Confirmation of the three-factor model of problematic internet use on off-line adolescent and adult samples.

As the Internet became widely used, problems associated with its excessive use became increasingly apparent. Although for the assessment of these problems several models and related questionnaires have been elaborated, there has been little effort made to confirm them. The aim of the present study was to test the three-factor model of the previously created Problematic Internet Use Questionnaire (PIUQ) by data collection methods formerly not applied (off-line group and face-to-face settings), on the one hand, and by testing on different age groups (adolescent and adult representative samples), on the other hand. Data were collected from 438 high-school students (44.5 percent boys; mean age: 16.0 years; standard deviation=0.7 years) and also from 963 adults (49.9 percent males; mean age: 33.6 years; standard deviation=11.8 years). We applied confirmatory factor analysis to confirm the measurement model of problematic Internet use. The results of the analyses carried out inevitably support the original three-factor model over the possible one-factor solution. Using latent profile analysis, we identified 11 percent of adults and 18 percent of adolescent users characterized by problematic use. Based on exploratory factor analysis, we also suggest a short form of the PIUQ consisting of nine items. Both the original 18-item version of PIUQ and its short 9-item form have satisfactory reliability and validity characteristics, and thus, they are suitable for the assessment of problematic Internet use in future studies

Problematic Internet Use and Problematic Online Gaming Are Not the Same: Findings from a Large Nationally Representative Adolescent Sample

There is an ongoing debate in the literature whether problematic internet use (PIU) and problematic online gaming (POG) are two distinct conceptual and nosological entities or whether they are the same. The present study contributes to this question by examining the interrelationship and the overlap between PIU and POG in terms of gender, school achievement, time spent using the internet and/or online gaming, psychological wellbeing, and preferred online activities. Questionnaires assessing these variables were administered to a nationally representative sample of adolescent gamers (N=2,073; mean age 16.4 years, SD=0.87, 68.4% male). Data showed that internet use was a common activity among adolescents while online gaming was engaged in by a considerably smaller group. Similarly, more adolescents met the criteria for PIU than for POG and a small group of adolescents showed symptoms of both problem behaviors. The most notable difference between the two problem behaviors was in terms of gender. POG was much more strongly associated with being male. Self-esteem had low effect sizes on both behaviors, while depressive symptoms were associated with both PIU and POG, affecting PIU slightly more. In terms of preferred online activities, PIU was positively associated with online gaming, online chatting, and social networking while POG was only associated with online gaming. Based on our findings POG appears to be a conceptually different behavior than PIU and therefore data support the notion that Internet Addiction Disorder and Internet Gaming Disorder are separate nosological entities

Gaming addiction in adolescence (revisited)

Gaming addiction has become a topic of increasing research interest. Over the last 25 years, I have written many articles on adolescent video gaming for Education and Health as it is one of the research fields that is constantly evolving. In fact, over the last decade, there has been a significant increase in the number of scientific studies examining various aspects of online addiction particularly among adolescents and young adults (Kuss & Griffiths, 2012; Kuss, Griffiths, Karila & Billieux, 2014). Although the amount and the quality of research in the field has progressed much over this period, it is still in its infancy compared to other more established behavioural addictions (such as pathological gambling). This article briefly examines (i) how adolescent gaming addiction research has changed over the last three decades, (ii) how online gaming addiction has gained genuine psychiatric status, (iii) excessive gaming as an addiction, and (iv) where the gaming addiction field is going

Internet addiction and loneliness among children and adolescents in the education setting: an empirical pilot study

Research into various behavioural addictions has shown that such behaviour can negatively impact psychological wellbeing. One behavioural addiction that has been increasingly studied empirically is that of Internet Addiction (IA). Despite general consensus concerning the negative effects of IA on mental health and other indices of physical and psychosocial health, little research has been done in child and adolescent populations in specific contexts. The main objectives of this study were to (i) investigate the extent of problems caused by IA in children and adolescents, (ii) determine the socio-demographic and behavioural characteristics of children and adolescents with IA, and (iii) to provide a model capable of predicting IA in the educational context among the target population. A total of 131 Portuguese school children and adolescents participated in this study. Results indicated a relatively high incidence of IA in the sample (13%). Additionally, the correlational analyses revealed associations between IA and loneliness, social loneliness, and other variables related to the educational context. Results demonstrated that IA could be predicted using a model encompassing three variables (i.e., weekly Internet usage, loneliness, and classroom behaviour). Overall, the present findings corroborated results from other studies and added to the behavioural addiction literature by examining a younger cohort than previous empirical studies

The mediating effect of self-esteem, depression and anxiety between satisfaction with body appearance and problematic Internet use

Background and objectives: Given that dissatisfaction with bodily appearance can sometimes lead to the avoidance of personal contacts and the increase of internet use, this study examines this relationship. The direct role of dissatisfaction with bodily appearance along with the possible mediation effects of depression, anxiety and self-esteem were tested. Methods: A total of 694 participants completed an online questionnaire (58.5% male, mean age 21.5 years), containing measures on problematic internet use, depression and anxiety symptoms, self-esteem and satisfaction with body image. Path analyses were used to test direct and indirect effects. Results: Satisfaction with body appearance had a significant negative direct effect on problematic internet use among both sexes. Though, satisfaction with body appearance had a positive effect on self-esteem and negative on anxiety, neither self-esteem nor anxiety had a direct significant effect on problematic internet use. The effect of dissatisfaction with body appearance was mediated via the self-esteem–depression path toward problematic internet use. Conclusions: Dissatisfaction with physical appearance seems to have a significant role in individuals’ immersing themselves in internet use

