江苏省中学生遭受校园欺凌的影响因素分析及列线图预测模型构建

杨文漪; 王艳; 张锡彦; 项耀; 王欣; 杨婕

doi:10.16835/j.cnki.1000-9817.2023.12.007

江苏省中学生遭受校园欺凌的影响因素分析及列线图预测模型构建

doi: 10.16835/j.cnki.1000-9817.2023.12.007

江苏省疾病预防控制中心儿童青少年健康促进所，南京 210009

基金项目:

江苏省重点研发计划(社会发展)专项基金项目 BE2021617

详细信息

作者简介:
杨文漪(1989-)，女，江苏南京人，硕士，主管医师，主要研究方向为儿童青少年心理健康

通讯作者:
杨婕, E-mail: 51478536@qq.com

利益冲突声明 所有作者声明无利益冲突。
中图分类号: G444 C913.5 G478
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- 被引次数: 0
出版历程
- 收稿日期: 2023-07-13
- 修回日期: 2023-09-11
- 网络出版日期: 2023-12-26
- 刊出日期: 2023-12-25

Analysis of factors influencing campus bullying among junior and senior school students and construction of a nomogram model from Jiangsu Province

Institute of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing (210009), Jiangsu Province, China

摘要

摘要: 目的探讨中学生遭受校园欺凌的影响因素并建立风险预测的列线图模型，为防控中学生遭受校园欺凌提供理论依据。方法于2021年9—11月，采用分层整群随机抽样方法在江苏省13个设区市范围内抽取22 034名中学生，使用学生健康行为调查表对其进行问卷调查。采用χ²检验和多因素Logistic回归分析得出遭受校园欺凌的影响因素，绘制列线图预测模型。结果有540名中学生遭受校园欺凌，遭受校园欺凌报告率为2.45%。处于非常态家庭(OR=1.30, 95%CI=1.02~1.65)、超重肥胖(OR=1.35, 95%CI=1.09~1.67)、过去30 d内被家长打骂(OR=2.27, 95%CI=1.82~2.84)、过去30 d内吸烟(OR=1.54, 95%CI=1.11~2.15)、网络成瘾(OR=2.03，95%CI=1.34~3.08)、抑郁症状(OR=5.24，95%CI=4.16~6.61)均与中学生遭受校园欺凌呈正相关，女生(OR=0.58, 95%CI=0.46~0.72)、高中生(OR=0.68，95%CI=0.54~0.83)、有时吃早餐(OR=0.37，95%CI=0.22~0.62)、每天吃早餐(OR=0.28，95%CI=0.17~0.49)与中学生遭受校园欺凌均呈负相关(P值均 < 0.05)。基于以上影响因素建立的列线图，曲线下面积为0.792(95%CI=0.769~0.815)，校准曲线显示预测值与实测值基本一致。结论处在非常态家庭、超重肥胖、男生、初中生、被家长打骂、吸烟、网络成瘾、有抑郁症状的中学生容易遭受校园欺凌。研究构建的列线图可为有效预测中学生遭受校园欺凌的风险并采取积极主动的干预措施提供依据。
- 暴力 /
- 回归分析 /
- 列线图 /
- 精神卫生 /
- 学生
Abstract: Objective To explore the influencing factors of exposure to campus bullying among junior and senior school students, and to establish a column-line diagram model for risk prediction, while providing a theoretical basis for campus bullying prevention and control in secondary schools. Methods A total of 22 034 junior and senior school students were selected via direct sampling technique from September to November 2021 in 13 cities in Jiangsu Province, China, and questionnaires were administered using the Student Health Behavior Questionnaire. The Chi-squared test and multifactor Logistic regression analysis were used to derive the influencing factors of exposure to campus bullying, and a column-line graph prediction model was drawn. Results A total of 540 students reported that they had experienced campus bullying, with a prevalence rate of 2.45%. Being in a non-conventional family (OR=1.30, 95%CI=1.02-1.65), overweight/obesity (OR=1.35, 95%CI=1.09-1.67), scolding by parents in the past 30 days (OR=2.27, 95%CI=1.82-2.84), cigarette smoking in the past 30 days (OR=1.54, 95%CI=1.11-2.15), Internet addiction (OR=2.03, 95%CI=1.34-3.08), and depressive symptoms(OR=5.24, 95%CI=4.16-6.61), all of which were positively correlated with exposure to campus bullying among junior and senior school students (P < 0.05). Furthermore, the following factors were negatively associated with junior and senior school students' protection from campus bullying in female students (OR=0.58, 95%CI=0.46-0.72), senior school students (OR=0.68, 95%CI=0.54-0.83), eating breakfast sometimes (OR=0.37, 95%CI=0.22-0.62), and eating breakfast everyday (OR=0.28, 95%CI=0.17-0.49) (P < 0.05). The column line graph established based on the above influencing factors had an area under the curve of 0.792 (95%CI=0.769-0.815), and the calibration curve showed that the predicted value was basically the same as the measured value. Conclusions Non-conventional families, overweight/obesity, male students, junior school students, scolding by parents, cigarette smoking, Internet addiction, and depressive symptoms are correlated with school bullying among middle school students. The predictive model constructed in the study can provide an effective basis to predict the risk of school bullying and facilitate the implementation of proactive interventions for junior and senior school students.
- Violence /
- Regression analysis /
- Nomograms /
- Mental health /
- Students
注释:

