Using client-side event logging and path tracing to assess and improve the quality of web-based surveys

Web-based data collection has considerable appeal. However, the quality of data collected using such instruments is often questionable. There can be systematic problems with the wording of the surveys, and/or the means with which they are deployed. In unsupervised data collection, there are also concerns about whether subjects understand the questions, and wehther they are answering honestly. This paper presents a schema for using client-side timestamps and traces of subjects' paths through instruments to detect problems with the definition of instruments and their deployment. We discuss two large, anonymous, web-based, medical surveys as examples of the utility of this approach.