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Article(id=1241102826298995090, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102813938380911, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202402248, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1708963200000, receivedDateStr=2024-02-27, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773831572364, onlineDateStr=2026-03-18, pubDate=1724515200000, pubDateStr=2024-08-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773831572364, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773831572364, creator=13701087609, updateTime=1773831572364, updator=13701087609, issue=Issue{id=1241102813938380911, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='16', pageStart='2881', pageEnd='3072', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773831569418, creator=13701087609, updateTime=1773831807198, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241103811318706322, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102813938380911, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241103811318706323, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241102813938380911, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3010, endPage=3015, ext={EN=ArticleExt(id=1241102827775390132, articleId=1241102826298995090, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Development trajectory and related factors of suicide ideation in college students, columnId=1228016572451718132, journalTitle=Modern Preventive Medicine, columnName=Health and Social Behavior, runingTitle=null, highlight=null, articleAbstract=
Objective

Background Suicide has become a major public health issue of global concern. Suicidal ideation represents the initial psychological and one of the strongest predictorsactivities associated with suicidal behavior. Suicidal ideation is a dynamic state factor rather than a static trait factor, so it is necessary to study the development trajectory of suicidal ideation and its related factors.Objective To investigate the development trajectory and relatedfactors of suicide ideation college students.

Methods

From 2019 to 2021,1438 college students in a university in Guangdong Province were selected for three longitudinal tracking each October by using the method of convenient sampling. The Self-rating ideas of suicide scale (SIOSS) was used to measure the level of suicide ideation. Data analysis was mainly based on the Latent Growth Mixed Model(LGMM) to analyze the development trajectory of students’ suicide ideation. Multivariate Logistic Regression model was established to analyze the related factors to the variation of each potential category of suicidal ideation.

Results

From 2019 to 2021, the total scores of college students’ suicidal ideation were 3.79±2.87, 3.71±2.90 and 3.32±2.87, showing a decreasing trend over time. The development tendencies of college students’suicide ideation have been classified into 3 categories: C1 group(worsening suicidal ideation group)(11.8%)，C2 group(persistent low suicidal ideation group)(79.6%), and C3 group (relieving suicidal ideation group) (8.6%). Compared with C1 group, college students who had an average (OR=2.52, 95% CI:1.31-4.86) or happy childhood (OR=3.95,95% CI:2.02-7.74), no history of suicide attempt (OR=9.03，95% CI:3.49-23.36), and were extroverted (OR=1.03, 95% CI:1.01-1.05) were more likely to enter C2 group. Students who were from cities (OR=0.54, 95% CI:0.31-0.93),got high neuroticism scores (OR=0.86, 95% CI:0.84-0.88) were less likely to enter the C2 group. College students with happy childhood life(OR=3.29, 95% CI:1.40-7.74)were more likely to enter the C3 group, but students from cities(OR=0.37, 95% CI:0.18-0.78)were less likely to enter the C3 group.

Conclusion

The development tendencies of college students’ suicide ideation can be classified into three categories: worsening suicidal ideation group,persistent low suicidal ideation group, and relieving suicidal ideation group. The developmental trajectory of suicidal ideation is related to birthplace, childhood life, suicide history, and personality traits.

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目的

考察大学生自杀意念的动态发展轨迹及其相关因素。

方法

在2019—2021年间，采用方便取样的方法，每年10月对广东省某高校1438名学生进行3次纵向追踪。采用自杀意念自评量表(SIOSS) 测量自杀意念水平，使用潜变量混合增长模型（LGMM）分析大学生自杀意念发展轨迹，建立多元logistic回归模型，分析自杀意念各潜在类别变化的相关因素。

结果

2019—2021年间，大学生自杀意念总分分别为3.79±2.87、3.71±2.90、3.32±2.87,随时间呈现一定的下降趋势；大学生自杀意念的发展轨迹可划分为3个类别：C1自杀意念加重组（11.8%）、C2持续低自杀意念组（79.6%）、C3自杀意念缓解组（8.6%）；相对于C1组，童年生活一般（OR=2.52，95% CI：1.31~4.86）或童年生活幸福（OR=3.95，95% CI：2.02~7.74）、无自杀未遂史（OR=9.03，95% CI：3.49~23.36）、外向（OR=1.03，95% CI：1.01~1.05）的大学生更容易进入C2组，而生源地为城市（OR=0.54，95% CI：0.31~0.93）、神经质得分高（OR=0.86，95% CI：0.84~0.88）的大学生更不容易进入C2组；童年生活幸福（OR=3.29，95% CI：1.40~7.74）的大学生更容易进入C3组，而生源地为城市（OR=0.37，95% CI：0.18~0.78）的大学生更不容易进入C3组。

