Web Survey Bibliography
The rapid acceptance of the Web as a vehicle for survey data collection raises important questions for survey designers. Web surveys are the latest example of computerized self-administration of survey questions, and we suspect they may ultimately turn out to be the most popular. Aside from the gains from computerization and self-administration, Web data collection eliminates interviewers entirely, sharply reducing the cost of data collection. Furthermore, Web surveys can deliver rich visual content that is impossible or prohibitively expensive to incorporate in other modes. Not surprisingly, the growth in Web surveys has been dramatic. Despite serious concerns about coverage and nonresponse in Web surveys (Couper, 2001), the commercial research sector has rapidly embraced the Internet for faster and cheaper data collection, and almost daily there are reports of new surveys being done over the Web. A key characteristic of Web surveys is their reliance on visual presentation of the questions. Of course, sound can be added to Web questionnaires, but so far Web surveys have remained a visual medium. Visual presentation is not unique to Web data collection, but is shared to varying degrees with most other methods of self-administration, including mail surveys. Still, the implications of visual presentation are not especially well understood, even for the older methods; the literature on the design of mail or paper-based self-administered questionnaires is not large. Although several good texts offer practical guidelines for the design of paper self-administered questionnaires (e.g., Dillman, 1978; Mangione, 1995), there has been relatively little empirical work or theoretical analysis of the issues involved. The forms design literature is sparse in general (see, e.g., Burgess, 1984; Waller, 1984; Wright and Barnard, 1975). The one notable exception has been the work of Redline and Dillman, who have applied principles rooted in visual perception theory to the design of selfadministered forms (Dillman, Redline, and Carley-Baxter, 1999; Jenkins and Dillman, 1995; Redline and Dillman, 2002). The focus of this work has been on designing forms so that respondents are willing and able to complete them. But the design of paper forms and computer screens may affect not only whether respondents answer the questions but also which answers they give (e.g., Sanchez, 1992; Smith, 1995). The study of forms design is in its infancy, and the impact of forms design on measurement error has been almost entirely neglected. The studies we present here support a few general conclusions about the impact of visual information on responses to questions in Web surveys:
Respondents notice images in Web surveys and the content of these images can affect the answers they give;
Respondents also take in such visual cues as the spacing and relative position of the response options and these cues can alter their interpretation of survey questions;
Respondents are sensitive to information that is immediately visible and may ignore information that is equally critical but not equally available. Taken together, our results suggest that, whether we want them to or not, respondents attend to the visual design of Web questionnaires as well as to the verbal content of the questions.
Web survey bibliography (4086)
- Displaying Videos in Web Surveys: Implications for Complete Viewing and Survey Responses; 2017; Mendelson, J.; Lee Gibson, J.; Romano Bergstrom, J. C.
- Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not...; 2017; Toepoel, V.; Emerson, H.
- Mind the Mode: Differences in Paper vs. Web-Based Survey Modes Among Women With Cancer; 2017; Hagan, T. L.; Belcher, S. M.; Donovan, H. S.
- Answering Without Reading: IMCs and Strong Satisficing in Online Surveys; 2017; Anduiza, E.; Galais, C.
- Ideal and maximum length for a web survey; 2017; Revilla, M.; Ochoa, C.
- Social desirability bias in self-reported well-being measures: evidence from an online survey; 2017; Caputo, A.
- Web-Based Survey Methodology; 2017; Wright, K. B.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
- Lessons from recruitment to an internet based survey for Degenerative Cervical Myelopathy: merits of...; 2017; Davies, B.; Kotter, M. R.
- Web Survey Gamification - Increasing Data Quality in Web Surveys by Using Game Design Elements; 2017; Schacht, S.; Keusch, F.; Bergmann, N.; Morana, S.
- Effects of sampling procedure on data quality in a web survey; 2017; Rimac, I.; Ogresta, J.
- Comparability of web and telephone surveys for the measurement of subjective well-being; 2017; Sarracino, F.; Riillo, C. F. A.; Mikucka, M.
- Achieving Strong Privacy in Online Survey; 2017; Zhou, Yo.; Zhou, Yi.; Chen, S.; Wu, S. S.
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Telephone versus Online Survey Modes for Election Studies: Comparing Canadian Public Opinion and Vote...; 2017; Breton, C.; Cutler, F.; Lachance, S.; Mierke-Zatwarnicki, A.
- Examining Factors Impacting Online Survey Response Ratesin Educational Research: Perceptions of Graduate...; 2017; Saleh, A.; Bista, K.
