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大学男性基于技术的性胁迫的前瞻性预测因素

Prospective Predictors of Technology-Based Sexual Coercion by College Males.

作者信息

Thompson Martie P, Morrison Deidra J

机构信息

Department of Public Health Sciences, Clemson University;

出版信息

Psychol Violence. 2013 Jul 1;3(3):233-246. doi: 10.1037/a0030904.

Abstract

OBJECTIVE

Technology-based coercive behavior (TBC) represents an emerging public health problem. This study contributes to the literature by identifying prospective individual-, social-, and community-level predictors of TBC.

METHOD

Data were collected from 800 males who participated in a prospective study on attitudes and behaviors regarding relationships with women. Variables across multiple ecological layers were used to predict TBC.

RESULTS

Bivariate analyses indicated that 16 of the 17 risk variables significantly predicted TBC including anger, impulsivity, sexual compulsivity, hostility towards women, rape supportive beliefs, high-risk drinking, childhood sexual abuse, interparental conflict, peer pressure to engage in sex, peer approval of forced sex, number of sexual partners, perceived negative sanctions for sexual aggression, exposure to pornography, and participation in varsity sports, student government, and religious groups. Multivariate regression analyses indicated five variables uniquely accounted for TBC behaviors, including rape supportive beliefs, peer approval of forced sex, number of sexual partners, exposure to pornography, and participation in student government.

CONCLUSIONS

Our findings that TBC can be prospectively predicted by these risk factors suggest that computer-based technology interventions focusing on these factors through social network ads that promote reflection on healthy social and romantic relationship behaviors and attitudes could help prevent and reduce TBC.

摘要

目的

基于技术的强制行为(TBC)是一个新出现的公共卫生问题。本研究通过确定TBC在个体、社会和社区层面的潜在预测因素,为相关文献做出了贡献。

方法

数据收集自800名参与一项关于与女性关系的态度和行为前瞻性研究的男性。使用多个生态层面的变量来预测TBC。

结果

双变量分析表明,17个风险变量中的16个显著预测了TBC,包括愤怒、冲动、性强迫、对女性的敌意、支持强奸的信念、高危饮酒、童年性虐待、父母间冲突、同伴的性压力、同伴对强迫性行为的认可、性伴侣数量、对性侵犯的感知负面制裁、接触色情制品,以及参与大学体育运动、学生会和宗教团体。多变量回归分析表明,五个变量独特地解释了TBC行为,包括支持强奸的信念、同伴对强迫性行为的认可、性伴侣数量、接触色情制品,以及参与学生会。

结论

我们的研究结果表明,这些风险因素可以前瞻性地预测TBC,这意味着通过社交网络广告,针对这些因素进行基于计算机的技术干预,促进对健康的社会和浪漫关系行为及态度的反思,可能有助于预防和减少TBC。

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