OBJECTIVE: To described the prevalence of school physical violence behaviors and to explore its associated factors among middle school students in Beijing. METHODS: In 2009, a randomly selected cross-sectional survey was conducted among 5718 students in grades 7 to 12 in Beijing. A self-report anonymous questionnaire involving physical violence at school and socio-demographic variables, such as sex, grades, family economic status and family structure, peer relationships, and communication with their parents etc. were completed by students themselves. Logistic regression was used to estimate the association between physical violence and socio-demographic variables. RESULTS: Among the students, 14.3% reported that they had had physical violence behavior in school during the past 12 months. Male students had been more likely to have physical violence behaviors than female students (Male 25.2%, Female 5.1%). For both male and female students, poor school cohesion were the risk factors of physical violence behaviors (Male OR = 1.060, Female OR = 1.065). For male students, factors as father's lower education level (OR = 1.653), remarried/single-parent families (OR = 1.834), low-grade (grade 7 OR = 5.291; grade 11 OR = 1.526), poor school performance (OR = 1.470) etc were the risk factors of physical violence behaviors; while better-off family economic status (OR = 0.546), good peer relationships (OR = 0.618), and easy to communicate with the father (OR = 0.756) were the protective factors of physical violence behaviors. For female students, easy to communicate with her mother (OR = 0.358) were the protective factors of physical violence behaviors. CONCLUSION: For male and female students, the prevalence of school physical violence and its related factors were different. Actions on prevention against physical violence behaviors should be fully considered, including factors as gender, personal characteristics, family, school and peers etc.
OBJECTIVE: To described the prevalence of school physical violence behaviors and to explore its associated factors among middle school students in Beijing. METHODS: In 2009, a randomly selected cross-sectional survey was conducted among 5718 students in grades 7 to 12 in Beijing. A self-report anonymous questionnaire involving physical violence at school and socio-demographic variables, such as sex, grades, family economic status and family structure, peer relationships, and communication with their parents etc. were completed by students themselves. Logistic regression was used to estimate the association between physical violence and socio-demographic variables. RESULTS: Among the students, 14.3% reported that they had had physical violence behavior in school during the past 12 months. Male students had been more likely to have physical violence behaviors than female students (Male 25.2%, Female 5.1%). For both male and female students, poor school cohesion were the risk factors of physical violence behaviors (Male OR = 1.060, Female OR = 1.065). For male students, factors as father's lower education level (OR = 1.653), remarried/single-parent families (OR = 1.834), low-grade (grade 7 OR = 5.291; grade 11 OR = 1.526), poor school performance (OR = 1.470) etc were the risk factors of physical violence behaviors; while better-off family economic status (OR = 0.546), good peer relationships (OR = 0.618), and easy to communicate with the father (OR = 0.756) were the protective factors of physical violence behaviors. For female students, easy to communicate with her mother (OR = 0.358) were the protective factors of physical violence behaviors. CONCLUSION: For male and female students, the prevalence of school physical violence and its related factors were different. Actions on prevention against physical violence behaviors should be fully considered, including factors as gender, personal characteristics, family, school and peers etc.
Authors: Huan Wang; Jingjing Tang; Sarah-Eve Dill; Jiusi Xiao; Matthew Boswell; Claire Cousineau; Scott Rozelle Journal: Int J Environ Res Public Health Date: 2022-01-11 Impact factor: 3.390