Web Survey Bibliography
Relevance & Research Question: Open-ended questions are often used to gather short numeric information in self-administered web questionnaires. Respondents are encouraged to enter numbers, quantities or frequencies into input fields, most often without any computerized formatting constraints predominantly in order to prevent item nonresponse. However, the absence of any formatting restrictions encourages large variances in answers deviating from the desired format, including value ranges, estimations, alphanumeric supplements, or even different measuring units which affect data quality negatively, and increase the efforts for data cleansing and preparation. Thus, concise and clear formatting instructions are needed to guide respondents providing answers in the desired format. Considering the fact that instructions are likely to be ignored the question arises how different modes of verbal instructions and visual cues can be applied to improve the impact of formatting instructions, and finally to enhance data quality.
Methods & Data: In a between-subjects field experiment conducted among university freshman students in an opt-in panel (N=670), we tested different visual modes of formatting instructions in open-ended numeric questions: (1) conventional instruction in a static manner, (2) dynamic instruction in a tooltip appearing when the mouse cursor hovers over the input field, and (3) symbolic instruction in terms of pre-defined default values in the input field indicating the desired response format. The effectiveness of each instruction mode was determined by the proportion of formally correct answers.
Results: Findings indicated that the implementation of dynamic formatting elements in terms of tooltips or default values had no positive effect on an improvement of response quality compared to conventional static formatting instructions. Even a combination of tooltips and pre-filled symbols could not achieve a significant increase in correctly formatted answers compared to the sole presentation of a fixed instruction.
Added Value: The results indicated that static formatting instructions should not be replaced hastily without examining the effect of dynamic elements sufficiently. However, initial findings suggested the potential of dynamic formatting instructions in enhancing the positive effect of conventional instructions.
GOR Homepage (abstract) / (presentation)
Web Survey Bibliography - Nonresponse (1913)
- Effects of Lotteries on Response Behavior in Online Panels; 2013; Goeritz, A., Luthe, S. C.
- Lotteries and study results in market research online panels; 2013; Goeritz, A., Luthe, S. C.
- Using Paradata to Study Response to Within-Survey Requests; 2013; Sakshaug, J. W.
- Improving Surveys with Paradata: Analytic Uses of Process Information; 2013; Kreuter, F.
- A nationwide web-based freight data collection; 2013; Samimi, A., Mohammadian, A., Kawamura, K.
- Mode Matters: Evaluating Response Comparability in a Mixed-Mode Survey; 2013; Bowyer, B. T., Rogowski, J. C.
- Comparing Survey Results Obtained via Mobile Devices and Computers: An Experiment With a Mobile Web...; 2013; de Bruijne, M., Wijnant, A.
- Methodological Considerations of Qualitative Email Interviews; 2013; Nehls, K.
- Reducing Response Burden for Enterprises Combining Methods for Data Collection on the Internet; 2013; Vik, T.
- Advancing Research Methods with New Technologies; 2013; Sappleton, N.
- Data Quality in PC and Mobile Web Surveys; 2013; Mavletova, A. M.
- By the Numbers: Theory of adaptation or survival of the fittest?; 2013; Cavallaro, K.
- Designing and conducting business surveys; 2013; Snijkers, G.,Araldsen, G., , Willimack, D. K.Jones, J.
- Do I Have Your Full Attention?; 2013; Cape, P. J.
- Optimizing Surveys for Smartphones: Maximizing Response Rates While Minimizing Bias; 2013; Lattery, K., Park Bartolone, G., Saunders, T.
- Solving the Unintentional Mobile Challenge; 2013; Peterson, G., Mechling, J., LaFrance, J., Ham, G.
- Mobile Research Risk: What Happens to Data Quality When Respondents Use a Mobile Device for a Survey...; 2013; Baker-Prewitt, J.
- Challenges for Researchers Investigating Contraceptive Use and Pregnancy Intentions of Young Women Living...; 2013; Herbert, D. L., Loxton, D., Bateson, D., Weisberg, E., Lucke, J. C.