结论

大学生自杀意念的发展轨迹可划分为3个类别：自杀意念加重组、持续低自杀意念组、自杀意念缓解组，自杀意念的发展轨迹与生源地、童年生活、自杀史、人格特质等因素相关。

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鲁丹凤，Email:
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王苑芮（1986—），女，博士在读，讲师，研究方向：临床心理学

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Medicine and Society, 2019, 32(7): 103-106, 114., articleTitle=Study on relationship among psychological stress, positive psychological capital and suicidal ideas of college students inGanzhou city, refAbstract=null), Reference(id=1241102842568700044, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, doi=null, pmid=null, pmcid=null, year=2020, volume=41, issue=2, pageStart=254, pageEnd=257, url=null, language=null, rfNumber=[24], rfOrder=43, authorNames=庄文婷, 李彦鑫, 姜涛, journalName=中国学校卫生, refType=null, unstructuredReference=庄文婷，李彦鑫，姜涛，等．大学生童年期负性生活事件人格特征与自杀意念关系[J]．中国学校卫生，2020，41（2）：254-257., articleTitle=大学生童年期负性生活事件人格特征与自杀意念关系, refAbstract=null), Reference(id=1241102842644197519, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, doi=null, pmid=null, pmcid=null, year=2020, volume=41, issue=2, pageStart=254, pageEnd=257, url=null, language=null, rfNumber=[24], rfOrder=44, authorNames=Zhuang WT, Li YX, Jiang T, journalName=Chinese Journal of School Health, refType=null, unstructuredReference=Zhuang WT, Li YX, Jiang T, et al. Mediating role of personality in the relationship between adverse childhoodlife events and suicide ideation among college students[J]. Chinese Journal of School Health, 2020, 41(2): 254-257., articleTitle=Mediating role of personality in the relationship between adverse childhoodlife events and suicide ideation among college students, refAbstract=null)], funds=[Fund(id=1241102836545680298, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, awardId=2018WQNCX175, language=CN, fundingSource=2018年度广东省普通高校青年创新人才类项目(2018WQNCX175), fundOrder=null, country=null), Fund(id=1241102836625372081, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, awardId=2021WQNCX076, language=CN, fundingSource=2021年度广东省普通高校青年创新人才类项目(2021WQNCX076), fundOrder=null, country=null), Fund(id=1241102836721841078, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, awardId=HZSK2024GJ008, language=CN, fundingSource=2024年惠州市哲学社会科学规划项目(HZSK2024GJ008), fundOrder=null, country=null), Fund(id=1241102836818310079, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, awardId=05-K0223011, language=CN, fundingSource=广州城市理工学院2023年度校级科研项目(05-K0223011), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241102828916240901, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, xref=1., ext=[AuthorCompanyExt(id=1241102828920435206, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, companyId=1241102828916240901, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Huizhou University, Huizhou, Guangdong 516007, China), AuthorCompanyExt(id=1241102828928823815, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, companyId=1241102828916240901, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.惠州学院，广东 惠州 516007)]), AuthorCompany(id=1241102829054652946, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, xref=2., ext=[AuthorCompanyExt(id=1241102829067235858, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, companyId=1241102829054652946, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.广州大学)]), AuthorCompany(id=1241102829155316252, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, xref=3., ext=[AuthorCompanyExt(id=1241102829159510557, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, companyId=1241102829155316252, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.广州中医药大学)]), AuthorCompany(id=1241102829235008036, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, xref=4., ext=[AuthorCompanyExt(id=1241102829243396646, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, companyId=1241102829235008036, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.广州城市理工学院)])], figs=[ArticleFig(id=1241102833592890185, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=EN, label=Fig.1, caption=Trend chart of suicidal ideation scores in different categories, figureFileSmall=C3ULCi69yVTjIc0FSceK+A==, figureFileBig=apvGI3/viouWMMiocRFuRA==, tableContent=null), ArticleFig(id=1241102833680970574, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=CN, label=图1, caption=各类别自杀意念得分变化趋势图, figureFileSmall=C3ULCi69yVTjIc0FSceK+A==, figureFileBig=apvGI3/viouWMMiocRFuRA==, tableContent=null), ArticleFig(id=1241102833911657307, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=EN, label=Table 1, caption=

The general demographic characteristics of the subjects were investigated

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分组人数构成比（%）
性别男35624.8
女1 08275.2
是否独生独生子女19813.8
非独生子女1 24086.2
生源地农村76353.1
城镇36625.4
城市30921.5
家庭经济情况贫困25017.4
一般1 00870.1
良好18012.5
是否单亲家庭单亲家庭1238.6
非单亲家庭1 31591.4
父母关系良好98768.6
一般38526.8
较差664.6
童年生活幸福87761.0
一般46232.1
不幸996.9
自杀未遂史有402.8
无1 39897.2
), ArticleFig(id=1241102834024903525, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=CN, label=表1, caption=

