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Article(id=1311349978170229284, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349919793905738, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202602095, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1770480000000, receivedDateStr=2026-02-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1790579798499, onlineDateStr=2026-09-28, pubDate=1782316800000, pubDateStr=2026-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790579798499, onlineIssueDateStr=2026-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790579798499, creator=13701087609, updateTime=1790579798499, updator=13701087609, issue=Issue{id=1311349919793905738, tenantId=1146029695717560320, journalId=1227665162245664772, year='2026', volume='53', issue='12', pageStart='2113', pageEnd='2304', issueExtLink='null', onlineDate='null', pubDate='1782316800000', pubDateStr='2026-06-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790579784582, creator='13701087609', updateTime=1790588408144, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1311386089701597565, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349919793905738, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1311386089701597566, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1311349919793905738, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2232, endPage=2237, ext={EN=ArticleExt(id=1311349978396721701, articleId=1311349978170229284, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Empirical study on the network analysis of college students’ mental health and sleep quality ina military medical university, Chongqing, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the correlation patterns and group differences between college students’ mental health and sleep quality using network analysis methods, providing empirical evidence for targeted interventions.

Methods

A total of 428 college students were selected as the research subjects, and surveys were conducted using the General Health Questionnaire (GHQ-20) and the Pittsburgh Sleep Quality Index (PSQI). The mental health-sleep quality network was constructed using the qgraph package in R software, and centrality indicators of each node were calculated. The Network Comparison Test (NCT) was used to analyze the influence of gender and military status on this network.

Results

In the overall network, daytime dysfunction (a7), anxiety (b3), and subjective sleep quality (a1) were core nodes, while anxiety (b3), daytime dysfunction (a7), and depression (b2) served as core bridges between modules. Gender differences were reflected in higher global connectivity strength in males (s=0.960,P=0.048), with statistically significant edge association differences between sleep disorders and daytime dysfunction (P=0.005), and between daytime dysfunction and self-denial (P=0.045). Military status only had a moderating effect on the association between subjective sleep quality and sleep efficiency (P=0.018), with no significant difference in the overall network.

Conclusion

Network analysis reveals the correlation characteristics between college students’ sleep and mental health, providing a scientific path for targeted services.

, authors=Jia CHEN1, Xiao-xiao XU2, Da-li YI1, Fang LI1, Ya-zhou WU1, authorsList=Jia CHEN, Xiao-xiao XU, Da-li YI, Fang LI, Ya-zhou WU, authorCompany=null, correspAuthors=Ya-zhou WU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1311349979508212268, articleId=1311349978170229284, tenantId=1146029695717560320, journalId=1227665162245664772, language=CN, title=重庆市某军医大学大学生心理健康与睡眠质量的网络分析实证研究, columnId=1228016572640461823, journalTitle=现代预防医学, columnName=健康与社会行为, runingTitle=null, highlight=null, articleAbstract=
目的

本研究旨在运用网络分析方法，探究大学生心理健康与睡眠质量的关联模式及组别差异，为精准干预提供实证依据。

方法

以428名大学生为研究对象，采用一般健康问卷（GHQ-20）和匹兹堡睡眠质量指数（PSQI）进行调查，通过R软件的qgraph包构建心理健康-睡眠质量网络，计算各节点中心性指标，并采用网络比较检验（NCT）分析性别与军籍对该网络的影响。

结果

总体网络中，日间功能障碍（a7）、焦虑（b3）、主观睡眠质量（a1）为核心节点，焦虑（b3）、日间功能障碍（a7）、忧郁（b2）为模块间核心桥梁；性别差异体现在男性全局连接强度更高（s=0.960，p=0.048），其中睡眠障碍与日间功能障碍（P=0.005）、日间功能障碍与自我否定（P=0.045）的边关联差异具有统计学意义；军籍身份仅对主观睡眠质量与睡眠效率的关联存在调节作用（P=0.018），在整体网络上无显著差异。

结论

网络分析揭示了大学生睡眠-心理健康的关联特征，为精准服务提供科学路径。

, authors=陈佳1, 徐晓晓2, 易大莉1, 李芳1, 伍亚舟1, authorsList=陈佳, 徐晓晓, 易大莉, 李芳, 伍亚舟, authorCompany=null, correspAuthors=伍亚舟, authorNote=

