潮汕地区农村留守中学生多重伤害预测模型构建

罗燕东; 昌萍; 周家俊; 曹子成; 李丽萍

doi:10.16835/j.cnki.1000-9817.2024126

潮汕地区农村留守中学生多重伤害预测模型构建

doi: 10.16835/j.cnki.1000-9817.2024126

罗燕东^{1, 2},
昌萍^{1, 2},
周家俊^{1, 2},
曹子成¹,
李丽萍^1, ,

1.
汕头大学公共卫生学院，广东 515063
2.
汕头大学医学院伤害预防研究中心

基金项目:

广东省哲学社会科学规划一般项目 GD19CSH08

详细信息

作者简介:
罗燕东(1997-)，女，广西贵港人，硕士，主要研究方向为儿童伤害

通讯作者:
李丽萍，E-mail：lpli@stu.edu.cn

利益冲突声明 所有作者声明无利益冲突。
中图分类号: R179 B845.67 B844.1 B845.6
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- 被引次数: 0
出版历程
- 收稿日期: 2023-11-03
- 修回日期: 2024-02-28
- 网络出版日期: 2024-04-25
- 刊出日期: 2024-04-25

Establishment of a risk prediction model for poly-victimization among rural left-behind children

LUO Yandong^{1, 2},
CHANG Ping^{1, 2},
ZHOU Jiajun^{1, 2},
CAO Zicheng¹,
LI Liping^{1
, ,}

1.
School of Public Health, Shantou University, Shantou (515063), Guangdong Province, China

摘要

摘要: 目的构建潮汕地区农村留守中学生多重伤害(PV)的风险预测模型，并评估模型的预测效果，为早期识别并预防学生PV的发生提供数据依据。方法于2020年1月—2021年9月，采用分层随机整群抽样方法在汕头市和揭阳市农村地区选取7所中学1 005名留守学生进行问卷调查。调查内容包括个人、家庭、外部环境因素和心理因素(心理韧性、应对方式、自尊、领悟社会支持)及PV情况。运用R软件、采用Logistic回归筛选预测变量构建风险预测模型，使用ROC曲线下面积(AUC)、准确率、精确度、召回率、F1值和校准曲线对模型进行效果评价。结果留守中学生PV报告率为23.38%。Logistic回归分析结果显示，身体患病或残疾(β=1.02)、最近一年留级(β=1.31)、无亲密伙伴(β=1.00)、自伤意图(很少：β=0.58，偶尔：β=0.79)、同伴不良行为(β=0.90)、家庭成员吸烟(β=0.59)、父母/看护人违法犯罪史(β=1.04)、旁观过校园欺凌(β=0.78)、搬家(β=0.58)、采用发泄(β=0.34)和忍耐(β=0.28)的应对方式与潮汕地区留守中学生发生PV均呈正相关，心理韧性中的家庭支持(β=-0.31)与PV呈负相关(P值均<0.05)。对纳入多因素分析有意义的变量构建列线图预测模型，预测模型AUC为0.88，准确度为82.00%，精确度为77.78%，F1值为43.75%，校准图拟合良好，模型具有较好的区分度和校准度。结论构建的留守中学生PV的风险预测模型预测效能较好，有利于学校和社区早期识别发生PV的留守中学生。
- 暴力 /
- 回归分析 /
- 儿童 /
- 农村人口
Abstract: Objective To construct a risk prediction model for poly-victimization (PV) among rural left-behind middle and high school students in Chaoshan, and to evaluate the prediction effect of the model, so as to provide scientific basis for early identification and prevention of PV among students. Methods A questionnaire survey was conducted among 1 005 left-behind students, selected from 7 middle and high schools in rural areas of Shantou City and Jieyang City by a stratified random cluster sampling method from January 2020 to September 2021, for the personal, family, external environmental factors, psychological factors (mental resilience, coping approaches, self-esteem and social support) and PV situations. R software and Logistic regression were used to screen predictor variables to build a risk prediction model, and the area under the ROC curve (area under the curve, AUC), accuracy, precision, recall, F1 value and calibration curve were used to evaluate the model's effect. Results The incidence rate of PV among left-behind middle and high school students was 23.38%. The results of Logistic regression analysis showed that physical illness or disability (β=1.02), grade retention during the past year (β=1.31), having no close partner (β=1.00), self-harm intention (seldom: β=0.58, occasionally: β=0.79), negative peer behavior (β=0.90), family member smoking (β=0.59), criminal offenses of parents (β=1.04), witnessing school bullying (β=0.78), house moving (β=0.58), using venting (β=0.34) and the coping style of patience (β=0.28) were positively correlated with PV among left-behind children in Chaoshan area, and family support in psychological flexibility (β=-0.31) was negatively correlated with PV (P<0.05). A nomogram prediction model was constructed for the meaningful variables included in the multivariate analysis, and the prediction model AUC was 0.88, the accuracy was 82.00%, the precision was 77.78%, and the F1 value was 43.75%. The calibration plot fitted well, and the model had good discrimination and calibration. Conclusion The risk prediction model for left-behind middle and high school students with PV has good predictive performance and is helpful for schools and communities to early identify high-risk middle and high school students with PV.
- Violence /
- Regression analysis /
- Child /
- Rural population
注释:

