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Assessing environmental features related to mental health: a reliability study of visual streetscape images / Yu-Tzu Wu; Paul Nash; Linda E Barnes; Thais Minett; Fiona E Matthews; Andy Jones; Carol Brayne
BMC Public Health, Volume: 14, Issue: 1, Start page: 1094
Swansea University Author: Nash, Paul
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DOI (Published version): 10.1186/1471-2458-14-1094
Background: An association between depressive symptoms and features of built environment has been reportedin the literature. A remaining research challenge is the development of methods to efficiently capture pertinentenvironmental features in relevant study settings. Visual streetscape images have...
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Background: An association between depressive symptoms and features of built environment has been reportedin the literature. A remaining research challenge is the development of methods to efficiently capture pertinentenvironmental features in relevant study settings. Visual streetscape images have been used to replace traditionalphysical audits and directly observe the built environment of communities. The aim of this work is to examine theinter-method reliability of the two audit methods for assessing community environments with a specific focus onphysical features related to mental health.Methods: Forty-eight postcodes in urban and rural areas of Cambridgeshire, England were randomly selected froman alphabetical list of streets hosted on a UK property website. The assessment was conducted in July and August2012 by both physical and visual image audits based on the items in Residential Environment Assessment Tool(REAT), an observational instrument targeting the micro-scale environmental features related to mental health in UKpostcodes. The assessor used the images of Google Street View and virtually “walked through” the streets toconduct the property and street level assessments. Gwet’s AC1 coefficients and Bland-Altman plots were used tocompare the concordance of two audits.Results: The results of conducting the REAT by visual image audits generally correspond to direct observations.More variations were found in property level items regarding physical incivilities, with broad limits of agreementwhich importantly lead to most of the variation in the overall REAT score. Postcodes in urban areas had lowerconsistency between the two methods than rural areas.Conclusions: Google Street View has the potential to assess environmental features related to mental healthwith fair reliability and provide a less resource intense method of assessing community environments thanphysical audits.
Neighbourhood, Audit tool development, Mental health, Built environment, Residential environmental assessment tool
College of Human and Health Sciences