Assessing environmental features related to mental health: a reliability study of visual streetscape images

BMC Public Health

Carol Brayne²  Andy Jones¹  Fiona E Matthews³  Thais Minett²  Linda E Barnes²  Paul Nash⁴  Yu-Tzu Wu² 

[1] Norwich Medical School, University of East Anglia, Norwich, Norfolk NR4 7TJ, UK;Department of Public Health and Primary Care, Institute of Public Health, Forvie Site, University of Cambridge, School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge CB2 0SR, UK;MRC Biostatistics Unit, Institute of Public Health, University of Cambridge, Cambridge CB2 0SR, UK;Centre for Innovative Ageing, College of Human and Health Science, Swansea University, Swansea SA2 8PP, UK

关键词: Residential environmental assessment tool;    Built environment;    Mental health;    Audit tool development;    Neighbourhood;   

Others  :  1126056
DOI  :  10.1186/1471-2458-14-1094

 received in 2014-03-09, accepted in 2014-10-13,  发布年份 2014

【 摘 要 】

Background

An association between depressive symptoms and features of built environment has been reported in the literature. A remaining research challenge is the development of methods to efficiently capture pertinent environmental features in relevant study settings. Visual streetscape images have been used to replace traditional physical audits and directly observe the built environment of communities. The aim of this work is to examine the inter-method reliability of the two audit methods for assessing community environments with a specific focus on physical features related to mental health.

Methods

Forty-eight postcodes in urban and rural areas of Cambridgeshire, England were randomly selected from an alphabetical list of streets hosted on a UK property website. The assessment was conducted in July and August 2012 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 UK postcodes. The assessor used the images of Google Street View and virtually "walked through" the streets to conduct the property and street level assessments. Gwet’s AC1 coefficients and Bland-Altman plots were used to compare 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 agreement which importantly lead to most of the variation in the overall REAT score. Postcodes in urban areas had lower consistency between the two methods than rural areas.

Conclusions

Google Street View has the potential to assess environmental features related to mental health with fair reliability and provide a less resource intense method of assessing community environments than physical audits.

【 授权许可】

   
2014 Wu et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

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