1) 利益冲突声明 所有作者声明无利益冲突。

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图 1 潮汕地区留守中学生PV的预测模型

Figure 1. Prediction model of PV left-behind middle and high school students in Chaoshan Area

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表 1 不同组别留守中学生PV报告率比较

Table 1. Comparison of the reporting rate of PV among left-behind middle and high school students in different groups

组别	选项	人数	PV人数	χ²值	P值	组别	选项	人数	PV人数	χ²值	P值
性别	女	521	101(19.39)	9.65	< 0.01	父母婚姻状况	在婚/再婚	890	198(22.25)	5.60	0.02
	男	484	134(27.69)				离异/丧偶	115	37(32.17)
身体状况	健康	954	209(21.91)	22.84	< 0.01	父母身体状况	健康	954	212(22.22)	14.14	< 0.01
	患病/残疾	51	26(50.98)				患病/残疾	51	23(45.10)
是否吸烟	否	956	214(22.38)	10.90	< 0.01	主要看护人身体状况	健康	864	192(22.22)	4.63	0.03
	是	49	21(42.86)				患病	141	43(30.50)
是否饮酒	否	895	189(21.12)	23.43	< 0.01	主要看护人职业	白领	80	28(35.00)	8.75	0.01
	是	110	46(41.82)				蓝领	664	140(21.08)
接触色情书籍视频频率	从来没有	896	182(20.31)	45.68	< 0.01		无业待业家务	261	67(25.67)
	很少	76	34(44.74)			家庭成员吸烟	否	170	27(15.88)	6.43	0.01
	偶尔	22	13(59.09)				是	835	208(24.91)
	经常	11	6(54.55)			家庭成员酗酒	否	914	195(21.33)	23.64	< 0.01
最近一年是否留级	否	978	223(22.80)	6.87	< 0.01		是	91	40(43.96)
	是	27	12(44.44)			父母/看护人违法犯罪史	无	962	213(22.14)	19.35	< 0.01
亲密伙伴	有	864	181(20.95)	20.37	< 0.01		有	43	22(51.16)
	无	141	54(38.30)			旁观过校园欺凌	无	690	115(16.67)	55.43	< 0.01
自伤意图	从来没有	791	142(17.95)	65.78	< 0.01		有	315	120(38.10)
	很少	140	55(39.29)			搬家	否	812	171(21.06)	12.75	< 0.01
	偶尔	57	28(49.12)				是	193	64(33.16)
	经常	17	10(58.82)			周围环境治安水平	安全	523	96(18.36)	15.39	< 0.01
同伴不良行为	无	812	142(17.49)	82.03	< 0.01		不安全	482	139(28.84)
	有	193	93(48.19)
注： ()内数字为报告率/%。

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表 2 PV组与非PV组留守中学生社会支持与应对方式得分比较(x±s)

