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 - Germany (361)
- Mobile, webmail, desktops: Where are we viewing email now?; 2011
- Assessing personality traits through response latencies using item response theory; 2011; Ranger, J., Ortner, T. M.
- Web-based rating scales: HTML 5 and other innovations; 2011; Funke, F.
- E-dater, Artificial Actors, and German Households; 2011; Hebing, M.
- Seeing Through the Eyes of the Respondent: An Eye-tracking Study on Survey Question Comprehension; 2011; Lenzner, A., Kaczmirek, L., Galesic, M.
- Eye Tracking in testing questionnaires: What’s the added value?; 2011; Tries, S.
- Improving validity in web surveys with hard‐to‐reach targets: Online Respondent Driven Sampling...; 2011; Mavletova, A. M.
- Ignoring the compatibility of online questionnaires may bias the psychological composition of your sample...; 2011; Funke, F.
- Video enhanced web survey; 2011; Fuchs, M., Kunz, T., Gebhard, F.
- Scrolling or paging - it depends; 2011; Blanke, K.
- The German Access Panel and the Impact of Response Propensities; 2011; Amarov, B., Enderle, T., Muennich, R., Rendtel, U., Zins, S.
- 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.
- 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.
- 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.
- Lösungsansätze gegen den Allgemeinarztmangel auf dem Land - Ergebnisse einer Online-Befragung unter Ä...; 2011; Steinhäuser, J., Annan, N. F., Roos, M., Szecsenyi, J., Joos, S.
- Question Comprehensibility and Satisficing Behavior in Web Surveys; 2011; Lenzner, T.
- Agree-Disagree Response Format versus Importance Judgment; 2011; Krebs, D.
- Germans' segregation preferences and immigrant group size: A factorial survey approach; 2011; Schlueter, E., Ullrich, J., Schmidt, P.
- Benefits of Structured DDI Metadata across the Data Lifecycle: The STARDAT Project at the GESIS Data...; 2011; Linne, M., Brislinger, E., Zenk-Moeltgen, W.
- Microdata Information System MISSY; 2011; Bohr, J.,
- Explaining more variance with visual analogue scales: A Web experiment; 2011; Funke, F.
- Cognitive process in answering questions: Are verbal labels in rating scales attended to?; 2011; Menold, N., Kaczmirek, L., Lenzner, T.
- Experiments on the Design of the Left-Right Self-Assessment Scale; 2011; Zuell, C., Scholz, E., Behr, D.
- Separating selection from mode effects when switching from single (CATI) to mixed mode design (CATI /...; 2011; Carstensen, J., Kriwy, P., Krug, G., Lange, C.
- Asking Sensitive Questions: Do They Affect Participation In Follow-Up Surveys?; 2011; Schaurer, I., Struminskaya, B., Kaczmirek, L., Bandilla, W.
- Does social desirability compromise self-reports of physical activity in web-based research?; 2011; Crutzen, R., Goeritz, A.
- Testing for measurement equivalence of human values across online and paper-and-pencil surveys; 2011; Davidov, E., Depner, F.
- The use of paradata to monitor and manage survey data collection; 2010; Kreuter, F., Couper, M. P., Lyberg, L. E.
- Optimizing response rates in online surveys; 2010; Kaczmirek, L.
- There is an app for that! A review of smartphone apps for marketing research; 2010; Michelson, M.
- Innovative mobile research in developing countries; 2010; Bellity, E.
- Mobile location based research: Cross cultural examination of coffee culture; 2010; Morden, M., Ferneyhough, C., Grenville, A.
- Online research….and all that Jazz!; 2010; Gittelman, S. H., Trimarchi, E.
- Why are we trying to create new communities for market research purposes?; 2010; Pearson, C., Kateley, V.
- Internet-Based Measurement With Visual Analogue Scales: An Experimental Investigation; 2010; Funke, F.
- Managing the knowledge base - the DUVA system, from data entry to output tools; 2010; Then, R., Bangert, D.
- Recruiting Online Panel Members from a Mail survey in the General Population: Results from an Exploratory...; 2010; Reuband, K. H.
- Testing the Applicability of Respondent Driven Sampling as an Online Research Method to Sample Hidden...; 2010; Pajak, D.
- Seriousness Checks are Useful to Improve Data Validity in Online Research; 2010; Diedenhofen, D., Aust, F., Ullrich, S., Musch, J.
- Enrichment of Qualitative Research through Online Approaches: New Insights due to Online CoCreation...; 2010; Krischke-Ramaswamy, M., Knorr, H.
- Eye Tracking and Cognitive Interviewing: Steps to improve online questionnaires; 2010; Tries, S., Sattelberger, S.
- How new engagement techniques and question approaches are revolutionizing online research data gathering...; 2010; Puleston, J.
- Social Networking Sites: New approaches for Online-Panels?; 2010; Drosdow, M., Geißler, H.
- The Impact of Visual and Functional Design Elements in Online Survey Research; 2010; Hammen, K.