Web Survey Bibliography
Relevance & Research Question: Many studies found that the wording of a survey question can influence the answers that respondents provide. In particular, it has been shown that vague and ambiguous terms are often interpreted idiosyncratically by respondents, and thus can introduce a systematic bias into the survey data. In addition to ambiguity, the cognitive effort required to understand survey questions may affect data quality in a similar way. Earlier research identified several problematic text features (such as low-frequency words, left-embedded syntactic structures, low syntactic redundancy) that reduce question clarity and make survey questions difficult to comprehend (e.g. Lenzner, Kaczmirek, & Lenzner, 2010). This paper extends the earlier findings and examines whether the effort required to comprehend survey questions affects data quality.
Methods & Data: An experiment was carried out in which respondents were asked to complete two Web surveys (N1=825, N2=515) at a two-week interval. Approximately half of the respondents answered questionnaires that included unclear and less comprehensible questions, the other half received control questions that were easier to comprehend. Indicators of data quality were drop-out rates, number of non-substantive responses (“Don’t know’s”), number of neutral (midpoint) responses, and over-time consistency of responses across the two surveys. In addition, respondents’ verbal intelligence and motivation were assessed to examine whether question clarity effects were moderated by these two respondent characteristics.
Results: As expected, respondents receiving unclear questions provided lower-quality responses than respondents answering more comprehensible questions. Moreover, some of these effects were more pronounced among respondents with limited verbal skills and among respondents with low motivation to answer surveys.
Added value: These findings indicate that survey results can be systematically biased if questions are difficult to understand and exceed the processing effort that respondents are willing or able to invest. Making it easy for respondents to retrieve the meaning of a survey question seems to be an important requirement for obtaining high-quality answers.
Conference Homepage (abstract) / (presentation)
Web survey bibliography - General Online Research Conference (GOR) 2011 (17)
- Sampling v. Scale: An investigation the tension between convenience sampling, response rates, probability...; 2011; Garland, P.
- Effectiveness and consequences of various recruitment methods in psychological research: case study; 2011; Poltorak, M.
- A new approach to the analysis of survey drop-out. Results from Follow-up Surveys in the German Longitudinal...; 2011; Rossmann, J., Blumenstiel, J. E., Steinbrecher, M.
- Tracking the decision-making process – Findings from an Online Rolling Cross-Section Panel Study...; 2011; Faas, T.
- Should we use the progress bar in online surveys? A meta-analysis of experiments manipulating progress...; 2011; Callegaro, M., Yang, Y., Villar, A.
- From "Web Questions" to "Propensity Score Weighting": An Evaluation of Topics and...; 2011; Welker, M., Taddicken, M.
- Rich Profiles – Or: What's the problem with self-disclosure data?; 2011; Tress, F.
- Who are leaving our panel: panel attrition and personality traits; 2011; Marchand, M.
- Mobile Research Apps – Adding New Capabilities to Market Research; 2011; Rieber, D.
- The influence of personality traits and motives for joining on participation behavior in online panels...; 2011; Keusch, F.
- Asking sensitive questions in a recruitment interview for an online panel: the income question; 2011; Schaurer, I., Struminskaya, B., Kaczmirek, L., Bandilla, W.
- Speeders in Online Value Research: Cross-checking results of fast and slow respondents in two separate...; 2011; Beckers, T., Siegers, P., Kuntz, A.
- Effects of survey question clarity on data quality; 2011; Lenzner, T.
- Respondent Characteristics as Explanations for Uninformative Survey Response: Sources of Nondifferentiation...; 2011; Van Meurs, L., Klausch, L. T., Schoenbach, K.
- Response Quantity, Response Quality, and Costs of Building an Online Panel via Social Contacts.; 2011; Toepoel, V.
- The Influence Of The Direction Of Likert-Type Scales In Web Surveys On Response Behavior In Different...; 2011; Keusch, F.
- Social desirability and self-reported health risk behaviors in web-based research: three longitudinal...; 2010; Crutzen, R., Goeritz, A.