Latent class analysis of loneliness and the influencing factors among school-age children: A cross-sectional survey.

Background: Children's loneliness has become an increasingly pervasive issue of public health due to the vulnerability of school-aged children. This study aims to identify latent classes of school-age children based on their exhibited symptoms of loneliness and explore the influencing factors.

Methods: A cross-sectional study was conducted from March to June 2023 in Shantou, China. Demographic characteristics, Abbreviated Symptom Questionnaire (ASQ), Children's Loneliness Scale (CLS), Perceived social support Scale (PSSS), and Children's Hope Scale (CHS) were collected by questionnaires. Latent class analysis (LCA) was performed based on loneliness symptoms among school-age children, with class characteristics and influencing factors explored through chi-square tests, analysis of variance, lasso regression, and multinomial logistic regression analyses.

Results: A total of 2514 school-age children were enrolled. Four diverse latent classes were identified, namely, the low loneliness group, the borderline loneliness group, the moderate loneliness group, and the high loneliness group, with 37.0 %, 40.4 %, 10.3 % and 12.3 % in each class, respectively. Compared with the low loneliness group, the factors influencing loneliness symptoms in other groups were grade, academic performance, father's education level, experience of being bullied, experience of being physical attacked, homework help from parents, one-child status, number of friends, relationship with friends, feeling respect from parents, perceived social support, as well as hope (all P < 0.05).

Limitations: The study's cross-sectional design, limited sample and area, and self-reporting method may affect the findings' reliability and generalizability.

Conclusions: LCA can categorize different school-age children according to their loneliness symptoms, offering a new perspective of addressing loneliness issues.