A Phenotype Classification of Internet Use Disorder in a Large-Scale High-School Study
Bibliographic Data
| ID | 15499010 |
|---|---|
| Authors | Katajun Lindenberg (0000-0001-7415-9856, Heidelberg University of Education, corresponding author), Katharina Halasy (0000-0003-2031-451X, Heidelberg University of Education), Carolin Szász-Janocha (Heidelberg University of Education), Lutz Wartberg (0000-0003-4422-5730, Universität Hamburg) |
| Year | 2018 |
| Volume | 15 |
| Issue | 4 |
| Pages | 733-733 |
| Publication date | 2018-04-12 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Environmental Research and Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1661-7827 • E-ISSN: 1660-4601 |
| Publisher | Multidisciplinary Digital Publishing Institute (PUBLISHER • CH) |
| DOI | 10.3390/ijerph15040733 |
| PMID | 29649137 |
| OpenAlex | W2797231029 |
| Language | EN |
| Citations received | 13 |
| References cited | 33 |
Internet Use Disorder (IUD) affects numerous adolescents worldwide, and (Internet) Gaming Disorder, a specific subtype of IUD, has recently been included in DSM-5 and ICD-11. Epidemiological studies have identified prevalence rates up to 5.7% among adolescents in Germany. However, little is known about the risk development during adolescence and its association to education. The aim of this study was to: (a) identify a clinically relevant latent profile in a large-scale high-school sample; (b) estimate prevalence rates of IUD for distinct age groups and (c) investigate associations to gender and education. N = 5387 adolescents out of 41 schools in Germany aged 11-21 were assessed using the Compulsive Internet Use Scale (CIUS). Latent profile analyses showed five profile groups with differences in CIUS response pattern, age and school type. IUD was found in 6.1% and high-risk Internet use in 13.9% of the total sample. Two peaks were found in prevalence rates indicating the highest risk of IUD in age groups 15-16 and 19-21. Prevalence did not differ significantly between boys and girls. High-level education schools showed the lowest (4.9%) and vocational secondary schools the highest prevalence rate (7.8%). The differences between school types could not be explained by academic level
Biology · Cartography · Gene · Geography · Phenotype · Scale (ratio · The Internet · World Wide Web · Child Development and Digital Technology · Computer Science · Impact of Technology on Adolescents · Psychology · Social Media and Politics · Genetics
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| Unique citing works | 13 |
|---|---|
| Citations per year | 1,63 |
| Citation span | 2018 - 2026 (9) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 13 |