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 - 2011 (358)
- The Validity of Surveys: Online and Offline; 2016; Wiersma, W.
- Computer science security research and human subjects: Emerging considerations for research ethics boards...; 2013; Buchanan, E. A., Aycock, J., Dexter, S., Dittrich, D., Hvizdak, E. E.
- Multiple Sources of Nonobservation Error in Telephone Surveys: Coverage and Nonresponse; 2011; Peytchev, A.; Carley-Baxter, L. R.; Black, M. C.
- Online Questionnaires for Outbreak Investigations; 2011; Parry, A. E.; Johnson, D. R.; Byron-Gray, K.; Raupach, J. C. A.; McPherson, M.
- Inventory of published research: Response burden measurement and reduction in official business statistics...; 2011; Giesen, D. & Snijkers, G. (Eds.), Bavdaz, M., Bergstrom, Y., Gravem, D. F., Haraldsen, G., Hedlin, D...
- Effects of speeding on satisficing in Mixed-Mode Surveys; 2011; Bathelt, S., Bauknecht, J.
- Using Research-Based Practices to Increase Response Rates of Web-Based Surveys; 2011; Perkins, R. A.
- Using break-offs in web interviews for predicting web response in mixed mode surveys; 2011; Beukenhorst, D.
- Web panels in Slovenia; 2011; Lenar, J.
- Traditional and non-traditional treatments for autism spectrum disorder with seizures: an on-line survey...; 2011; Frye, R. E., Sreenivasula, S., Adams, J. B.
- Understanding the new digital divide—A typology of Internet users in Europe; 2011; Brandtzæg, P.B.; Heim, J.; Karahasanoviæ, A.
- Patients’ attitudes toward side effects of antidepressants: an Internet survey; 2011; Kikuchi, T., Uchida, H., Suzuki, T., Watanabe, K., Kashima, H.
- Web-based or paper-based surveys: a quandary?; 2011; Bennett, L., Sid Nair, C.
- Refining the Total Survey Error Perspective; 2011; Smith, T. W.
- ELIPSS: Étude Longitudinale par Internet Pour les Sciences Sociales; 2011; Legleye, S., Lesnard, L.
- Less questions, more data: Revitalizing the european currency in single source affluent audience measurement...; 2011; Hartman, H.
- Linking website exposure data to survey data: A single-source solution; 2011; Krahn, J., Landi, J., Melton, E.
- Inference in surveys with sequential mixed-mode data collection; 2011; Buelens, B., van der Brakel, J.
- Using a Probability-based Online Panel to Survey American Jews; 2011; Wright, G., Phillips, B. T., Tobias, J., Peugh, J., Semans, K.
- Choice of Content Presentation Mode in Web-Based Survey Administration; 2011; Osborn, L., Mansfield, W., Ramirez, C. M., Lacey, J. N., etc.
- Seasonal Yield Variation and Related Response Patterns in Address-based Mail Samples; 2011; DiSogra, C., Hendarwan, E.
- Gender-specific on-line shopping preferences; 2011; Ulbrich, F., Christensen, T., Stankus, L.
- Mixing modes in the LFS - Computer-assisted, cost effective and respondent friendly; 2011; Koerner, T., van der Valk, J.
- Peanuts and Monkeys: Incentivisation and engagement in online access panels; 2011; Marks, B.
- Establishing Cross-National Equivalence of Measures of Xenophobia: Evidence from Probing in Web Surveys...; 2011; Braun, M., Behr, D., Kaczmirek, L.
- Methodological challenges in the use of the Internet for scientific research: Ten solutions and recommendations...; 2011; Reips, U.-D., Buchanan, T., Krantz, J. H., McGrawn, K.Reips, U.-D.
- Search and email still top the list of most popular online activities; 2011; Purcell, K.
- Using Internet in Stated Preference Surveys: A Review and Comparison of Survey Modes; 2011; Lindhjem, H., Navrud, S.
- On the experience and evidence about mixing modes of data collection in large-scale surveys where the...; 2011; Dex, S., Gumy, J.
- Survey Gamification: Old Wine in New Bottles?; 2011; Baker, R. P.
- The Game Experiments: Researching how gaming techniques can be used to improve the quality of feedback...; 2011; Sleep, D., Puleston, J.
- Statistical Estimation of Word Acquisition With Application to Readability Prediction; 2011; Kidwell, P., Lebanon, G., Collins-Thompson, K.
- What is Probit; 2011
- Voice-of-the-customer marketing: A revolutionary 5-step process to create customers who care, spend,...; 2011; Roman, E.
- User agent; 2011
- Unpublisihed internal Google report on break off rates by device type; 2011; Callegaro, M.
- Toward wiser public judgment; 2011; Yankelovich, D., Friedman, W.
- The impact of cookie deletion on site-server and ad-server metrics in Australia. An empirical comScore...; 2011
- The changing role of address-based sampling in survey research; 2011; Iannacchione, V. G.
- State of mobile measurement; 2011; Gluck, M.
- Some issues in the application of latent class models for questionnaire design; 2011; Biemer, P. P., Berzofsky, M.
- Self-administered mobile surveys; 2011; Bosnjak, M.
- SDSC Announces scalable, high-performance data storage cloud; 2011
- Ratings and audience measurement; 2011; Napoli, P. M.
- Randomized response models in survey sampling. Randomized response models; 2011; Hussain, Z.
- Online survey research: Findings, best practices, and future research. Report prepared for the Advertising...; 2011; Vannette, D.
- Online survey research: Findings, Best practices, and future research; 2011
- New Esomar survey on use of cookies and tracking technologies; 2011
- Mobile, webmail, desktops: Where are we viewing email now?; 2011
- Measuring americans' issue priorities. A new version of the most important problem question reveals...; 2011; Yeager, D. S., Larson, S. B., Krosnick, J. A., Tompson, T.