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Article(id=1325521436974133314, tenantId=1146029695717560320, journalId=1256213402557890569, issueId=1325521023759691810, articleNumber=null, orderNo=null, doi=10.16835/j.cnki.1000-9817.2025199, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1725379200000, receivedDateStr=2024-09-04, revisedDate=1744646400000, revisedDateStr=2025-04-15, acceptedDate=null, acceptedDateStr=null, onlineDate=1793958537571, onlineDateStr=2026-11-06, pubDate=1753372800000, pubDateStr=2025-07-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793958537571, onlineIssueDateStr=2026-11-06, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793958537571, creator=13701087609, updateTime=1793958537571, updator=13701087609, issue=Issue{id=1325521023759691810, tenantId=1146029695717560320, journalId=1256213402557890569, year='2025', volume='46', issue='7', pageStart='913', pageEnd='1064', issueExtLink='null', onlineDate='null', pubDate='1753372800000', pubDateStr='2025-07-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793958439054, creator='13701087609', updateTime=1793958439054, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=975, endPage=979, ext={EN=ArticleExt(id=1325521438727352387, articleId=1325521436974133314, tenantId=1146029695717560320, journalId=1256213402557890569, language=EN, title=Network structure characteristics of trait aggression in children and adolescents based on psychometric network analysis, columnId=1259565855189418448, journalTitle=Chinese Journal of School Health, columnName=Mental Health, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the core features of trait aggression in children and adolescents, so as to provide a theoretical basis for behavioral interventions targeting the central psychological characteristics of aggression in children and adolescents.

Methods

From March to May 2020, a simple random convenience sampling method was employed to recruit 39 165 students from grades 4 to 12 in Sichuan, Chongqing, Guizhou, and Shandong. Data were collected via online questionnaires, with all participants completing the Chinese Version of the Aggression Questionnaire. Psychometric network analysis was utilized for data processing.

Results

Trait aggression among Chinese children and adolescents was at a moderately low level. The core nodes of the network structure included physical aggression [if someone intentionally causes trouble for me, I will hit them severely (AGG6); if someone hits me, I will retaliate (AGG11)] and self-aggression [When I am very irritable, I think of hurting myself (AGG5); when I am in a bad mood, I engage in behaviors that harm my health, such as overeating (AGG25)]. Across grade levels, core nodes primarily originated from the anger dimension [When I'm angry, I feel like a powder magazine that could explode at any moment (AGG13); I can't control my temper (AGG18); I am prone to getting angry when I see things that are not pleasing to the eye (AGG23); I will get angry for no reason (AGG27)]. Except for grades 7 and 9, core nodes in other grades included the verbal aggression dimension [I am prone to arguments with people (AGG22)]. Before grade 8, core nodes incorporated the self-aggression dimension (AGG 5, AGG 25); after grade 8, core nodes included the physical aggression dimension [AGG 6, AGG 11, I fight slightly more than others (AGG16), and if people around me make things difficult for me to a certain extent, I will fight with them (AGG26)]. No statistically significant differences were found in the trait aggression network structures across grades, genders, or within-gender comparisons of different grades.

Conclusion

These findings broaden our understanding of aggression in children and adolescents, suggesting that behavioral interventions can effectively reduce aggressive behaviors in this population.

, authors=Xu WANG1, 2, Yanling LIU*, 1, 2, Mingchen WEI3, Ni ZHU4, Yibo GENG1, 2, Weijun LIU1, 2, Shuai CHEN5, authorsList=Xu WANG, Yanling LIU, Mingchen WEI, Ni ZHU, Yibo GENG, Weijun LIU, Shuai CHEN, authorCompany=null, correspAuthors=Yanling 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=1325521447455699015, articleId=1325521436974133314, tenantId=1146029695717560320, journalId=1256213402557890569, language=CN, title=基于心理测量网络分析儿童青少年特质攻击的网络结构特征, columnId=1259565858817491410, journalTitle=中国学校卫生, columnName=心理卫生, runingTitle=null, highlight=null, articleAbstract=
目的

探讨儿童青少年攻击特质的核心特征，为针对儿童青少年攻击性的核心心理特征开展行为干预提供理论依据。

方法

2020年3—5月，采用单纯随机方便抽样法从四川、重庆、贵州和山东抽取小学四年级至高中三年级共39 165名学生，以网络问卷的方式展开调查，所有被试均完成中文版攻击特质问卷，采用心理测量网络分析进行数据分析。