- Usability Testing for Survey Research; 2017; Geisen, E.; Romano Bergstrom, J. C.
- Paradata as an aide to questionnaire design: Improving quality and reducing burden; 2017; Timm, E.; Stewart, J.; Sidney, I.
- Fieldwork monitoring and managing with time-related paradata; 2017; Vandenplas, C.
- Interviewer effects on onliner and offliner participation in the German Internet Panel; 2017; Herzing, J. M. E.; Blom, A. G.; Meuleman, B.
- Interviewer Gender and Survey Responses: The Effects of Humanizing Cues Variations; 2017; Jablonski, W.; Krzewinska, A.; Grzeszkiewicz-Radulska, K.
- Millennials and emojis in Spain and Mexico.; 2017; Bosch Jover, O.; Revilla, M.
- Where, When, How and with What Do Panel Interviews Take Place and Is the Quality of Answers Affected...; 2017; Niebruegge, S.
- Comparing the same Questionnaire between five Online Panels: A Study of the Effect of Recruitment Strategy...; 2017; Schnell, R.; Panreck, L.
- Nonresponses as context-sensitive response behaviour of participants in online-surveys and their relevance...; 2017; Wetzlehuetter, D.
- Do distractions during web survey completion affect data quality? Findings from a laboratory experiment...; 2017; Wenz, A.
- Predicting Breakoffs in Web Surveys; 2017; Mittereder, F.; West, B. T.
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- Humanizing Cues in Internet Surveys: Investigating Respondent Cognitive Processes; 2017; Jablonski, W.; Grzeszkiewicz-Radulska, K.; Krzewinska, A.
- A Comparison of Emerging Pretesting Methods for Evaluating “Modern” Surveys; 2017; Geisen, E., Murphy, J.
- The Effect of Respondent Commitment on Response Quality in Two Online Surveys; 2017; Cibelli Hibben, K.
- Pushing to web in the ISSP; 2017; Jonsdottir, G. A.; Dofradottir, A. G.; Einarsson, H. B.
- The 2016 Canadian Census: An Innovative Wave Collection Methodology to Maximize Self-Response and Internet...; 2017; Mathieu, P.
- Push2web or less is more? Experimental evidence from a mixed-mode population survey at the community...; 2017; Neumann, R.; Haeder, M.; Brust, O.; Dittrich, E.; von Hermanni, H.
- In search of best practices; 2017; Kappelhof, J. W. S.; Steijn, S.
- Redirected Inbound Call Sampling (RICS); A New Methodology ; 2017; Krotki, K.; Bobashev, G.; Levine, B.; Richards, S.
- An Empirical Process for Using Non-probability Survey for Inference; 2017; Tortora, R.; Iachan, R.
- The perils of non-probability sampling; 2017; Bethlehem, J.
- A Comparison of Two Nonprobability Samples with Probability Samples; 2017; Zack, E. S.; Kennedy, J. M.
- Rates, Delays, and Completeness of General Practitioners’ Responses to a Postal Versus Web-Based...; 2017; Sebo, P.; Maisonneuve, H.; Cerutti, B.; Pascal Fournier, J.; Haller, D. M.
- Necessary but Insufficient: Why Measurement Invariance Tests Need Online Probing as a Complementary...; 2017; Meitinger, K.
- Nonresponse in Organizational Surveying: Attitudinal Distribution Form and Conditional Response Probabilities...; 2017; Kulas, J. T.; Robinson, D. H.; Kellar, D. Z.; Smith, J. A.
- Theory and Practice in Nonprobability Surveys: Parallels between Causal Inference and Survey Inference...; 2017; Mercer, A. W.; Kreuter, F.; Keeter, S.; Stuart, E. A.
- Is There a Future for Surveys; 2017; Miller, P. V.
- Reducing speeding in web surveys by providing immediate feedback; 2017; Conrad, F.; Tourangeau, R.; Couper, M. P.; Zhang, C.
- Social Desirability and Undesirability Effects on Survey Response latencies; 2017; Andersen, H.; Mayerl, J.
- A Working Example of How to Use Artificial Intelligence To Automate and Transform Surveys Into Customer...; 2017; Neve, S.
- A Case Study on Evaluating the Relevance of Some Rules for Writing Requirements through an Online Survey...; 2017; Warnier, M.; Condamines, A.
- Estimating the Impact of Measurement Differences Introduced by Efforts to Reach a Balanced Response...; 2017; Kappelhof, J. W. S.; De Leeuw, E. D.
- Targeted letters: Effects on sample composition and item non-response; 2017; Bianchi, A.; Biffignandi, S.