Evidence map›Paper›PMID 35380646›Full record

ArticleJAMA network open2022

Firearm Violence Following the Implementation of California's Gun Violence Restraining Order Law.

Veronica A Pear, Garen J Wintemute, Nicholas P Jewell, Jennifer Ahern

Abstract read
In one paragraph

Article in JAMA network open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

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  15. Gun violence restraining orders in California, 2016-2018: case details and respondent mortality.Injury prevention : journal of the International Society for Child and Adolescent Injury Prevention · 2022
    Article
  16. Article
  17. Article
  18. Firearm Restraining Order Implementation Case Study in Lake County, Illinois.Inquiry : a journal of medical care organization, provision and financing
    Article
  19. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Veronica A PearViolence Prevention Research Program, Department of Emergency Medicine, University of California, Davis School of Medicine.
Garen J WintemuteViolence Prevention Research Program, Department of Emergency Medicine, University of California, Davis School of Medicine.
Nicholas P JewellDepartment of Medical Statistics, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Jennifer AhernDivision of Epidemiology, University of California, Berkeley School of Public Health.

Funding

A Rigorous System to Determine the Health Impacts of Policies and ProgramsDP2HD080350 · NICHD · UNIVERSITY OF CALIFORNIA BERKELEY · PI AHERN, JENNIFER · 2013 to 2013
$2.4M
Emerging methods and applications for test-negative studies of of infectious disease interventionsR01AI148127 · NIAID · UNIVERSITY OF CALIFORNIA BERKELEY · PI JEWELL, NICHOLAS P · 2020 to 2023
$1.8M
NIAID NIH HHS R01 AI148127NICHD NIH HHS DP2 HD080350
6 · The paper itself

Abstract

Importance: California's gun violence restraining order (GVRO) law, implemented beginning in 2016, allows for people at high risk of harming themselves or others with a firearm to be temporarily disarmed and prevented from purchasing firearms for 3 weeks to 1 year; many states have recently enacted similar laws. The research to date is on older and more limited risk-warrant laws. Objective: To determine whether implementation of the California GVRO law was associated with decreased rates of firearm assault or firearm self-harm in a large metropolitan county between 2016 and 2019. Design, Setting, and Participants: This serial cross-sectional study including data from 28 counties used the synthetic control method to evaluate differences in firearm violence between San Diego County and its synthetic control following implementation of the California law from 2016 to 2019. San Diego County was used as the treated unit because it issued substantially more GVROs than any other county in California during the study period. A total of 27 California counties that issued no or very few gun violence restraining orders from 2016 to 2019 and that had stable rates of firearm violence between 2005 and 2015 were included in the control pool. Data were analyzed from February 2021 to July 2021. Exposures: Implementation of the statewide GVRO law in 2016 in San Diego County. Main Outcomes and Measures: Annual rates of fatal and nonfatal firearm assault injuries and firearm self-harm injuries per 100 000 people. Results: In the study period, there were 355 GVROs in San Diego county, and a median (IQR) total of 8 (3-20) GVROs per donor county. The mean difference between the observed rate in San Diego County and the estimated rate in the synthetic San Diego County, 2016-2019, was -0.74 firearm assaults per 100 000 (-13% difference) and 0.13 firearm self-harm injuries per 100 000 (3% difference). Results from in-space placebo tests suggested that these differences cannot be distinguished from variation due to chance (pseudo-P values from a 1-sided test: P for assault = .35, P for self-harm = .67). Conclusions and Relevance: To our knowledge, this study was the first to analyze the association between GVRO implementation and firearm violence in California and the first to evaluate the association between risk-based firearm removal laws and firearm assault in any state. GVROs were not associated with reduced population-level rates of firearm violence in San Diego County, but this may change as the number of orders increases over time; the association between GVROs and firearm violence at the individual level cannot be inferred from our findings and should be the subject of future studies.

Indexed as

FirearmsGun ViolenceWounds, GunshotCross-Sectional StudiesHumansViolence

Identifiers

PMID35380646
PMCPMC8984773

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.