PDF(Pubmed)
Abstract：
UNASSIGNED: The 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.
UNASSIGNED: We 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).
UNASSIGNED: The 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.
UNASSIGNED: This 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.
UNASSIGNED: We 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).
UNASSIGNED: The 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.
UNASSIGNED: This 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.
摘要：
■这项研究的目的是根据手机成瘾的严重程度对青少年的不同亚组进行分类，并调查这些群体在心理社会特征方面的差异。我们使用三种不同的问卷对2,230名青少年进行了调查，以评估他们手机成瘾的严重程度。压力，焦虑,抑郁症,心理韧性，和个性。采用潜在类别分析来识别子组，并利用受试者工作特征(ROC)曲线和多项逻辑回归进行统计分析。所有数据分析均使用SPSS26.0和Mplus8.5进行。
■我们根据受试者的手机成瘾严重程度将其分为亚组，结果揭示了基于手机成瘾可能性水平的三类模型的清晰规律（p<0.05）。我们研究了心理社会特征的共同趋势，如年龄，在学校的年级，父母的教育水平，焦虑程度,和韧性。对各种手机成瘾指数（MPAI）评分的敏感性与1-特异性的ROC分析得出曲线下面积（AUC）为0.893（95％CI，0.879至0.905，p<0.001）。我们还确定了从8到40的潜在截止点的诊断价值指数。发现MPAI的最佳截止值>14，这对应于最大Youden指数（Youden指数=0.751）。
■本研究中的潜在分类过程证实了三个不同的手机用户群体的存在。我们还研究了与成瘾严重程度相关的社会心理特征。
■这项研究根据手机成瘾的严重程度对青少年进行分类提供了有价值的见解，并阐明了与不同成瘾水平相关的社会心理特征。这些发现有望增强我们对手机成瘾特征的理解，并刺激该领域的进一步研究。
■我们根据受试者的手机成瘾严重程度将其分为亚组，结果揭示了基于手机成瘾可能性水平的三类模型的清晰规律（p<0.05）。我们研究了心理社会特征的共同趋势，如年龄，在学校的年级，父母的教育水平，焦虑程度,和韧性。对各种手机成瘾指数（MPAI）评分的敏感性与1-特异性的ROC分析得出曲线下面积（AUC）为0.893（95％CI，0.879至0.905，p<0.001）。我们还确定了从8到40的潜在截止点的诊断价值指数。发现MPAI的最佳截止值>14，这对应于最大Youden指数（Youden指数=0.751）。
■本研究中的潜在分类过程证实了三个不同的手机用户群体的存在。我们还研究了与成瘾严重程度相关的社会心理特征。
■这项研究根据手机成瘾的严重程度对青少年进行分类提供了有价值的见解，并阐明了与不同成瘾水平相关的社会心理特征。这些发现有望增强我们对手机成瘾特征的理解，并刺激该领域的进一步研究。
