心理学
焦虑
潜在类模型
验证性因素分析
临床心理学
毒物控制
萧条(经济学)
结构方程建模
精神科
医学
统计
环境卫生
数学
宏观经济学
经济
作者
Yuhan Zhang,Hai-Ping Liao,Jingjing Gu,Jin‐Liang Wang
标识
DOI:10.1016/j.chiabu.2022.105630
摘要
Few studies have employed person-centered approaches (i.e. latent profile analysis in this study) to investigate the specific patterns of childhood maltreatment in a large sample of Chinese adolescents, and little is known about the predictive validity of latent profile analysis on internalizing problems, compared with multiple individual risk model and cumulative risk model. The purpose of this study was to investigate whether differential patterns of maltreatment existed by employing latent profile analysis with a sample of 9071 Chinese adolescents, and further examined the predictive validity of latent profile analysis on internalizing problems, relative to the cumulative risk and multiple individual risk model. Using a stratified sampling approach, 10,515 participants (Mean age = 14.24; SD = 1.73) were chosen from three different types of middle schools in Chongqing city, China. 9071 valid responses (males = 4775; females = 4296) were obtained for final analysis. Participants reported their childhood maltreatment experience, anxiety and depression symptoms. Latent profile analysis was used to obtain possible patterns of maltreatment with Mplus version 7. 4. Bolck-Croon-Hagenaars (BCH) method was used to test the association between maltreatment patterns and anxiety and depression symptoms. Relative weight analysis and analysis of variance (ANOVA) were used to test the predictive validity of latent profile analysis, multiple individual risk and cumulative risk model. Using latent profile analysis, two patterns of childhood maltreatment were uncovered ("No Maltreatment" and "Multiple Maltreatment"). Further analysis showed that multiple individual risk model accounted for the largest variance in anxiety (R2 = 26.7%) and depression (R2 = 33%), followed by the latent profile analysis (R2 = 14.7% for anxiety and 18.6% for depression) and the cumulative risk model (R2 = 12.9% for anxiety and 15.2% for depression). Our findings suggested that the multiple individual risk model is the optimal model for identifying adolescents at the risk of developing anxiety and depression symptoms, and the results suggested emotional abuse and emotional neglect are risk factors for higher levels of anxiety and depression among adolescents.
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