调查对象一般人口学特征

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分组人数构成比（%）
性别男35624.8
女1 08275.2
是否独生独生子女19813.8
非独生子女1 24086.2
生源地农村76353.1
城镇36625.4
城市30921.5
家庭经济情况贫困25017.4
一般1 00870.1
良好18012.5
是否单亲家庭单亲家庭1238.6
非单亲家庭1 31591.4
父母关系良好98768.6
一般38526.8
较差664.6
童年生活幸福87761.0
一般46232.1
不幸996.9
自杀未遂史有402.8
无1 39897.2
), ArticleFig(id=1241102834121372521, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=EN, label=Table 2, caption=

The mean, standarddeviation and correlation matrix of the variable（n=1 438)

, figureFileSmall=null, figureFileBig=null, tableContent=
变量T1SIOSS总分T2SIOSS总分T3SIOSS总分
T1SIOSS总分1.003.79±2.87
T2SIOSS总分0.63a1.003.71±2.90
T3SIOSS总分0.58a0.66a1.003.32±2.87
), ArticleFig(id=1241102834230424432, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=CN, label=表2, caption=

变量的均值、标准差及相关矩阵(n=1 438)

, figureFileSmall=null, figureFileBig=null, tableContent=
变量T1SIOSS总分T2SIOSS总分T3SIOSS总分
T1SIOSS总分1.003.79±2.87
T2SIOSS总分0.63a1.003.71±2.90
T3SIOSS总分0.58a0.66a1.003.32±2.87
), ArticleFig(id=1241102834322699128, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=EN, label=Table 3, caption=

Fitting information of Latent Growth Mixed Model (LGMM)

, figureFileSmall=null, figureFileBig=null, tableContent=
类别KLog(L)AICBICaBICEntropyLMRBLRT
1C8-9 859.8419 735.6819 777.8519 752.43---
2C11-9 699.5719 421.1319 479.1119 444.170.86<0.001<0.001
3C14-9 632.4119 292.8219 366.6219 322.140.84<0.001<0.001
4C17-9 594.6919 223.3819 312.9819 258.980.830.579<0.001
5C20-9 563.0319 166.0619 271.4819 207.940.820.081<0.001
), ArticleFig(id=1241102834465305471, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=CN, label=表3, caption=

潜变量混合增长模型（LGMM）模型拟合信息

, figureFileSmall=null, figureFileBig=null, tableContent=
类别KLog(L)AICBICaBICEntropyLMRBLRT
1C8-9 859.8419 735.6819 777.8519 752.43---
2C11-9 699.5719 421.1319 479.1119 444.170.86<0.001<0.001
3C14-9 632.4119 292.8219 366.6219 322.140.84<0.001<0.001
4C17-9 594.6919 223.3819 312.9819 258.980.830.579<0.001
5C20-9 563.0319 166.0619 271.4819 207.940.820.081<0.001
), ArticleFig(id=1241102834607911813, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=EN, label=Table 4, caption=

Average probability (column) of belonging of subjects in three potential categories (row)

, figureFileSmall=null, figureFileBig=null, tableContent=
类别C1(%)C2(%)C3(%)
C188.306.305.40
C21.6095.602.80
C36.6013.9079.50
), ArticleFig(id=1241102834712769418, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=CN, label=表4, caption=

3个潜在类别被试（行）的平均归属概率（列）

, figureFileSmall=null, figureFileBig=null, tableContent=
类别C1(%)C2(%)C3(%)
C188.306.305.40
C21.6095.602.80
C36.6013.9079.50
), ArticleFig(id=1241102834851181460, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=EN, label=Table 5, caption=

Multiple logistic regression analysis results（n=1 438)

