Using Attributes of Survey Items to Predict Response Times May Benefit Survey Research.

Field methods

Center for Self-Report Science & Center for Economic and Social Research, University of Southern California, Los Angeles, CA 90089-3332, USA.

Published: May 2023

Researchers have become increasingly interested in response times to survey items as a measure of cognitive effort. We used machine learning to develop a prediction model of response times based on 41 attributes of survey items (e.g., question length, response format, linguistic features) collected in a large, general population sample. The developed algorithm can be used to derive reference values for expected response times for most commonly used survey items.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10553081PMC
http://dx.doi.org/10.1177/1525822x221100904DOI Listing

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