Prevalence of problematic internet use in Slovenia

BACKGROUND: Internet use is an integral part of our everyday activities; however, Internet use may become problematic and harmful in a minority of cases. The majority of reported prevalence rates of problematic Internet use refer to adolescent samples, whereas epidemiological studies on representative adult populations are lacking. This study aimed to reveal the prevalence and characteristics of problematic Internet use in Slovenia. METHODS: Problematic Internet Use Questionnaire (PIUQ) was included in European Health Interview Study (EHIS) on representative Slovenian sample. The frequency of Internet use and problematic Internet use were both assessed. RESULTS: 59.9% of Slovenian adult population uses the Internet daily, and 3.1% are at risk of becoming problematic Internet users, 11% in the age group from 20 to 24 years. Those being at risk for becoming problematic Internet users are younger (mean age 31.3 vs. 48.3 for non-problematic users), more likely to be males (3.6% of males, whereas 2.6% of females are affected), students (12.0%), unemployed (6.3%) or unable to work (8.7%), single (6.5%), with high education (4.5%). Regression analysis revealed that the strongest predictor of being at risk for problematic Internet use is age (ß=-0.338, p<0.001); followed by high educational level (ß=0.145; p<0.001) and student status (ß=0.136; p<0.001). CONCLUSION: 3.1% of Slovenian adult population are at risk of becoming problematic Internet users, whereas 3 out of 20 Slovenian adolescents aged from 18 to 19 years are at risk (14.6%). Prevention programs and treatment for those affected are paramount, especially for the young generation

Psychometric properties of the Problematic Internet Use Questionnaire Short-Form (PIUQ-SF-6) in a nationally representative sample of adolescents

Despite the large number of measurement tools developed to assess problematic Internet use, numerous studies use measures with only modest investigation into their psychometric properties. The goal of the present study was to validate the short (6-item) version of the Problematic Internet Use Questionnaire (PIUQ) on a nationally representative adolescent sample (n = 5,005; mean age 16.4 years, SD = 0.87) and to determine a statistically established cut-off value. Data were collected within the framework of the European School Survey Project on Alcohol and Other Drugs project. Results showed an acceptable fit of the original three-factor structure to the data. In addition, a MIMIC model was carried out to justify the need for three distinct factors. The sample was divided into users at-risk of problematic Internet use and those with no-risk using a latent profile analysis. Two latent classes were obtained with 14.4% of adolescents belonging to the at-risk group. Concurrent and convergent validity were tested by comparing the two groups across a number of variables (i.e., time spent online, academic achievement, self-esteem, depressive symptoms, and preferred online activities). Using the at-risk latent profile analysis class as the gold standard, a cut-off value of 15 (out of 30) was suggested based on sensitivity and specificity analyses. In conclusion, the brief version of the (6-item) PIUQ also appears to be an appropriate measure to differentiate between Internet users at risk of developing problematic Internet use and those not at risk. Furthermore, due to its brevity, the shortened PIUQ is advantageous to utilize within large-scale surveys assessing many different behaviors and/or constructs by reducing the overall number of survey questions, and as a consequence, likely increasing completion rates

The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large-scale cross-sectional study

Over the last decade, research into ‘addictive technological behaviors’ has substantially increased. Research has also demonstrated strong associations between addictive use of technology and comorbid psychiatric disorders. In the present study, 23,533 adults (mean age 35.8 years, ranging from 16 to 88 years) participated in an online cross-sectional survey examining whether demographic variables, symptoms of Attention Deficit/Hyperactivity Disorder (ADHD), Obsessive-Compulsive Disorder (OCD), anxiety, and depression could explain variance in addictive use (i.e., compulsive and excessive use associated with negative outcomes) of two types of modern online technologies: social media and video games. Psychometrically robust instruments were utilized. Correlations between symptoms of addictive technology use and mental disorder symptoms were all positive and significant, including the interrelationship between the two addictive technological behaviors. Age appeared to be inversely related to the addictive use of these technologies. Being male was significantly associated with addictive use of video games, whereas being female was significantly associated with addictive use of social media. Being single was positively related to both addictive social networking and video gaming. Hierarchical regression analyses showed that demographic factors explained between 11% and 12% of the variance in addictive technology use. The mental health variables explained between 7% and 15% of the variance. The study significantly adds to our understanding of mental health symptoms and their role in addictive use of modern technology. Clinical implications, strengths, and limitations are discussed

The development and psychometric evaluation of the Internet Disorder Scale (IDS-15)

Introduction: Previously published research suggests that improvement in the assessment of Internet addiction (IA) is paramount in advancing the field. However, little has been done to address inconsistencies in the assessment of IA using a more updated framework. The aim of the present study was to develop a new instrument to assess IA based on a modification of the nine Internet Gaming Disorder (IGD) criteria as suggested by the American Psychiatric Association in the latest (fifth) edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), and to provide a taxonomy of the potential risk of IA risk among participants. Methods: A heterogeneous sample of Internet users (n=1,105) was recruited online (61.3% males, mean age 33 years). Construct validity of the new instrument – Internet Disorder Scale (IDS-15) – was assessed by means of factorial, convergent, and discriminant validity. Criterion-related validity and reliability were also investigated. Additionally, latent profile analysis (LPA) was carried out to differentiate and characterize Internet users based on their potential IA risk. Results: The construct and criterion-related validity of the IDS-15 were both warranted. The IDS-15 proved to be a valid and reliable tool. Using the LPA, participants were classed as “low addiction risk” (n = 183, 18.2%), “medium addiction risk” (n = 456, 41.1%), and “high addiction risk” (n = 455, 40.77%). Furthermore, key differences emerged among these classes in terms of age, relationship status, cigarette consumption, weekly Internet usage, age of Internet use initiation, and IDS-15 total scores. Conclusions: The present findings support the viability of using adapted IGD criteria as a framework to assess IA