, figureFileSmall=null, figureFileBig=null, tableContent=
变量参照组C2组C3组
βS.E.WaldOR(95%CI)PβS.E.WaldOR(95%CI)P
性别男女0.330.241.931.39（0.87~2.23）0.165-0.280.310.810.7（0.41~1.39）0.367
独生子女否是-0.240.330.550.78（0.41~1.49）0.457-0.450.421.170.64（0.28~1.45）0.280
生源地城市农村-0.620.284.860.54（0.31~0.93）0.027-0.990.386.690.37(0.18~0.78)0.008
城镇-0.260.251.110.77（0.48~1.25)0.291-0.500.312.620.61(0.34~1.11)0.106
家庭经济贫困良好-0.220.400.290.81（0.37~1.78）0.591-0.480.500.940.62(0.23~1.63)0.332
一般0.060.370.031.06（0.55~2.06）0.854-0.260.410.410.77(0.34~1.72)0.522
单亲家庭否是-0.440.371.450.64（0.32~1.32）0.229-0.620.422.250.54（0.24~1.21）0.133
父母关系良好一般0.410.450.821.50（0.62~3.65）0.366-0.200.540.140.82(0.28~2.34)0.704
较差-0.360.440.660.70（0.30~1.65）0.415-0.550.521.150.58(0.21~1.58)0.284
童年生活幸福不幸1.370.3416.013.95（2.02~7.74）<0.0011.200.447.433.29（1.40~7.74）0.006
一般0.930.347.642.52（1.31~4.86）0.0060.760.433.182.13(0.92~4.91)0.075
自杀未遂史无有2.200.4920.599.03（3.49~23.36）<0.0010.660.511.641.93(0.71~5.27)0.201
内外向（E）0.030.018.801.03（1.01~1.05）0.003-0.000.010.071.00（0.97~1.02）0.791
神经质（N）-0.150.01137.490.86（0.84~0.88）<0.0010.030.022.591.03（0.99~1.06）0.107
精神质（P）0.010.020.221.01（0.98~1.04）0.6370.020.020.941.02（0.98~1.06）0.333
), ArticleFig(id=1241102836377908123, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241102826298995090, language=CN, label=表5, caption=

多元logistic回归分析结果（n=1 438)

, figureFileSmall=null, figureFileBig=null, tableContent=
变量参照组C2组C3组
βS.E.WaldOR(95%CI)PβS.E.WaldOR(95%CI)P
性别男女0.330.241.931.39（0.87~2.23）0.165-0.280.310.810.7（0.41~1.39）0.367
独生子女否是-0.240.330.550.78（0.41~1.49）0.457-0.450.421.170.64（0.28~1.45）0.280
生源地城市农村-0.620.284.860.54（0.31~0.93）0.027-0.990.386.690.37(0.18~0.78)0.008
城镇-0.260.251.110.77（0.48~1.25)0.291-0.500.312.620.61(0.34~1.11)0.106
家庭经济贫困良好-0.220.400.290.81（0.37~1.78）0.591-0.480.500.940.62(0.23~1.63)0.332
一般0.060.370.031.06（0.55~2.06）0.854-0.260.410.410.77(0.34~1.72)0.522
单亲家庭否是-0.440.371.450.64（0.32~1.32）0.229-0.620.422.250.54（0.24~1.21）0.133
父母关系良好一般0.410.450.821.50（0.62~3.65）0.366-0.200.540.140.82(0.28~2.34)0.704
较差-0.360.440.660.70（0.30~1.65）0.415-0.550.521.150.58(0.21~1.58)0.284
童年生活幸福不幸1.370.3416.013.95（2.02~7.74）<0.0011.200.447.433.29（1.40~7.74）0.006
一般0.930.347.642.52（1.31~4.86）0.0060.760.433.182.13(0.92~4.91)0.075
自杀未遂史无有2.200.4920.599.03（3.49~23.36）<0.0010.660.511.641.93(0.71~5.27)0.201
内外向（E）0.030.018.801.03（1.01~1.05）0.003-0.000.010.071.00（0.97~1.02）0.791
神经质（N）-0.150.01137.490.86（0.84~0.88）<0.0010.030.022.591.03（0.99~1.06）0.107
精神质（P）0.010.020.221.01（0.98~1.04）0.6370.020.020.941.02（0.98~1.06）0.333
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大学生自杀意念的发展轨迹及相关因素
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王苑芮 1, 2 , 鲁丹凤 3, 4 , 黄时华 3 , 陈超男 1 , 蓝韶清 3
现代预防医学 | 健康与社会行为 2024,51(16): 3010-3015
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现代预防医学 | 健康与社会行为 2024, 51(16): 3010-3015
大学生自杀意念的发展轨迹及相关因素
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王苑芮1, 2, 鲁丹凤3, 4 , 黄时华3, 陈超男1, 蓝韶清3
作者信息
  • 1.惠州学院，广东 惠州 516007
  • 2.广州大学
  • 3.广州中医药大学
  • 4.广州城市理工学院

    • 王苑芮（1986—），女，博士在读，讲师，研究方向：临床心理学

通讯作者:

鲁丹凤，Email:
Development trajectory and related factors of suicide ideation in college students
Yuan-rui WANG1, 2, Dan-feng LU3, 4 , Shi-hua HUANG3, Chao-nan CHEN1, Shao-qing LAN3
Affiliations
  • Huizhou University, Huizhou, Guangdong 516007, China
出版时间: 2024-08-25 doi: 10.20043/j.cnki.MPM.202402248
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摘要
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目的