陈佳（1992—），女，硕士，讲师，研究方向：基于机器学习及深度学习的医学数据预测模型

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伍亚舟，E-mail:
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Chronobiology International, 2023, 40(3): 246-252., articleTitle=Network structure of insomnia symptoms in shift workers compared to non-shift workers, refAbstract=null)], funds=[Fund(id=1311349983987728987, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, awardId=2020XRW15, language=CN, fundingSource=陆军军医大学人文社科基金项目(2020XRW15), fundOrder=null, country=null), Fund(id=1311349984063226460, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, awardId=82304249, language=CN, fundingSource=国家自然科学基金青年项目(82304249), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1311349979768259117, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, xref=1., ext=[AuthorCompanyExt(id=1311349979776647726, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, companyId=1311349979768259117, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Military Preventive Medicine, Military Health Statistics Teaching and Research Office, Army Medical University, Chongqing 400038, China), AuthorCompanyExt(id=1311349979785036335, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, companyId=1311349979768259117, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.陆军军医大学军事预防医学系军队卫生统计学教研室，重庆 400038)]), AuthorCompany(id=1311349979873116720, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, xref=2., ext=[AuthorCompanyExt(id=1311349979885699633, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, companyId=1311349979873116720, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.陆军军医大学医学心理系基础心理学教研室)])], figs=[ArticleFig(id=1311349983123702353, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, language=EN, label=Fig.1, caption=Overall sample mental health-sleep quality network structure, figureFileSmall=lVJlSkW+vk4yk/I0IskdUQ==, figureFileBig=cj2bcHWQXkwhwMsO1QQHLA==, tableContent=null), ArticleFig(id=1311349983199199826, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, language=CN, label=图1, caption=总体样本心理健康-睡眠质量网络结构, figureFileSmall=lVJlSkW+vk4yk/I0IskdUQ==, figureFileBig=cj2bcHWQXkwhwMsO1QQHLA==, tableContent=null), ArticleFig(id=1311349983379554899, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, language=EN, label=Fig.2, caption=Analysis of centrality index and bridging expectation impact characteristics, figureFileSmall=BluKCS4rSCv9m0x3KOXwwQ==, figureFileBig=LNWOREdLX+a4c42gVXxBIw==, tableContent=null), ArticleFig(id=1311349983450858068, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, language=CN, label=图2, caption=中心性指数与桥接期望影响特征分析

注：A为中心性指数图；B为桥接期望影响图。

, figureFileSmall=BluKCS4rSCv9m0x3KOXwwQ==, figureFileBig=LNWOREdLX+a4c42gVXxBIw==, tableContent=null), ArticleFig(id=1311349983517966933, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, language=EN, label=Fig.3, caption=Network structure of mental health-sleep quality among college students of different genders, figureFileSmall=mlnUKgjLqb3FEW3l+Go2hg==, figureFileBig=0Buj4uMEIimQpmwMw2DYZw==, tableContent=null), ArticleFig(id=1311349983580881494, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, language=CN, label=图3, caption=不同性别大学生的心理健康-睡眠质量网络结构, figureFileSmall=mlnUKgjLqb3FEW3l+Go2hg==, figureFileBig=0Buj4uMEIimQpmwMw2DYZw==, tableContent=null), ArticleFig(id=1311349983643796055, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, language=EN, label=Table 1, caption=

