大学生抑郁和焦虑共病的潜在剖面分析及其与社交网络成瘾的关联

doi:10.3969/j.issn.1674-8115.2026.02.010

上海交通大学学报（医学版） ›› 2026, Vol. 46 ›› Issue (2): 213-219.doi: 10.3969/j.issn.1674-8115.2026.02.010

• 论著 · 公共卫生 • 上一篇

大学生抑郁和焦虑共病的潜在剖面分析及其与社交网络成瘾的关联

李剑¹, 王甦平²()

^1.上海交通大学医学院附属仁济医院，上海 200127
^2.上海交通大学医学院学科规划处，上海 201318

收稿日期:2025-07-14 接受日期:2025-10-16 出版日期:2026-02-04 发布日期:2026-02-04
通讯作者: 王甦平，副研究员，博士；电子信箱：wangsuping@shsmu.edu.cn。
作者简介:第一联系人：为共同第一作者（co-first authors）。
基金资助:
国家重点研发计划(2020YFC2006400);上海市教育卫生党委系统党建研究会课题(2023ZX165);2023年度上海交通大学“晨星优秀青年管理人员计划”

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

Li Jian¹, Wang Suping²()

^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

Received:2025-07-14 Accepted:2025-10-16 Online:2026-02-04 Published:2026-02-04
Contact: Wang Suping, E-mail：wangsuping@shsmu.edu.cn.
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

摘要/Abstract

摘要：

目的·探究大学生抑郁症状与焦虑症状的共病情况及其与社交网络成瘾之间的关联。方法·通过在上海市5所高等院校进行的针对本科生的横断面问卷调查，收集调查对象的人口学信息，采用患者健康问卷9条目（Patient Health Questionnaire-9，PHQ-9）、广泛性焦虑量表（Generalized Anxiety Disorder，GAD-7）和青少年社交网络成瘾评估量表评估抑郁、焦虑及社交网络成瘾情况。采用Logistic回归对大学生社交网络成瘾进行多因素分析。采用潜在剖面分析对大学生的抑郁症状和焦虑症状进行分类，识别大学生抑郁和焦虑情况的异质性，并通过稳健三步法校正分类误差。运用χ²检验和Logistic回归分析明确各剖面的社交网络成瘾率差异是否存在统计学意义。结果·共纳入调查对象1 768名，23.53%的调查对象存在抑郁和焦虑共病的情况，66.29%的调查对象有社交网络成瘾。调整人口学因素后，大学生抑郁和焦虑共病组（n=416）发生社交网络成瘾的概率是无抑郁或焦虑组（n=618）的6.093倍（OR=6.093，95%CI 4.426~8.389），仅有抑郁或焦虑组（n=734）发生社交网络成瘾的概率是无抑郁或焦虑组的2.442倍（OR=2.442，95%CI 1.947~3.064）。大学生抑郁和焦虑症状的潜在剖面可划分为中水平组（45.4%）、低水平组（46.3%）和高水平组（8.3%）。3个剖面的社交网络成瘾率差异存在统计学意义，中水平组和高水平组较低水平组更易发生社交网络成瘾（均P<0.001）。结论·大学生抑郁和焦虑情况存在异质性，且易出现抑郁合并焦虑的情况。对于高抑郁、高焦虑情况的大学生，其社交网络成瘾情况也较严重。因此，应高度关注大学生的心理健康状况，针对抑郁合并焦虑症状严重的大学生，就其社交网络成瘾问题开展精准化干预工作。

关键词: 大学生, 抑郁合并焦虑, 社交网络成瘾, 潜在剖面分析

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

中图分类号:

R749

李剑, 王甦平. 大学生抑郁和焦虑共病的潜在剖面分析及其与社交网络成瘾的关联[J]. 上海交通大学学报（医学版）, 2026, 46(2): 213-219.

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.

图/表 5

参考文献 30

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Item	Number	Percent/%
Gender
Male	859	48.59
Female	909	51.41
Enrollment year
2022	896	50.68
2021	437	24.72
2020	325	18.38
2019	80	4.52
2018	30	1.70
Family economic condition
Excellent	43	2.43
Good	365	20.64
Average	1 156	65.38
Poor	162	9.16
Extremely poor	42	2.38
Divorced family
No	1 600	90.50
Yes	168	9.50
Only child in the family
No	882	49.89
Yes	886	50.11
Depression symptoms
No	682	38.57
Yes	1 086	61.43
Anxiety symptoms
No	838	47.40
Yes	930	52.60
Comorbidity of depression and anxiety symptoms
No	1 352	76.47
Yes	416	23.53
Social networking service addiction
No	596	33.71
Yes	1 172	66.29

Item	Number	Percent/%
Gender
Male	859	48.59
Female	909	51.41
Enrollment year
2022	896	50.68
2021	437	24.72
2020	325	18.38
2019	80	4.52
2018	30	1.70
Family economic condition
Excellent	43	2.43
Good	365	20.64
Average	1 156	65.38
Poor	162	9.16
Extremely poor	42	2.38
Divorced family
No	1 600	90.50
Yes	168	9.50
Only child in the family
No	882	49.89
Yes	886	50.11
Depression symptoms
No	682	38.57
Yes	1 086	61.43
Anxiety symptoms
No	838	47.40
Yes	930	52.60
Comorbidity of depression and anxiety symptoms
No	1 352	76.47
Yes	416	23.53
Social networking service addiction
No	596	33.71
Yes	1 172	66.29

Item	OR	95%CI	P value
Only depression or only anxiety symptoms	2.493	1.994‒3.117	<0.001
Comorbidity of depression and anxiety symptoms	6.129	4.477‒8.391	<0.001

Item	OR	95%CI	P value
Only depression or only anxiety symptoms	2.493	1.994‒3.117	<0.001
Comorbidity of depression and anxiety symptoms	6.129	4.477‒8.391	<0.001

Item	OR	95%CI	P value
Comorbidity
Only depression or only anxiety symptom	2.442	1.947‒3.064	<0.001
Comorbidity of depression and anxiety symptoms	6.093	4.426‒8.389	<0.001
Gender	1.123	0.910‒1.387	0.278
Enrollment year
2021	1.114	0.860‒1.443	0.413
2020	0.889	0.670‒1.179	0.414
2019	1.431	0.841‒2.437	0.187
2018	0.633	0.283‒1.415	0.265
Family economic condition
Good	0.640	0.311‒1.316	0.224
Average	0.841	0.418‒1.692	0.628
Poor	0.759	0.349‒1.651	0.487
Extremely poor	0.527	0.200‒1.391	0.196
Divorced family	0.739	0.507‒1.077	0.116
Being one-child in the family	1.473	1.186‒1.830	<0.001

大学生抑郁和焦虑共病的潜在剖面分析及其与社交网络成瘾的关联

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

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参考文献 30

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Metrics

Categorical model	AIC	BIC	aBIC	Entropy	LMR (P value)	BLRT (P value)	Categorical probability
M1	36 279.037	36 311.902	36 292.841	‒	‒	‒	‒
M2	20 678.622	20 716.966	20 694.727	0.872	<0.001	<0.001	0.199, 0.801
M3	20 087.546	20 142.322	20 110.553	0.866	0.006	0.007	0.454, 0.463, 0.083
M4	19 600.573	19 671.782	19 630.482	0.934	<0.001	<0.001	0.426, 0.113, 0.439, 0.021

Category	OR	95%CI	P value
Medium-level group	3.044	2.457‒3.770	<0.001
High-level group	5.467	3.377‒8.852	<0.001

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