Abstract
Background:
Problematic Internet use (PIU) is the inability of individuals to control their Internet use, resulting in marked distress and/or functional impairment in daily life.
Aim/Objective:
We assessed the frequency of PIU and predictors of PIU, including social anxiety disorder (SAD), quality of sleep, quality of life and Internet-related demographic variables among school going adolescents.
Methods:
This was an observational, single-centered, cross-sectional, questionnaire-based study of 1,312 school going adolescents studying in Grades 10, 11 and 12 in Bhavnagar, India. Every participant was assessed by a pro forma containing demographic details, questionnaires of Internet Addiction Test (IAT), Social Phobia Inventory (SPIN), Pittsburgh Sleep Quality Index (PSQI) and Satisfaction With Life Scale (SWLS) for PIU severity, SAD severity, Quality of Sleep assessment and Quality of Life assessment, respectively. The statistical analysis was done with SPSS Version 23 (IBM Corporation) using chi-square test, Student’s t test and Pearson’s correlation. Multiple linear regression analysis was applied to find the predictors of PIU.
Results:
We found frequency of PIUs as 16.7% and Internet addiction as 3.0% among school going adolescents. Participants with PIU are more likely to experience SAD (p < .0001), poor quality of sleep (p < .0001) and poor quality of life (p < .0001). There is positive correlation between severity of PIU and SAD (r = .411, p < .0001). Linear regression analysis shows PIU can be predicted by SAD, sleep quality, quality of life, English medium, male gender, total duration of Internet use, monthly cost of Internet use, education, social networking, gaming, online shopping and entertainment as purpose of Internet use.
Conclusion:
Participants with PIU are more likely to experience SAD, poor quality of sleep and poor quality of life.
Introduction
The Internet is a boon of modern science for the public. The past decade witnessed a dramatic surge in use of Internet around the globe (Goel, Subramanyam, & Kamath, 2013). It has revolutionized the field of communication, education, entertainment, exchange of information and social interaction (Krishnamurthy and Chetlapalli, 2015; Salehi, Khalili, Hojjat, Salehi, & Danesh, 2014). Excessive, uncontrolled use of Internet can lead to problematic Internet use (PIU). The term ‘Internet addiction’ was first introduced by Dr. Ivan Goldberg for pathological Internet use in 1995 and Internet addiction disorder can be defined as ‘the inability of individuals to control their Internet use, resulting in marked distress and/or functional impairment in daily life’ (Ha et al., 2006: 821–826; Pies, 2009 : 31–37). Lack of self control, peer influence and low self-esteem contribute to adolescent’s vulnerability against PIU (Aktepe, Olgaç-Dündar, Soyöz, & Sönmez, 2013; Meena, Mittal, & Solanki, 2012). PIU can cause social isolation, sedentary life, nutritional problems and poor academic performance (Meena et al., 2012). PIU can be commonly associated with various psychiatric disorders, such as social anxiety disorder (SAD), attention deficit hyperactivity disorder, major depressive disorder, obsessive compulsive disorder and substance use disorder (Bozkurt, Coskun, Ayaydin, Adak, & Zoroglu, 2013).
SAD is marked fear or anxiety about social situations and may cause avoidance of social situations (American Psychiatric Association, 2013). SAD usually starts in adolescent age and leads to poor academic performance, lack of social skills and restricted social interactions (Ollendick & March, 2004). Person with SAD may prefer to interact online with others rather than communicating face-to-face to alleviate discomfort produced by it (Shepherd & Edelmann, 2005).
Insomnia is dissatisfaction with sleep quality and quantity, with difficulty initiating or maintaining sleep or early morning awakening (American Psychiatric Association, 2013). Hypersomnia is self-reported excessive sleepiness with excessive quantity of sleep, deteriorated quality of wakefulness and sleep inertia (American Psychiatric Association, 2013). Insomnia may be a risk factor for the depression, anxiety and addiction (Gillin, 1998). Sleep disturbance can occur in patients having substance addiction (Mahfoud, Talih, Streem, & Budur, 2009). Insomnia is a risk factor for development of anxiety disorder (Breslau, Roth, Rosenthal, & Andreski, 1996). Studies suggest that social phobia is associated with insomnia (Buckner, Bernert, Cromer, Joiner, & Schmidt, 2008).
There is a paucity of evidence-based clinical studies evaluating PIU and its predictors among adolescents in India. So, we undertook this study to venture further into this issue.
In the present study, we aimed to assess the frequency of PIU and predictors of PIU among school going adolescents, including SAD, sleep quality and quality of life and Internet-related demographic variables.
