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Wu, Anise M. S.; Lau, Joseph T. F.; Cheng, Kit-man; Law, Rita W.; Tse, Vincent W. S.; Lau, Mason M. C. – Journal of Early Adolescence, 2018
Internet addiction (IA) is prevalent among adolescents and imposes a serious public health threat. Familial risk and protective factors may co-exist and interact with each other to determine IA. We conducted a cross-sectional survey among 9,618 Secondary 1 to 4 students in Hong Kong, China. About 16% of the surveyed students were classified as…
Descriptors: Risk, Addictive Behavior, Multivariate Analysis, Intervention
Portešová, Šárka; Urbánek, Tomáš – Journal of Early Adolescence, 2013
This study assessed differences in Parker's typology of perfectionism (healthy perfectionist, unhealthy perfectionist, and nonperfectionist). We compared the results from previous research with follow-up 2005 and 2010 data collected from highly gifted Czech mathematicians aged 12 to 16 years. The study examined whether the same three…
Descriptors: Classification, Personality Traits, Scores, Foreign Countries
Reid, Joan A.; Sullivan, Christopher J. – Journal of Early Adolescence, 2016
Using latent class analysis (LCA), this study identified a dyadic taxonomy of delinquent youth categorized by varying types of maternal-youth reporting discrepancies (i.e., youth < maternal, youth > maternal) within a sample of 764 14-year-old high-risk youth. Four distinctive subgroups of youth were identified, two of which reported more…
Descriptors: Delinquency, Classification, Mothers, Behavior Problems
Zettergren, Peter – Journal of Early Adolescence, 2007
A modern clustering technique was applied to age-10 and age-13 sociometric data with the purpose of identifying longitudinally stable peer status clusters. The study included 445 girls from a Swedish longitudinal study. The identified temporally stable clusters of rejected, popular, and average girls were essentially larger than corresponding…
Descriptors: Females, Multivariate Analysis, Classification, Preadolescents