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Article(id=1325535937631118297, tenantId=1146029695717560320, journalId=1256213402557890569, issueId=1325535161890398372, articleNumber=null, orderNo=null, doi=10.16835/j.cnki.1000-9817.2025350, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1753200000000, receivedDateStr=2025-07-23, revisedDate=1758556800000, revisedDateStr=2025-09-23, acceptedDate=null, acceptedDateStr=null, onlineDate=1793961994797, onlineDateStr=2026-11-06, pubDate=1766592000000, pubDateStr=2025-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793961994797, onlineIssueDateStr=2026-11-06, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793961994797, creator=13701087609, updateTime=1793961994797, updator=13701087609, issue=Issue{id=1325535161890398372, tenantId=1146029695717560320, journalId=1256213402557890569, year='2025', volume='46', issue='12', pageStart='1673', pageEnd='1824', issueExtLink='null', onlineDate='null', pubDate='1766592000000', pubDateStr='2025-12-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793961809846, creator='13701087609', updateTime=1793961809846, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=1727, endPage=1730, ext={EN=ArticleExt(id=1325535942479733722, articleId=1325535937631118297, tenantId=1146029695717560320, journalId=1256213402557890569, language=EN, title=Network analysis of emotional intelligence and sleep problems among junior and senior high school students, columnId=1259565855189418448, journalTitle=Chinese Journal of School Health, columnName=Mental Health, runingTitle=null, highlight=null, articleAbstract=
Objective

To investigate the association between emotional intelligence and sleep problems at the symptom level among junior and senior high school students, so as to provide new insights for interventions targeting junior and senior high school students sleep disorders.

Methods

From November 2023 to May 2024, a stratified cluster random sampling method was employed to select 3 531 first-year junior high school and first-year senior high school students from 6 schools in Guangyuan City and Liangshan Yi Autonomous Prefecture in Sichuan Province, as well as Lhasa City in Tibet Autonomous Region. The Insomnia Severity Index Scale and the Wong and Law Emotional Intelligence Scale(WLEIS) were used to assess sleep problems and emotional intelligence. A network analysis was performed to explore the relationship between emotional intelligence and sleep disorders, and a gender-based network comparison analysis was conducted.

Results

The reported rate of sleep problems among junior and senior high school students was 47.3%, with severe sleep problems of 2.2%. Difficulty maintaining sleep, worry about sleep, and emotional application were the core symptoms in the network (node strength values: 1.11, 0.98, and 0.82, respectively). Dissatisfaction with sleep and emotional application served as bridge symptoms connecting emotional intelligence and sleep problems (bridge strength values: 1.77 and 1.59, respectively). The edge weights of the emotional intelligence and sleep problems network differed significantly between genders (maximum difference in edge weight values was 0.13, P < 0.05).

Conclusions

Emotional application ability and dissatisfaction with sleep are the key nodes in the network connecting emotional intelligence and sleep problems. Targeted efforts to enhance emotional application ability may effectively reduce the risk of sleep problems among junior and senior high school students.

, authors=Ruizhe SHANG1, Shuyu YANG1, Lan YU1, Zihao YUAN1, Zhiwei CHEN2, MUKEDAISI·Tuerxun1, Qiaolan LIU*, 1, authorsList=Ruizhe SHANG, Shuyu YANG, Lan YU, Zihao YUAN, Zhiwei CHEN, MUKEDAISI·Tuerxun, Qiaolan LIU, authorCompany=null, correspAuthors=Qiaolan LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2025 Chinese Journal of School Health. All rights reserved., 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=1325535950117561309, articleId=1325535937631118297, tenantId=1146029695717560320, journalId=1256213402557890569, language=CN, title=中学生情绪智力与睡眠问题的网络分析, columnId=1259565858817491410, journalTitle=中国学校卫生, columnName=心理卫生, runingTitle=null, highlight=null, articleAbstract=
目的

