Article(id=1240738482344219028, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202411165, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1731254400000, receivedDateStr=2024-11-11, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773744705997, onlineDateStr=2026-03-17, pubDate=1746806400000, pubDateStr=2025-05-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773744705997, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773744705997, creator=13701087609, updateTime=1773744705997, updator=13701087609, issue=Issue{id=1240738480549065614, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='9', pageStart='1537', pageEnd='1728', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773744705569, creator=13701087609, updateTime=1773744787657, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240738824918192654, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240738824922386959, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240738480549065614, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1674, endPage=1680, ext={EN=ArticleExt(id=1240738482595877272, articleId=1240738482344219028, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Study on the relationship between substance use, problematic internet use, and co-occurring behaviors among college students and unintentional injuries, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the relationship between substance use, problematic internet use, and their co-occurring behaviors with unintentional injuries among college students.

Methods

A cross-sectional study design was employed, with a questionnaire survey conducted among 1 700 enrolled students from two ordinary higher education institutions in Beijing. The CRAFFT scale was used to assess substance use, while the Internet Addiction Test (IAT) evaluated problematic internet use. Information on unintentional injuries and related influencing factors was also collected. Multivariate binary logistic regression was utilized to analyze the association between substance use, problematic internet use, co-occurring behaviors, and unintentional injuries, as well as to explore the influencing factors of unintentional injuries in the co-occurring behavior population.

Results

A total of 1 626 valid questionnaires were collected. The prevalence of substance use was 35.85% (583 cases), the prevalence of problematic internet use was 52.34% (851 cases), and the co-occurrence prevalence was 20.05% (326 cases). The prevalence of unintentional injuries was 16.91% (275 cases). After adjusting for confounding factors, the multivariate logistic regression analysis indicated that compared to the control group, the odds ratio for unintentional injuries in the co-occurring behavior group was 1.57 (95%CI: 1.054-2.340), while neither substance use (aOR=1.117, 95%CI: 0.717-1.741) nor problematic internet use (aOR=1.098, 95%CI: 0.758-1.589) showed significant correlation with unintentional injuries. Among the co-occurring behavior population, suicidal ideation was identified as an independent risk factor for unintentional injuries (aOR=2.118, 95%CI: 1.184-3.787).

Conclusion

The simultaneous presence of substance uses and problematic internet use significantly increases the risk of unintentional injuries among college students. It is crucial to focus on high-risk populations exhibiting co-occurring behaviors, especially those with suicidal ideation, and to implement targeted preventive interventions.

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目的

探讨大学生物质使用、问题性网络使用及其共存行为与非故意伤害的关系。

方法

采用横断面研究设计,以北京市两所普通高等学校为研究现场,对1 700名在校学生进行问卷调查。采用CRAFFT量表评估物质使用情况,网络成瘾测验(IAT)评估问题性网络使用情况,同时收集非故意伤害及相关影响因素信息。采用多因素二元logistic回归方法,分析物质使用、问题性网络使用及其共存行为与非故意伤害的关联,并探讨共存行为人群非故意伤害的影响因素。

结果

最终回收有效问卷1 626份。物质使用患病率为35.85%(583例),问题性网络使用患病率为52.34%(851例),两者共存患病率为20.05%(326例),非故意伤害患病率为16.91%(275例)。调整混杂因素后的多因素logistic回归分析显示,与对照组相比,共存行为组的非故意伤害风险比值(aOR)为1.57(95%CI:1.054~2.340),而单独的物质使用(aOR=1.117,95%CI:0.717~1.741)或问题性网络使用(aOR=1.098,95%CI:0.758~1.589)与非故意伤害均无显著相关性。在共存行为人群中,自杀意念是非故意伤害的独立危险因素(aOR=2.118,95%CI:1.184~3.787)。

结论

同时存在物质使用和问题性网络使用显著增加了大学生非故意伤害风险,应重点关注具有共存行为的高危人群,尤其是伴有自杀意念者,开展针对性预防干预。

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祝慧萍,E-mail:
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点,除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=CjFNvE0RDJR9+M4rQnHsdQ==, magXml=uzVohXl6IFYX+YffjibVyg==, pdfUrl=null, pdf=SkIA72Rk0UqVOIzeuXfixw==, pdfFileSize=669212, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=VUU8q6TFj2woa8T9MsKcZQ==, mapNumber=null, authorCompany=null, fund=null, authors=