结果

中国儿童青少年的特质攻击处于中等偏下水平，其网络结构的核心节点包括身体攻击[如果有人故意找我麻烦，严重时我会揍他(AGG6)；如果有人打我，我会还击(AGG11)]和自我攻击[很烦躁时我会想到伤害自己(AGG5)；情绪不好时我会做出诸如暴饮暴食等危害自身健康的行为(AGG25)]；各年级的核心节点主要来自愤怒维度[我生气时感觉像个火药库，随时会爆炸(AGG13)；我难以控制自己的脾气(AGG18)；看到不顺眼的事，我容易发火(AGG23)；我会无缘无故发脾气(AGG27)]，除七和九年级外，其他年级的核心节点包含言语攻击维度[我容易与人发生争吵(AGG22)]；八年级前，核心节点包含自我攻击维度(AGG 5，AGG 25)；八年级后，核心节点包含身体攻击维度[AGG 6，AGG 11，我比别人打架稍多一些(AGG16)，如果周围人为难我到一定程度，我和他们会动手打架(AGG26)]；不同年级、不同性别或同一性别不同年级学生的特质攻击性网络结构差异无统计学意义。

结论

扩展对儿童青少年攻击性的理解，采用行为干预可减少儿童青少年攻击性行为的发生。

, authors=王旭1, 2, 刘衍玲*, 1, 2, 魏铭辰3, 朱霓4, 耿毅博1, 2, 刘韦君1, 2, 陈帅5, authorsList=王旭, 刘衍玲, 魏铭辰, 朱霓, 耿毅博, 刘韦君, 陈帅, authorCompany=null, correspAuthors=刘衍玲, authorNote=

王旭(1995-), 男, 安徽蚌埠人, 在读博士, 主要研究方向为儿童青少年心理健康

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刘衍玲，E-mail:
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注：图中线越粗表示相关性越强。

, figureFileSmall=QrQdmJkWF5AMumtv4yjKsA==, figureFileBig=1RwsBtfe7/yTF114uA33ag==, tableContent=null), ArticleFig(id=1325521483845480586, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325521436974133314, language=EN, label=Tab.1, caption=

Trait aggression scores of surveyed children and adolescents(n=39 165, x ± s)

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序号题项得分序号题项得分
AGG1某些情况下，我会控制不住打人2.07±1.17AGG16我比别人打架稍多一些1.57±0.95
AGG2我不同意朋友意见时，就当面反对2.61±1.15AGG17当人们与我意见不同时，我会忍不住与其争论2.39±1.15
AGG3我的脾气一点就着，但一会儿就好2.91±1.32AGG18我难以控制自己的脾气2.21±1.21
AGG4我的嫉妒心较强2.02±1.09AGG19我对某些事情感到耿耿于怀2.49±1.29
AGG5很烦躁时我会想到伤害自己1.94±1.22AGG20很自责时我会惩罚自己2.30±1.24
AGG6如果有人故意找我麻烦，严重时我会揍他2.18±1.23AGG21必要时我用武力维护自己的权利2.25±1.24
AGG7我喜欢否定他人的意见1.88±1.03AGG22我容易与人发生争吵1.95±1.07
AGG8事情不顺利时我的烦躁会表现出来2.59±1.23AGG23看到不顺眼的事，我容易发火2.08±1.15
AGG9我觉得我遇到不公平的事较多2.39±1.20AGG24我认为有“朋友”说我的坏话2.12±1.18
AGG10很生气时我会因不小心而受伤2.25±1.22AGG25情绪不好时我会做出如暴饮暴食等危害自身健康的行为1.69±1.05
AGG11如果有人打我，我会还击2.80±1.24AGG26如果周围人为难我到一定程度，我和他们会动手打架1.95±1.14
AGG12当人们干扰我时，我会毫不客气地指责他们2.40±1.15AGG27我会无缘无故发脾气1.76±1.08
AGG13我生气时感觉像个火药库，随时会爆炸2.36±1.29AGG28当别人对我特别好时，我觉得他们有所企图2.08±1.18
AGG14陌生人对我过于友好时，我怀疑对方另有目的2.79±1.33AGG29我很生气时，会当他人面摔东西1.73±1.06
AGG15特别激动时我会忽视自身安全2.25±1.23AGG30我怀疑有人在背后嘲笑我2.04±1.21
), ArticleFig(id=1325521484302659723, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325521436974133314, language=CN, label=表1, caption=

