Building community resilience to prevent and mitigate community impact of gun violence: conceptual framework and intervention design.
Building community resilience to prevent and mitigate community impact of gun violence: conceptual framework and intervention design.
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DOI：
10.1136/bmjopen-2020-040277
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发表时间：
2020-10-10
期刊：
影响因子：
2.9
通讯作者：
Roy B
中科院分区：
文献类型：
--
作者：
Wang EA;Riley C;Wood G;Greene A;Horton N;Williams M;Violano P;Brase RM;Brinkley-Rubinstein L;Papachristos AV;Roy B
美国是所有发达民主国家中社区枪支暴力发生率最高的国家。迫切需要制定可行、可扩展和社区主导的干预措施，以减轻枪支暴力事件及其相关的健康影响。我们的社区学术研究团队获得了美国国立卫生研究院的资助，以设计一项社区主导的干预措施，以减轻生活在枪支暴力高发社区对健康的影响。我们采用了“增强抗灾能力”这一自然灾害防备概念框架，以指导多个部门和更广泛的社区采取行动，应对枪支暴力这一人为灾难。使用这个框架，我们将确定现有的社区资产，作为未来社区主导干预措施的基石。为了确定现有的社区资产，我们将对社区中的枪支暴力事件进行社交网络和空间分析，并利用这些分析来识别成功避免枪支暴力的人和社区街区。我们将对网络中避免暴力的个人样本 (n=45) 以及在非受害地点的街区生活或工作的人 (n=45) 进行定性访谈，以识别现有资产。最后，我们将使用基于社区的系统动力学建模过程来创建社区级枪支暴力影响的贡献者和缓解者的计算机模拟，其中包含基于当地人口的数据进行校准。我们将与多利益相关方团体合作，并利用定性访谈和计算机模拟的主题来确定可行的社区主导干预措施。耶鲁大学医学院人类研究委员会 (#2000022360) 批准了研究。我们将通过同行评审的出版物以及学术和社区演示来传播研究结果。定性访谈指南、系统动力学模型和小组模型构建脚本将广泛共享。
The USA has the highest rate of community gun violence of any developed democracy. There is an urgent need to develop feasible, scalable and community-led interventions that mitigate incident gun violence and its associated health impacts. Our community-academic research team received National Institutes of Health funding to design a community-led intervention that mitigates the health impacts of living in communities with high rates of gun violence. We adapted ‘Building Resilience to Disasters’, a conceptual framework for natural disaster preparedness, to guide actions of multiple sectors and the broader community to respond to the man-made disaster of gun violence. Using this framework, we will identify existing community assets to be building blocks of future community-led interventions. To identify existing community assets, we will conduct social network and spatial analyses of the gun violence episodes in our community and use these analyses to identify people and neighbourhood blocks that have been successful in avoiding gun violence. We will conduct qualitative interviews among a sample of individuals in the network that have avoided violence (n=45) and those living or working on blocks that have not been a location of victimisation (n=45) to identify existing assets. Lastly, we will use community-based system dynamics modelling processes to create a computer simulation of the community-level contributors and mitigators of the effects of gun violence that incorporates local population-based based data for calibration. We will engage a multistakeholder group and use themes from the qualitative interviews and the computer simulation to identify feasible community-led interventions. The Human Investigation Committee at Yale University School of Medicine (#2000022360) granted study approval. We will disseminate study findings through peer-reviewed publications and academic and community presentations. The qualitative interview guides, system dynamics model and group model building scripts will be shared broadly.
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影响因子：
4.2
作者：
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影响因子：
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