Data Collection Methods to Improve Measurement of Community Contextual Features
Scott T. Yabiku, Arizona State University
Jennifer E. Glick, Arizona State University
Data on community context is an increasingly important part of social, behavioral, and medical studies. These data are designed to capture aspects of a respondent’s surrounding at a level of measurement above the single individual. There are several challenges, however, that impede the collection of accurate community context data in both developed and developing settings. We present the results of a pilot test in Chitwan, Nepal, that uses an improved instrument containing two key innovations: (1) a respondent-focused interface design featuring touch input and large map displays and (2) efficient field-based GIS. These two features are designed to promote respondent-interviewer collaboration. The results suggest that the instrument is highly usable by a wide range of respondents, even those who have never used a computer before. Usability appeared to be lower among less educated and older respondents, but this did not detract from the overall success of the instrument.