调查儿童青少年特质攻击得分情况(n=39 165，x ± s)

, figureFileSmall=null, figureFileBig=null, tableContent=
序号题项得分序号题项得分
AGG1某些情况下，我会控制不住打人2.07±1.17AGG16我比别人打架稍多一些1.57±0.95
AGG2我不同意朋友意见时，就当面反对2.61±1.15AGG17当人们与我意见不同时，我会忍不住与其争论2.39±1.15
AGG3我的脾气一点就着，但一会儿就好2.91±1.32AGG18我难以控制自己的脾气2.21±1.21
AGG4我的嫉妒心较强2.02±1.09AGG19我对某些事情感到耿耿于怀2.49±1.29
AGG5很烦躁时我会想到伤害自己1.94±1.22AGG20很自责时我会惩罚自己2.30±1.24
AGG6如果有人故意找我麻烦，严重时我会揍他2.18±1.23AGG21必要时我用武力维护自己的权利2.25±1.24
AGG7我喜欢否定他人的意见1.88±1.03AGG22我容易与人发生争吵1.95±1.07
AGG8事情不顺利时我的烦躁会表现出来2.59±1.23AGG23看到不顺眼的事，我容易发火2.08±1.15
AGG9我觉得我遇到不公平的事较多2.39±1.20AGG24我认为有“朋友”说我的坏话2.12±1.18
AGG10很生气时我会因不小心而受伤2.25±1.22AGG25情绪不好时我会做出如暴饮暴食等危害自身健康的行为1.69±1.05
AGG11如果有人打我，我会还击2.80±1.24AGG26如果周围人为难我到一定程度，我和他们会动手打架1.95±1.14
AGG12当人们干扰我时，我会毫不客气地指责他们2.40±1.15AGG27我会无缘无故发脾气1.76±1.08
AGG13我生气时感觉像个火药库，随时会爆炸2.36±1.29AGG28当别人对我特别好时，我觉得他们有所企图2.08±1.18
AGG14陌生人对我过于友好时，我怀疑对方另有目的2.79±1.33AGG29我很生气时，会当他人面摔东西1.73±1.06
AGG15特别激动时我会忽视自身安全2.25±1.23AGG30我怀疑有人在背后嘲笑我2.04±1.21
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Core nodes in the network structure of trait aggression in children adolescents of different genders

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年级核心节点
四AGG 22、AGG 23、AGG 25、AGG 30
五AGG 13、AGG 22、AGG 25、AGG 30
六AGG 5、AGG 13、AGG 22、AGG 25
七AGG 5、AGG 13、AGG 23、AGG 25
八AGG 11、AGG 22、AGG 25、AGG 27
九AGG 6、AGG 16、AGG 18、AGG 26
高一AGG 13、AGG 16、AGG 22、AGG 26
高二AGG 16、AGG 22、AGG 23、AGG 26
高三AGG 13、AGG 16、AGG 22、AGG 23
), ArticleFig(id=1325521487268032654, tenantId=1146029695717560320, journalId=1256213402557890569, articleId=1325521436974133314, language=CN, label=表2, caption=

不同年级学生特质攻击网络结构的核心节点

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年级核心节点
四AGG 22、AGG 23、AGG 25、AGG 30
五AGG 13、AGG 22、AGG 25、AGG 30
六AGG 5、AGG 13、AGG 22、AGG 25
七AGG 5、AGG 13、AGG 23、AGG 25
八AGG 11、AGG 22、AGG 25、AGG 27
九AGG 6、AGG 16、AGG 18、AGG 26
高一AGG 13、AGG 16、AGG 22、AGG 26
高二AGG 16、AGG 22、AGG 23、AGG 26
高三AGG 13、AGG 16、AGG 22、AGG 23
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基于心理测量网络分析儿童青少年特质攻击的网络结构特征
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王旭 1, 2 , 刘衍玲 *, 1, 2 , 魏铭辰 3 , 朱霓 4 , 耿毅博 1, 2 , 刘韦君 1, 2 , 陈帅 5
中国学校卫生 | 心理卫生 2025,46(7): 975-979
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中国学校卫生 |心理卫生 2025 , 46 (7) : 975 -979
基于心理测量网络分析儿童青少年特质攻击的网络结构特征
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王旭1, 2, 刘衍玲*, 1, 2 , 魏铭辰3, 朱霓4, 耿毅博1, 2, 刘韦君1, 2, 陈帅5
作者信息
  • 1西南大学心理学部, 重庆 400715
  • 2西南大学心理健康教育研究中心
  • 3华东师范大学教育学部
  • 4重庆渝北启诚巴蜀小学校
  • 5华南师范大学心理学院
通讯作者:
刘衍玲，E-mail:
作者简介:

王旭(1995-), 男, 安徽蚌埠人, 在读博士, 主要研究方向为儿童青少年心理健康

Network structure characteristics of trait aggression in children and adolescents based on psychometric network analysis
Xu WANG1, 2, Yanling LIU*, 1, 2 , Mingchen WEI3, Ni ZHU4, Yibo GENG1, 2, Weijun LIU1, 2, Shuai CHEN5
Affiliations
  • 1Faculty of Psychology, Southwest University, Chongqing 400715, China
出版时间: 2025-07-25 doi: 10.16835/j.cnki.1000-9817.2025199
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摘要
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目的

探讨儿童青少年攻击特质的核心特征，为针对儿童青少年攻击性的核心心理特征开展行为干预提供理论依据。

方法

2020年3—5月，采用单纯随机方便抽样法从四川、重庆、贵州和山东抽取小学四年级至高中三年级共39 165名学生，以网络问卷的方式展开调查，所有被试均完成中文版攻击特质问卷，采用心理测量网络分析进行数据分析。

结果

中国儿童青少年的特质攻击处于中等偏下水平，其网络结构的核心节点包括身体攻击[如果有人故意找我麻烦，严重时我会揍他(AGG6)；如果有人打我，我会还击(AGG11)]和自我攻击[很烦躁时我会想到伤害自己(AGG5)；情绪不好时我会做出诸如暴饮暴食等危害自身健康的行为(AGG25)]；各年级的核心节点主要来自愤怒维度[我生气时感觉像个火药库，随时会爆炸(AGG13)；我难以控制自己的脾气(AGG18)；看到不顺眼的事，我容易发火(AGG23)；我会无缘无故发脾气(AGG27)]，除七和九年级外，其他年级的核心节点包含言语攻击维度[我容易与人发生争吵(AGG22)]；八年级前，核心节点包含自我攻击维度(AGG 5，AGG 25)；八年级后，核心节点包含身体攻击维度[AGG 6，AGG 11，我比别人打架稍多一些(AGG16)，如果周围人为难我到一定程度，我和他们会动手打架(AGG26)]；不同年级、不同性别或同一性别不同年级学生的特质攻击性网络结构差异无统计学意义。

结论

扩展对儿童青少年攻击性的理解，采用行为干预可减少儿童青少年攻击性行为的发生。

精神卫生  /  网络分析  /  攻击  /  儿童  /  青少年
Objective

To explore the core features of trait aggression in children and adolescents, so as to provide a theoretical basis for behavioral interventions targeting the central psychological characteristics of aggression in children and adolescents.

Methods

From March to May 2020, a simple random convenience sampling method was employed to recruit 39 165 students from grades 4 to 12 in Sichuan, Chongqing, Guizhou, and Shandong. Data were collected via online questionnaires, with all participants completing the Chinese Version of the Aggression Questionnaire. Psychometric network analysis was utilized for data processing.

Results

Trait aggression among Chinese children and adolescents was at a moderately low level. The core nodes of the network structure included physical aggression [if someone intentionally causes trouble for me, I will hit them severely (AGG6); if someone hits me, I will retaliate (AGG11)] and self-aggression [When I am very irritable, I think of hurting myself (AGG5); when I am in a bad mood, I engage in behaviors that harm my health, such as overeating (AGG25)]. Across grade levels, core nodes primarily originated from the anger dimension [When I'm angry, I feel like a powder magazine that could explode at any moment (AGG13); I can't control my temper (AGG18); I am prone to getting angry when I see things that are not pleasing to the eye (AGG23); I will get angry for no reason (AGG27)]. Except for grades 7 and 9, core nodes in other grades included the verbal aggression dimension [I am prone to arguments with people (AGG22)]. Before grade 8, core nodes incorporated the self-aggression dimension (AGG 5, AGG 25); after grade 8, core nodes included the physical aggression dimension [AGG 6, AGG 11, I fight slightly more than others (AGG16), and if people around me make things difficult for me to a certain extent, I will fight with them (AGG26)]. No statistically significant differences were found in the trait aggression network structures across grades, genders, or within-gender comparisons of different grades.

