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本文引用的文献

1
Purchaser Licensing, Point-of-Sale Background Check Laws, and Firearm Homicide and Suicide in 4 US States, 1985-2017.购买者许可、销售点背景调查法与 1985-2017 年美国 4 个州的枪支凶杀和自杀
Am J Public Health. 2020 Oct;110(10):1546-1552. doi: 10.2105/AJPH.2020.305822. Epub 2020 Aug 20.
2
Prevalence and number of children living in institutional care: global, regional, and country estimates.儿童机构照料的流行率和人数:全球、区域和国家估计数。
Lancet Child Adolesc Health. 2020 May;4(5):370-377. doi: 10.1016/S2352-4642(20)30022-5. Epub 2020 Mar 6.
3
Synthetic control methodology as a tool for evaluating population-level health interventions.合成控制法作为一种评估人群健康干预措施的工具。
J Epidemiol Community Health. 2018 Aug;72(8):673-678. doi: 10.1136/jech-2017-210106. Epub 2018 Apr 13.
4
Compared with what? Estimating the effects of injury prevention policies using the synthetic control method.与什么相比?使用合成控制法估计伤害预防政策的效果。
Inj Prev. 2018 Jun;24(Suppl 1):i60-i66. doi: 10.1136/injuryprev-2017-042360. Epub 2017 Nov 10.
5
Comprehensive background check policy and firearm background checks in three US states.全面背景调查政策与美国三个州的枪支背景调查
Inj Prev. 2018 Dec;24(6):431-436. doi: 10.1136/injuryprev-2017-042475. Epub 2017 Oct 6.
6
Changes in Attitudes toward Guns and Shootings following Implementation of the Baltimore Safe Streets Intervention.巴尔的摩安全街道干预措施实施后对枪支和枪击事件态度的变化。
J Urban Health. 2016 Aug;93(4):609-26. doi: 10.1007/s11524-016-0060-y.
7
Managing Conflicts in Urban Communities: Youth Attitudes Regarding Gun Violence.城市社区冲突管理:青年对枪支暴力的态度。
J Interpers Violence. 2018 Dec;33(24):3815-3828. doi: 10.1177/0886260516639584. Epub 2016 Mar 27.
8
Effects of changes in permit-to-purchase handgun laws in Connecticut and Missouri on suicide rates.康涅狄格州和密苏里州购买手枪许可法律的变化对自杀率的影响。
Prev Med. 2015 Oct;79:43-9. doi: 10.1016/j.ypmed.2015.07.013. Epub 2015 Jul 23.
9
Association Between Connecticut's Permit-to-Purchase Handgun Law and Homicides.康涅狄格州手枪购买许可法与杀人案之间的关联
Am J Public Health. 2015 Aug;105(8):e49-54. doi: 10.2105/AJPH.2015.302703. Epub 2015 Jun 11.
10
Cure violence: a public health model to reduce gun violence.治愈暴力:减少枪支暴力的公共卫生模型。
Annu Rev Public Health. 2015 Mar 18;36:39-53. doi: 10.1146/annurev-publhealth-031914-122509. Epub 2015 Jan 7.

采用合成控制法估计马里兰州巴尔的摩市干预措施的效果。

Using synthetic control methodology to estimate effects of a intervention in Baltimore, Maryland.

机构信息

Violence Prevention Research Program, Department of Emergency Medicine, University of California Davis, Sacramento, California, USA

Center for Gun Violence Prevention and Policy, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.

出版信息

Inj Prev. 2022 Feb;28(1):61-67. doi: 10.1136/injuryprev-2020-044056. Epub 2021 Feb 8.

DOI:10.1136/injuryprev-2020-044056
PMID:33558396
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9019528/
Abstract

OBJECTIVE

To estimate the long-term impact of Safe Streets Baltimore, which is based on the outreach and violence interruption model, on firearm violence.

METHODS

We used synthetic control methods to estimate programme effects on homicides and incidents of non-fatal penetrating firearm injury (non-fatal shootings) in neighbourhoods that had Safe Streets' sites and model-generated counterfactuals. Synthetic control analyses were conducted for each firearm violence outcome in each of the seven areas where Safe Streets was implemented. The study also investigated variation in programme impact over time by generating effect estimates of varying durations for the longest-running programme sites.

RESULTS

Synthetic control models reduced prediction error relative to regression analyses. Estimates of Safe Streets' effects on firearm violence varied across intervention sites: some positive, some negative and no effect. Beneficial programme effects on firearm violence reported in prior research were found to have attenuated over time.

CONCLUSIONS

For highly targeted interventions, synthetic control methods may provide more valid estimates of programme impact than panel regression with data from all city neighbourhoods. This research offers new understanding about the effectiveness of the intervention over extended periods of time in seven neighbourhoods. Combined with existing evaluation literature, it also raises questions about contextual and implementation factors that might influence programme outcomes.

摘要

目的

评估基于外展和暴力干预模式的巴尔的摩安全街道计划对枪支暴力的长期影响。

方法

我们使用合成控制方法,根据 Safe Streets 计划实施的社区和模型生成的反事实情况,估计该计划对凶杀案和非致命性穿透性枪支伤害(非致命性枪击)事件的影响。针对 Safe Streets 实施的七个地区中的每个枪支暴力结果进行了合成控制分析。该研究还通过生成最长运行计划地点的不同持续时间的效果估计值,研究了计划效果随时间的变化。

结果

与回归分析相比,合成控制模型降低了预测误差。Safe Streets 对枪支暴力的影响估计因干预地点而异:有些是积极的,有些是消极的,有些则没有影响。先前研究报告的对枪支暴力有益的计划效果随着时间的推移而减弱。

结论

对于高度针对性的干预措施,合成控制方法可能比使用所有城市社区数据的面板回归提供更有效的计划影响估计。这项研究提供了关于该干预措施在七个社区的长时间内的有效性的新认识。结合现有的评估文献,它还提出了一些关于可能影响计划结果的背景和实施因素的问题。