Literature DB >> 31637579

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

Elizabeth D Nesoff1, Adam J Milam2,3, Clara B Barajas3, C Debra M Furr-Holden3,4.   

Abstract

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.

Entities:  

Keywords:  Disorder; Drug use; Google Street View; Neighborhood; Violent crime

Mesh:

Year:  2020        PMID: 31637579      PMCID: PMC6992509          DOI: 10.1007/s11121-019-01062-w

Source DB:  PubMed          Journal:  Prev Sci        ISSN: 1389-4986


  39 in total

1.  Crosswalk markings and the risk of pedestrian-motor vehicle collisions in older pedestrians.

Authors:  Thomas Koepsell; Lon McCloskey; Marsha Wolf; Anne Vernez Moudon; David Buchner; Jess Kraus; Matthew Patterson
Journal:  JAMA       Date:  2002-11-06       Impact factor: 56.272

2.  Metric properties of the Neighborhood Inventory for Environmental Typology (NIfETy): an environmental assessment tool for measuring indicators of violence, alcohol, tobacco, and other drug exposures.

Authors:  C D M Furr-Holden; K D M Campbell; A J Milam; M J Smart; N A Ialongo; P J Leaf
Journal:  Eval Rev       Date:  2010-06

Review 3.  Intraclass correlations: uses in assessing rater reliability.

Authors:  P E Shrout; J L Fleiss
Journal:  Psychol Bull       Date:  1979-03       Impact factor: 17.737

4.  Off-Premise Alcohol Outlets and Substance Use in Young and Emerging Adults.

Authors:  Adam J Milam; C Debra M Furr-Holden; Paul Harrell; Nicholas Ialongo; Philip J Leaf
Journal:  Subst Use Misuse       Date:  2013-08-02       Impact factor: 2.164

5.  Exposure to Hazardous Neighborhood Environments in Late Childhood and Anxiety.

Authors:  C Debra M Furr-Holden; Adam J Milam; Kevin C Young; Laura Macpherson; Carl W Lejuez
Journal:  J Community Psychol       Date:  2011-09

6.  Using Google Earth to conduct a neighborhood audit: reliability of a virtual audit instrument.

Authors:  Philippa Clarke; Jennifer Ailshire; Robert Melendez; Michael Bader; Jeffrey Morenoff
Journal:  Health Place       Date:  2010-08-11       Impact factor: 4.078

Review 7.  Are neighbourhood characteristics associated with depressive symptoms? A review of evidence.

Authors:  C Mair; A V Diez Roux; S Galea
Journal:  J Epidemiol Community Health       Date:  2008-09-05       Impact factor: 3.710

Review 8.  Blues from the neighborhood? Neighborhood characteristics and depression.

Authors:  Daniel Kim
Journal:  Epidemiol Rev       Date:  2008-08-27       Impact factor: 6.222

9.  Direct and indirect associations of neighborhood disorder with drug use and high-risk sexual partners.

Authors:  Carl A Latkin; Aaron D Curry; Wei Hua; Melissa A Davey
Journal:  Am J Prev Med       Date:  2007-06       Impact factor: 5.043

10.  Developing and testing a street audit tool using Google Street View to measure environmental supportiveness for physical activity.

Authors:  Pippa Griew; Melvyn Hillsdon; Charlie Foster; Emma Coombes; Andy Jones; Paul Wilkinson
Journal:  Int J Behav Nutr Phys Act       Date:  2013-08-23       Impact factor: 6.457

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  3 in total

1.  Validating a spatio-temporal model of observed neighborhood physical disorder.

Authors:  Jesse J Plascak; Stephen J Mooney; Mario Schootman; Andrew G Rundle; Adana A M Llanos; Bo Qin; Chi-Chen Hong; Kitaw Demissie; Elisa V Bandera; Xinyi Xu
Journal:  Spat Spatiotemporal Epidemiol       Date:  2022-03-24

2.  Using 164 Million Google Street View Images to Derive Built Environment Predictors of COVID-19 Cases.

Authors:  Quynh C Nguyen; Yuru Huang; Abhinav Kumar; Haoshu Duan; Jessica M Keralis; Pallavi Dwivedi; Hsien-Wen Meng; Kimberly D Brunisholz; Jonathan Jay; Mehran Javanmardi; Tolga Tasdizen
Journal:  Int J Environ Res Public Health       Date:  2020-09-01       Impact factor: 3.390

3.  A Qualitative Assessment of Place and Mental Health: Perspectives of Young Women Ages 18-24 Living in the Urban Slums of Kampala, Uganda.

Authors:  Monica H Swahn; Jacqueline Nassaka; Anna Nabulya; Jane Palmier; Seneca Vaught
Journal:  Int J Environ Res Public Health       Date:  2022-10-10       Impact factor: 4.614

  3 in total

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