周小丁(1998—),女,硕士在读,研究方向:伤害流行病学

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The influence of interpersonal sensitivity on suicide ideation among college students: The chain mediating effect of loneliness and depression[D].Wuhan: Central China Normal University, 2020.(In Chinese), articleTitle=The influence of interpersonal sensitivity on suicide ideation among college students: The chain mediating effect of loneliness and depression, refAbstract=null), Reference(id=1241081878225146675, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, doi=null, pmid=null, pmcid=null, year=2020, volume=47, issue=null, pageStart=179, pageEnd=195, url=null, language=null, rfNumber=[35], rfOrder=37, authorNames=Swann AC, Lijffijt M, O'Brien B, journalName=Current Topics in Behavioral Neurosciences, refType=null, unstructuredReference=Swann AC, Lijffijt M, O'Brien B, et al. Impulsivity and suicidal behavior[J]. 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[2025-04-02]. https://www.uptodate.com/contents/screening-for-unhealthy-use-of-alcohol-and-other-drugs-in-primary-care?topicRef=323&source=see_link., articleTitle=Screening for unhealthy use of alcohol and other drugs in primary care, refAbstract=null), Reference(id=1241081878560691018, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, doi=null, pmid=null, pmcid=null, year=2015, volume=31, issue=1, pageStart=100, pageEnd=107, url=null, language=null, rfNumber=[38], rfOrder=40, authorNames=方晓义, 刘璐, 邓林园, journalName=心理发展与教育, refType=null, unstructuredReference=方晓义,刘璐,邓林园,等.青少年网络成瘾的预防与干预研究[J].心理发展与教育201531(1):100-107., articleTitle=青少年网络成瘾的预防与干预研究, refAbstract=null), Reference(id=1241081878703297361, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, doi=null, pmid=null, pmcid=null, year=2015, volume=31, issue=1, pageStart=100, pageEnd=107, url=null, language=null, rfNumber=[38], rfOrder=41, authorNames=Fang XY, Liu L, Deng LY, journalName=Psychological Development and Education, refType=null, unstructuredReference=Fang XY, Liu L, Deng LY, et al. The prevention and intervention on adolescent Internet addiction[J]. Psychological Development and Education, 2015, 31(1): 100-107.(In Chinese), articleTitle=The prevention and intervention on adolescent Internet addiction, refAbstract=null), Reference(id=1241081878854292315, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, doi=null, pmid=null, pmcid=null, year=2015, volume=16, issue=4, pageStart=487, pageEnd=507, url=null, language=null, rfNumber=[39], rfOrder=42, authorNames=Conley CS, Durlak JA, Kirsch AC, journalName=Prevention Science, refType=null, unstructuredReference=Conley CS, Durlak JA, Kirsch AC. A meta-analysis of Universal mental health prevention programs for higher education students[J]. Prevention Science, 2015, 16(4): 487-507., articleTitle=A meta-analysis of Universal mental health prevention programs for higher education students, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1241081864040009857, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, xref=1., ext=[AuthorCompanyExt(id=1241081864048398466, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, companyId=1241081864040009857, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing 100069, China), AuthorCompanyExt(id=1241081864056787075, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, companyId=1241081864040009857, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.首都医科大学公共卫生学院流行病与卫生统计学系,北京 100069)]), AuthorCompany(id=1241081864170033285, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, xref=2., ext=[AuthorCompanyExt(id=1241081864186810502, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, companyId=1241081864170033285, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.首都医科大学公共卫生学院儿少卫生与妇幼保健学系,北京 100069)])], figs=[ArticleFig(id=1241081868855071055, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, language=EN, label=Table 1, caption=

Comparison of baseline characteristics among study subjects [($ \bar{x} \pm s$),n(%)]

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变量总人群
(n=1 626)
物质使用问题性网络使用共存行为

(n=1 043)

(n=583)
Pa
(n=775)

(n=851)
Pb
(n=1 300)