了解中学生情绪智力与睡眠问题在症状层面上的关联，为中学生睡眠问题的干预提供新的视角。

方法

2023年11月—2024年5月，采用分层整群随机抽样方法在四川省广元市、凉山彝族自治州和西藏拉萨市抽取6所中学3 531名初一和高一学生进行自填式问卷调查。使用失眠严重程度指数量表、情绪智力量表(WLEIS)评估中学生的睡眠问题和情绪智力水平，构建网络模型分析中学生情绪智力与睡眠问题的关系，并进行不同性别的网络比较分析。

结果

中学生睡眠问题报告率为47.3%，其中严重睡眠问题报告率为2.2%。睡眠维持困难、对睡眠的担忧和情绪运用为该网络核心症状(节点强度分别为1.11，0.98，0.82)，对睡眠的不满和情绪运用为连接中学生情绪智力和睡眠问题的桥接症状(桥接强度分别为1.77，1.59)。不同性别中学生情绪智力和睡眠问题网络的边线系数差异有统计学意义(最大边线加权值差异为0.13，P＜0.05)。

结论

情绪运用能力与对睡眠的不满是中学生情绪智力和睡眠问题网络的关键节点，有针对性提升情绪运用能力有利于降低中学生睡眠问题发生的风险。

, authors=尚睿哲1, 杨舒羽1, 喻斓1, 袁梓皓1, 陈志伟2, 木克代斯·吐尔逊1, 刘巧兰*, 1, authorsList=尚睿哲, 杨舒羽, 喻斓, 袁梓皓, 陈志伟, 木克代斯·吐尔逊, 刘巧兰, authorCompany=null, correspAuthors=刘巧兰, authorNote=

尚睿哲(2001-)，女，安徽怀远人，在读硕士，主要研究方向为健康与社会行为学

, correspAuthorsNote=
刘巧兰，E-mail:
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注：实线表示正相关，虚线表示负相关；边线越粗代表相关性越强。

, figureFileSmall=Mc7zudollTF9jgL/WKgL4w==, figureFileBig=AqHErt624TC8Z9/6X63bmQ==, tableContent=null), ArticleFig(id=1325535989032312853, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325535937631118297, language=EN, label=Tab.1, caption=

Comparison of scores for emotional intelligence and sleep problems among junior and senior high school students with different demographic characteristics

, figureFileSmall=null, figureFileBig=null, tableContent=
人口学指标选项情绪智力睡眠问题
x±st/F值M(P25，P75)Z/H值
年级初一72.33±17.6411.88**7.00(3.00, 11.00)1.82
高一73.16±16.167.00(4.00, 12.00)
性别男74.90±18.397.62**7.00(3.00, 11.44)2.48*
女70.54±15.557.00(3.00, 11.00)
民族汉族74.70±16.6039.93**6.00(3.00, 10.00)41.59**
彝族67.30±16.339.00(6.00, 13.00)
藏族68.32±17.709.00(4.00, 13.00)
其他74.11±20.028.00(2.75, 10.50)
自评家庭经济状况好68.22±24.134.30**7.00(2.50, 11.00)46.95**
较好73.92±17.858.00(4.00, 12.00)
中等72.98±17.057.00(3.00, 11.00)
较差71.39±16.309.00(4.00, 13.00)
差65.39±18.239.53(5.00, 13.50)
自评学习成绩差66.87±17.4127.27**9.53(4.00, 14.00)66.24**
较差70.50±17.238.00(3.00, 12.00)
中等73.49±16.327.00(3.00, 11.00)
较好75.31±16.536.00(2.00, 10.00)
好78.31±18.636.00(2.00, 11.00)
), ArticleFig(id=1325535989493686294, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325535937631118297, language=CN, label=表1, caption=

