Latent Profile Analysis of Left-behind Adolescents’ Psychosocial Adaptation in Rural China

2019 ◽  
Vol 48 (6) ◽  
pp. 1146-1160 ◽  
Author(s):  
Jingxin Zhao ◽  
Qianyu Li ◽  
Liwei Wang ◽  
Lingyu Lin ◽  
Wenxin Zhang
2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S630-S630
Author(s):  
Haimin Pan

Abstract Grief experiences among older adults in China are understudied, though a variety of negative bereavement outcomes have been delineated. The present work sought to explore grief patterns among Chinese older people in rural areas, as well as the factors influencing the bereavement results. Participants were 352 older residents who responded to a face-to-face interview and lived in rural areas in Zhejiang Province of China. Latent profile analysis (LPA) was used to identify subtypes of class membership in combing complicated grief (CG), depression, anxiety, and meaning in life. Afterwards, these subgroups were compared on demographic characteristics and meaning making variable. The LPA model best fitting the data was a three-class solution comprised of “adaptive” (n=235; 66.8% of the sample), “moderate maladaptive” (n=83; 23.6% of the sample), and “severe maladaptive” groups (n=34; 9.7% of the sample). Compared to the “severe maladaptive” group, participants in the “adaptive” group had better physical functioning, higher education and incomes levels, and less meaning making engagement, while participants in the “moderate maladaptive” group had longer bereavement duration, better physical functioning, and less meaning making activities. Relative to the “moderate maladaptive” group, participants who were adaptive to the loss possessed longer bereavement duration better physical functioning, higher education and incomes levels, and less meaning making engagement. Findings suggest three distinct patterns of bereavement outcomes among Chinese older adults. Multiple factors impacting the results were taken into consideration. Future replication is necessary to validate these subgroups, and professional services should be provided to bereaved older Chinese in need.


2019 ◽  
pp. 003022281987040
Author(s):  
Haimin Pan ◽  
Rong Hu

The present work sought to explore grief patterns among Chinese older people in rural areas as well as the factors influencing the diverse bereavement results. Participants were 352 older residents who lived in rural areas in China. Latent profile analysis was used to identify subtypes of class membership in combing complicated grief, depression, anxiety, and meaning in life. One-way analysis of variance, chi-square analysis, and multinomial regression analysis were performed together to examine the predictor best distinguishing between classes. The latent profile analysis model best fitting the data was a three-class solution comprised of adaptive ( n = 235; 66.8%), moderate maladaptive ( n = 83; 23.6%), and severe maladaptive groups ( n = 34; 9.7%). Compared to the severe maladaptive and moderate maladaptive groups, participants in the adaptive group had better physical functioning. Participants in the moderate maladaptive group had longer bereavement duration than those in the severe maladaptive group. Future replication is desirable for validating these subgroups.


BMJ Open ◽  
2019 ◽  
Vol 9 (6) ◽  
pp. e029331 ◽  
Author(s):  
Haining Liao ◽  
Minyi Pan ◽  
Weinan Li ◽  
Changqi Lin ◽  
Xuhao Zhu ◽  
...  

ObjectivesPrevious studies have used latent profile analysis (LPA) to examine rural left-behind children’s anxiety. Further study is needed to identify the heterogeneous characteristics of rural left-behind children’s anxiety and explore the related factors.SettingA cross-sectional survey using a school-based sample was conducted in January 2018 in Qingxin district, Qingyuan city, Guangdong province.Participants1026 left-behind children (effective response rate of the questionnaire: 95.39%).Main outcome measuresProfile latent classes (LC) and anxiety disorder.ResultsThe LPA identified three anxiety LC: ‘low anxiety’ (56.6%), ‘medium anxiety’ (34.8%) and ‘severe anxiety’ (8.6%). The multinomial logistic regression model was used to predict the relationship between personal, family, school factors and anxiety. We found that the variables directly related to lower anxiety classes included age (12–14 years), harmonious or fair relationship with classmates, no neglect, harmonious parental relationship and the duration of mother migration <6 months.ConclusionsThese findings suggested the need for careful consideration of differences in anxieties among rural left-behind children. Identifying latent subgroups may provide an empirical basis for teachers and public health practitioners to implement anxiety intervention efforts.


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