考察大学生自杀意念的动态发展轨迹及其相关因素。

方法

在2019—2021年间，采用方便取样的方法，每年10月对广东省某高校1438名学生进行3次纵向追踪。采用自杀意念自评量表(SIOSS) 测量自杀意念水平，使用潜变量混合增长模型（LGMM）分析大学生自杀意念发展轨迹，建立多元logistic回归模型，分析自杀意念各潜在类别变化的相关因素。

结果

2019—2021年间，大学生自杀意念总分分别为3.79±2.87、3.71±2.90、3.32±2.87,随时间呈现一定的下降趋势；大学生自杀意念的发展轨迹可划分为3个类别：C1自杀意念加重组（11.8%）、C2持续低自杀意念组（79.6%）、C3自杀意念缓解组（8.6%）；相对于C1组，童年生活一般（OR=2.52，95% CI：1.31~4.86）或童年生活幸福（OR=3.95，95% CI：2.02~7.74）、无自杀未遂史（OR=9.03，95% CI：3.49~23.36）、外向（OR=1.03，95% CI：1.01~1.05）的大学生更容易进入C2组，而生源地为城市（OR=0.54，95% CI：0.31~0.93）、神经质得分高（OR=0.86，95% CI：0.84~0.88）的大学生更不容易进入C2组；童年生活幸福（OR=3.29，95% CI：1.40~7.74）的大学生更容易进入C3组，而生源地为城市（OR=0.37，95% CI：0.18~0.78）的大学生更不容易进入C3组。

结论

大学生自杀意念的发展轨迹可划分为3个类别：自杀意念加重组、持续低自杀意念组、自杀意念缓解组，自杀意念的发展轨迹与生源地、童年生活、自杀史、人格特质等因素相关。

大学生  /  自杀意念  /  发展轨迹  /  相关因素  /  潜变量混合增长模型
Objective

Background Suicide has become a major public health issue of global concern. Suicidal ideation represents the initial psychological and one of the strongest predictorsactivities associated with suicidal behavior. Suicidal ideation is a dynamic state factor rather than a static trait factor, so it is necessary to study the development trajectory of suicidal ideation and its related factors.Objective To investigate the development trajectory and relatedfactors of suicide ideation college students.

Methods

From 2019 to 2021,1438 college students in a university in Guangdong Province were selected for three longitudinal tracking each October by using the method of convenient sampling. The Self-rating ideas of suicide scale (SIOSS) was used to measure the level of suicide ideation. Data analysis was mainly based on the Latent Growth Mixed Model(LGMM) to analyze the development trajectory of students’ suicide ideation. Multivariate Logistic Regression model was established to analyze the related factors to the variation of each potential category of suicidal ideation.

Results

From 2019 to 2021, the total scores of college students’ suicidal ideation were 3.79±2.87, 3.71±2.90 and 3.32±2.87, showing a decreasing trend over time. The development tendencies of college students’suicide ideation have been classified into 3 categories: C1 group(worsening suicidal ideation group)(11.8%)，C2 group(persistent low suicidal ideation group)(79.6%), and C3 group (relieving suicidal ideation group) (8.6%). Compared with C1 group, college students who had an average (OR=2.52, 95% CI:1.31-4.86) or happy childhood (OR=3.95,95% CI:2.02-7.74), no history of suicide attempt (OR=9.03，95% CI:3.49-23.36), and were extroverted (OR=1.03, 95% CI:1.01-1.05) were more likely to enter C2 group. Students who were from cities (OR=0.54, 95% CI:0.31-0.93),got high neuroticism scores (OR=0.86, 95% CI:0.84-0.88) were less likely to enter the C2 group. College students with happy childhood life(OR=3.29, 95% CI:1.40-7.74)were more likely to enter the C3 group, but students from cities(OR=0.37, 95% CI:0.18-0.78)were less likely to enter the C3 group.

Conclusion

The development tendencies of college students’ suicide ideation can be classified into three categories: worsening suicidal ideation group,persistent low suicidal ideation group, and relieving suicidal ideation group. The developmental trajectory of suicidal ideation is related to birthplace, childhood life, suicide history, and personality traits.

