PIU is common among high school students and observed that PIU is associated with some health-related life habits. Having at least one type of sleep problem, skipping breakfast, and consuming salty snacks and sugary-carbonated drinks more were found to be associated with PIU.

PIU has become a new public health problem with a high prevalence that negatively affects the daily health habits of adolescents. It would be appropriate to address the action plans to be implemented to solve this problem in two ways. First, awareness of this issue should be raised among individuals who have frequent contact with adolescents, including parents, clinicians, and teachers. Providing families with guidance on developing a family media plan and implementing bedroom screen-time recommendations, delivered through clinicians or educators, as well as conducting screenings for PIU using validated tools within school counseling services to facilitate referral to professional help, may contribute to addressing the problem. In addition, both national and international health policy developers and implementers need to show the necessary sensitivity to this issue, and the implementation of large-scale measures globally should not be delayed.

Ethical approval

The study was approved by Afyonkarahisar Health Sciences University’s Clinical Research Ethics Committee (date: 14.06.2019, number: 2011-KAEK-2). Written informed consent was provided by each participant. All study procedures were performed in accordance with the Declaration of Helsinki.

Author contribution

The authors confirm contribution to the paper as follows: Study conception and design: EÇ, AO; data collection: EÇ, AO; analysis and interpretation of results: EÇ, AO, AB; draft manuscript preparation: EÇ, AO, AB. All authors reviewed the results and approved the final version of the article.

Source of funding

The authors declare the study received no funding.

Conflict of interest

The authors declare that there is no conflict of interest.