Expanding Tools for Investigating Neighborhood Indicators of Drug Use and Violence: Validation of the NIfETy for Virtual Street Observation

Details

• Alternative Title:
  Prev Sci
• Personal Author:
  Nesoff, Elizabeth D. ; Milam, Adam J. ; Barajas, Clara B. ; Furr-Holden, C. Debra M.
• Description:
  A growing body of evidence suggests that characteristics of the neighborhood environment in urban areas significantly impact risk for drug use behavior and exposure to violent crime. Identifying areas of community need, prioritizing planning projects, and developing strategies for community improvement require inexpensive, easy to use, evidence-based tools to assess neighborhood disorder that can be used for a variety of research, urban planning, and community needs with an environmental justice frame. This study describes validation of the Neighborhood Inventory for Environmental Typology (NIfETy), a neighborhood environmental observational assessment tool designed to assess characteristics of the neighborhood environment related to violence, alcohol, and other drugs, for use with Google Street View (GSV). GSV data collection took place on a random sample of 350 blocks located throughout Baltimore City, Maryland, which had previously been assessed through in-person data collection. Inter-rater reliability metrics were strong for the majority of items (ICC ≥ 0.7), and items were highly correlated with in-person observations (r ≥ 0.6). Exploratory factor analysis and constrained factor analysis resulted in one, 14-item disorder scale with high internal consistency (alpha = 0.825) and acceptable fit indices (CFI = 0.982; RMSEA = 0.051). We further validated this disorder scale against locations of violent crimes, and we found that disorder score was significantly and positively associated with neighborhood crime (IRR = 1.221, 95% CI = (1.157, 1.288), p < 0.001). The NIfETy provides a valid, economical, and efficient tool for assessing modifiable neighborhood risk factors for drug use and violence prevention that can be employed for a variety of research, urban planning, and community needs.
• Subjects:
  Article Baltimore Disorder Drug Use Factor Analysis, Statistical Forecasting Geographic Mapping Google Street View Humans Neighborhood Observation Residence Characteristics Risk Assessment Search Engine Substance-Related Disorders Violence Violent Crime

  More +
• Source:
  Prev Sci. 21(2):203-210
• Pubmed ID:
  31637579
• Pubmed Central ID:
  PMC6992509
• Document Type:
  Journal Article
• Funding:
  R01CE002682/ACL/ACL HHS/United States ; R01 CE002682/CE/NCIPC CDC HHS/United States ; T32DA031099/DA/NIDA NIH HHS/United States ; R01 AA015196/AA/NIAAA NIH HHS/United States ; T32 DA031099/DA/NIDA NIH HHS/United States ; 1R01AA015196/AA/NIAAA NIH HHS/United States ; 1R01CE002682/CC/CDC HHS/United States
• Volume:
  21
• Issue:
  2
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:6e6edd9d0219d2a016c0b50c5c88b2939536ad841a517ec072deabdec27500c5
• Download URL:
  https://stacks.cdc.gov/view/cdc/84709/cdc_84709_DS1.pdf
• File Type:
  [PDF - 699.55 KB ]