(n=326)
Pc
年龄 (岁)20.33±2.7320.05±2.6520.84±2.81<0.00120.53±2.9620.15±2.490.00620.26±2.7820.63±2.520.026
BMI (kg/m2)22.24±5.3722.12±5.4322.45±5.270.24522.11±5.2222.35±5.500.36822.24±5.4722.25±4.970.980
压力水平32.36±9.6631.63±9.6633.68±9.52<0.00129.33±9.5335.13±8.92<0.00131.38±9.6136.28±8.81<0.001
睡眠质量5.49±3.685.02±3.506.46±3.87<0.0014.93±3.665.97±3.64<0.0015.21±3.606.68±3.81<0.001
心理得分121.52±43.59118.79±40.60126.41±48.120.001109.29±34.24132.66±48.00<0.001117.73±40.78136.63±50.64<0.001
性别<0.0010.2310.049
403 (24.78)220 (21.09)183 (31.39)203 (26.19)200 (23.50)308 (23.69)95 (29.14)
1 223 (75.22)823 (78.91)400 (68.61)572 (73.81)651 (76.50)992 (76.31)231 (70.86)
民族0.6490.2500.696
汉族1 297 (79.77)836 (80.15)461 (79.07)628 (81.03)669 (78.61)1 040 (80.00)257 (78.83)
少数民族329 (20.23)207 (19.85)122 (20.93)147 (18.97)182 (21.39)260 (20.00)69 (21.17)
居住地0.0580.1860.552
城市1 057 (65.01)660 (63.28)397 (68.10)517 (66.71)540 (63.45)840 (64.62)217 (66.56)
农村569 (34.99)383 (36.72)186 (31.90)258 (33.29)311 (36.55)460 (35.38)109 (33.44)
非自杀性自伤0.014<0.001<0.001
1 535 (94.40)996 (95.49)539 (92.45)754 (97.29)781 (91.77)1 241 (95.46)294 (90.18)
91 (5.60)47 (4.51)44 (7.55)21 (2.71)70 (8.23)59 (4.54)32 (9.82)
自杀意念0.001<0.001<0.001
1 133 (69.68)758 (72.67)375 (64.32)608 (78.45)525 (61.69)946 (72.77)187 (57.36)
493 (30.32)285 (27.33)208 (35.68)167 (21.55)326 (38.31)354 (27.23)139 (42.64)
人际暴力0.1690.7470.369
1 598 (98.28)1 029 (98.66)569 (97.60)763 (98.45)835 (98.12)1 280 (98.46)318 (97.55)
28 (1.72)14 (1.34)14 (2.40)12 (1.55)16 (1.88)20 (1.54)8 (2.45)
非故意伤害0.0060.006<0.001
1 351 (83.09)887 (85.04)464 (79.59)665 (85.81)686 (80.61)1 102 (84.77)249 (76.38)
275 (16.91)156 (14.96)119 (20.41)110 (14.19)165 (19.39)198 (15.23)77 (23.62)
), ArticleFig(id=1241081868989288791, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, language=CN, label=表1, caption=

研究对象的基线特征比较[($ \bar{x} \pm s$),n(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
变量总人群
(n=1 626)
物质使用问题性网络使用共存行为

(n=1 043)

(n=583)
Pa
(n=775)

(n=851)
Pb
(n=1 300)

(n=326)
Pc
年龄 (岁)20.33±2.7320.05±2.6520.84±2.81<0.00120.53±2.9620.15±2.490.00620.26±2.7820.63±2.520.026
BMI (kg/m2)22.24±5.3722.12±5.4322.45±5.270.24522.11±5.2222.35±5.500.36822.24±5.4722.25±4.970.980
压力水平32.36±9.6631.63±9.6633.68±9.52<0.00129.33±9.5335.13±8.92<0.00131.38±9.6136.28±8.81<0.001
睡眠质量5.49±3.685.02±3.506.46±3.87<0.0014.93±3.665.97±3.64<0.0015.21±3.606.68±3.81<0.001
心理得分121.52±43.59118.79±40.60126.41±48.120.001109.29±34.24132.66±48.00<0.001117.73±40.78136.63±50.64<0.001
性别<0.0010.2310.049
403 (24.78)220 (21.09)183 (31.39)203 (26.19)200 (23.50)308 (23.69)95 (29.14)
1 223 (75.22)823 (78.91)400 (68.61)572 (73.81)651 (76.50)992 (76.31)231 (70.86)
民族0.6490.2500.696
汉族1 297 (79.77)836 (80.15)461 (79.07)628 (81.03)669 (78.61)1 040 (80.00)257 (78.83)
少数民族329 (20.23)207 (19.85)122 (20.93)147 (18.97)182 (21.39)260 (20.00)69 (21.17)
居住地0.0580.1860.552
城市1 057 (65.01)660 (63.28)397 (68.10)517 (66.71)540 (63.45)840 (64.62)217 (66.56)
农村569 (34.99)383 (36.72)186 (31.90)258 (33.29)311 (36.55)460 (35.38)109 (33.44)
非自杀性自伤0.014<0.001<0.001
1 535 (94.40)996 (95.49)539 (92.45)754 (97.29)781 (91.77)1 241 (95.46)294 (90.18)
91 (5.60)47 (4.51)44 (7.55)21 (2.71)70 (8.23)59 (4.54)32 (9.82)
自杀意念0.001<0.001<0.001
1 133 (69.68)758 (72.67)375 (64.32)608 (78.45)525 (61.69)946 (72.77)187 (57.36)
493 (30.32)285 (27.33)208 (35.68)167 (21.55)326 (38.31)354 (27.23)139 (42.64)
人际暴力0.1690.7470.369
1 598 (98.28)1 029 (98.66)569 (97.60)763 (98.45)835 (98.12)1 280 (98.46)318 (97.55)
28 (1.72)14 (1.34)14 (2.40)12 (1.55)16 (1.88)20 (1.54)8 (2.45)
非故意伤害0.0060.006<0.001
1 351 (83.09)887 (85.04)464 (79.59)665 (85.81)686 (80.61)1 102 (84.77)249 (76.38)
275 (16.91)156 (14.96)119 (20.41)110 (14.19)165 (19.39)198 (15.23)77 (23.62)
), ArticleFig(id=1241081869102535005, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, language=EN, label=Table 2, caption=