Statistics of scores for each scale dimension

, figureFileSmall=null, figureFileBig=null, tableContent=
量表编码项目男女Z值P值有军籍学员无军籍地方生Z值P
匹兹堡睡眠质量指数（ PSQI）a1睡眠质量1（1,1）1（1,1）-0.22 0.8231（0.75,1）1（1,1）-0.83 0.405
a2入睡时间1（0,2）1（0,2）-0.40 0.6901（0,2）1（0,1）-1.29 0.198
a3睡眠时间1（0,1）1（1,1）-1.09 0.2781（0,1）1（1,1）-2.03 0.043a
a4睡眠效率0（0,0）0（0,1）-2.36 0.018a0（0,0）0（0,0）-0.83 0.409
a5睡眠障碍1（0,1）1（1,1）-1.69 0.0921（0.75,1）1（0,1）-0.54 0.592
a6催眠药物0（0,0）0（0,0）-0.03 0.9800（0,0）0（0,0）-0.69 0.489
a7日间功能障碍1（0,2）2（1,2）-1.00 0.320 1（0.75,2）1（0,2）-0.27 0.785
一般健康问卷（GHQ-20）b1自我否定3（1,6）4（2,6）-2.21 0.027a3（1.75,6）4（2,6）-2.05 0.040a
b2忧郁1（1,2）1（1,2）-0.22 0.8251（1,2）1（1,2）-0.29 0.775
b3焦虑0（0,2）0（0,2）-0.96 0.3370（0,2）0（0,2）-0.44 0.664
), ArticleFig(id=1311349983719293528, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, language=CN, label=表1, caption=

各量表维度得分情况统计

, figureFileSmall=null, figureFileBig=null, tableContent=
量表编码项目男女Z值P值有军籍学员无军籍地方生Z值P
匹兹堡睡眠质量指数（ PSQI）a1睡眠质量1（1,1）1（1,1）-0.22 0.8231（0.75,1）1（1,1）-0.83 0.405
a2入睡时间1（0,2）1（0,2）-0.40 0.6901（0,2）1（0,1）-1.29 0.198
a3睡眠时间1（0,1）1（1,1）-1.09 0.2781（0,1）1（1,1）-2.03 0.043a
a4睡眠效率0（0,0）0（0,1）-2.36 0.018a0（0,0）0（0,0）-0.83 0.409
a5睡眠障碍1（0,1）1（1,1）-1.69 0.0921（0.75,1）1（0,1）-0.54 0.592
a6催眠药物0（0,0）0（0,0）-0.03 0.9800（0,0）0（0,0）-0.69 0.489
a7日间功能障碍1（0,2）2（1,2）-1.00 0.320 1（0.75,2）1（0,2）-0.27 0.785
一般健康问卷（GHQ-20）b1自我否定3（1,6）4（2,6）-2.21 0.027a3（1.75,6）4（2,6）-2.05 0.040a
b2忧郁1（1,2）1（1,2）-0.22 0.8251（1,2）1（1,2）-0.29 0.775
b3焦虑0（0,2）0（0,2）-0.96 0.3370（0,2）0（0,2）-0.44 0.664
), ArticleFig(id=1311349983790596697, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, language=EN, label=Table 2, caption=

Gender-specific node centrality indicators （Z-scores）

, figureFileSmall=null, figureFileBig=null, tableContent=
编码项目男（Z分数）女（Z分数）
强度中心性期望影响桥接期望影响强度中心性期望影响桥接期望影响
a1睡眠质量0.669 1.344 -0.786 1.637 1.637 -0.161
a2入睡时间-0.591 -0.761 -1.407 0.891 0.891 -0.417
a3睡眠时间-0.857 -0.417 -0.882 -0.738 -0.738 -0.998
a4睡眠效率-0.247 -0.893 -0.649 -1.248 -1.248 -1.395
a5睡眠障碍0.431 1.070 -0.518 -0.257 -0.257 -0.350
a6催眠药物-0.637 -1.193 -0.081 -0.703 -0.703 -0.231
a7日间功能障碍1.954 0.618 1.459 0.693 0.693 0.763
b1自我否定-1.585 -1.257 1.084 -1.250 -1.250 -0.186
b2忧郁0.668 0.693 1.029 0.071 0.071 0.924
b3焦虑0.195 0.797 0.752 0.903 0.903 2.052
), ArticleFig(id=1311349983878677082, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1311349978170229284, language=CN, label=表2, caption=

