Author:
Wu Jun Xiao,Jia Lin,Li Yan,Liu Qian,Zhang Ying Ying,Zhang Jin,Jia Yan Rong,Fan Zhen
Abstract
BackgroundThe aim of this study was to classify distinct subgroups of adolescents based on the severity levels of their mobile phone addiction and to investigate how these groups differed in terms of their psychosocial characteristics. We surveyed a total of 2,230 adolescents using three different questionnaires to assess the severity of their mobile phone addiction, stress, anxiety, depression, psychological resilience, and personality. Latent class analysis was employed to identify the subgroups, and we utilized Receiver Operating Characteristic (ROC) curves and multinomial logistic regression for statistical analysis. All data analyses were conducted using SPSS 26.0 and Mplus 8.5.MethodsWe classified the subjects into subgroups based on their mobile phone addiction severity, and the results revealed a clear pattern with a three-class model based on the likelihood level of mobile phone addiction (p < 0.05). We examined common trends in psychosocial traits such as age, grade at school, parental education level, anxiety levels, and resilience. ROC analysis of sensitivity versus 1-specificity for various mobile phone addiction index (MPAI) scores yielded an area under the curve (AUC) of 0.893 (95% CI, 0.879 to 0.905, p < 0.001). We also determined diagnostic value indices for potential cutoff points ranging from 8 to 40. The optimal cutoff value for MPAI was found to be >14, which corresponded to the maximum Youden index (Youden index = 0.751).ResultsThe latent classification process in this research confirmed the existence of three distinct mobile phone user groups. We also examined the psychosocial characteristics that varied in relation to the severity levels of addiction.ConclusionThis study provides valuable insights into the categorization of adolescents based on the severity of mobile phone addiction and sheds light on the psychosocial characteristics associated with different addiction levels. These findings are expected to enhance our understanding of mobile phone addiction traits and stimulate further research in this area.