不同人口学特征中学生情绪智力和睡眠问题得分比较

, figureFileSmall=null, figureFileBig=null, tableContent=
人口学指标选项情绪智力睡眠问题
x±st/F值M(P25，P75)Z/H值
年级初一72.33±17.6411.88**7.00(3.00, 11.00)1.82
高一73.16±16.167.00(4.00, 12.00)
性别男74.90±18.397.62**7.00(3.00, 11.44)2.48*
女70.54±15.557.00(3.00, 11.00)
民族汉族74.70±16.6039.93**6.00(3.00, 10.00)41.59**
彝族67.30±16.339.00(6.00, 13.00)
藏族68.32±17.709.00(4.00, 13.00)
其他74.11±20.028.00(2.75, 10.50)
自评家庭经济状况好68.22±24.134.30**7.00(2.50, 11.00)46.95**
较好73.92±17.858.00(4.00, 12.00)
中等72.98±17.057.00(3.00, 11.00)
较差71.39±16.309.00(4.00, 13.00)
差65.39±18.239.53(5.00, 13.50)
自评学习成绩差66.87±17.4127.27**9.53(4.00, 14.00)66.24**
较差70.50±17.238.00(3.00, 12.00)
中等73.49±16.327.00(3.00, 11.00)
较好75.31±16.536.00(2.00, 10.00)
好78.31±18.636.00(2.00, 11.00)
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中学生情绪智力与睡眠问题的网络分析
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尚睿哲 1 , 杨舒羽 1 , 喻斓 1 , 袁梓皓 1 , 陈志伟 2 , 木克代斯·吐尔逊 1 , 刘巧兰 *, 1
中国学校卫生 | 心理卫生 2025,46(12): 1727-1730
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中国学校卫生 |心理卫生 2025 , 46 (12) : 1727 -1730
中学生情绪智力与睡眠问题的网络分析
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尚睿哲1, 杨舒羽1, 喻斓1, 袁梓皓1, 陈志伟2, 木克代斯·吐尔逊1, 刘巧兰*, 1
作者信息
  • 1四川大学华西公共卫生学院/华西第四医院健康行为与社会医学系, 成都 610041
  • 2成都市郫都区疾病预防控制中心应急与业务管理办公室
通讯作者:
刘巧兰，E-mail:
作者简介:

尚睿哲(2001-)，女，安徽怀远人，在读硕士，主要研究方向为健康与社会行为学

Network analysis of emotional intelligence and sleep problems among junior and senior high school students
Ruizhe SHANG1, Shuyu YANG1, Lan YU1, Zihao YUAN1, Zhiwei CHEN2, MUKEDAISI·Tuerxun1, Qiaolan LIU*, 1
Affiliations
  • 1Department of Health Behavior and Social Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, Sichuan Province, China
出版时间: 2025-12-25 doi: 10.16835/j.cnki.1000-9817.2025350
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摘要
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目的

了解中学生情绪智力与睡眠问题在症状层面上的关联，为中学生睡眠问题的干预提供新的视角。

方法

2023年11月—2024年5月，采用分层整群随机抽样方法在四川省广元市、凉山彝族自治州和西藏拉萨市抽取6所中学3 531名初一和高一学生进行自填式问卷调查。使用失眠严重程度指数量表、情绪智力量表(WLEIS)评估中学生的睡眠问题和情绪智力水平，构建网络模型分析中学生情绪智力与睡眠问题的关系，并进行不同性别的网络比较分析。

结果

中学生睡眠问题报告率为47.3%，其中严重睡眠问题报告率为2.2%。睡眠维持困难、对睡眠的担忧和情绪运用为该网络核心症状(节点强度分别为1.11，0.98，0.82)，对睡眠的不满和情绪运用为连接中学生情绪智力和睡眠问题的桥接症状(桥接强度分别为1.77，1.59)。不同性别中学生情绪智力和睡眠问题网络的边线系数差异有统计学意义(最大边线加权值差异为0.13，P＜0.05)。

结论

情绪运用能力与对睡眠的不满是中学生情绪智力和睡眠问题网络的关键节点，有针对性提升情绪运用能力有利于降低中学生睡眠问题发生的风险。

情绪  /  睡眠  /  精神卫生  /  网络分析  /  学生
Objective

To investigate the association between emotional intelligence and sleep problems at the symptom level among junior and senior high school students, so as to provide new insights for interventions targeting junior and senior high school students sleep disorders.