分性别节点中心性指标（Z分数）

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编码项目男（Z分数）女（Z分数）
强度中心性期望影响桥接期望影响强度中心性期望影响桥接期望影响
a1睡眠质量0.669 1.344 -0.786 1.637 1.637 -0.161
a2入睡时间-0.591 -0.761 -1.407 0.891 0.891 -0.417
a3睡眠时间-0.857 -0.417 -0.882 -0.738 -0.738 -0.998
a4睡眠效率-0.247 -0.893 -0.649 -1.248 -1.248 -1.395
a5睡眠障碍0.431 1.070 -0.518 -0.257 -0.257 -0.350
a6催眠药物-0.637 -1.193 -0.081 -0.703 -0.703 -0.231
a7日间功能障碍1.954 0.618 1.459 0.693 0.693 0.763
b1自我否定-1.585 -1.257 1.084 -1.250 -1.250 -0.186
b2忧郁0.668 0.693 1.029 0.071 0.071 0.924
b3焦虑0.195 0.797 0.752 0.903 0.903 2.052
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重庆市某军医大学大学生心理健康与睡眠质量的网络分析实证研究
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陈佳 1 , 徐晓晓 2 , 易大莉 1 , 李芳 1 , 伍亚舟 1
现代预防医学 | 健康与社会行为 2026,53(12): 2232-2237
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现代预防医学 |健康与社会行为 2026 , 53 (12) : 2232 -2237
重庆市某军医大学大学生心理健康与睡眠质量的网络分析实证研究
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陈佳1, 徐晓晓2, 易大莉1, 李芳1, 伍亚舟1
作者信息
  • 1.陆军军医大学军事预防医学系军队卫生统计学教研室，重庆 400038
  • 2.陆军军医大学医学心理系基础心理学教研室
通讯作者:
伍亚舟，E-mail:
作者简介:

陈佳（1992—），女，硕士，讲师，研究方向：基于机器学习及深度学习的医学数据预测模型

Empirical study on the network analysis of college students’ mental health and sleep quality ina military medical university, Chongqing
Jia CHEN1, Xiao-xiao XU2, Da-li YI1, Fang LI1, Ya-zhou WU1
Affiliations
  • Department of Military Preventive Medicine, Military Health Statistics Teaching and Research Office, Army Medical University, Chongqing 400038, China
出版时间: 2026-06-25 doi: 10.20043/j.cnki.MPM.202602095
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摘要
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目的

本研究旨在运用网络分析方法，探究大学生心理健康与睡眠质量的关联模式及组别差异，为精准干预提供实证依据。

方法

以428名大学生为研究对象，采用一般健康问卷（GHQ-20）和匹兹堡睡眠质量指数（PSQI）进行调查，通过R软件的qgraph包构建心理健康-睡眠质量网络，计算各节点中心性指标，并采用网络比较检验（NCT）分析性别与军籍对该网络的影响。

结果

总体网络中，日间功能障碍（a7）、焦虑（b3）、主观睡眠质量（a1）为核心节点，焦虑（b3）、日间功能障碍（a7）、忧郁（b2）为模块间核心桥梁；性别差异体现在男性全局连接强度更高（s=0.960，p=0.048），其中睡眠障碍与日间功能障碍（P=0.005）、日间功能障碍与自我否定（P=0.045）的边关联差异具有统计学意义；军籍身份仅对主观睡眠质量与睡眠效率的关联存在调节作用（P=0.018），在整体网络上无显著差异。

结论

网络分析揭示了大学生睡眠-心理健康的关联特征，为精准服务提供科学路径。

心理健康  /  睡眠质量  /  网络分析
Objective

To explore the correlation patterns and group differences between college students’ mental health and sleep quality using network analysis methods, providing empirical evidence for targeted interventions.

Methods

A total of 428 college students were selected as the research subjects, and surveys were conducted using the General Health Questionnaire (GHQ-20) and the Pittsburgh Sleep Quality Index (PSQI). The mental health-sleep quality network was constructed using the qgraph package in R software, and centrality indicators of each node were calculated. The Network Comparison Test (NCT) was used to analyze the influence of gender and military status on this network.

Results

In the overall network, daytime dysfunction (a7), anxiety (b3), and subjective sleep quality (a1) were core nodes, while anxiety (b3), daytime dysfunction (a7), and depression (b2) served as core bridges between modules. Gender differences were reflected in higher global connectivity strength in males (s=0.960,P=0.048), with statistically significant edge association differences between sleep disorders and daytime dysfunction (P=0.005), and between daytime dysfunction and self-denial (P=0.045). Military status only had a moderating effect on the association between subjective sleep quality and sleep efficiency (P=0.018), with no significant difference in the overall network.