Material and methods
It is a single center, questionnaire-based, observational, cross-sectional study. The study was started after prior approval from local ethics committee and respective school authorities. The list of secondary and higher secondary schools inside the Bhavnagar city was obtained from the District Education Office and nine schools were selected to participate in the study by simple random sampling method; all the students studying in Grades 10, 11 and 12 from selected schools who were using Internet regularly since at least 1 year and gave consent to participate in the study were taken for the study. A total of 1,312 adolescents of both gender, studying in different schools of Bhavnagar city, India, were recruited for the study between August 2016 and January 2017. Students studying in Gujarati medium as well as those studying in English medium were included in the study. The consenting participants were instructed to fill up their demographic details, self-administered questionnaire of Internet Addiction Test (IAT), Social Phobia Inventory (SPIN), Pittsburgh Sleep Quality Index (PSQI) and Satisfaction With Life Scale (SWLS) in the given pro forma after explaining the purpose of study. Anonymity and confidentiality of participants were maintained.
IAT is a self-reported scale that measures PIU. It is a 20-item, 5-point Likert-type scale. Total scores are obtained by sum of 20 items that ranges from 20 to 100. According to Young’s criteria, total IAT scores of 20 to 49 denote average users having total control on their Internet usage, scores 50 to 79 denote overusers with frequent problems due to their Internet usage and scores 80 to 100 denote Internet addicts having significant problems due to their Internet usage. The scale showed good internal consistency and concurrent validity, with an alpha coefficient of .54 to .82 (Young, 1998). Cutoff value of 51 was taken to divide subjects into problematic Internet user and nonproblematic Internet user categories in an earlier study (Stavropoulos, Alexandraki, & Motti-Stefanidi, 2013).
SPIN is a 17-item self-rating screening instrument, to be rated in 0 (not at all) to 4 (extremity) Likert-type scale, assessing three domains of social fear, avoidance behavior and physical symptoms in a variety of social situations. According to SPIN, a score of < 20 represents no social phobia, 21 to 30 represents mild, 31 to 40 represents moderate, 41 to 50 represents severe and 51 or more represents very severe social phobia. It shows an alpha coefficient of .92 with good test–retest reliability, internal consistency, convergent and divergent validity (Connor et al., 2000). The cutoff value of SPIN for SAD was recommended as 24 in an earlier study (Ranta, Kaltiala-Heino, Rantanen, Tuomisto, & Marttunen, 2007).
PSQI is a self-report instrument designed to evaluate sleep quality and disturbance over the past month. It consists of 19 items to produce seven aspects of sleep quality (subjective sleep quality, sleep onset latency, sleep duration, efficiency, quality disturbances, medication and daytime dysfunction). The sum of these seven aspects (0–3) yields one global score of sleep quality (0–21); a high score is an indication of poor sleep quality. The cutoff score of > 5 has been found to be an accurate score to distinguish between patients with primary insomnia and those without insomnia. It shows Cronbach’s alpha coefficient of .83 with good test–retest reliability and internal consistency (Buysse, Reynolds, Monk, Berman, & Kupfer, 1989).
SWLS is a five-item 7-point Likert-type scale designed to measure global life satisfaction. Participants indicate how much they agree or disagree with each of the five items that ranges from 7 (strongly agree) to 1 (strongly disagree). A lower score on the scale indicates low life satisfaction. A score of 20 represents the neutral point on the scale. Scores on the SWLS can be categorized as extremely dissatisfied (5–9), dissatisfied (10–14), slightly dissatisfied (15–19), neutral (20), slightly satisfied (21–25), satisfied (26–30) and extremely satisfied (31–35). This scale shows high internal consistency and temporal reliability (Diener, Emmons, Larsen, & Griffin, 1985).
The original questionnaires were translated into Gujarati language by committee approach. The translated version of questionnaire was given to 40 students on pilot basis to look for any misunderstandings in translation. The students studying in English medium were given the original questionnaire while students of Gujarati medium were given the translated version of the questionnaire. In the present study, the Cronbach’s alpha coefficients for the Gujarati translated version of questionnaires used were .930, .809, .679 and .824 for IAT, SPIN, PSQI and SWLS Scale, respectively.
Qualitative data were expressed in proportions, while quantitative data were expressed in M ± SD. The statistical analysis of proportions was done by chi-square test, while the scores of IAT, SPIN, PSQI and SWLS were compared by Student’s Two-Tailed t test using SPSS Version 23 (NY, IBM Corporation). Correlation between IAT score and SPIN score was analysed by applying Pearson’s correlation. Multiple linear regression analysis was applied to find the predictors of PIU, with PIU as outcome variable and SPIN score, PSQI score, SWLS score and Internet-related demographic variables as predictor variable. A p value ⩽ .05 was considered significant statistically.