Methods

From November 2023 to May 2024, a stratified cluster random sampling method was employed to select 3 531 first-year junior high school and first-year senior high school students from 6 schools in Guangyuan City and Liangshan Yi Autonomous Prefecture in Sichuan Province, as well as Lhasa City in Tibet Autonomous Region. The Insomnia Severity Index Scale and the Wong and Law Emotional Intelligence Scale(WLEIS) were used to assess sleep problems and emotional intelligence. A network analysis was performed to explore the relationship between emotional intelligence and sleep disorders, and a gender-based network comparison analysis was conducted.

Results

The reported rate of sleep problems among junior and senior high school students was 47.3%, with severe sleep problems of 2.2%. Difficulty maintaining sleep, worry about sleep, and emotional application were the core symptoms in the network (node strength values: 1.11, 0.98, and 0.82, respectively). Dissatisfaction with sleep and emotional application served as bridge symptoms connecting emotional intelligence and sleep problems (bridge strength values: 1.77 and 1.59, respectively). The edge weights of the emotional intelligence and sleep problems network differed significantly between genders (maximum difference in edge weight values was 0.13, P < 0.05).

Conclusions

Emotional application ability and dissatisfaction with sleep are the key nodes in the network connecting emotional intelligence and sleep problems. Targeted efforts to enhance emotional application ability may effectively reduce the risk of sleep problems among junior and senior high school students.