Conclusion

Network analysis reveals the correlation characteristics between college students’ sleep and mental health, providing a scientific path for targeted services.

Mental health  /  Sleep quality  /  Network analysis
陈佳, 徐晓晓, 易大莉, 李芳, 伍亚舟. 重庆市某军医大学大学生心理健康与睡眠质量的网络分析实证研究. 现代预防医学, 2026 , 53 (12) : 2232 -2237 . DOI: 10.20043/j.cnki.MPM.202602095
Jia CHEN, Xiao-xiao XU, Da-li YI, Fang LI, Ya-zhou WU. Empirical study on the network analysis of college students’ mental health and sleep quality ina military medical university, Chongqing[J]. Modern Preventive Medicine, 2026 , 53 (12) : 2232 -2237 . DOI: 10.20043/j.cnki.MPM.202602095
正文
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近年来，大学生群体的心理健康与睡眠质量问题愈发受到社会关注，已成为影响其学业发展与身心健康的重要因素。相关研究表明，大学生睡眠障碍发生率呈上升趋势，且常与焦虑、抑郁等心理健康问题相伴出现，二者相互影响、形成恶性循环，严重降低学生的生活质量与适应能力［1-2］。目前，国内外已有多项研究采用网络分析探讨二者复杂关系，其中外文研究［3-5］覆盖多群体且包含大学生相关研究，国内研究［6-8］也证实二者存在显著关联，但现有研究多侧重整体关联分析，对各具体维度的精细交互模式揭示不足，且较少结合性别、军籍等群体特征开展异质性网络比较，针对性与应用价值有待提升；而网络分析可直观呈现多变量关联结构、识别核心节点、量化交互强度，为解析二者复杂关系提供新视角［9-10］，基于此，本研究在梳理相关研究基础上，构建大学生睡眠与心理健康多维度关联网络，重点探讨性别、军籍对网络结构的差异影响，弥补既往研究不足，为二者精准干预提供针对性科学依据。
1　对象与方法
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1.1　研究对象
本研究于2025年7—9月，以重庆市某军医大学全体专业在校本科生为研究对象，采用便利抽样法，通过问卷星平台发放匿名自愿线上问卷，由学员队干部转发问卷链接及二维码至班级微信群，每人仅可作答一次。共回收电子问卷440份，剔除规律性作答、填写时间过短及关键变量缺失的问卷后，获得有效问卷428份，有效回收率为97.27%。本研究已获得陆军军医大学医学伦理委员会审批（2025第7-02）。
1.2　调查工具
本研究采用问卷星制作和发放调查问卷，问卷内容包括三部分：（1）一般资料调查：包括性别、年级、学生类别、（2）心理健康调查：采用《一般健康问卷（general health questionnaire, GHQ-20）》进行，该量表共20个条目，包括自我肯定、忧郁和焦虑3个维度。每个条目记1（是）、0（否）分，将自我肯定反向计分为自我否定，3维度之和即为总分，总分越高心理健康水平越低。本次调查的Cronbach α系数为0.834，信效度良好。（3）睡眠质量调查：采用匹兹堡睡眠质量指数（Pittsburgh sleep quality index, PSQI）量表调查大学生近1个月的睡眠质量，该量表包含18个条目7个维度（分别为主观睡眠质量、入睡时间、睡眠时间、睡眠效率、睡眠障碍、催眠药物和日间功能障碍）。各维度按0～3分计分，7维度得分之和即为PSQI总分，范围为0～21分，将PSQI评分>7分判定为睡眠障碍，得分越高睡眠质量越差。本次调查的Cronbach α系数为0.859。
1.3　统计学方法