Multivariate binary logistic regression analysis of substance use, problematic internet use and unintentional injury

, figureFileSmall=null, figureFileBig=null, tableContent=
变量对照组仅物质使用仅问题性网络使用共存行为
aOR (95%CI)aOR (95%CI)aOR (95%CI)
人数 [患病率(%)]518 (31.9)257 (15.8)525 (32.3)326 (20.0)
模型1Reference1.293 (0.851~1.963)1.333 (0.946~1.877)2.046 (1.426~2.936)
模型2Reference1.341 (0.879~2.044)1.313 (0.931~1.851)2.086 (1.451~2.998)
模型3Reference1.254 (0.820~1.918)1.127 (0.788~1.613)1.699 (1.157~2.496)
模型4Reference1.117 (0.717~1.741)1.098 (0.758~1.589)1.570 (1.054~2.340)
), ArticleFig(id=1241081869211586919, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, language=CN, label=表2, caption=

物质使用、问题性网络使用与非故意伤害发生的多因素二元logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
变量对照组仅物质使用仅问题性网络使用共存行为
aOR (95%CI)aOR (95%CI)aOR (95%CI)
人数 [患病率(%)]518 (31.9)257 (15.8)525 (32.3)326 (20.0)
模型1Reference1.293 (0.851~1.963)1.333 (0.946~1.877)2.046 (1.426~2.936)
模型2Reference1.341 (0.879~2.044)1.313 (0.931~1.851)2.086 (1.451~2.998)
模型3Reference1.254 (0.820~1.918)1.127 (0.788~1.613)1.699 (1.157~2.496)
模型4Reference1.117 (0.717~1.741)1.098 (0.758~1.589)1.570 (1.054~2.340)
), ArticleFig(id=1241081869333221745, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, language=EN, label=Table 3, caption=

Logistic regression analysis of unintentional injury in co-occurring population

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因素偏回归系数标准误Wald χ2PaOR (95%CI)
年龄 (岁)0.0160.0550.0850.7711.016 (0.912~1.133)
BMI (kg/m2)0.0100.0290.1250.7241.010 (0.955~1.069)
性别0.1140.3220.1250.7241.121 (0.596~2.107)
居住地0.0140.3020.0020.9621.014 (0.561~1.834)
非自伤性自杀0.5530.4491.5170.2181.738 (0.721~4.186)
自杀意念0.7500.2976.4050.0112.118 (1.184~3.787)
压力水平-0.0100.0170.3820.5370.990 (0.958~1.023)
心理得分0.0010.0030.1250.7231.001 (0.995~1.007)
常量-2.0121.3762.1370.1440.134
), ArticleFig(id=1241081869568102788, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240738482344219028, language=CN, label=表3, caption=

共存行为人群非故意伤害发生的logistic影响因素分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
因素偏回归系数标准误Wald χ2PaOR (95%CI)
年龄 (岁)0.0160.0550.0850.7711.016 (0.912~1.133)
BMI (kg/m2)0.0100.0290.1250.7241.010 (0.955~1.069)
性别0.1140.3220.1250.7241.121 (0.596~2.107)
居住地0.0140.3020.0020.9621.014 (0.561~1.834)
非自伤性自杀0.5530.4491.5170.2181.738 (0.721~4.186)
自杀意念0.7500.2976.4050.0112.118 (1.184~3.787)
压力水平-0.0100.0170.3820.5370.990 (0.958~1.023)
心理得分0.0010.0030.1250.7231.001 (0.995~1.007)
常量-2.0121.3762.1370.1440.134
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大学生物质使用、问题性网络使用及其共存行为与非故意伤害的关联性研究
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周小丁 1 , 李如钰 1 , 高琦 1 , 成佩霞 2 , 祝慧萍 2
现代预防医学 | 健康与社会行为 2025,52(9): 1674-1680
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现代预防医学 | 健康与社会行为 2025, 52(9): 1674-1680
大学生物质使用、问题性网络使用及其共存行为与非故意伤害的关联性研究
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周小丁1, 李如钰1, 高琦1, 成佩霞2, 祝慧萍2
作者信息
  • 1.首都医科大学公共卫生学院流行病与卫生统计学系,北京 100069
  • 2.首都医科大学公共卫生学院儿少卫生与妇幼保健学系,北京 100069
  • 周小丁(1998—),女,硕士在读,研究方向:伤害流行病学

通讯作者:

祝慧萍,E-mail:
Study on the relationship between substance use, problematic internet use, and co-occurring behaviors among college students and unintentional injuries
Xiao-ding ZHOU1, Ru-yu LI1, Qi GAO1, Pei-xia CHENG2, Hui-ping ZHU2
Affiliations
  • Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing 100069, China
出版时间: 2025-05-10 doi: 10.20043/j.cnki.MPM.202411165
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目的

探讨大学生物质使用、问题性网络使用及其共存行为与非故意伤害的关系。

方法

采用横断面研究设计,以北京市两所普通高等学校为研究现场,对1 700名在校学生进行问卷调查。采用CRAFFT量表评估物质使用情况,网络成瘾测验(IAT)评估问题性网络使用情况,同时收集非故意伤害及相关影响因素信息。采用多因素二元logistic回归方法,分析物质使用、问题性网络使用及其共存行为与非故意伤害的关联,并探讨共存行为人群非故意伤害的影响因素。

结果

最终回收有效问卷1 626份。物质使用患病率为35.85%(583例),问题性网络使用患病率为52.34%(851例),两者共存患病率为20.05%(326例),非故意伤害患病率为16.91%(275例)。调整混杂因素后的多因素logistic回归分析显示,与对照组相比,共存行为组的非故意伤害风险比值(aOR)为1.57(95%CI:1.054~2.340),而单独的物质使用(aOR=1.117,95%CI:0.717~1.741)或问题性网络使用(aOR=1.098,95%CI:0.758~1.589)与非故意伤害均无显著相关性。在共存行为人群中,自杀意念是非故意伤害的独立危险因素(aOR=2.118,95%CI:1.184~3.787)。

结论

同时存在物质使用和问题性网络使用显著增加了大学生非故意伤害风险,应重点关注具有共存行为的高危人群,尤其是伴有自杀意念者,开展针对性预防干预。

物质使用  /  问题性网络使用  /  共存行为  /  非故意伤害  /  大学生
Objective

To explore the relationship between substance use, problematic internet use, and their co-occurring behaviors with unintentional injuries among college students.

Methods

A cross-sectional study design was employed, with a questionnaire survey conducted among 1 700 enrolled students from two ordinary higher education institutions in Beijing. The CRAFFT scale was used to assess substance use, while the Internet Addiction Test (IAT) evaluated problematic internet use. Information on unintentional injuries and related influencing factors was also collected. Multivariate binary logistic regression was utilized to analyze the association between substance use, problematic internet use, co-occurring behaviors, and unintentional injuries, as well as to explore the influencing factors of unintentional injuries in the co-occurring behavior population.

Results

A total of 1 626 valid questionnaires were collected. The prevalence of substance use was 35.85% (583 cases), the prevalence of problematic internet use was 52.34% (851 cases), and the co-occurrence prevalence was 20.05% (326 cases). The prevalence of unintentional injuries was 16.91% (275 cases). After adjusting for confounding factors, the multivariate logistic regression analysis indicated that compared to the control group, the odds ratio for unintentional injuries in the co-occurring behavior group was 1.57 (95%CI: 1.054-2.340), while neither substance use (aOR=1.117, 95%CI: 0.717-1.741) nor problematic internet use (aOR=1.098, 95%CI: 0.758-1.589) showed significant correlation with unintentional injuries. Among the co-occurring behavior population, suicidal ideation was identified as an independent risk factor for unintentional injuries (aOR=2.118, 95%CI: 1.184-3.787).

Conclusion

The simultaneous presence of substance uses and problematic internet use significantly increases the risk of unintentional injuries among college students. It is crucial to focus on high-risk populations exhibiting co-occurring behaviors, especially those with suicidal ideation, and to implement targeted preventive interventions.

