Abstract：
BACKGROUND: Peer influence on risky behavior is particularly potent in adolescence and varies by gender. Smoking prevention programs focused on peer-group leaders have shown great promise, and a social influence model has proven effective in understanding adult smoking networks but has not been applied to adolescent vaping until 2023. This work aims to apply a social influence model to analyze vaping by gender in a high school network.
METHODS: A high school\'s student body was emailed an online survey asking for gender, age, grade level, vape status, and the names of three friends. Custom Java and MATLAB scripts were written to create a directed graph, compute centrality measures, and perform Fisher\'s exact tests to compare centrality measures by demographic variables and vape status.
RESULTS: Of 192 students in the school, 102 students responded. Students who vape were in closer-knit friend groups than students who do not vape (p < .05). Compared to males who vape, females who vape had more social ties to other students who vape, exhibiting greater homophily (p < .01). Compared to females who do not vape, females who vape were in closer-knit friend groups (p < .05) and had more ties to other students who vape (p < .01).
CONCLUSIONS: Differences in vaping by social connectedness and gender necessitate school and state policies incorporating the social aspect of vaping in public health initiatives. Large-scale research should determine if trends can be generalized across student bodies, and more granular studies should investigate differences in motivations and social influence by demographic variables to individualize cessation strategies.
METHODS: A high school\'s student body was emailed an online survey asking for gender, age, grade level, vape status, and the names of three friends. Custom Java and MATLAB scripts were written to create a directed graph, compute centrality measures, and perform Fisher\'s exact tests to compare centrality measures by demographic variables and vape status.
RESULTS: Of 192 students in the school, 102 students responded. Students who vape were in closer-knit friend groups than students who do not vape (p < .05). Compared to males who vape, females who vape had more social ties to other students who vape, exhibiting greater homophily (p < .01). Compared to females who do not vape, females who vape were in closer-knit friend groups (p < .05) and had more ties to other students who vape (p < .01).
CONCLUSIONS: Differences in vaping by social connectedness and gender necessitate school and state policies incorporating the social aspect of vaping in public health initiatives. Large-scale research should determine if trends can be generalized across student bodies, and more granular studies should investigate differences in motivations and social influence by demographic variables to individualize cessation strategies.
摘要：
背景：同伴对危险行为的影响在青春期尤其有效，并且因性别而异。针对同行团体领导人的吸烟预防计划显示出了巨大的希望，社会影响模型已被证明在理解成人吸烟网络方面是有效的，但直到2023年才被应用于青少年吸烟。这项工作旨在应用社会影响模型来分析高中网络中按性别划分的电子烟。
方法：一所高中的学生团体通过电子邮件发送了一份在线调查，询问性别，年龄,等级,vape状态,还有三个朋友的名字.编写自定义Java和MATLAB脚本来创建有向图，计算中心性度量，并执行Fisher的精确测试，以比较人口统计变量和vape状态的中心性度量。
结果：在学校的192名学生中，102名学生回答。与不使用电子烟的学生相比，使用电子烟的学生在更紧密的朋友组中（p<.05）。与vape的男性相比，vape的女性与其他vape的学生有更多的社会关系，表现出更大的同质性(p<0.01)。与不使用vape的女性相比，vape的女性在更紧密的朋友群体中（p<.05），并且与其他vape的学生有更多的联系（p<.01）。
结论：由于社会联系和性别而产生的电子烟差异，需要学校和州制定政策，将电子烟的社会方面纳入公共卫生举措。大规模的研究应该确定趋势是否可以在学生群体中推广，更细粒度的研究应该通过人口统计学变量来调查动机和社会影响的差异，以个性化戒烟策略。
方法：一所高中的学生团体通过电子邮件发送了一份在线调查，询问性别，年龄,等级,vape状态,还有三个朋友的名字.编写自定义Java和MATLAB脚本来创建有向图，计算中心性度量，并执行Fisher的精确测试，以比较人口统计变量和vape状态的中心性度量。
结果：在学校的192名学生中，102名学生回答。与不使用电子烟的学生相比，使用电子烟的学生在更紧密的朋友组中（p<.05）。与vape的男性相比，vape的女性与其他vape的学生有更多的社会关系，表现出更大的同质性(p<0.01)。与不使用vape的女性相比，vape的女性在更紧密的朋友群体中（p<.05），并且与其他vape的学生有更多的联系（p<.01）。
结论：由于社会联系和性别而产生的电子烟差异，需要学校和州制定政策，将电子烟的社会方面纳入公共卫生举措。大规模的研究应该确定趋势是否可以在学生群体中推广，更细粒度的研究应该通过人口统计学变量来调查动机和社会影响的差异，以个性化戒烟策略。