1.3.1　基础统计分析
采用SPSS 27.0软件，因本研究数据均不服从正态分布，计量资料以［M（P25，P75）］描述；组间差异比较采用Wilcoxon秩和检验，变量间相关性分析采用Spearman秩相关分析。
1.3.2　网络分析
通过R 4.5.1软件qgraph包构建并可视化网络模型，bootnet包进行统计分析；全样本建立总体网络（节点大小与强度中心性成正比，边宽/颜色反映关联强度/方向），并按性别、学生类别分层建模。所有网络均使用EBICglasso算法估计正则化偏相关结构，计算介数中心性（Betweenness）、接近中心性（Closeness）、强度中心性（Strength）、期望影响（Expected Influence, EI）及桥接期望影响（Bridge Expected Influence, BEI）等中心性指标，Z标准化后可视化，以强度中心性（稳定性好）作为核心节点判定依据。采用1 000次自助法评估网络稳定性，相关性稳定性系数（CS）≥0.25为可接受标准（CS>0.5为优秀）［11］；通过networktools包行组间网络比较检验，P<0.05为差异有统计学意义。
2　结果
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2.1　一般资料与量表得分总体情况
本研究共纳入428名学生作为研究对象，其中男生223人（52.2%），女生205人（47.8%）；有军籍学员230人（53.7%），无军籍地方生198人（46.3%）。研究对象年龄范围为18-24岁，平均年龄（20.32±1.56）岁。各量表维度得分及组间比较如表1所示，PSQI量表中，仅睡眠效率维度得分在男女组间存在统计学差异（Z=-2.36，P=0.018），睡眠时间维度得分在有军籍与无军籍学员组间存在统计学差异（Z=-2.03，P=0.043）；GHQ-20量表中，自我否定维度得分在男女组间及不同学籍组间均存在统计学差异（均P<0.05）。Spearman相关性分析提示，心理健康得分与睡眠质量得分呈正相关（r=0.479，P<0.001）。
2.2　总体样本睡眠-心理健康网络特征
图1展示了总体样本（n=428）的心理健康-睡眠质量网络。从网络结构来看，心理健康模块（自我否定 b1、忧郁 b2、焦虑b3）与睡眠质量模块（主观睡眠质量 a1、入睡时间 a2、睡眠时间 a3、睡眠效率 a4、睡眠障碍 a5、催眠药物 a6、日间功能障碍 a7）内部及模块间均存在复杂的关联。其中，a1-a2、b3-b2、a7-a1之间的关联边较粗，表明这些维度间的关联强度较大。a4-a7线条为红色，说明两个指标呈负相关，其余指标连线均为正相关。
图2A（中心性指数）显示，a1、a7、b3在4项中心性指标上均处于高位，且无明显异常波动，提示核心节点稳定性良好。图2B（桥接期望影响）直观呈现 b3、a7、b2的桥梁作用显著高于其他节点，与表1结果一致。通过bootstrapping检验（1 000次重复抽样），核心节点的中心性指标 95%置信区间无重叠，验证了结果可靠性。对整体网络进行稳定性分析，Strength的CS系数为0.593，说明强度稳定性优秀。
2.3　性别组网络差异分析
2.3.1　网络比较检验（NCT）
性别组网络分析显示，尽管男女在睡眠质量与心理困扰的整体关联模式上无显著差异（M=0.240，P=0.261），但男性表现出更强的全局连接强度（s=0.960，P=0.048），提示其睡眠问题与心理症状的交互更为紧密。具体而言：（1）男性中睡眠障碍（a5）与日间功能障碍（a7）的关联差异具有统计学意义（P=0.005），可能反映睡眠问题对其日常功能的更大影响；（2）日间功能障碍（a7）与自我否定（b1）的关系存在性别差异（P=0.045），需进一步探讨社会文化因素的作用；（3）女性入睡时间（a2）与忧郁（b2）的关联更强（P=0.027），或为针对性干预提供依据；（4）忧郁（b2）-焦虑（b3）连接的性别差异（P=0.024）与既往关于女性情绪共病性更高的研究一致。这些发现强调了睡眠-心理健康关联的性别特异性，对制定性别差异化干预策略具有启示意义。
2.3.2　不同性别组节点中心性指标和稳定性分析