College students  /  Suicidal ideation  /  Development trajectory  /  Related factors  /  Latent growth mixture model
王苑芮, 鲁丹凤, 黄时华, 陈超男, 蓝韶清. 大学生自杀意念的发展轨迹及相关因素. 现代预防医学, 2024 , 51 (16) : 3010 -3015 . DOI: 10.20043/j.cnki.MPM.202402248
Yuan-rui WANG, Dan-feng LU, Shi-hua HUANG, Chao-nan CHEN, Shao-qing LAN. Development trajectory and related factors of suicide ideation in college students[J]. Modern Preventive Medicine, 2024 , 51 (16) : 3010 -3015 . DOI: 10.20043/j.cnki.MPM.202402248
正文
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自杀已成为全球关注的重大公共卫生问题，据世界卫生组织统计，自杀分别是15-29岁女性和男性的第三和第四大死因[1]。近年来，大学生自杀的发生率呈上升趋势[2]。自杀意念是指从事自杀相关行为的想法[3]。近年来，大学生的自杀意念检出率为13.77%[4]，女生自杀意念报告率高于男生[5]。自杀意念是自杀行为的前提和必经阶段，是预测自杀行为的敏感因素[6]。因此，有必要研究自杀意念的影响机制。
以往关于大学生自杀意念的研究，主要涉及流行病学的调查以及影响因素分析[7-8]，且大多以横向研究为主，但横向研究不能确定自杀意念的动态发展趋势，研究发现，自杀意念是动态变化的状态因素而非静态不变的特质因素[9]，因此有必要从发展的角度来研究自杀意念，但以往的研究把大学生作为同质的整体来探讨自杀意念的发展轨迹，较少涉及大学生自杀意念发展轨迹的个体差异性。为探讨自杀意念在大学生群体的内部异质性和发展轨迹，本研究运用潜变量混合增长模型以个体为中心的视角，考察大学生自杀意念的发展轨迹，探讨性别、独生子女、生源地、家庭经济情况、单亲家庭、父母关系、童年生活、自杀未遂史和人格特质等因素对自杀意念各潜在类别的影响。
1　对象与方法
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1.1　对象
采用方便取样的方法，以广东省某本科院校2019级秋季入学的大一新生为研究对象，于2019—2021年每年10月进行一次在线问卷测查，一共进行连续3次的追踪测查，排除因参军入伍、辍学、休学、退学等原因不在校学生、有精神疾病和因其他原因不能完成问卷的学生。调查前告知被试保密协定，在取得被试知情同意后发放问卷链接，要求按照问卷指导语如实填写。问卷包括“自杀意念自评量表(SIOSS) ”、“艾森克人格问卷(EPQ)（成人版）”和“一般情况调查问卷”。
为严控问卷质量，根据题目数量设置及问卷填写预实验时间估算，首次测查答题时间低于420 s，或第二、第三次测查时任一次答题时间低于70s，均视为无效问卷；同时，在题目中设置陷阱题，未通过陷阱题测试，视为无效问卷。第一次有1 688人参与调查，第二次有1 655人参与调查，第三次有1 603人参与测查，3次施测结束后，剔除无效样本，最终获得有效样本1 438份。本研究已得到惠州学院伦理委员会的批准（编号：2023IAC006）
1.2　工具
1.2.1　自杀意念自评量表(Self-rating Idea of Suicide Scale，SIOSS)
采用夏朝云等编制的自杀意念自评量表(SIOSS)[10],共26道题，包括绝望因子、乐观因子、睡眠因子、掩饰因子等四个因子。本研究中，3次测量该量表的Cronbach α系数分别为0.76、0.77、0.78。
1.2.2　艾森克人格问卷(Eysenck Personality Questionnaire，EPQ)（成人版）
采用陈仲庚教授修订的的艾森克人格问卷（成人版）[11]，共85道题，包括内外向（E）、神经质（N）、精神质（P）、掩饰性（L）四个因子。本研究中，该问卷Cronbach α系数为0.85。
1.2.3　一般情况调查问卷
自行编制一般情况调查问卷，内容包括性别、是否独生子女、生源地、家庭经济情况、是否来自单亲家庭、父母关系、童年生活是否幸福、以往是否有自杀经历等。
1.3　统计方法
使用 SPSS 23.0和Mplus 8.0进行数据分析，分为三步进行。第一步，使用 SPSS 23.0对变量进行描述统计并计算相关系数；第二步，使用Mplus 8.0对潜变量增长混合模型(LGMM) 的拟合度进行评估，分析大学生自杀意念的变化轨迹是否存在异质性的潜类别差异。第三步，在第二步对大学生自杀意念变化轨迹进行潜在分类后，以潜在类别的分类结果作为因变量，以性别、独生子女、生源地、家庭经济情况、单亲家庭、父母关系、童年生活、自杀未遂史和人格特质等作为协变量，建立多元logistic回归模型,考察大学生自杀意念潜在类别转变的相关因素。检验水准α=0.05
