Ј Бехав Аддицт. КСНУМКС Мај КСНУМКС: КСНУМКС-КСНУМКС. дои: КСНУМКС / КСНУМКС.
Лее СИ1, Лее Д2, Нам ЦР3, Kim DY2, Парк С4, Квон ЈГ4, Квеон ИС1, Лее И5, Ким ДЈ6, Цхои ЈС3,7.
Апстрактан
Позадина и циљеви
The ubiquitous Internet connections by smartphones weakened the traditional boundaries between computers and mobile phones. We sought to explore whether smartphone-related problems differ from those of computer use according to gender using latent class analysis (LCA).
Методе
After informed consents, 555 Korean middle-school students completed surveys on gaming, Internet use, and smartphone usage patterns. They also completed various psychosocial instruments. LCA was performed for the whole group and by gender. In addition to ANOVA and χ2 tests, post-hoc tests were conducted to examine differences among the LCA subgroups.
Резултати
In the whole group (n = 555), four subtypes were identified: dual-problem users (49.5%), problematic Internet users (7.7%), problematic smartphone users (32.1%), and “healthy” users (10.6%). Dual-problem users scored highest for addictive behaviors and other psychopathologies. The gender-stratified LCA revealed three subtypes for each gender. With dual-problem and healthy subgroup as common, problematic Internet subgroup was classified in the males, whereas problematic smartphone subgroup was classified in the females in the gender-stratified LCA. Thus, distinct patterns were observed according to gender with higher proportion of dual-problem present in males. While gaming was associated with problematic Internet use in males, aggression and impulsivity demonstrated associations with problematic smartphone use in females.
Закључци
An increase in the number of digital media-related problems was associated with worse outcomes in various psychosocial scales. Gaming may play a crucial role in males solely displaying Internet-related problems. The heightened impulsivity and aggression seen in our female problematic smartphone users requires further research.
КЉУЧНЕ РЕЧИ: Internet; addiction; game; gender; latent class analysis; smartphone
ПМИД: КСНУМКС
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