Table 2. Comparison of scores of coping approaches and social support among left-behind middle and high school students between PV and non-PV groups(x±s)

组别	人数	社会支持				应对方式
组别	人数	家庭支持	朋友支持	其他支持	总分	问题解决	求助	退避	发泄	幻想	忍耐
非PV	770	4.66±1.27	4.65±1.30	4.75±1.31	4.69±1.20	2.80±0.81	2.48±0.80	2.60±0.73	2.17±0.74	1.93±0.89	2.72±0.92
PV	235	4.30±1.54	4.41±1.63	4.51±1.50	4.41±1.39	2.89±0.88	2.53±0.92	2.81±0.83	2.45±0.86	2.28±1.02	3.11±0.94
t值		3.28	2.11	2.19	2.80	-1.37	-0.68	-3.83	-4.59	-4.73	-5.64
P值		< 0.01	0.04	0.03	0.01	0.17	0.50	< 0.01	< 0.01	< 0.01	< 0.01

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表 3 PV组与非PV组留守中学生自尊与心理韧性得分比较(x±s)

Table 3. Comparison of scores of self-esteem and mental resilience among left-behind middle and high school students between PV and non-PV groups(x±s)

组别	人数	自尊	心理韧性
组别	人数	自尊	情绪控制	家庭支持	人际协助	目标专注	积极认知	总分
非PV	770	2.63±0.36	3.10±0.69	3.33±0.66	3.10±0.67	3.27±0.76	3.35±0.81	3.22±0.44
PV	235	2.50±0.47	2.80±0.81	3.06±0.70	2.78±0.85	3.19±0.80	3.39±0.86	3.01±0.49
t值		3.74	5.17	5.47	5.19	1.45	-0.56	6.12
P值		< 0.01	< 0.01	< 0.01	< 0.01	0.15	0.78	< 0.01

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表 4 潮汕地区留守中学生发生PV的多因素Logistic回归分析(n=1 005)

Table 4. Multi-factor Logistic regression analysis of PV among left-behind middle and high school students in Chaoshan Area(n=1 005)

自变量与常量	选项	β值	标准误	P值	OR值(95%CI)
身体状况	患病/残疾	1.02	0.35	< 0.01	2.76(1.39~5.50)
接触色情书籍视频频率	很少	0.70	0.29	0.02	2.01(1.14~3.53)
	偶尔	1.10	0.50	0.03	3.01(1.13~8.02)
	经常	0.84	0.82	0.30	2.32(0.47~11.55)
最近一年是否留级	是	1.31	0.46	0.01	3.71(1.50~9.18)
亲密伙伴	无	1.00	0.23	< 0.01	2.72(1.74~4.25)
自伤意图	很少	0.58	0.23	0.01	1.78(1.13~2.80)
	偶尔	0.79	0.34	0.02	2.20(1.12~4.32)
	经常	0.90	0.56	0.10	2.47(0.83~7.32)
同伴不良行为	有	0.90	0.20	< 0.01	2.45(1.66~3.63)
家庭成员吸烟	是	0.59	0.26	0.02	1.80(1.09~2.97)
父母/看护人违法犯罪史	有	1.04	0.38	0.01	2.82(1.35~5.88)
旁观过校园欺凌	有	0.78	0.18	< 0.01	2.17(1.51~3.11)
搬家	是	0.58	0.20	< 0.01	1.79(1.20~2.67)
应对方式	忍耐	0.28	0.10	0.01	1.32(1.09~1.61)
	发泄	0.34	0.12	< 0.01	1.41(1.12~1.77)
心理韧性	家庭支持	-0.31	0.13	0.02	0.73(0.57~0.95)
常量		-3.53	0.62	< 0.01	0.03
注：自变量中身体状况以健康，接触色情书籍视频频率以从来没有，最近一年留级以否，亲密伙伴以有，自伤意图以从来没有，同伴不良行为以无，家庭成员吸烟以否，父母/看护人违法犯罪史以无，旁观过校园欺凌以无，搬家以否为参照，应对方式和心理韧性各维度为连续型变量。

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