Web Survey Bibliography
It is universally acknowledged that the wording of a survey question can have a strong influence on the answers that respondents provide. For example, many studies have shown that vague and ambiguous terms are often interpreted idiosyncratically by respondents, and thus can increase measurement error. In addition to ambiguity, the cognitive effort required to comprehend survey questions may affect data quality in a similar way. This aspect of survey question design has received comparatively little attention to date and has rarely been examined experimentally. The present thesis suggests that applying a psycholinguistic perspective to survey question design may shed some light on the relationship between the cognitive effort required to comprehend survey questions and the quality of respondents’ answers. Theoretical and empirical evidence from psycholinguistics indicates that text (or question) comprehensibility is reduced by a set of specific text features: low-frequency words, vague or imprecise relative terms, vague or ambiguous noun phrases, complex syntax, complex logical structures, low syntactic redundancy, and bridging inferences. Three experimental studies were conducted to examine whether these seven text features indeed undermine question comprehensibility and, in turn, how question comprehensibility affects the quality of respondents’ answers. Study 1 revealed that six of the seven text features reduce question comprehensibility as indicated by significantly longer response times. Moreover, the text features were found to reduce response quality by producing more neutral (i.e., midpoint) answers. For the most part, these findings were supported by study 2, in which eye-tracking parameters were used as more direct measures of cognitive effort: respondents fixated longer on questions containing one of these text features and required more fixations to process, re-read and interpret these questions in comparison to control questions that did not include the text features. Finally, study 3 showed that respondents receiving less comprehensible questions provided lower-quality responses (as indicated by number of non-substantive responses, number of neutral responses, and over-time consistency of responses) than respondents receiving control questions that were easier to comprehend. Moreover, interaction effects of question comprehensibility with respondents’ verbal skills and their motivation to answer surveys were found. Taken together, these findings indicate that response quality is reduced if questions are difficult to comprehend and exceed the processing effort that respondents are willing or able to invest during survey responding. Hence, survey designers should try to minimize the cognitive effort required to comprehend a question by avoiding the problematic text features discussed above.
Universität Mannheim Homepage (abstract) / (full text)
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.