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 - Questionnaire design (1335)
- The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study; 2013; West, B. T.
- Survey quality prediction system 2.0; 2013
- Cognitive Probes in Web Surveys: On the Effect of Different Text Box Size and Probing Exposure on Response...; 2013; Behr, D., Bandilla, W., Kaczmirek, L., Braun, M.
- Best Practice in Online Survey Research with Sensitive Topics; 2013; Kays, K., Keith, T. L., Broughal, M. T.
- Research Intentions are Nothing without Technology: Mixed-Method Web Surveys and the Coberen Wall of...; 2013; Ganassali, S., Rodriguez-Santos, C.
- The Distinctiveness of Online Research: Descriptive Assemblages, Unobtrusiveness, and Novel Kinds of...; 2013; Lanfrey, D.
- Advancing Research Methods with New Technologies; 2013; Sappleton, N.
- Data Quality in PC and Mobile Web Surveys; 2013; Mavletova, A. M.
- Virtual research assistants: Replacing human interviewers by automated avatars in virtual worlds; 2013; Hasler, B. S., Tuchman, P., Friedman, D.
- From mixed-mode to multiple devices. Web surveys, smartphone surveys and apps: has the respondent gone...; 2013; Callegaro, M.
- Designing and conducting business surveys; 2013; Snijkers, G.,Araldsen, G., , Willimack, D. K.Jones, J.
- Battle of the Scales: Understanding Respondent Scale Usage in the US and Abroad; 2013; Courtright, M., Pashupati, K., Pettit, F. A.
- Modular Survey Design: A Bite Size Proposal; 2013; Kelly, F., Stevens, S., Johnson, A.
- Cyborgs vs. Monsters: Assembling Modular Surveys to Create Complete Datasets; 2013; Johnson, E. P., Siluk, L., Tarraf, S.
- Optimizing Surveys for Smartphones: Maximizing Response Rates While Minimizing Bias; 2013; Lattery, K., Park Bartolone, G., Saunders, T.
- Shorter Isn't Always Better; 2013; Burdein, I.
- 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.
- 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.
- Pros and cons of virtual interviewers – vote in the discussion about surveytainment; 2013; Póltorak, M., Kowalski, J.
- Addressing Disclosure Concerns and Analysis Demands in a Real-Time Online Analytic System; 2013; Krenzke, T., Gentleman, J. F., Li, J., Moriarity, C.
- The General Survey System Initiative at RTI International: An Integrated System for the Collection and...; 2013; Thalji, L., Mitchell, S., Hill, C. A., Suresh, R., Speizer, H., Pratt, D.
- 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.
- Clarifying Categorical Concepts in a Web Survey.; 2013; Redline, C. D.
- Interview Duration in Web Surveys: Integrating Different Levels of Explanation; 2013; Rossmann, J., Gummer, T.
- The monetary value of good questionnaire design; 2013; Tress, F.
- Using interactive feedback to enhance response quality in Web surveys. The case of open-ended questions...; 2013; Emde, M., Fuchs, M.
- Reducing Response Order Effects in Check-All-That-Apply Questions by Use of Dynamic Tooltip Instructions...; 2013; Kunz, T., Fuchs, M.
- Slide to ruin data: How slider scales may negatively affect data quality and what to do about it; 2013; Funke, F.
- Identifying and Mitigating Satisficing in Web Surveys: Some Experimental Evidence; 2013; Blumenstiel, J. E., Rossmann, J.
- Does one really know?: Avoiding noninformative answers in a reliable way.; 2013; de Leeuw, E. D., Boevee, A., Hox, J.
- Online Mixed Mode Surveying using a Responsive Design; 2013; Kissau, K.
- Prison break: Releasing offline experiments from methodological constraints by transforming them into...; 2013; Förstel, H., Manthei, K., Mohnen, A., Berger, G.
- Research Design as an Influencing Factor for Reliability in Online Market Research; 2013; Wengrzik, J., Theuner, G.
- Seducing the respondent – how to optimise invitations in on-site online research?; 2013; Póltorak, M., Kowalski, J.
- Online Survey – Research with children on advertising impact; 2013; Funkenweh, V., Busch, J., Amthor, A. L., Boeer, A., Gaedke, J.
- HTML5 and mobile Web surveys: A Web experiment on new input types; 2013; Funke, F.
- How the screen-out influence the dropout of a commercial panel; 2013; Bartoli, B.
- Innovation in Data Collection: the Responsive Design Approach; 2013; Bianchi, A., Biffignandi, S.
- Mixed-mode including web: Recent developments at Statistics Netherlands; 2013; Luiten, A., Schouten, B.
- Web coverage in the UK and its potential impact on general population web surveys; 2013; Callegaro, M.
- Surveys on Mobile Devices: Opportunities and Challenges; 2013; Couper, M. P.
- Life history calendars - a viable method for web-based data collection?; 2013; Glasner, T., van der Vaart, W.
- Online Research, Game On!; 2013; Puleston, J.
- Comparison of web-based versus paper-and-pencil administration of a humor survey; 2013; Wang, C.-C., Cheng, C.-L.;, Liu, K.-S., Cheng, Y.-Y.
- The Design of Grids in Web Surveys; 2013; Couper, M. P., Tourangeau, R., Conrad, F. G., Zhang, C.
- Survey Research; 2013; Abbott, M. L., McKinney, J.
- Understanding and Applying Research Design; 2013; Abbott, M. L., McKinney, J.
- Large-Scale Analysis and Testing; 2013; Cao, M., Zhang, Q.
- The Science of Web Surveys; 2013; Tourangeau, R., Conrad, F. G., Couper, M. P.