- Using a web-based survey tool to undertake a Delphi study: Application for nurse education research; 2013; Gill, F. J., Leslie, G. D., Grech, C., Latour, J. M.
- Addressing Survey Nonresponse Issues: Implications for ATE Principal Investigators, Evaluators, and...; 2013; Welch, W. W., Barlau, A. N.
- Pros and cons of virtual interviewers – vote in the discussion about surveytainment; 2013; Póltorak, M., Kowalski, J.
- Examination of the equivalence of self-report survey-based paper-and-pencil and internet data collection...; 2013; Weigold, A., Weigold, I. K., Russell, E. J.
- An Assessment of Incentive Versus Survey Length Trade-offs in a Web Survey of Radiologists; 2013; Ziegenfuss, J. Y., Niederhauser, B. D., Kallmes, D., Beebe, T. J.
- Using Online and Paper Surveys - The Effectiveness of Mixed-Mode Methodology for Populations Over 50; 2013; De Bernardo, D. H., Curtis, A.
- The monetary value of good questionnaire design; 2013; Tress, F.
- Slide to ruin data: How slider scales may negatively affect data quality and what to do about it; 2013; Funke, F.
- Measuring wages via a volunteer web survey – a cross-national analysis of item nonresponse; 2013; Steinmetz, S., Annmaria, B.
- Does one really know?: Avoiding noninformative answers in a reliable way.; 2013; de Leeuw, E. D., Boevee, A., Hox, J.
- Sensitive Topics in PC and Mobile Web Surveys; 2013; Mavletova, A. M., Couper, M. P.
- Mobile Research Performance: How Mobile Respondents Differ from PC Users Concerning Interview Quality...; 2013; Schmidt, S., Wenzel, O.
- Who responds to website visitor satisfaction surveys?; 2013; Andreadis, I.
- Why are you leaving me?? - Personality predictors of answering drop out in an online-study; 2013; Thielsch, M., Nestler, S., Back, M.
- Seducing the respondent – how to optimise invitations in on-site online research?; 2013; Póltorak, M., Kowalski, J.
- E-questionnaire in cross-sectional household surveys; 2013; Karaganis, M.
- GESIS Online Panel Pilot: Results from a Probability-Based Online Access Panel; 2013; Kaczmirek, L., Bandilla, W., Schaurer, I., Struminskaya, B., Weyandt, K.
- How the screen-out influence the dropout of a commercial panel; 2013; Bartoli, B.
- Break-off and attrition in the GIP amongst technologically experienced and inexperienced participants...; 2013; Blom, A. G., Bossert, D., Clark, V., Funke, F., Gebhard, F., Holthausen, A., Krieger, U., Wachenfeld...
- Nonresponse and Nonresponse Bias in a Probability-Based Internet Panel; 2013; Blom, A. G., Bossert, D., Funke, F., Gebhard, F., Holthausen, A., Krieger, U.
- Rewards - Money for Nothing?; 2013; Cape, P. J., Martin, P.
- Effects of incentive reduction after a series of higher incentive waves in a probability-based online...; 2013; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- Timing of Nonparticipation in an Online Panel: The effect of incentive strategies; 2013; Douhou, S., Scherpenzeel, A.
- Mixed-mode including web: Recent developments at Statistics Netherlands; 2013; Luiten, A., Schouten, B.
- Surveys on Mobile Devices: Opportunities and Challenges; 2013; Couper, M. P.
- Experiences from a probability-based Internet panel: Sample, recruitment and participation; 2013; Scherpenzeel, A.
- Participation and engagement in web surveys of the general population: An overview of challenges and...; 2013; Roberts, C.
- Using Web Survey Panels to Estimate Population Characteristics: A Comparison of Alternative Approaches...; 2013; Rivers, D.
- Online Research, Game On!; 2013; Puleston, J.
- The Design of Grids in Web Surveys; 2013; Couper, M. P., Tourangeau, R., Conrad, F. G., Zhang, C.
- Understanding and Applying Research Design; 2013; Abbott, M. L., McKinney, J.
- Virtual Research Methods; 2013; Hine, C.
