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使用分位数回归分析探讨大学生抑郁障碍的相关因素。

Factors associated with depressive disorders in college students using quantile regression analysis.

作者信息

Xu Haibo, Zhang Chaoran, Wang Zhen, Zhang Chen, Peng Lixin, Liu Xin

机构信息

School of Management, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.

Center for Mental Health Education and Research, Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.

出版信息

BMC Psychiatry. 2025 Sep 26;25(1):868. doi: 10.1186/s12888-025-07334-w.

Abstract

BACKGROUND

Depressive disorders among college students are a significant public health issue. Most existing studies on factors related to depressive disorders use traditional linear regression models, which have limited ability to reveal deeper insights. This study aims to explore the complexities of depressive disorders further by applying quantile regression.

METHODS

The study was conducted at six universities in China from November 26 to December 6, 2022, using a cross-sectional questionnaire survey with a cluster sampling design. The questionnaire includes the Patient Health Questionnaire-9, the Interpersonal Sensitivity subscale of the Symptom Checklist-90, the Positive Psychological Capital Questionnaire, and the Perceived Social Support Scale. Data analysis was performed using quantile regression with SPSS 26.0.

RESULTS

A total of 3,156 college students participated, and 2,580 valid questionnaires were collected. The prevalence of depressive disorders was 22.4%. Quantile regression indicated that depressive disorders were linked to social support (β = -0.044, β = -0.111, β = -0.244, p < 0.001), interpersonal sensitivity (β = 0.073, β = 0.127, β = 0.232, p < 0.001), psychological capital (β = -0.077, β = -0.154, β = -0.252, p < 0.001), and regular contact with family (β = -0.057, p < 0.05). Social support and psychological capital showed negative associations with depressive disorders, while interpersonal sensitivity had a positive association. The strength of these correlations varied across quartiles, with social support, psychological capital, and interpersonal sensitivity being more strongly associated with depressive disorders at higher quartile points.

CONCLUSION

This study identifies the factors influencing college students with varying levels of depressive disorders. Students with severe depression tend to exhibit higher levels of interpersonal sensitivity, psychological capital, and social support. Percentile analysis helps to explore mental health issues more thoroughly, providing valuable details for targeted intervention.

摘要

背景

大学生抑郁症是一个重大的公共卫生问题。大多数现有的关于抑郁症相关因素的研究使用传统线性回归模型,其揭示深层次见解的能力有限。本研究旨在通过应用分位数回归进一步探索抑郁症的复杂性。

方法

本研究于2022年11月26日至12月6日在中国的六所大学进行,采用整群抽样设计的横断面问卷调查。问卷包括患者健康问卷-9、症状自评量表90中的人际敏感分量表、积极心理资本问卷和领悟社会支持量表。使用SPSS 26.0进行分位数回归数据分析。

结果

共有3156名大学生参与,收集到有效问卷2580份。抑郁症患病率为22.4%。分位数回归表明,抑郁症与社会支持(β = -0.044,β = -0.111,β = -0.244,p < 0.001)、人际敏感(β = 0.073,β = 0.127,β = 0.232,p < 0.001)、心理资本(β = -0.077,β = -0.154,β = -0.252,p < 0.001)以及与家人定期联系(β = -0.057,p < 0.05)有关。社会支持和心理资本与抑郁症呈负相关,而人际敏感呈正相关。这些相关性的强度在四分位数间有所不同,社会支持、心理资本和人际敏感在较高四分位数点与抑郁症的关联更强。

结论

本研究确定了影响不同抑郁水平大学生的因素。重度抑郁学生往往表现出更高水平的人际敏感、心理资本和社会支持。百分位数分析有助于更全面地探索心理健康问题,为针对性干预提供有价值的细节。

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