Substance use  /  Problematic internet use  /  Co-occurring behaviors  /  Unintentional injuries  /  College students
周小丁, 李如钰, 高琦, 成佩霞, 祝慧萍. 大学生物质使用、问题性网络使用及其共存行为与非故意伤害的关联性研究. 现代预防医学, 2025 , 52 (9) : 1674 -1680 . DOI: 10.20043/j.cnki.MPM.202411165
Xiao-ding ZHOU, Ru-yu LI, Qi GAO, Pei-xia CHENG, Hui-ping ZHU. Study on the relationship between substance use, problematic internet use, and co-occurring behaviors among college students and unintentional injuries[J]. Modern Preventive Medicine, 2025 , 52 (9) : 1674 -1680 . DOI: 10.20043/j.cnki.MPM.202411165
物质使用和问题性网络使用是当代大学生面临的重要健康问题[1-2]。物质使用是指包括酒精、大麻和其他非法药物在内的不良使用行为;问题性网络使用则指过度使用网络对个体心理健康、社会适应、学习和工作产生不良影响的行为,也被称为网络成瘾、病理性网络使用等[3]。已有研究表明,这两种行为不仅在行为学上相互关联,还可能对个体产生叠加效应,从而进一步加剧伤害风险[4]
既往大量研究已证实物质使用和问题性网络使用会显著增加故意伤害的风险,如暴力[5]和非自杀性自伤[6],这可能与个体较差的心理健康状况和压力水平高有关[7-8]。在非故意伤害方面,研究发现使用酒精和其他药物可能导致个体认知和协调能力下降、判断力受损,进而增加交通事故、溺水和跌落的风险[9]。同样,过度使用网络则可能导致睡眠不足、社交隔离和身体活动减少,从而提高非故意伤害风险[10-11]。更值得关注的是,当个体同时存在物质使用和问题性网络使用时,非故意伤害的风险可能会进一步提高[12]
然而,目前国内关于大学生中物质使用和问题性网络使用对非故意伤害影响的研究仍十分匮乏。现有研究多关注物质使用或问题性网络使用与故意伤害的独立关系,较少考虑两种行为的共存关系及其对非故意伤害的联合影响。因此,本研究将物质使用和问题性网络使用作为预测变量,不仅探讨其对非故意伤害的直接影响,还将进一步结合故意伤害行为,心理健康状况、睡眠质量和压力水平等相关因素进行分析,系统探讨物质使用、问题性网络使用及其共存行为对非故意伤害的影响机制,深入分析高危人群的特征及影响因素,为制定针对性的预防干预策略提供实证依据。
本研究采用便利抽样方法,选取北京市两所普通高等学校的在校本科生和研究生作为研究对象。在每所学校中,便利选取1~3个专业,调查该专业下的所有班级,并对被选中的班级全体学生进行电子问卷调查,调查通过问卷星平台完成。调查时间为2023年7月。调查对象纳入标准:(1)年龄在18~25岁之间的在校学生;(2)自愿参与本研究并签署知情同意书;(3)具有独立完成问卷调查的能力。排除标准:(1)休学或停学学生;(2)外籍留学生;(3)因身心疾病无法独立完成问卷的学生。共发放电子问卷1 700份,回收1 629份,排除3份回答存在明显逻辑错误的问卷后,最终纳入1 626份有效问卷,有效回收率为95.6%。本研究获得首都医科大学伦理委员会批准(Z2023SY039)。
自编基本情况调查问卷,内容包括性别、年龄、身体质量指数(body mass index,BMI)、民族等基本人口学资料。
(1)非故意伤害:根据以往伤害相关研究的测量经验[13],采用自评伤害量表,以二分类(是、否)选择题的形式,逐一询问被调查者在过去12个月内各类非故意伤害的发生情况。根据国际疾病分类标准(ICD-10)[14],本研究共纳入了以下10种非故意伤害类型:中毒(ICD-10: X20-X29,X40-X49)、触电(ICD-10:W85-W88)、窒息(ICD-10: W75-W84)、烧伤(ICD-10:X00-X19)、溺水(ICD-10: W65-W74)、摔伤(ICD-10:W00-W19)、动物咬伤(ICD-10: W53-W64)、交通事故(ICD-10: V01-V99)、抨击伤和砸伤(ICD-10: W20-W24)和其他伤害。此外,为确保被调查者准确理解各类非故意伤害的定义,每种伤害类型均配有相应的解释说明,以提高调查的准确性和有效性。
非故意伤害定义为在过去12个月内发生以下任一情况:因非故意伤害就医并被诊断为一项或多项伤害;因非故意伤害导致一天以上停课、休息或活动受限[15]。若发生以上任一类伤害即定义为存在非故意伤害。