Conclusion

These findings broaden our understanding of aggression in children and adolescents, suggesting that behavioral interventions can effectively reduce aggressive behaviors in this population.

Mental health  /  Network analysis  /  Aggression  /  Child  /  Adolescents
王旭, 刘衍玲, 魏铭辰, 朱霓, 耿毅博, 刘韦君, 陈帅. 基于心理测量网络分析儿童青少年特质攻击的网络结构特征. 中国学校卫生, 2025 , 46 (7) : 975 -979 . DOI: 10.16835/j.cnki.1000-9817.2025199
Xu WANG, Yanling LIU, Mingchen WEI, Ni ZHU, Yibo GENG, Weijun LIU, Shuai CHEN. Network structure characteristics of trait aggression in children and adolescents based on psychometric network analysis[J]. Chinese Journal of School Health, 2025 , 46 (7) : 975 -979 . DOI: 10.16835/j.cnki.1000-9817.2025199
正文
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儿童青少年攻击性行为作为全球性公共卫生问题受到广泛关注[1]。实证研究表明，高攻击性水平与较差的学习表现[2]、心理健康问题[3]和自杀倾向[4]等呈负性相关；同时，儿童青少年时期的攻击也可能预测成年之后的攻击和反社会行为[5-6]。但现有文献中探讨攻击性网络结构的实证研究且对特质攻击性网络结构的系统性分析尚存不足[7-8]。
心理测量网络分析方法[8]的应用不仅通过可视化建模技术为理解儿童青少年攻击性的核心心理特征提供了理论依据，更为行为干预研究开辟了新的方法论路径。具体而言，通过针对特质攻击性的核心节点进行干预，可以更大程度降低儿童青少年的攻击行为。此外，研究数据同时揭示了显著的性别差异特征，男性的攻击性高于女性[9-10]；并且随着年级的上升，攻击性总体呈上升趋势[11]。基于此，本研究进一步考察了性别和年级差异对儿童青少年攻击性网络结构的影响，旨在为针对儿童青少年攻击性的核心心理特征进行行为干预提供理论依据。
1　对象与方法
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1.1　对象
2020年3—5月，采用单纯随机方便抽样方法从四川、重庆、贵州和山东共4个省的中小学校抽取小学四年级至高三年级学生，通过网络问卷收集数据，在排除测谎题未通过、信息填写不正确等数据后，得到39 165份问卷。其中男生18 714名，女生20 451名；独生子女11 711名，非独生子女27 454名；农村学生16 156名，城镇学生9 367名，城市学生13 642名；小学生17 493名，初中生15 277名，高中生6 395名；年龄9~19岁。本调查已得到学生和家长的知情同意，并获得西南大学心理学部伦理委员会批准(IRB NO. H25006)。
1.2　方法
采用由Buss等[12]编制，李献云等[13]修订的特质攻击问卷，该问卷共30题，包含愤怒(6个条目)、敌意(7个条目)、身体攻击(7个条目)、言语攻击(5个条目)和自我攻击(5个条目)共5个维度。采用5点计分，“1=完全不符合”~“5=完全符合”，得分越高代表攻击性越强。已有研究中该问卷的信、效度良好[14]，本研究中该问卷内部一致性系数为0.95。
1.3　质量控制
采用网络问卷的形式，在题项上设置多道测谎题，并根据个人信息和答题时间对问卷进行排查。在问卷施测前，课题组将本次调查的目的、数据用途、调查链接等通过网络发送给各个学校；学校同意后将上述内容通过微信家长群发送给学生家长；家长同意之后，将手机或者链接交给学生，由学生完成填写。在上述过程中对学校和家长强调了自愿参与和随时退出原则；在问卷首页上也告知学生调查用途及自愿性、保密性原则，允许学生随时终止或放弃测试。
1.4　统计学分析
