Evidence map›Paper›PMID 25545769›Full record

ArticleHealth & place2015

Development and deployment of the Computer Assisted Neighborhood Visual Assessment System (CANVAS) to measure health-related neighborhood conditions.

Michael D M Bader, Stephen J Mooney, Yeon Jin Lee, Daniel Sheehan, Kathryn M Neckerman, Andrew G Rundle, Julien O Teitler

Abstract read
In one paragraph

Article in Health & place, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 1 pooled it
–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

56 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Urban Health Indicator Tools of the Physical Environment: a Systematic Review.Journal of urban health : bulletin of the New York Academy of Medicine · 2018
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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

7 authors.

Michael D M BaderDepartment of Sociology and Center on Health, Risk and Society, American University, Washington, DC, United States. Electronic address: bader@american.edu.
Stephen J MooneyDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States.
Yeon Jin LeeDepartment of Sociology and Population Studies Center, University of Pennsylvania, Philadelphia, PA, United States.
Daniel SheehanDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States.
Kathryn M NeckermanColumbia Population Research Center, Columbia University, New York, NY, United States.
Andrew G RundleDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, United States.
Julien O TeitlerSchool of Social Work, Columbia University, New York, NY, United States.

Funding

Development CoreP2CHD058486 · NICHD · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI Jennifer S Hirsch, Julien O Teitler · 2014 to 2026
$4.3M
Using Google Streetview to Measure Neighborhood CharacteristicsR21HD062965 · NICHD · COLUMBIA UNIV NEW YORK MORNINGSIDE · PI RUNDLE, ANDREW G, TEITLER, JULIEN O · 2010 to 2011
$449k
NICHD NIH HHS 5R21HD062965-02NICHD NIH HHS P2C HD058486NICHD NIH HHS R21 HD062965
6 · The paper itself

Abstract

Public health research has shown that neighborhood conditions are associated with health behaviors and outcomes. Systematic neighborhood audits have helped researchers measure neighborhood conditions that they deem theoretically relevant but not available in existing administrative data. Systematic audits, however, are expensive to conduct and rarely comparable across geographic regions. We describe the development of an online application, the Computer Assisted Neighborhood Visual Assessment System (CANVAS), that uses Google Street View to conduct virtual audits of neighborhood environments. We use this system to assess the inter-rater reliability of 187 items related to walkability and physical disorder on a national sample of 150 street segments in the United States. We find that many items are reliably measured across auditors using CANVAS and that agreement between auditors appears to be uncorrelated with neighborhood demographic characteristics. Based on our results we conclude that Google Street View and CANVAS offer opportunities to develop greater comparability across neighborhood audit studies.

Indexed as

Residence CharacteristicsEnvironment DesignGeographic Information SystemsHumansNew York CityReproducibility of ResultsDisorderGoogle Street ViewNeighborhood auditSystematic social observationWalkability

Identifiers

PMID25545769
PMCPMC4315325

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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.