(2)故意伤害:本研究评估的故意伤害包括非自杀性自伤、自杀意念和人际暴力三类。其中,非自杀性自伤指个体在未带有自杀意图的情况下,故意损害自身身体组织的行为[16];自杀意念则指个体产生过结束自己生命的念头[17];人际暴力定义为个体遭受的身体、语言或心理上的故意伤害行为,包括但不限于肢体冲突、威胁恐吓和情感虐待[18]。对于以上每一类故意伤害的评估,均通过问卷中的二分类(是、否)问题进行评估。
采用CRAFFT量表评估物质使用(包括酒精、大麻和其他非法药物)情况[19]。根据CRAFFT 2.1评分标准,将物质使用分为低风险、中风险和高风险三组。低风险定义为过去12个月内无物质使用且车辆(CAR)问题回答是“否”;中风险定义为过去12个月无物质使用但CAR问题回答是“是”,或有物质使用但CRAFFT总分为0~1分;高风险定义为有物质使用且CRAFFT总分≥2分。最终将低风险归类为无物质使用组。
采用网络成瘾测验(IAT)中文版评估问题性网络使用情况[20]。IAT包含20个条目,总分20~100分,主要用于评估网络使用对日常生活的影响。条目采用5点李克特量表(1=完全不符合至5=总是如此)。本研究以IAT≥50分作为问题性网络使用的界值。IAT得分20~49分为一般网络用户,50~79分为轻中度问题性网络使用,80~100分为重度问题性网络使用。该量表半分信度为0.86,Cronbach α系数为0.90。
分别采用症状自评量表(SCL-90)[21]、匹兹堡睡眠质量指数(PSQI)[22]、知觉压力量表(PSS-14)[23]评估被调查者的心理健康状况、睡眠质量和压力水平。
应用问卷星导出数据并建立数据库,采用SPSS 22.0软件进行数据分析。首先对研究对象基本情况进行描述性分析,计量资料以($ \bar{x} \pm s$)表示,计数资料以频数(构成比)表示。其次,根据物质使用和问题性网络使用的情况,将研究对象分为对照组(无物质使用和问题性网络使用)、仅物质使用组、仅问题性网络使用组和共存行为组。采用多因素二元logistic回归方法,分析物质使用、问题性网络使用及其共存行为与非故意伤害发生的关系,通过逐步引入协变量,计算调整后的比值比(aOR)及其95%可信区间(95%CI)。最后,对共存行为人群进行logistic回归分析,探讨年龄、BMI、性别、居住地、非自杀性自伤、自杀意念、压力水平和心理得分等因素对非故意伤害发生的影响。双侧检验,检验水准α=0.05。
本研究共纳入研究对象1 626例,平均年龄为(20.33±2.73)岁,平均BMI为(22.24±5.37) kg/m2,其中男性403例(24.78%),女性1 223例(75.22%)。在民族构成上,汉族1 297例(79.77%),少数民族329例(20.23%)。居住地分布方面,城市人口1 057例(65.01%),农村人口569例(34.99%)。各项评分方面,压力水平得分为(32.36±9.66),睡眠质量得分为(5.49±3.68),心理得分为(121.52±43.59)。在不良行为方面,非自杀性自伤91例(5.60%),自杀意念493例(30.32%),人际暴力28例(1.72%)。
在全部1 626例研究对象中,物质使用行为总患病率为35.85%(583例),其中单纯物质使用257例(15.81%),与问题性网络使用共存326例(20.05%)。按严重程度分级:轻中度物质使用524例(占物质使用的89.88%),重度物质使用59例(占物质使用的10.12%)。物质使用与非物质使用组比较,两组在年龄、压力水平、睡眠质量、心理得分、性别、非自杀性自伤、自杀意念和非故意伤害行为的差异均有统计学意义(P<0.05)。见表1
问题性网络使用行为总患病率为52.34%(851例),其中单纯问题性网络使用525例(32.29%),与物质使用共存326例(20.05%)。按严重程度分级:轻中度818例(占问题性网络使用者的96.12%),重度33例(3.88%)。问题性网络使用组与非问题性网络使用组比较,两组在压力水平、睡眠质量、心理得分、非自杀性自伤、自杀意念和非故意伤害行为方面的差异均有统计学意义(P<0.05)。见表1
物质使用和问题性网络使用共存行为的患病率为20.05%(326例)。共存行为与非共存行为组比较,两组在年龄、压力水平、睡眠质量、心理得分、性别、非自杀性自伤、自杀意念和非故意伤害行为方面的差异均有统计学意义(P<0.05)。见表1
在调查人群中,非故意伤害的患病率为16.91%。其中,物质使用组与非物质使用组非故意伤害的患病率分别为20.41%和14.96%,差异具有统计学意义(P=0.006)。问题性网络使用组与非问题性网络使用组非故意伤害的患病率分别为19.39%和14.19%,差异具有统计学意义(P=0.006)。共存行为组与非共存行为组非故意伤害的患病率分别为23.62%和15.23%,差异具有统计学意义(P<0.001)。见表1
多因素二元logistic回归分析结果显示,在未调整混杂因素的模型1中,共存行为组较对照组的非故意伤害风险比值更高,见表2。在调整了年龄、性别后,共存行为组的风险比仍然显著(模型2)。进一步调整压力水平和心理得分后,风险比有所降低但仍具有统计学意义(模型3)。在最终模型(模型4)中调整非自杀性自伤、自杀意念和人际暴力行为后,共存行为组发生非故意伤害的风险仍显著高于对照组(aOR=1.570,95%CI:1.054~2.340)。而单独的物质使用或问题性网络使用与非故意伤害均无显著关联。