2　结果
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2.1　研究对象的基本信息
本研究中研究对象共1 438人，男生356人(24.8%)、女生1 082人(75.2%),在2019年10月测查（T1）时，有效样本的平均年龄为(18.8±0.81)岁。是否独生、生源地、家庭经济情况、是否单亲家庭、父母关系、童年生活情况和自杀未遂史等结果见表1。
2.2　描述性统计结果
各测量时间点SIOSS的均值、标准差及相关系数矩阵如表2所示,三个测试时间点SIOSS得分两两之间均呈显著正相关（P<0.001）；T1、T2时间点SIOSS均值变化较小，T3时间点均值下降较明显；表明大学生自杀意念随时间呈现一定的下降趋势。
2.3　潜变量混合增长模型（LGMM）分析结果
2.3.1　潜变量混合增长模型（LGMM）的拟合信息
研究分别选取 1-5 种潜在类别的潜变量混合增长模型（LGMM）进行模型拟合度分析，具体结果见表3。依据模型信息拟合指数AIC、BIC、aBIC数值越小，Entropy越高（取值在0.8以上，说明分类精确性高于90%），LMR和BLRT两个指标P值达到显著水平，模型拟合越好的原理[12-15]，本研究2个类别和3个类别模型的LMR和BLRT两个指标P值均达到显著水平，且Entropy均在0.8以上，说明保留2个类别和3个类别的模型精确性均较高，而3个类别模型的AIC、BIC、aBIC低于2个类别，综合考虑模型的实际意义，最终选择3个类别（C1、C2、C3）的分类模型。
由表4可知，3个潜在类别被试的平均归属概率分别为88.3%、95.6%和79.5%，说明3个潜在类别分类模型的结果是可信的。
2.3.2　大学生自杀意念在各潜在类别的发展轨迹
通过综合分析LGMM模型拟合度指标，大学生自杀意念变化轨迹的3个类别模型为最优模型。下面进一步考察每个潜在类别的变化特征，并对不同类别进行命名。C1组SIOSS平均初始得分为7.25，斜率为0.83，P<0.001，表明该组学生自杀意念呈上升趋势，增长速率为0.83；C2组SIOSS平均初始得分为2.75，斜率为-0.17，P<0.001，表明该组学生自杀意念呈下降趋势，下降速率为0.17；C3组SIOSS平均初始得分为8.25，斜率为-2.22，P<0.001，表明该组学生自杀意念呈下降趋势，下降速率为2.22，3个类别间在初始水平及变化斜率上均有较大差异。
综合3个类别的初始水平和变化速率可以对其进行命名，C1组自杀意念初始水平较高，自杀意念随时间显著增加；C2组自杀意念初始水平较低，自杀意念随时间显著减低；C3组自杀意念初始水平较高，自杀意念随时间显著降低；因此，把3个潜在类别命名为：C1组为“自杀意念加重组”，共169人，占比为11.8%；C2为“持续低自杀意念组”，共1145人，占比为79.6%；C3为“自杀意念缓解组”，共124人，占比为8.6%。各类别的变化趋势见图1。
2.3.3　大学生自杀意念发展轨迹的影响因素分析
从表5可知，相对于C1（自杀意念加重）组，童年生活一般（OR=2.52）或童年生活幸福（OR=3.95）、无自杀未遂史（OR=9.03）、外向（OR=1.03）的大学生更容易进入C2（持续低自杀意念）组，而生源地为城市（OR=0.543）、神经质得分高（OR=0.86）的大学生更不容易进入C2组；童年生活幸福（OR=3.29）的大学生更容易进入C3（自杀意念缓解）组，而生源地为城市（OR=0.37）的大学生更不容易进入C3组。性别、独生子女、家庭经济情况、单亲家庭、父母关系和精神质得分对潜在类别的转变无显著影响（P>0.05)。
3　讨论
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本研究对大学生自杀意念进行为其3年的追踪调查，运用潜变量混合增长模型以个体为中心的视角对大学生自杀意念的变化轨迹进行分析，同时，以性别、独生子女、生源地、家庭经济情况、单亲家庭、父母关系、童年生活、自杀未遂史和人格特质作为协变量，探讨上述因素对自杀意念潜在类别发展轨迹的影响。由此，我们分别就大学生自杀意念发展轨迹的群体异质性及其相关因素进行讨论和分析。
本研究结果显示大学生自杀意念的发展轨迹存在显著的群体异质性，根据初始水平和发展趋势的不同，分为持续低自杀意念组、自杀意念加重组和自杀意念缓解组三个不同亚群，与以往潜剖面分析发现大学生自杀意念存在两个不同潜在类别的结果不一致[8]，可能是因为以往潜剖面分析为横向研究，本研究为追踪研究，研究的视角不同导致潜在类别的差异。持续低自杀意念组表现出较低的起始水平，随时间呈下降趋势，占比为79.6%，说明大部分大学生的自杀意念始终保持在低水平，几乎没有出现悲观绝望，结束生命的念头。自杀意念加重组表现出较高的起始水平和显著的增长速度，占比为11.8%，说明该组大学生自杀意念水平较高，且随时间呈现上升趋势。自杀意念缓解组表现出较高的起始水平和显著的下降趋势，占比8.6%，说明该组大学生在刚开始时自杀意念水平较高，但自杀意念随时间显著降低。自杀意念虽不会直接转化成自杀行为，但自杀意念是大学生自杀行为的最重要风险因素[16]，因此，高校应加强对大学生的筛查，寻找其产生自杀意念、加重或缓解自杀意念的相关因素，开展必要的心理干预，帮助其改善心理状态，消除自杀意念。
