↓ Skip to main content

Characterizing the spatial mismatch between intimate partner violence related healthcare services and arrests in Miami-Dade County, Florida

Overview of attention for article published in BMC Public Health, August 2018
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
46 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Characterizing the spatial mismatch between intimate partner violence related healthcare services and arrests in Miami-Dade County, Florida
Published in
BMC Public Health, August 2018
DOI 10.1186/s12889-018-5985-5
Pubmed ID
Authors

Jessica Williams, Nick Petersen, Justin Stoler

Abstract

Routine screening and intervention for intimate partner violence (IPV) in healthcare settings constitutes an important secondary prevention strategy for identifying individuals experiencing IPV early and connecting them with appropriate services. Considerable variation in available IPV-related healthcare services exists and interventions are needed to improve the quality of these services. One way to prioritize intervention efforts is by examining the level of services provided in communities most at risk relative to local incidence or prevalence of IPV. To inform future interventions, this study examined the spatial relationship between IPV-related healthcare services and IPV arrests in Miami-Dade County, Florida, and identified predictors of the observed spatial mismatch. Survey data collected in 2014 from 278 health facilities pertaining to IPV services were geocoded, computed into a density layer, and aggregated at the census tract level to create a population-based normalized comprehensiveness score (NCS) as a proxy for IPV-related healthcare resources. IPV arrests from 2011 to 2015, collected from the county court, were geocoded and summarized by census tracts to serve as a proxy for IPV prevalence. These measures were combined into a resource disparity score (RDS) that compared relative service density to relative arrest rates, where positive RDS represented over-resourced neighborhoods and negative RDS corresponded to under-resourced neighborhoods. We used correlation analyses and a two-phase spatial modeling approach to evaluate correlates of NCS and RDS. A spatial lag model did not yield an association between NCS and IPV arrests, demonstrating a spatial mismatch, which we visualized using a Geographic Information System (GIS). A spatial error model revealed that the percentage of white non-Hispanic residents was positively associated with RDS, while percent black non-Hispanic, median age, ethnic heterogeneity, and economic disadvantage were negatively associated with RDS. These findings underscore the need to further evaluate the adequacy of IPV-related healthcare resources for secondary prevention relative to local IPV arrest rates, particularly within economically disadvantaged neighborhoods. Our approach demonstrates the utility of GIS for identifying potential priority regions for IPV prevention efforts and resource allocation.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 13%
Student > Master 6 13%
Researcher 6 13%
Student > Ph. D. Student 5 11%
Student > Postgraduate 3 7%
Other 4 9%
Unknown 16 35%
Readers by discipline Count As %
Medicine and Dentistry 6 13%
Social Sciences 6 13%
Nursing and Health Professions 5 11%
Psychology 3 7%
Environmental Science 2 4%
Other 8 17%
Unknown 16 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 September 2018.
All research outputs
#7,766,401
of 13,480,923 outputs
Outputs from BMC Public Health
#6,285
of 9,316 outputs
Outputs of similar age
#137,444
of 266,010 outputs
Outputs of similar age from BMC Public Health
#8
of 12 outputs
Altmetric has tracked 13,480,923 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,316 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 266,010 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.