对共存行为人群进行logistic回归分析,结果显示自杀意念是非故意伤害的独立危险因素(aOR=2.118,95%CI:1.184~3.787)。其他因素如年龄、BMI、性别、居住地、非自杀性自伤、压力水平和心理得分与非故意伤害的发生均无统计学意义,见表3
物质使用和问题性网络使用是大学生中常见的行为问题,且常常呈现出共同发生的趋势。本研究旨在调查该群体中物质使用和问题性网络使用的流行情况,并深入探讨这两种行为及其共存状态与非故意伤害之间的关联性。研究发现,共存行为会增加非故意伤害的发生风险,而自杀意念则是这一风险的独立危险因素。这提示我们需要重点关注具有共存行为且伴随自杀意念的高危个体。
本研究调查数据显示,物质使用行为的总患病率为35.85%,问题性网络使用行为的总患病率为 52.34%,而两种行为的共存患病率为20.05%。这种高患病率提示我们需要深入探讨导致大学生风险行为的多重影响因素。从人口学特征来看,性别和年龄对物质使用行为具有重要影响。物质使用的大学生通常是男性且年龄较大者,这可能与男性更容易受到同伴压力的影响[24],以及随着年龄增长,社交场合增多,接触和使用物质的机会相应增加有关。在环境因素方面,学业压力和就业不确定性等因素可能是导致大学生承受较高压力水平和较差睡眠质量的重要原因[25],而这些压力因素的存在又可能进一步增加物质使用的风险。与物质使用的诱因相似,问题性网络使用也与压力水平密切相关,但更多体现在个体的心理特征层面。问题性网络使用者往往表现出较差的心理健康水平,更容易出现非自杀性自伤和自杀意念等行为。这通常源于个体情绪调节能力不足,且倾向于将网络作为消极的应对方式,尤其是在学业、社交或情感压力面前[26-27]。值得注意的是,当这些不同层面的风险因素叠加时,个体更容易同时出现两种问题行为。这也解释了为何共存行为组往往承受更大的生活压力和心理困扰,并可能陷入物质使用和问题性网络使用相互促进的恶性循环中[28]
为阐明共存行为与非故意伤害之间的关联,我们探索了其潜在作用机制。既往研究提示这种现象源于物质使用和问题性网络使用之间的协同作用。这两种行为具有共同的神经生物学基础,涉及相似的脑区(如背外侧前额叶和眶额皮质)[29],有物质使用行为的个体问题性网络使用风险更高[30],诸多研究也已证实问题性网络使用是物质使用的重要预测因素[31]。这种协同作用通过多重途径增加非故意伤害风险:一方面,物质使用可能通过生理和药理作用直接损害个体的心理和神经认知发展,进而降低判断力和反应能力[32];另一方面,问题性网络使用可能导致个体注意力分散和疲劳,产生焦虑和抑郁等心理健康问题[33],进一步增加伤害风险。除了生物学机制外,本研究还对共存行为人群进行了危险因素分析,发现自杀意念是非故意伤害的独立危险因素。自杀意念与个体的心理脆弱性和风险行为密切相关[34],高水平的自杀意念往往伴随着更多的冲动性行为和风险决策[35]。此外,伴有自杀意念的个体普遍存在情绪调节障碍,这种持续的负性情绪状态可能影响其对危险情境的判断和应对,从而增加意外伤害的发生风险[36]。这些发现为理解共存行为人群较高的非故意伤害风险提供了重要线索。
基于本研究发现,建议从以下几个方面开展预防干预:首先,针对共存行为与非故意伤害的显著相关性,应建立常态化的早期筛查机制[37],定期评估学生的物质使用和网络使用情况,通过早期识别和干预可有效降低高危人群的伤害风险[38]。其次,鉴于本研究证实自杀意念是重要的危险因素,高校应系统开展情绪管理、压力应对技能培训等心理健康项目,同时构建多部门协作的预防体系,将心理咨询与学业辅导相结合。相关研究表明,这类综合干预措施能有效增强学生的心理韧性,提升适应水平,降低抑郁症状和问题行为的发生率[39]。通过上述干预策略的实施,有望降低共存行为人群非故意伤害的风险。
本研究仍存在一些局限性:首先,横断面研究设计难以确定变量间的因果关系;其次,自我报告的数据可能存在报告偏倚;最后,由于纳入的调查对象主要来源于北京市两所普通高等学校,代表性相对较差,需谨慎进行外推。建议未来研究采用多中心、前瞻性设计,收集更细化的伤害数据,以进一步阐明共存行为与非故意伤害的关系机制。
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doi: 10.20043/j.cnki.MPM.202411165
  • 接收时间:2024-11-11
  • 首发时间:2026-03-17
  • 出版时间:2025-05-10
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    1.首都医科大学公共卫生学院流行病与卫生统计学系,北京 100069
    2.首都医科大学公共卫生学院儿少卫生与妇幼保健学系,北京 100069

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