Results
In our study, 1,361 students had participated, out of whom 49 students were excluded due to incomplete questionnaire. So in the final analysis, 1,312 students were included. Among them, 403 (30.7%) were females and 909 (69.3%) were males. A total of 1,205 (91.8%) students were residing at home and 107 (8.2%) students were staying at hostel. There were 799 (60.9%) students studying in Gujarati medium and 513 (39.1%) students studying in English medium. The mean age of participants was 15.9 years. The number of students studying in Grades 10, 11 and 12 were 473, 428 and 411, respectively. The mean duration of starting of Internet use was 31.3 months and mean time spent per day on Internet was 1.7 hours. The mean monthly cost of Internet services was 285.2 Indian Rupees.
Using Young’s original criteria, the users were divided into groups of average users (83.3%), overusers or possible addicts (13.7%) and addicts (3.0%) and thus the percentage of students having PIU was 16.7%. Out of 1,312 participants, 300 (22.8%) students were having SAD while 305 (23.2%) students were having insomnia.
As shown in Table 1, participants with PIU are likely to have higher scores in SPIN (p < .0001) and PSQI (p < .0001) and lower scores in SWLS (p < .0001).
Results of analytic tests to compare demographic characteristics and SAD severity, sleep quality and satisfaction with life between nonproblematic and problematic Internet using groups.
SAD = social anxiety disorder; IAT = Internet Addiction Test for Internet use; SPIN = Social Phobia Inventory; PSQI = Pittsburgh Sleep Quality Index; SWLS = Satisfaction With Life Scale.
Note: Data are represented in No. (%) and M ± SD groups were compared by chi-square test, Student’s Two-Tailed t test; p < .05 is considered to be statistically significant.
Participants were allowed to choose more than one option so there is difference in number of participants.
There was a significant correlation between severity of PIU and severity of SAD using the Pearson’s correlation (r = .411, p < .0001).
Linear regression analysis for predictors of Problematic Internet Use.
PSQI = Pittsburgh Sleep Quality Index; SPIN = Social Phobia Inventory; SWLS = Satisfaction With Life Scale; VIF = variance inflation factor.
Linear regression analysis was applied to find the predictors of PIU by stepwise technique. All the predictors that were found to be significant with p value less than .05 in the univariate analysis were entered into multivariate analysis. In this model, IAT score was considered as outcome variable.
The multiple regression model with all 12 predictors produced adjusted R² = .420, indicating that 42% variance in the outcome variable can be explained by the predictors. This model was significant in prediction, F(14, 1297) = 68.747, p < .0001.
After 12 steps linear regression model, SPIN score (B = 0.485, p < .0001), PSQI score (B = 1.938, p < .0001), SWLS score (B = – 0.240, p < .0001), English medium (B = 6.538, p < .0001), male gender (B = 3.057, p = .002), total duration of Internet use (B = 0.137, p < .0001), monthly cost of Internet use (B = 0.006, p = .001), social networking (B = 3.185, p < .0001), education (B = –6.114, p < .0001), gaming (B = 2.006, p = .024), online shopping (B = 2.460, p = .027) and entertainment (B = 2.109, p = .024) as purpose of Internet use were the significant predictors of Internet use.
As can be seen in Table 2, SPIN score, PSQI score, English medium, male gender, total duration of Internet use, monthly cost of Internet use, social networking, gaming, online shopping and entertainment as purposes of Internet use had significant positive regression weightage, indicating adolescents with higher scores on SPIN Scale and PSQI Scale, being male, studying in English medium, using Internet since long time, spending more money on Internet service, using Internet for the prime purpose of social networking, gaming, online shopping and entertainment are expected to have higher IAT score. The SWLS score and education as a purpose of using Internet has a significant negative weightage, indicating that adolescents who are having lower SWLS score and using Internet less for education purpose are expected to have higher IAT Score.
As can be observed from the values of unstandardized B coefficient in Table 2, studying in English medium received the strongest weightage in the model followed by education as purpose of using Internet and then other predictors, indicating that studying in English medium is the strongest predictor of higher IAT Score.
The unstandardized B coefficients indicate the predicted change in the outcome for every unit increase in that predictor. PSQI Score was having an unstandardized B coefficient of 1.938, indicating that for every additional point within this variable, there would be an expected increase of 1.938 points on IAT Score, and likewise for other predictors. This can be counted by an equation, which is described below.
