Longitudinal study on anxiety and intolerance of uncertainty among Chinese college students
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摘要:
目的 探讨中国大学生焦虑与无法忍受不确定(IU)的纵向变化及相关预测因素,为促进学生心理健康提供理论参考。 方法 采用无法忍受不确定性简版量表(IUS-SF)、广泛性焦虑障碍量表(GAD-7),分别在2021年9月10日至10月17日(T1,基线调查)、2023年3月15日至4月22日(T2)对广东省22所高校5 683名在校大学生进行问卷调查。采用配对样本t检验分析大学生焦虑和IU的变化,建立线性回归模型探索能够预测T1、T2时期焦虑、IU及其变化的因素。 结果 T1时,大学生焦虑和IU得分分别为(3.26±3.46,34.88±7.96)分,T2时分别为(4.41±4.16,36.40±8.07)分;T2时大学生的焦虑和IU水平均高于T1时(t值分别为19.59,13.67,P值均 < 0.01)。线性回归结果发现,年龄(B=-0.02)、中等(B=-0.18)和较差(B=-0.88)的心理健康状况、在线浏览新型冠状病毒感染疫情(以下简称“疫情”)相关信息时间为>1~ < 3 h/d(B=-0.30)和≥3 h/d(B=-0.22)均能负向预测T1至T2时焦虑的变化;居住在农村(B=0.11)能正向预测T1至T2时焦虑的变化(P值均 < 0.05)。中等(B=-0.19)和较差(B=-0.47)的心理健康状况,在线浏览疫情相关信息>1~ < 3 h/d(B=-0.32)和≥3 h/d(B=-0.33),学业受到疫情的中等影响(B=-0.10),个人计划受到疫情的中等(B=-0.13)和严重(B=-0.22)影响,均能负向预测T1至T2时IU的变化(P值均 < 0.05)。 结论 大学生焦虑和IU的水平在疫情后显著提高。需要长期监测大学生的心理健康状况,尤其对存在不良心理状况的学生应特别关注。 Abstract:Objective To explore the longitudinal changes and related predictive factors of anxiety and intolerance of uncertainty (IU) among Chinese college students, so as to provide theoretical reference for promoting students' mental health. Methods Intolerance of Uncertainty Scale-short Form and the 7-item Generalized Anxiety Disorder Scale were administered among 5 683 students from 22 universities in Guangdong Province from September 10 to October 17, 2021 (T1, baseline survey), and from March 15 to April 22, 2023 (T2). Using paired sample t-test to analyze the changes in anxiety and IU among college students, a linear regression model was established to explore factors that can predict anxiety, IU and their changes during T1 and T2 periods. Results During the T1 period, the average scores of anxiety and IU among college students were (3.26±3.46, 34.88±7.96), while during the T2 period, they were (4.41±4.16, 36.40±8.07). During the T2 period, the levels of anxiety and IU among college students were higher than those during the T1 period (t=19.59, 13.67, P < 0.01). The linear regression results showed that age (B=-0.02), moderate (B=-0.18) and poor (B=-0.88) mental health status, as well as online browsing of Corona Virus Disease 2019 (COVID-19) epidemic (later called as epidemic) related information for >1- < 3 hours (B=-0.30) and ≥3 hours (B=-0.22), all of which could negatively predict changes in anxiety during T1 to T2 periods. Living in rural areas (B=0.11) could positively predict changes in anxiety during T1 to T2 periods (P < 0.05). Moderate (B=-0.19) and poor (B=-0.47) mental health status, browsing epidemic related information online for >1- < 3 hours (B=-0.32) and ≥3 hours (B=-0.33), academic performance being moderately affected by the epidemic (B=-0.10), and personal planning being moderately affected by the epidemic (B=-0.13) and severely affected (B=-0.22), all of which could negatively predict changes in IU during T1 to T2 periods (P < 0.05). Conclusions Levels of anxiety and intolerance of uncertainty increases significantly after epidemic. Mental health status of college students should need long-term monitoring, and students with poor mental health should need special attention. -
Key words:
- Anxiety /
- Mental Health /
- Follow-up studies /
- Regression analysis /
- Students
1) 利益冲突声明 所有作者声明无利益冲突。 -
表 1 大学生焦虑、无法忍受不确定及其变化的线性回归模型[B值(标准误),n=5 683]
Table 1. Linear regression models of anxiety, IU and their changes among college students[B (SE), n=5 683]
自变量 选项 焦虑 IU 焦虑的变化 IU的变化 T1 T2 T1 T2 年龄 -0.02(-0.03)** -0.04(-0.06)** -0.03(0.01)** -0.04(-0.06)** -0.02(-0.03)* 0.00(-0.01) 性别 0.09(0.04)** 0.04(0.02) 0.16(0.03)** 0.15(0.07)** -0.03(-0.02) -0.01(0.00) 家庭居住地 -0.02(-0.01) 0.10(0.05)** -0.01(0.03) 0.00(0.00) 0.11(0.05)** 0.01(0.00) 独生子女 -0.04(-0.02) -0.07(-0.03) -0.09(0.03)** -0.06(-0.03) -0.03(-0.01) 0.03(0.01) 心理健康状况 中等 0.80(0.25)** 0.47(0.15)** 0.55(0.04)** 0.35(0.11)* -0.18(-0.06)** -0.19(-0.06)** 较差 1.90(0.20)** 0.65(0.07)** 0.78(0.12)** 0.28(0.03)* -0.88(-0.09)** -0.47(-0.05)** 过去2周在线浏览疫情信息时间/(h·d-1) >1~ < 3 -0.07(-0.02) -0.38(-0.13)** 0.08(0.10) -0.25(-0.09)* -0.30(-0.10)** -0.32(-0.11)** ≥3 -0.01(0.00) -0.24(-0.09)* 0.27(0.09)** -0.08(-0.03) -0.22(-0.08)* -0.33(-0.12)** 学业受到疫情影响程度 严重 0.20(0.09)** 0.39(0.08)** 0.33(0.08) 0.22(0.04)* 0.00(0.00) -0.11(-0.02) 中等 0.09(0.06) 0.14(0.06)** 0.19(0.04)* 0.09(0.04)* 0.02(0.01) -0.10(-0.04)* 家庭收入受到疫情影响程度 严重 0.47(0.04)** 0.16(0.03)* 0.14(0.08)** 0.12(0.02) -0.01(0.00) -0.02(0.00) 中等 0.14(0.04)** 0.07(0.03) 0.08(0.04)** 0.04(0.02) -0.01(-0.01) -0.03(-0.01) 个人计划受到疫情影响程度 严重 0.32(0.09)** 0.31(0.09)** 0.49(0.06)** 0.25(0.07)** 0.04(0.01) -0.22(-0.07)** 中等 0.22(0.10)** 0.15(0.07)** 0.30(0.04)** 0.16(0.07)** -0.03(-0.01) -0.13(-0.06)** 注: *P < 0.05,**P < 0.01;年龄为连续型变量,性别、家庭居住地、独生子女、心理健康状况、过去2周在线浏览疫情信息时间分别以男生、城镇、非独生子女、良好、≤1 h为参照,学业、家庭收入、个人计划受到疫情影响程度均以较小或没有影响为参照。 -
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