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Designing Scalar Questions for Web Surveys

Author

Listed:
  • Leah Melani Christian

    (Pew Research Center for the People & the Press, Washington, DC)

  • Nicholas L. Parsons

    (Eastern Connecticut State University, Willimantic, CT)

  • Don A. Dillman

    (Washington State University, Pullman, WA)

Abstract

This paper explores how the visual design of scalar questions influences responses in web surveys. We present the results of five experiments embedded in two web surveys of university students. We find that consistently presenting the positive end of the scale first did not impact responses but increases response times. Displaying the categories in multiple columns influence how respondents process the scale and increase response times. Separating the midpoint, ``don't know'' option, or endpoints spatially does not impact responses when the visual and conceptual midpoint align. Removing the graphical layout of the scale influences responses when lower numbers indicate more positive categories and increases response time. Finally, response times are longer for polar point scales with numeric labels, but there are no differences in responses. Overall, our results suggest that the visual design of response scales impacts measurement, but that some manipulations produce larger and more significant differences than others.

Suggested Citation

  • Leah Melani Christian & Nicholas L. Parsons & Don A. Dillman, 2009. "Designing Scalar Questions for Web Surveys," Sociological Methods & Research, , vol. 37(3), pages 393-425, February.
    • Handle: RePEc:sae:somere:v:37:y:2009:i:3:p:393-425
    DOI: 10.1177/0049124108330004
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    References listed on IDEAS

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    1. Israel, Glenn D. & Taylor, C. L., 1990. "Can response order bias evaluations?," Evaluation and Program Planning, Elsevier, vol. 13(4), pages 365-371, January.
    2. Toepoel, V., 2008. "A closer look at web questionnaire design," Other publications TiSEM 119506d1-f613-46f5-ad59-e, Tilburg University, School of Economics and Management.
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    Cited by:

    1. Anna DeCastellarnau, 2018. "A classification of response scale characteristics that affect data quality: a literature review," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(4), pages 1523-1559, July.

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