Emotions  /  Sleep  /  Mental health  /  Network analysis  /  Students
尚睿哲, 杨舒羽, 喻斓, 袁梓皓, 陈志伟, 木克代斯·吐尔逊, 刘巧兰. 中学生情绪智力与睡眠问题的网络分析. 中国学校卫生, 2025 , 46 (12) : 1727 -1730 . DOI: 10.16835/j.cnki.1000-9817.2025350
Ruizhe SHANG, Shuyu YANG, Lan YU, Zihao YUAN, Zhiwei CHEN, MUKEDAISI·Tuerxun, Qiaolan LIU. Network analysis of emotional intelligence and sleep problems among junior and senior high school students[J]. Chinese Journal of School Health, 2025 , 46 (12) : 1727 -1730 . DOI: 10.16835/j.cnki.1000-9817.2025350
正文
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睡眠问题在青少年群体中的检出率较高[1]，会显著影响青少年的日常功能和整体健康状况[2]。研究发现，睡眠问题与消极的情绪体验和调节情绪的策略有关[3]。情绪智力作为一个关键因素，在青少年情绪调节、适应性应对策略和社会联系中起着至关重要的作用[4]；具有较高情绪智力水平的个体更可能采用多种应对方式来应对不良情绪，从而拥有更高的睡眠质量和健康结果[2]。此外，睡眠问题与情绪智力的关联可能因为性别不同而存在情绪感知和应对策略的差异[5]。
根据网络精神病理学理论，改善症状网络的核心症状可以对网络中的其他症状产生有效影响，而干预桥接症状可能会触发或减轻其他网络的症状[6]。因此，本研究旨在使用网络分析来探讨症状层面上睡眠问题与情绪智力之间的关联，进一步识别核心症状和桥接症状及其性别差异，为有针对性地干预中学生睡眠问题提供科学依据。
1　对象与方法
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1.1　对象
2023年11月—2024年5月，采用分层整群随机抽样方法选取研究对象，首先依据民族分布特点，选择四川省广元市、凉山彝族自治州和西藏自治区拉萨市；在3个市分别采用直接抽选法抽取2所中学，将每所学校中所有初一和高一年级的学生纳入研究，共抽取6所中学3 771名初一和高一的学生进行现场问卷调查，排除重要变量缺失的样本后，最终纳入3 531名中学生。其中男生1 697名(48.1%)，女生1 834名(51.9%)；汉族、藏族、彝族和其他民族学生分别为2 418名(68.5%)、739名(20.9%)、346名(9.8%)和28名(0.8%)；平均年龄为(14.84±2.31)岁。所有参与者均签署知情同意书并经过监护人知情同意，本研究已获得四川大学华西第四医院/华西公共卫生学院伦理委员会批准(编号: Gwll2023117)。
1.2　方法
1.2.1　一般情况
包括性别、年级、民族、自评家庭经济状况和自评学习成绩。
1.2.2　睡眠问题
使用Morin等[7]编制的失眠严重程度指数量表评估中学生睡眠问题的严重程度。该量表由7个条目组成，分别为入睡困难、睡眠维持困难、早醒、日间功能受损、失眠的显著性、对睡眠的担忧、对睡眠的不满，采用Likert 5级计分进行评分，每个条目评级从“0(没有困扰)”至“4(非常严重的困扰)”，总分0~28分，分数越高睡眠问题越严重。总分0~7，8~14，15~21，22~28分分别表示无、轻度、中度、严重睡眠问题。该量表在中学生中具有良好的信、效度[8]，本研究中量表的Cronbach α系数为0.88。
1.2.3　情绪智力
采用情绪智力量表(Wong and Law Emotional Intelligence Scale, WLEIS)[4]进行评估。该量表包括16个条目，分为自我情绪评估、情绪调节、情绪运用、他人情绪评估4个维度。每个条目按照Likert 7级计分(从1=“非常不同意”至7=“非常同意”)进行评分，总分范围为16~112分，分数越高表示情绪智力水平越高。该量表在中学生中具有良好的信、效度[9]，本研究中该量表的Cronbach α系数为0.72。
1.3　质量控制
为确保调查的准确性和可靠性，研究人员均接受专业培训，熟练掌握调查流程和技巧。学生均在教室自填问卷，以确保调查环境的统一和隐私的保护。问卷由研究人员当场收集、检查和签名，对于无效问卷给予剔除，抽查1%的问卷重复录入，确保数据的准确性和可信度。整个调查过程严格遵守伦理原则和调查程序，确保调查的科学性和公正性。