使用Mplus 8.3软件进行验证性因素分析，验证研究变量在本研究中的结构效度。使用SPSS 25.0软件计算特质攻击问卷所有题项的均值和标准差，并计算各题项之间的协方差矩阵。检验水准α=0.05。使用RStudio软件中的qgraph包进行网络分析，其中包括EBICglasso函数[15]。该函数允许使用扩展贝叶斯信息准则(extended bayesian information criterion, EBIC)和图形绝对值收敛和选择算子及套索算法(least absolute shrinkage and selection, LASSO)正则化进行网络分析，使用惩罚最大似然估计控制由于多次测试可能产生的虚假相关性。一般来说，中心性指数(强度、紧密度、中介度和预期影响)用于量化网络结构中每个节点的重要性。Robinaugh等[16]指出，当网络仅由正相关组成时，预期影响的表现与强度一致，故本研究中未包括预期影响。同时，紧密度和中介度测量的稳定性难以维持[16]。因此本研究将强度作为主要标准，而紧密度和中介度将作为评估节点中心性的次要标准。
使用Bootnet程序包评估网络结构的准确性和稳健性，计算相关稳定(correlation stability coefficient, CS系数)系数以量化中心性指数的稳定性，CS系数高于0.50被认为是可以接受的[17]。使用Network Comparison Test程序包[18]进行性别和年级之间的网络不变性、全局强度不变性(global strength invariance，GS)和中心性不变性的差异性检验。
2　结果
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2.1　儿童青少年特质攻击的基本情况
被试儿童青少年所有30个题项得分为正态分布，平均得分为2.91分，整体处于中等偏下水平，提示被试儿童特质攻击水平不高。见表1。
2.2　儿童青少年特质攻击的网络结构
图1A中心性指标显示，AGG 5、AGG 6、AGG 11和AGG 25是整体儿童青少年特质攻击网络中的核心节点。网络估计的准确性检验结果表明，儿童青少年攻击性特质的网络结构表现出高度的准确性和稳定性。图1BC中心性指标显示，男生样本的核心节点是AGG 5、AGG 25、AGG 26和AGG 27，而女生样本的核心节点是AGG 5、AGG 6、AGG 11和AGG 26。准确性检验结果表明，男生和女生特质攻击性的网络结构也是稳定的。男生和女生网络结构的差异分析显示，网络不变性差异有统计学意义(M=0.09，P < 0.01)。然而，在整体强度不变性上差异无统计学意义(GS男生=16.96，GS女生=17.38，t=0.42，P>0.05)。只有6个节点在男生和女生之间表现出显著的中心性不变性差异。进一步对各年级男生和女生的网络结构进行差异分析，结果表明，只有七、八、高一和高二年级在网络不变性上差异有统计学意义(P值均 < 0.05)。
2.3　特质攻击网络结构的年级差异
表2总结了基于中心性指数结果每个年级的核心节点，对每个年级的网络结构进行准确性和稳定性分析，结果显示，除高三年级的中介度CS系数为0.21，高三年级的紧密度CS系数和高二年级的中介度CS系数，以及九年级的3个中心性指数均低于0.5，其他所有年级的中心性指数CS系数均大于0.5。表明跨越9个年级的所有学生的特质攻击性网络结构相对稳定。对相邻年级学生的网络结构进行置换检验，结果表明，只有九年级和高一年级在整体强度不变性方面差异均有统计学意义(P值均 < 0.05)；相邻年级男女生之间的网络结构差异均无统计学意义(P值均>0.05)。进一步对小学、初中和高中3个不同学段的网络结构进行差异检验，结果表明，小学与初中和高中之间的网络不变性差异有统计学意义(P值均 < 0.05)，而初中和高中之间差异无统计学意义(P>0.05)。在整体强度不变性方面，小学、初中和高中之间的置换检验差异均无统计学意义(P值均>0.05)。小学与初中之间有6个不同的显著节点，小学与高中之间有5个不同的显著节点。
3　讨论
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在整体样本中，儿童青少年特质攻击性的核心特征集中体现于以下条目：“很烦躁时我会想到伤害自己(AGG 5)”“如果有人故意找我麻烦，严重时我会揍他(AGG 6)”“如果有人打我，我会还击(AGG 11)”和“情绪不好时我会做出如暴饮暴食等危害自身健康的行为(AGG 25)”。以上条目分别属于身体攻击和自我攻击2个维度，这意味着中小学生的攻击性特点偏向于行为层面；攻击的对象既指向他人，也包括自己。研究结果凸显对中小学生攻击性进行早期干预的必要性，该类群体不仅存在人际暴力风险，更潜藏自我伤害的可能性。与高攻击性水平还与自杀倾向[4]，甚至是自杀行为[19]正相关。
