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Open Access Research article

Development, scoring, and reliability of the Microscale Audit of Pedestrian Streetscapes (MAPS)

Rachel A Millstein1, Kelli L Cain2*, James F Sallis2, Terry L Conway2, Carrie Geremia2, Lawrence D Frank3, Jim Chapman4, Delfien Van Dyck56, Lindsay R Dipzinski7, Jacqueline Kerr2, Karen Glanz8 and Brian E Saelens7

Author Affiliations

1 SDSU/UCSD Joint Doctoral Program in Clinical Psychology, 3900 Fifth Avenue, Suite 310, San Diego, CA, 92103, USA

2 Department of Family and Preventive Medicine, University of California, San Diego, 3900 Fifth Avenue, Suite 310, San Diego, CA, 92103, USA

3 School of Population and Public Health, University of British Columbia, 2206 East Mall, Vancouver, BC, V6T 1Z3, Canada

4 Urban Design 4 Health, Inc., P.O. Box 78361, Seattle, WA, 98178, USA

5 Department of Movement and Sports Sciences, Ghent University, Watersportlaan 2, Ghent, 9000, Belgium

6 Research Foundation Flanders, Egmontstraat 5, Brussels, 1000, Belgium

7 Department of Pediatrics, University of Washington/Seattle Children’s Research Institute, PO Box 5371, M/S CW 8-6, Seattle, WA, 98145, USA

8 Departments of Epidemiology and Nursing, University of Pennsylvania Perelman School of Medicine and School of Nursing, 801 Blockley Hall, 423 Guardian Drive, Philadelphia, PA, 19104, USA

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BMC Public Health 2013, 13:403  doi:10.1186/1471-2458-13-403

Published: 27 April 2013

Abstract

Background

Streetscape (microscale) features of the built environment can influence people’s perceptions of their neighborhoods’ suitability for physical activity. Many microscale audit tools have been developed, but few have published systematic scoring methods. We present the development, scoring, and reliability of the Microscale Audit of Pedestrian Streetscapes (MAPS) tool and its theoretically-based subscales.

Methods

MAPS was based on prior instruments and was developed to assess details of streetscapes considered relevant for physical activity. MAPS sections (route, segments, crossings, and cul-de-sacs) were scored by two independent raters for reliability analyses. There were 290 route pairs, 516 segment pairs, 319 crossing pairs, and 53 cul-de-sac pairs in the reliability sample. Individual inter-rater item reliability analyses were computed using Kappa, intra-class correlation coefficient (ICC), and percent agreement. A conceptual framework for subscale creation was developed using theory, expert consensus, and policy relevance. Items were grouped into subscales, and subscales were analyzed for inter-rater reliability at tiered levels of aggregation.

Results

There were 160 items included in the subscales (out of 201 items total). Of those included in the subscales, 80 items (50.0%) had good/excellent reliability, 41 items (25.6%) had moderate reliability, and 18 items (11.3%) had low reliability, with limited variability in the remaining 21 items (13.1%). Seventeen of the 20 route section subscales, valence (positive/negative) scores, and overall scores (85.0%) demonstrated good/excellent reliability and 3 demonstrated moderate reliability. Of the 16 segment subscales, valence scores, and overall scores, 12 (75.0%) demonstrated good/excellent reliability, three demonstrated moderate reliability, and one demonstrated poor reliability. Of the 8 crossing subscales, valence scores, and overall scores, 6 (75.0%) demonstrated good/excellent reliability, and 2 demonstrated moderate reliability. The cul-de-sac subscale demonstrated good/excellent reliability.

Conclusions

MAPS items and subscales predominantly demonstrated moderate to excellent reliability. The subscales and scoring system represent a theoretically based framework for using these complex microscale data and may be applicable to other similar instruments.