1.4　统计学分析
描述性统计分析在SPSS 27.0软件中进行，经正态性检验，符合正态分布的计量资料采用(x±s)进行描述，组间比较采用t检验或方差分析；不符合正态分布的计量资料采用M(P25, P75)描述，组间比较采用Mann-Whitney U检验或Kruskal-Wallis H检验。
网络分析使用RStudio 4.3.3软件，使用R包的missForest v1.4.2实施随机森林估计来插补缺失数据，使用R包的Qgraph v1.9.8和Bootnet v1.5.3通过高斯马尔科夫随机场估计方法估计睡眠问题与情绪智力网络。(1)使用R包的Bootnet v1.5.3计算强度作为网络节点的中心性指标，强度是指连接到其他各节点的边线权重绝对值之和，节点强度越高表示该节点越重要[10]。使用R包Networktools v1.5.2计算桥接症状，桥接症状是指在网络模型中连接两种不同症状集群的症状。其中桥接强度是指与其他症状集群相连的各节点边线权重绝对值之和较大的节点，是识别桥接症状的较好指标[8]。本研究将桥接强度值位于P80及以上的节点定义为桥接症状。(2)使用R包的Bootnet v1.5.3估计准确性和稳定性。通过Bootstrap法对网络进行1 000次迭代来计算边线估计的准确性，绘制各条边线的95%非参数自举置信区间(CI)，较窄的区间表示更高的准确性。通过Bootstrap法进行1 000次迭代分析评估中心性指标的稳定性，中心性稳定性系数(centrality stability coefficient, CS-C)大于0.5表示可靠性较好。随后，使用R包的Network-ComparisonTest v2.2.2进行不同性别的网络比较分析，通过置换检验发掘不同网络间的结构差异，通过检验网络不变性、总体强度不变性、总体桥接强度不变性在不同性别间的一致性进行系统检验；双侧检验水准α=0.05。
2　结果
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2.1　中学生情绪智力和睡眠问题状况
47.3%(1 670名)的中学生有睡眠问题，其中轻度睡眠问题检出率为34.8%(1 229名)，中度睡眠问题为10.3%(363名)，严重睡眠问题为2.2%(78名)。中学生睡眠问题和情绪智力得分分别7.00(3.00，11.00)分和(72.64±11.11)分。不同性别、民族、自评家庭经济状况、自评学习成绩的中学生情绪智力和睡眠问题得分差异均有统计学意义；不同年级中学生情绪智力得分差异有统计学意义(P值均＜0.05)。见表1。
2.2　中学生情绪智力与睡眠问题的网络分析
控制性别、年龄、民族、自评家庭经济状况、自评学习成绩后，中学生情绪智力与睡眠问题的网络结构如图1所示，网络密度高(0.82，45/55)。在情绪智力子网络中，A2(情绪调节)-A3(情绪运用)存在最强的关联，边线系数为0.44。在睡眠问题严重程度网络中，B1(入睡困难)- B2(睡眠维持困难)之间存在最强的关联，边线系数为0.50。此外，情绪智力与睡眠问题严重程度之间存在关联，其中关联最强的是A3(情绪运用)- B7(对睡眠的不满)，其次是A3(情绪运用)- B1(入睡困难)，边线系数分别为-0.10和-0.08。男生和女生网络边线系数差异有统计学意义表明网络不变性检验未通过(最大边线加权值差异为0.13，P＜0.05)，即不同性别中学生情绪智力和睡眠问题网络结构存在差异，边线不变性检验显示，6/55条边缘差异有统计学意义。女生的A2(情绪调节)-B7(对睡眠的不满)和A3(情绪运用)-B1(入睡困难)连接强于男生；而在男生中A2(情绪调节)- B5(失眠的显著性)联系更强。
2.3　中学生情绪智力与睡眠问题的网络中心性
中心性结果显示，B2(睡眠维持困难)、B6(对睡眠的担忧)和A3(情绪运用)是强度值较高的节点，分别为0.82，1.11和0.98，表明这些节点是与网络中其他症状联系较为紧密的症状。此外，桥接强度指数表明B7(对睡眠的不满)和A3(情绪运用)是网络中联系情绪智力与睡眠问题的桥接症状，桥接强度分别为1.77和1.59。男生和女生网络的总体强度(4.56，4.67)和总体桥接强度(4.49，4.82)差异均无统计学意义(P值均>0.05)。
2.4　中学生情绪智力和睡眠问题的网络稳定性和准确性
在情绪智力和睡眠问题的网络中，Bootstrap过程方法的结果显示，各条边线的95%CI较窄，表明准确性高。节点强度和桥接强度的CS-C值均为0.75，表现出良好的稳定性。
3　讨论
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本研究发现，西南地区中学生的睡眠问题报告率较高(47.3%)，其中严重睡眠问题报告率为2.2%，高于中国其他地区的报道[11]；而情绪智力各维度的水平略高于同年龄段中学生[9]。青春期是中学生情绪智力发展的重要阶段，这些结果证实了探究此阶段中学生情绪智力各维度的发展与睡眠问题在症状水平关联模式的重要性，并且可以为有针对性的睡眠问题干预提供切入点。