本研究发现，相比较自杀意念加重组，农村比城市大学生更容易进入持续低自杀意念组和自杀意念缓解组，即城市大学生更容易进入自杀意念加重组，与张金健等研究发现大城市学生是自杀意念的高发群体结果一致[17]，这可能是因为城市大学生生活条件优越，经历挫折较少，抗挫折能力相对较弱，也有研究者认为城市竞争激烈，父母对其期待和要求较高，因而更易感受到来自各方面的压力[17]。本研究发现没有童年不幸或痛苦经历、无自杀未遂史的大学生更容易进入持续低自杀意念组，而有童年不幸或痛苦经历、有自杀未遂史的大学生更容易进入自杀意念加重组，说明童年创伤史和自杀史是大学生自杀意念的高危因素，提示高校心理健康教育者新生入学筛查时，应及时筛查出该类学生，予以重点跟踪和关注，开展生命教育，引导学生热爱生命、珍惜生命。此外，与自杀意念加重组相比，童年生活幸福的学生更容易进入自杀意念缓解组，说明童年生活经历对自杀意念的缓解有重要的影响。
人格特征可以作为大学生自杀意念类别转变的预测因子，在持续低自杀意念组和自杀意念加重组中比较发现，神经质得分高的个体更易进入自杀意念加重组，而性格外向的个体易进入持续低自杀意念组，这可能是因为神经质得分高的个体情绪稳定性较差，遇事容易紧张，情绪波动性较大，对负性信息存在认知偏差，如认为自杀可以逃离无法忍受的情绪或者状态，继而激活自杀意念[18-19]。而外向的人喜欢与别人交流，人格功能更稳定，因而不易产生自杀意念[20]。本研究发现性别、独生子女对潜在类别的转变无显著影响，这与前人相关研究结论相一致[7]，但单亲家庭、父母关系、家庭经济情况、精神质对自杀意念潜在类别的转变无显著影响与国内横向研究结论并不一致，如孙玮等人发现单亲家庭大学生自杀意念的发生率更高[21]；尹丹丹等发现父母关系会影响大学生自杀意念发生率[22]；赵玉发现家庭贫困生的自杀意念高于家庭经济一般的学生[23]；庄文婷等人的研究发现精神质能显著影响大学生自杀意念，精神质得分越高，自杀意念越强烈[24]，造成结果差异的原因可能是以往研究大多是横向研究，本研究是纵向研究，研究自杀意念的视角和潜在分类结果与以往不一致。
本研究运用潜变量混合增长模型以个体为中心的视角对大学生自杀意念的变化轨迹进行分析，发现大学生自杀意念发展轨迹具有显著的群体异质性和个体差异性，并考察了大学生自杀意念潜在类别转变的相关因素。但仍存在以下不足：（1）本研究样本选自广东某本科院校，虽然样本量足够，但代表性有限，接下来将扩大数据的收集范围；（2）本研究追踪时间为三年，未完成对学生大学四年时间自杀意念变化轨迹的追踪，未来可延长追踪时长来验证本研究的结论；（3）本研究只选取了部分影响大学生自杀意念潜在类别转变的因素，未来可考察其他因素的作用，以更全面的了解自杀意念的形成与发展机制。
基金
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  • 2018年度广东省普通高校青年创新人才类项目(2018WQNCX175)
  • 2021年度广东省普通高校青年创新人才类项目(2021WQNCX076)
  • 2024年惠州市哲学社会科学规划项目(HZSK2024GJ008)
  • 广州城市理工学院2023年度校级科研项目(05-K0223011)
文献
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2024年第51卷第16期
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文章信息
doi: 10.20043/j.cnki.MPM.202402248
  • 接收时间：2024-02-27
  • 首发时间：2026-03-18
  • 出版时间：2024-08-25
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出版历史
  • 收稿日期：2024-02-27
基金
2018年度广东省普通高校青年创新人才类项目(2018WQNCX175)
2021年度广东省普通高校青年创新人才类项目(2021WQNCX076)
2024年惠州市哲学社会科学规划项目(HZSK2024GJ008)
广州城市理工学院2023年度校级科研项目(05-K0223011)
作者信息
    1.惠州学院，广东 惠州 516007
    2.广州大学
    3.广州中医药大学
    4.广州城市理工学院

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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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