表2列出不同性别节点中心性指标，强度中心性指标显示，男性核心节点为a7（1.954）、a1（0.669）、b2（0.668），女性核心节点为a1（1.637）、b3（0.903）、a2（0.891）。组别间关键差异表现为：（1）男性a7的Strength显著高于女性（1.954 vs 0.693），表明男性日间功能障碍与其他维度关联更紧密；（2）女性b3的BEI（2.052）远高于男性（0.752），提示女性焦虑的模块桥梁作用更强；（3）男性b1的BEI（1.084）为正值，女性为负（-0.186），表明男性自我否定可促进睡眠-心理交互，女性则相反。Strength的强度稳定性CS女=0.361，CS男=0.516，整体稳定性在可接受范围内，男性整体网络各指标间的关联强度更稳定。
2.3.3　性别网络可视化
图3展示了不同性别（男/女）大学生的心理健康-睡眠质量网络。从图中可以看出，男性网络中各节点间的边整体更粗，表明男性节点间的关联强度更大，与NCT检验中男性全局连接强度更强的结果一致。
2.4　军籍组网络差异分析
2.4.1　网络比较检验（NCT）
军籍组网络比较分析显示，有军籍与无军籍学员在睡眠问题与心理症状的整体网络结构（M=0.133，P=0.970）及全局连接强度（s=0.100，P=0.840）上均无显著差异。然而，局部边差异检验发现 1条差异具有统计学意义的边：a1（主观睡眠质量）-a4（睡眠效率）（边权重：有军籍0.41，无军籍0.23，P=0.018），提示军籍身份对该关联的影响。
2.4.2　军籍组中心性差异
计算不同军籍的中心性指标，Strength指标显示，有军籍学员核心节点为a1（2.052）、a7（0.638）、b2（0.205），无军籍学员核心节点为a1（1.421）、a7（1.032）、b3（0.861）。两组间关键差异表现为：（1）有军籍学员 a1的Strength（2.052）显著高于无军籍（1.421），表明其主观睡眠质量与其他维度关联更紧密；（2）有军籍学员 b1的BEI（1.901）远高于无军籍（-0.209），提示有军籍学员自我否定的模块桥梁作用更强；（3）无军籍学员 b3的BEI（1.704）高于有军籍（0.238），表明无军籍学员焦虑的模块交互作用更突出。
3　讨论
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3.1　总体网络核心节点的意义与机制
本研究发现，日间功能障碍（a7）、焦虑（b3）、主观睡眠质量（a1）是大学生睡眠-心理健康网络的核心节点。主观睡眠质量（a1）的EI最高（1.647），表明主观感知是触发心理应激的关键，即使客观睡眠指标正常，主观感知差也会激活心理应激反应，进而加剧焦虑、忧郁［12］。本研究中a1与b2（忧郁）的强关联（0.35）也支持这一机制，提示改善主观睡眠感知可能切断“睡眠-心理”负向循环。日间功能障碍（a7）的Strength（1.480）与Betweenness（1.643）最高，这符合“日间功能是睡眠与心理的共同外在表现”假说，睡眠不足与心理问题会形成“睡眠差→日间功能差→心理差”的恶性循环［13］。焦虑（b3）作为心理模块核心，且BEI最高（1.269），是连接睡眠与心理模块的关键桥梁，二者双向交互，使其成为干预核心靶点［14］。
3.2　性别差异的深层原因与干预启示
男性全局连接强度更高（s=0.960，P=0.048），表明男性睡眠-心理关联更紧密，符合“男性情绪表达抑制”理论［15］：男性更倾向于压抑心理困扰，导致心理症状通过睡眠问题间接表现，使两者关联更强。具体差异的机制与干预方向如下：（1）男性睡眠障碍（a5）-日间功能障碍（a7）关联更强（P=0.005）：可能因为男性在社会文化中承担“能力者”角色，睡眠障碍导致的日间功能下降（如工作效率低）更易引发自我批判，进而强化两者关联。干预需聚焦“睡眠障碍→日间功能”的认知重构，如通过正念训练降低对日间表现的过度苛求。（2）女性入睡时间（a2）-忧郁（b2）、忧郁（b2）-焦虑（b3）关联更强（P<0.05）：符合女性“情绪敏感性”特征［16］：女性更易反刍负面情绪，导致入睡时思维活跃（延长入睡时间），且忧郁与焦虑更易共病。干预需强化情绪调节训练，如认知行为疗法（CBT）中的“思维停止”技术，减少睡前反刍；同时针对情绪共病设计整合干预方案。（3）男性自我否定（b1）的桥梁作用为正，女性为负：男性自我否定更易转向反思睡眠问题，而女性自我否定更易指向自我价值，形成独立负性循环。干预中，男性侧重问题解决导向，女性侧重自我认知提升。