睡眠维持困难和对睡眠的担心为中学生情绪智力与睡眠问题网络中的核心症状，与既往研究一致[12]。一项针对青少年的网络分析表明，在不同睡眠质量人群的失眠网络中，睡眠维持困难和对睡眠的担心均具有更高强度的中心性[12]。《国际睡眠障碍分类第3版》中将睡眠维持困难作为慢性失眠的标志性特征，且睡眠维持困难会导致日间功能损害、注意力不集中、消极情绪体验增加和情绪调节能力下降等功能障碍[13]。此外，情绪运用是另一个核心症状，虽然很少有研究将情绪运用确定为核心症状，但较之被广泛关注的情绪调节能力，情绪运用能力既是情绪感知、调节能力的综合结果，又从改善认知和促进行动的角度反映了情绪智力作为一种重要心理能力与睡眠问题各个症状产生关联的可能路径。对以上网络中具有高度中心性的核心症状的识别具有重要意义，有针对性地对这些核心症状采取干预措施可以改善邻近症状节点，从而有效降低中学生睡眠问题持续发生的风险。
本研究表明，对睡眠的不满和情绪运用是连接情绪智力和睡眠问题的桥接症状。根据网络精神病理学理论，桥接症状既是理解不同症状集群之间相互关联的重要节点，也提供了潜在的干预目标[6]。在本研究中，情绪智力子网络中的情绪运用与睡眠问题子网络紧密关联。情绪运用能力可通过对情绪的处理与利用来促进健康行为的动机内化与维持。既往研究表明，睡眠问题的康复高度依赖患者主动执行睡眠卫生行为[14]。而根据自我决定理论，个体的内在动机是健康行为维持的关键[15]。情绪运用能力在情绪调节能力的基础上进一步通过自我激励、情绪引导等方式内化动机，从而促进个体采取改善或加重睡眠障碍的行为，最终持续影响睡眠质量[4]。因此，本研究也提示有针对性的提升情绪运用能力可能是缓解睡眠问题的有效措施。此外，睡眠问题子网络中“对睡眠的不满”节点也与情绪智力子网络关联紧密。对睡眠的不满是睡眠问题在认知与情绪层面的症状体现，有研究表明睡眠满意度也可能与情绪智力的各个维度产生重要关联[5]。情绪运用和睡眠满意度的桥接作用提供了较为有益的干预路径，实践中可通过提升情绪运用能力以及改善睡眠满意度来提高中学生的情绪智力，也为整体睡眠质量带来积极影响。
情绪智力和睡眠问题网络结构存在性别差异。本研究表明，女生的“情绪调节-对睡眠的不满”和“情绪运用-入睡困难”连接强于男生，而在男生中“情绪调节-失眠的显著性”联系更强。既往研究表明，随着个体达到青春期发育成熟阶段，下丘脑-垂体-肾上腺轴的活动会发生性别特异性变化，尽管保持几乎相同的入睡时间和清醒时间，但中学女生对褪黑激素和体温的昼夜节律设定比男生更早[16-17]。因此，因情绪问题而导致的入睡困难的症状在女生中比男生表现的更为显著。此外，一项国外的研究发现，睡眠障碍的性别差异可能是由于中学女生更易感知到较高的压力水平以及会对压力源产生更大的情绪反应[18]。因此，调节自身情绪以减轻心理困扰并且合理利用情绪来采取积极行动更可能是女生减轻睡眠问题的有效方法。
本研究存在以下局限性：首先，由于研究采用的是横断面数据，无法深入探讨情绪智力与睡眠问题之间的轨迹变化和因果关系，未来应利用纵向数据进一步明确症状因果关联；其次，由于症状评估是基于自我报告，因此不能完全排除回忆或社会期望偏差对结果的影响，未来也应采用多种睡眠评估数据(如临床诊断数据、检验指标等)进行验证。
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  • 国家自然科学基金面上项目(82273745)
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2025年第46卷第12期
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doi: 10.16835/j.cnki.1000-9817.2025350
  • 接收时间：2025-07-23
  • 首发时间：2026-11-06
  • 出版时间：2025-12-25
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  • 收稿日期：2025-07-23
  • 修回日期：2025-09-23
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    1四川大学华西公共卫生学院/华西第四医院健康行为与社会医学系, 成都 610041
    2成都市郫都区疾病预防控制中心应急与业务管理办公室

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