年级异质性分析表明，任何相邻2个年级之间的核心节点都不完全一致。然而，在多个年级中某些节点会重复作为核心节点。(1)尽管在整体样本中没有任何核心节点包括愤怒维度的任何题项，但各年级特异性网络均包含1~2个愤怒维度节点(AGG 13、AGG 18、AGG 23、AGG 27)，表明“愤怒”可能在儿童青少年攻击行为的表现中起着重要作用。在广泛的年龄范围内，儿童和青少年特质攻击性的核心特征是攻击行为，但在特定年级水平上，其特质攻击性的核心特征并不排除攻击性情绪(愤怒)。因此，“愤怒”可能是中小学生特质攻击性在不同年级上的一个重要共同特征。(2)与愤怒维度的分布特征相仿，除了七和九年级外，各年级网络均显现言语攻击维度的核心节点，尤其AGG 22(我容易与人发生争吵)这一条目持续显现。不仅揭示了“言语攻击”是中小学生年级水平上特质攻击性的一个重要特征，还强调了AGG 22在言语攻击维度中的独特性和重要性。(3)攻击指向性呈现发展阶段效应。在从小学四年级到高三年级的9个年级中，自我攻击和身体攻击作为核心节点的表现出现了明显的“分界线”现象。在八年级之前，任何年级的4个核心节点中都包括1~2个来自“自我攻击”维度的节点，但不包括来自“身体攻击”维度的节点。而八年级之后，任何年级的4个核心节点中都至少包括1个来自“身体攻击”维度的节点，但不包括来自“自我攻击”维度的节点。另外，八年级作为过渡期，其网络同时包含自我攻击与身体攻击节点各1个，表明在中学低年级及之前(至少包括小学高年级)，学生的攻击特质主要是针对自己。然而在中学高年级之后，他们的攻击目标从自我转向他人，推测可能随着年龄的增长，青少年自我安全意识的发展可能会逐渐导致从自我攻击向对他人攻击的转变。本研究还分别探讨了男生和女生的特质攻击网络结构。男生特质攻击网络的核心特征条目涉及愤怒、身体攻击和自我攻击维度，而女生则以身体攻击和自我攻击维度为主。这一结果与整体样本网络结构的核心节点发现一致，特征为既有自我攻击也有对他人的攻击。此外，男生攻击特质的核心特征包括AGG 27(我会无缘无故发脾气)，表明情绪问题与男生在儿童青少年时期的攻击性有密切关联。然而，在整体样本中，男生和女生的攻击性网络结构差异无统计学意义。同时，各年级中男生和女生的特质攻击性网络结构均显示差异无统计学意义，表明男生和女生在特质攻击的核心特征上具有高度相似性，其差异可能只表现在程度或强度上。跨性别的一致性结果表明，教育者可以制定适用于同年龄段所有学生的干预措施。
本研究也存在一些局限：(1)高三年级的被试数量与其他年级的学生数量相比存在差距。(2)研究仅在国内部分省市收集了小学四年级至高三年级的学生数据，研究结果并不能代表全国学生。(3)使用大样本的横断面数据不能对中小学生攻击特质网络结构的发展趋势做出准确判断。未来可通过纵向追踪考察中小学生攻击性核心特征的变化。(4)数据依靠学生的自我报告，可能受到社会赞许效应的影响。未来的研究可以通过教师、家长和同伴的他评方式收集数据，进行多方面的综合考察。
基金
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  • 重庆市人文社会科学重点研究基地重点项目(14SKB033); 重庆市教育科学规划课题项目(K23YB2020021)
文献
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2025年第46卷第7期
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doi: 10.16835/j.cnki.1000-9817.2025199
  • 接收时间：2024-09-04
  • 首发时间：2026-11-06
  • 出版时间：2025-07-25
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  • 收稿日期：2024-09-04
  • 修回日期：2025-04-15
基金
重庆市人文社会科学重点研究基地重点项目(14SKB033); 重庆市教育科学规划课题项目(K23YB2020021)
作者信息
    1西南大学心理学部, 重庆 400715
    2西南大学心理健康教育研究中心
    3华东师范大学教育学部
    4重庆渝北启诚巴蜀小学校
    5华南师范大学心理学院

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刘衍玲，E-mail:
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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