Prevalence and Risk Factors of Internet Addiction among Hungarian High School Teachers

Abstract

The extensive availability of internet has led to the the recognition of problematic internet use (so called internet addiction, IA) mostly involving adolescents. There is limited data about the prevalence of IA in adults. Here we present a study focusing on the prevalence and risk factors of internet addiction among high school teachers. Overall 2500 paper-based questionnaires were successfully delivered and 1817 responses received (response rate of 72.7%). In our study 1194 females (65.7%) and 623 males (34.3%) participated. In a multivariate analysis including of all factors (demographic data, internet habits, comorbidity etc.) age <35 years (OR: 6.098, CI: 5.09–7.08, p < 0.001), male gender (OR = 5.413, CI: 4.39–6.18, p = 0.002), surfing on the internet > 5 h daily (OR 2.568, CI: 2.03–3.39, p < 0.001), having no children (OR: 1.353, CI: 1.13–1.99, p = 0.0248), and having secondary employment (OR = 11.377, CI: 8.67–13.07, p = 0.001) were significantly associated with internet addiction. This is the first study from Hungary showing the prevalence and risk factors of internet addiction among high school teachers. A small, but significant proportion suffered from IA. Our study also draws attention to the risk factors of IA such as younger age, family status and working type.

Prevalence and Risk Factors of Internet Addiction among Hungarian High School Students

“…Based on our results, about one fifth of our high school students suffered from internet addiction, which is significantly higher than the estimated overall pooled prevalence of 7% in the general population [ 31 ]. However, based on very recent data, IA prevalence can be much higher among adolescents, which is in line with our results [ 7 , 17 , 28 , 30 , 31 , 32 , 33 ]. A recent study showed a rate of 15.5% of problematic internet users in a representative sample of 16-year-old Hungarians, which is nearly comparable to our findings [ 34 ].…”

“…As there are no clear diagnostic criteria for internet addiction, it is highly recommended to measure excessive internet use with a continuous questionnaire [ 12 ]. We chose the Problematic Internet Use Questionnaire (PIUQ) because its structure tightly adheres to the proposed diagnostic criteria for internet addiction and was created based on the clinometric and psychometric analysis of Young’s internet addiction test, independently validated by several groups and used in our previous published work [ 7 , 28 , 29 , 30 ]. The questionnaire contains 18 items, each scored on a 5-point Likert-type scale ranging from 1 (never) to 5 (always).…”

“…Since in this study we focused on the global psychological consequences of internet addiction, we used the PIUQ total score in statistical analyses, which was computed by summing the scores on all the items of the scale. A total score exceeding 41 points suggests internet addiction [ 7 , 28 ].…”

The Effect of Primary and Middle School Teachers’ Problematic Internet Use and Fear of COVID-19 on Psychological Need Thwarting of Online Teaching and Psychological Distress

“…Our results suggest that that excessive problematic Internet use behaviors should be considered as contributing risk factors in terms of teachers’ psychological distress, particularly in the online teaching context during COVID-19. In explaining the role of PIU among teacher populations, certain characteristics (i.e., excessive Internet use and workaholic tendencies) should be considered in the context of COVID-19 [ 70 , 71 , 72 , 73 , 74 ]. Specifically, teachers using the Internet for 5 or more hours per day are susceptible to the development of PIU [ 70 ].…”

The Impact of Internet Addiction and Job Satisfaction on Mental Health Symptoms among a Sample of Portuguese Workers

“…Further research has suggested that IA is associated with relevant psychological impairment, such as psychopathology, serious mental illness including depression and anxiety [ 10 ], and suicidality [ 10 ]. Common significant predictors of IA include age (being < 35 years), being male, using the internet > 5 h daily, having no children, having secondary employment [ 11 ], taking illicit drugs, being diabetic [ 12 ], dysfunctional emotional regulation [ 13 ], loneliness [ 14 ], lower levels of self-control and higher levels of foreclosed and diffuse identity [ 15 ], low education among parents, lifetime tobacco use [ 16 ], social connectedness, social media addiction, digital game addiction and smartphone addiction [ 17 ], low self-esteem [ 18 ], and low emotional intelligence [ 19 ].…”