Journal of Shanghai Jiao Tong University (Medical Science) >

2026 , Vol. 46 >Issue 2: 213 - 219

DOI: https://doi.org/10.3969/j.issn.1674-8115.2026.02.010

Public health

Latent profile analysis of comorbidity of depression and anxiety symptoms in college students and its correlation with social networking service addiction

  • Li Jian ,
  • Wang Suping
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  • 1.Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
    2.Office of Academic Planning and Development, Shanghai Jiao Tong University School of Medicine, Shanghai 201318, China
Wang Suping, E-mail：wangsuping@shsmu.edu.cn.

Received date: 2025-07-14

  Accepted date: 2025-10-16

  Online published: 2026-02-04

Supported by

National Key Research and Development Program of China(2020YFC2006400);Project of the Working Committee of Education and Public Health of Shanghai Municipality(2023ZX165);2023 Shanghai Jiao Tong University Morning Star Outstanding Young Management Personnel Program

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Abstract

Objective ·To explore the comorbidity of depression and anxiety symptoms among college students and its correlation with social networking service addiction. Methods ·A cross-sectional questionnaire survey was conducted among undergraduate students from five colleges in Shanghai to collect the demographic characteristics of the participants, and the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder (GAD-7), and the Social Network Addiction Tendency Scale for Adolescents were used to assess the status of depression, anxiety, and social networking service addiction. Multivariate analysis of social networking service addiction among college students was conducted by using Logistic regression. Latent profile analysis was employed to categorize depression and anxiety symptoms among college students, and to identify their heterogeneity. Classification error was corrected by using the robust three-step method. The χ2 test and Logistic regression analysis were employed to examine whether significant differences existed in the rates of social networking service addiction across different categories. Results ·Among the 1 768 participants enrolled in the survey, 23.53% had comorbid depression and anxiety symptoms, and 66.29% exhibited social networking service addiction. The probability of social networking service addiction in the group with comorbid depression and anxiety symptoms (n=416) was 6.093 times that of the group without depression or anxiety symptoms (n=618) (OR=6.093, 95%CI 4.426‒8.389), after adjustment for demographic factors. The probability of social networking service addiction in the group with either depression or anxiety symptoms alone (n=734) was 2.442 times that of the group without depression or anxiety symptoms (OR=2.442, 95%CI 1.947‒3.064), after adjustment for demographic factors. Latent profile analysis classified depression and anxiety symptoms into three categories: a medium-level group (45.4%), a low-level group (46.3%), and a high-level group (8.3%). There were statistically significant differences in the social networking service addiction rates among the three categories. Moreover, compared with the low-level group, the medium-level group and the high-level group had a higher risk of developing social networking service addiction (all P<0.001). Conclusion ·Depression and anxiety symptoms among college students are heterogeneous, and comorbidity is common. Students with more severe comorbid depression and anxiety symptoms also have higher levels of social networking service addiction. Greater attention should be paid to the mental health of college students, and targeted interventions should be implemented to address social networking service addiction among college students with severe symptoms of depression and anxiety.

Key words： college students; comorbidity of depression and anxiety symptoms; social networking service addiction; latent profile analysis

Cite this article

Li Jian , Wang Suping . Latent profile analysis of comorbidity of depression and anxiety symptoms in college students and its correlation with social networking service addiction[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2026 , 46(2) : 213 -219 . DOI: 10.3969/j.issn.1674-8115.2026.02.010

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