3.3　军籍差异的特殊性与管理建议
有军籍与无军籍学员整体网络无显著差异，但存在局部特异性。有军籍学员主观睡眠质量与睡眠效率的关联具有统计学意义（P=0.018），可能与其军事化管理下作息更规律有关。规律作息使主观睡眠感受与客观睡眠效率更为一致［17-18］；而无军籍学员作息相对灵活，易出现熬夜、起床不规律等情况，导致二者关联较弱。建议在管理中保持有军籍学员的作息优势，同时引导无军籍学员建立规律作息习惯。
3.4　网络分析的方法学优势与实践价值
相较于传统线性分析，本研究的网络分析具有三大优势：一是精准识别核心靶点，通过中心性指标定位a1、a7、b3等核心节点，为干预提供明确方向，弥补传统回归仅能确定线性关系的不足；二是揭示模块交互，借助BEI指标量化节点模块桥梁作用，如b3作为睡眠-心理模块核心桥梁，干预后可同时改善两大模块问题；三是捕捉组别特异性，通过NCT检验识别性别、军籍的局部差异边，为差异化干预提供依据。
实践层面，基于网络特征构建“三级干预体系”：一级普适干预面向全体学生，通过睡眠卫生教育、日间压力管理、焦虑情绪疏导强化核心节点正向关联；二级性别干预针对性开展，男性侧重“睡眠障碍-日间功能”认知重构，女性侧重情绪调节与共病干预；三级军籍干预区分群体，有军籍学员侧重规律作息与情绪监测，无军籍学员强化时间管理与自我认知改善。
本研究基于428名大学生数据，揭示睡眠-心理健康网络核心特征及组别差异：总体网络中，a1（主观睡眠质量）、a7（日间功能障碍）、b3（焦虑）为核心节点，b3、a7、b2（忧郁）为模块间核心桥梁；性别差异体现在男性全局连接强度更高，睡眠障碍-日间功能障碍、日间功能障碍-自我否定关联更强，女性入睡时间-忧郁、忧郁-焦虑关联更强；军籍差异仅体现为主观睡眠质量-睡眠效率关联更强，整体网络无显著差异。
需说明的是，a4（睡眠效率）与a7（日间功能障碍）的负相关与常规直觉不符，结合样本53.7%为军校生的特点，这可能是人群特异性所致［19］，且网络分析边权重为偏相关，控制焦虑、忧郁等变量后正向关联可能反转，未来需结合客观睡眠测量验证。
本研究存在四点局限：一是指标测量依赖自评问卷，可能受回忆偏倚与社会期望影响，缺乏客观测量手段的验证；二是样本仅来源于重庆市某军医大学本科生，代表性有限，结论向其他地区、院校及研究生群体的推广需谨慎；三是未纳入学业压力、体育锻炼、家庭经济状况等潜在混杂因素，且无法推断因果关系；四是网络结构受样本量与变量选择影响，后续需通过纵向设计、多中心大样本研究进一步验证其稳定性与泛化能力。未来研究可结合多模态数据与因果推断方法，持续完善大学生健康服务的精细化干预体系。
基金
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  • 陆军军医大学人文社科基金项目(2020XRW15)
  • 国家自然科学基金青年项目(82304249)
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2026年第53卷第12期
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doi: 10.20043/j.cnki.MPM.202602095
  • 接收时间：2026-02-08
  • 首发时间：2026-09-28
  • 出版时间：2026-06-25
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  • 收稿日期：2026-02-08
基金
陆军军医大学人文社科基金项目(2020XRW15)
国家自然科学基金青年项目(82304249)
作者信息
    1.陆军军医大学军事预防医学系军队卫生统计学教研室，重庆 400038
    2.陆军军医大学医学心理系基础心理学教研室

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红菇属 Russula 17 8.13
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