中学生线上社交焦虑与抑郁症状和睡眠质量的关联

刘致宏; 张珊珊

doi:10.16835/j.cnki.1000-9817.2022.01.017

中学生线上社交焦虑与抑郁症状和睡眠质量的关联

doi: 10.16835/j.cnki.1000-9817.2022.01.017

刘致宏,
张珊珊^,

沈阳师范大学教育科学学院，辽宁 110034

基金项目:

全国教育科学规划教育部重点项目 DHA210344

详细信息

作者简介:
刘致宏(1998-)，男，辽宁沈阳人，在读硕士，主要研究方向为应用心理学

通讯作者:
张珊珊，E-mail: zhangxiaobai2@163.com

利益冲突声明 所有作者声明无利益冲突。
中图分类号: G479 G444 B844.2
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- 被引次数: 0
出版历程
- 收稿日期: 2021-07-02
- 修回日期: 2021-09-10
- 刊出日期: 2022-01-25

Association between online social anxiety in middle students with depressive symptoms and sleep quality

LIU Zhihong,
ZHANG Shanshan^,

College of Education Science, Shenyang Normal University, Shenyang (110034), China

摘要

摘要: 目的识别中学生线上社交焦虑的潜在类别，并进一步分析不同潜类别与抑郁症状、睡眠质量的关联。方法于2020年10—12月，采用方便整群随机抽样方法选取辽宁省4所中学1 402名初、高中学生，采用线上社交焦虑问卷(SAS-SMU)、流调中心抑郁量表(CES-D)和匹兹堡睡眠质量指数(PQSI)进行问卷调查，对数据进行潜在剖面分析及Logistic回归分析。结果中学生线上社交焦虑分为低线上社交焦虑型(47.00%，659名)、中线上社交焦虑型(43.37%，608名)和高线上社交焦虑型(9.63%，135名)3个潜在类别。Logistic回归分析结果显示，控制人口学变量后，中线上社交焦虑型和高线上社交焦虑型与抑郁症状(β值分别为1.22，2.23，P值均 < 0.01)和睡眠质量(β值分别为0.85，1.68，P值均 < 0.01)均呈正相关。结论中学生的线上社交焦虑存在异质性。学校和家庭应关注线上社交焦虑水平较高的中学生，防止出现抑郁症状和睡眠问题，促进心理健康发展。
- 焦虑 /
- 抑郁 /
- 睡眠 /
- 精神卫生 /
- 回归分析 /
- 学生
Abstract: Objective To identify the latent classes of various online social anxiety among middle school students and further analyze its correlation with depressive symptoms and sleep quality. Methods From October to December in 2020, a total of 1 402 students were randomly selected from 4 middle schools in Liaoning Province by convenient cluster random sampling method. Students completed the Social Anxiety Scale for Social Media Users(SAS-SMU), the Center for Epidemiologic Studies Depression Scale(CES-D) and Pittsburgh Sleep Quality Index(PSQI). Latent Profile Analysis(LPA) was used to identify online social anxiety types. Logistic regression analysis was used to explore the associations between online social anxiety, sleep quality. Results Online social anxiety among middle school students was classified into three potential categories: low online social anxiety type (47.00%, 659), medium online social anxiety type (43.37%, 608), and high online social anxiety type(9.63%, 135). Logistic regression analysis revealed that after controlling for demographic variables, medium online social anxiety type and high online social anxiety type significantly and positively predicted depressive symptoms (β=1.22, 2.23, P < 0.01) with sleep quality (β=0.85, 1.68, P < 0.01). Conclusion There is heterogeneity in online social anxiety among middle school students. Schools and families should pay attention to middle school students with high levels of online social anxiety to prevent depressive symptoms and sleep problems and to promote psychologically healthy development.
- Anxiety /
- Depression /
- Sleep /
- Mental health /
- Regression analysis /
- Students
注释:

1) 利益冲突声明 所有作者声明无利益冲突。

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表 1 中学生线上社交焦虑的潜在剖面分析拟合指数(n=1 402)

Table 1. Potential profile analysis fit indices of online social anxiety among middle school students(n=1 402)

模型	K	Log(L)	AIC值	BIC值	aBIC值	Entropy值	PLMRT值	PBLRT值
1	40	-45 489.07	91 058.14	91 267.97	91 140.90	-	-	-
2	61	-41 997.88	84 117.76	84 437.75	84 243.98	0.91	0.00	0.00
3	82	-40 874.10	81 912.19	82 342.34	82 081.85	0.92	0.00	0.00
4	106	-40 482.46	81 170.92	81 711.22	81 384.03	0.87	0.12	0.00
5	124	-40 16816	80 584.32	81 234.78	80 840.88	0.87	0.22	0.00
6	145	-39 959.07	80 208.13	80 968.75	80 508.14	0.86	0.14	0.00
7	166	-39 794.15	79 920.30	80 791.08	80 263.76	0.85	0.62	0.00

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表 2 不同人口学变量中学生线上社交焦虑潜在类别分布比较

Table 2. Comparison of the distribution of potential categories of online social anxiety among middle school students in different demographic variables

人口统计学指标	选项	人数	低线上社交焦虑型	中线上社交焦虑型	高线上社交焦虑型	χ²值
性别	男	597	321(53.8)	229(38.3)	47(7.9)	19.47^**
	女	805	338(42.0)	379(47.1)	88(10.9)
生源地	城市	544	265(48.7)	249(45.8)	30(5.5)	17.37^**
	农村	858	394(46.0)	359(41.8)	105(12.2)
留守经历	是	157	60(38.2)	79(50.3)	18(11.5)	6.49^*
	否	1 245	599(48.1)	529(42.5)	117(9.4)
学段	初中	653	289(44.3)	285(43.6)	79(12.1)	5.12
	高中	749	334(44.6)	351(46.9)	64(8.5)
独生子女	是	957	464(48.5)	385(40.2)	108(11.3)	5.27
	否	445	226(50.8)	187(42.0)	32(7.2)
注：P < 0.05，*P < 0.01；()内数字为构成比%。

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表 3 中学生线上社交焦虑潜类别与抑郁症状及社交焦虑的Logistic回归分析(n=1 402)

Table 3. Logistic regression analysis of online social anxiety latent category with depressive symptoms and social anxiety among middle school students(n=1 402)

潜在类别	抑郁症状					睡眠质量
潜在类别	β值	标准误	Wald χ²值	OR值(OR值95%CI)	P值	β值	标准误	Wald χ²值	OR值(OR值95%CI)	P值
1				1.00					1.00
2	1.22	0.12	97.56	3.39(2.62~4.23)	< 0.01	0.85	0.15	34.11	2.35(1.76~3.12)	< 0.01
3	2.23	0.25	78.34	9.27(5.66~15.17)	< 0.01	1.68	0.21	64.02	5.38(3.56~8.12)	< 0.01

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