Working model to predict IAT Score and its application to next adolescent is as follows:
IAT Score = 5.993 + 1.938 (PSQI Score) + 0.485 (total SPIN score) + 0.137 (total duration of Internet use) + 6.538 (medium) – 6.114 (education) + 3.057 (gender) – 0.240 (SWLS score) + 0.006 (monthly cost of Internet service) + 3.185 (social networking) + 2.006 (gaming) + 2.109 (entertainment) + 2.460 (online shopping)
Discussion
In our study, we found that 16.7% of participants are problematic Internet users and 3.0% are addicted users.
The prevalence of PIU found to be 2.5% to 3.2% among adolescents in earlier studies (Choi et al., 2009; Kuss, Griffiths, & Binder, 2013; Sung, Lee, Noh, Park, & Ahn, 2013) and our findings are consistent with their results.
Students with primary medium of school as English are found to be having more PIU than Gujarati medium students; this is consistent with an earlier study (Jhala & Sharma, 2016) and can be attributed to the language barrier faced by students of Gujarati medium while surfing on Internet as every information available on Internet cannot be translated to Gujarati language. English medium students being more comfortable with English language have an added advantage in this matter (Jhala & Sharma, 2016). Further studies are required to evaluate this aspect better.
The problematic users are using Internet for the prime purpose of entertainment. This finding is consistent with the fact confirmed by an earlier study (Cao, Sun, Wan, Hao, & Tao, 2011). There is a significant relationship between education, playing games and using social networking sites and PIU, which is observed in previous studies (Salehi et al., 2014; Srijampana, Endreddy, Prabhath, & Rajana, 2014; Sulania, Sachdeva, & Dwivedi, 2016; Yadav, Banwari, Parmar, & Maniar, 2013).
Consistent with previous studies, we found that problematic Internet users started using Internet since long time and spent more hours daily using Internet than nonproblematic Internet users (Krishnamurthy and Chetlapalli, 2015; Salehi et al., 2014; Yadav et al., 2013). We found a significant relationship of the total monthly expenditure and monthly cost of Internet services among the problematic Internet users in comparison with nonproblematic Internet users. This finding of our study corroborates with the result of a previous study (Salehi et al., 2014).
There is significant association between the high speed of Internet and PIU seen in our study; it is consistent with the result of the study conducted previously (Nagori, Vala, Panchal, Ratnani, & Vasava, 2016).
The participants with PIU are more likely to have SAD and severity of PIU is correlated with severity of SAD. This finding is corroborated with finding in another study (Fagiolini, 2015). This may be explained on the basis of anonymity offered by Internet to people, thus reducing one-to-one conversation and discomfort caused by it. Internet gives liberty to the individual to portray his or her desired appearance without worrying about the negative aspects of his or her personality. Escaping from discomforting interactions is possible in online tools (Huan, Ang, & Chye, 2014; Shepherd & Edelmann, 2005). However, PIU compels a person to interact less with his or her kith and kin and increase social anxiety, so this relationship can be bidirectional (Cardak, 2013).
We found a significant association between PIUs and sleep quality suggestive of poor quality of sleep in problematic Internet users as compared with nonproblematic group. These findings are consistent with the facts confirmed by another study (Cheung & Wong, 2011). It can be because increased time spent on the Internet disrupts the sleep–wake schedule, leading to insomnia among problematic Internet users. Night-time Internet use leads to a state of high arousal that interferes with the sleep (Spear, 2000).
The participants with PIU have poor quality of life as compared with nonproblematic Internet users and a similar finding is also seen in a previous study (Aktepe et al., 2013).
Although we have assessed association of PIU with SAD, sleep quality and quality of life among adolescents using validated scales of assessment, our study has several limitations like being a cross-sectional study, recruiting participants from a single center and questionnaire-based study; no interviews were taken and we studied only school going adolescents. Being a cross-sectional study, cause–effect relationship can’t be established with this study. Further large sample-sized, community-based, multicentric, interview-based cohort studies are recommended to have more insight in this subject.
Conclusion
We found that frequency of PIU was 16.7%. SAD, poor sleep quality and poor quality of life are more common among problematic Internet users. PIU can be predicted by SAD, sleep quality, quality of life, English medium, male gender, total duration of Internet use, monthly cost of Internet use, education, social networking, gaming, online shopping and entertainment as purposes of Internet use.
Future implications
This study’s results indicate that PIU is turning out to be a major public health problem, especially among adolescents. There is an intense need to develop plans for prevention of PIU and spreading cognizance of this issue among parents and teachers for healthy growth.