1) 利益冲突声明 所有作者声明无利益冲突。

HTML全文

图 1 中学生遭受校园欺凌风险列线图预测模型

Figure 1. A nomogram prediction model for middle school students' risk of school bullying

下载: 全尺寸图片幻灯片

图 2 列线图模型预测中学生遭受校园欺凌风险的校准曲线

Figure 2. Calibration curves for the nomogram model predicting secondary school students' risk of school bullying

下载: 全尺寸图片幻灯片

表 1 江苏省中学生遭受校园欺凌的单因素分析

Table 1. Univariate analysis of school bullying among middle school students from Jiangsu Province

因素	选项	人数	遭受校园欺凌人数	χ²值	P值
性别	男	8 075	247(3.06)	23.40	＜0.01
	女	7 365	136(1.85)
城乡	城市	9 798	219(2.24)	6.68	0.01
	郊县	5 642	164(2.91)
学段	初中	7 236	214(2.96)	12.80	＜0.01
	高中	8 204	169(2.06)
家庭类型	常态	12 595	284(2.25)	14.40	＜0.01
	非常态	2 845	99(3.48)
住校	是	5 249	131(2.50)	0.01	0.93
	否	10 191	252(2.47)
早餐情况	每天吃	12 356	280(2.27)	58.53	＜0.01
	有时吃	2 902	83(2.86)
	从不吃	182	20(10.99)
超重肥胖	否	9 997	214(2.14)	13.54	＜0.01
	是	5 443	169(3.10)
每周中高强度	0~2	7 294	185(2.54)	1.58	0.45
运动天数/d	3~4	4 127	92(2.23)
	5~7	4 019	106(2.64)
每周体育课节	0~1	1 430	39(2.73)	1.98	0.37
数/节	2~3	12 674	318(2.51)
	≥4	1 336	26(1.95)
过去30 d被家长	否	12 639	211(1.67)	189.49	＜0.01
打骂	是	2 801	172(6.14)
过去30 d内吸烟	否	14 673	334(2.28)	50.95	＜0.01
	是	767	49(6.39)
网络成瘾	否	15 130	352(2.33)	79.94	＜0.01
	是	310	31(10.00)
抑郁症状	否	11 417	125(1.09)	347.82	＜0.01
	是	4 023	258(6.41)
注： ()内数字为检出率/%。

下载: 导出CSV

表 2 江苏省中学生遭受校园欺凌多因素Logistic回归分析(n=15 440)

Table 2. Results of multi-factor Logistic regression analysis of school bullying among middle school students from Jiangsu Province (n=15 440)

自变量	选项	β值	标准误	Wald χ²值	P值	OR值(95%CI)
性别	男					1.00
	女	-0.55	0.11	23.49	＜0.01	0.58(0.46~0.72)
学段	初中					1.00
	高中	-0.40	0.11	13.18	0.01	0.68(0.54~0.83)
家庭类型	常态					1.00
	非常态	0.26	0.12	4.54	0.03	1.30(1.02~1.65)
早餐情况	从不吃					1.00
	有时吃	-1.00	0.25	14.43	＜0.01	0.37(0.22~0.62)
	每天吃	-1.26	0.28	20.39	＜0.01	0.28(0.17~0.49)
超重肥胖	否					1.00
	是	0.30	0.11	7.58	＜0.01	1.35(1.09~1.67)
过去30 d被家长打骂	否					1.00
	是	0.82	0.11	52.70	＜0.01	2.27(1.82~2.84)
过去30 d内吸烟	否					1.00
	是	0.43	0.17	6.55	0.01	1.54(1.11~2.15)
网络成瘾	否					1.00
	是	0.71	0.21	11.29	＜0.01	2.03(1.34~3.08)
抑郁症状	否					1.00
	是	1.66	0.12	195.79	＜0.01	5.24(4.16~6.61)

下载: 导出CSV

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