Web Survey Bibliography
This paper is based on two random sample trials with nearly 3,000 students in each trial (2009 and 2010 fall) which demonstrates that there are predictable drop-off points for questionnaires delivered over the Internet to a random sample of students. The questionnaire was designed to elicit alcohol, tobacco and drug-related behavior and attitudes as well as demographic information. The data suggests that in both the years the drop off rate reached 11% at the same point in the questionnaire. This point in the questionnaire was the 13th screen in a 29 screen questionnaire. After that, the drop off rate would plateau at 15% in both the years. The data also suggests that among those who dropped off, nearly 50% dropped off within the first five minutes of opening the questionnaire and the drop off would plateau about 30 minutes into the questionnaire by which time nearly 91% of the total number of drop offs had left the questionnaire. The same trend was observed in both years of the study. These findings suggest that it is useful to ensure that respondents can be offered some incentive to stay with the questionnaire when they are about half way through a long questionnaire. The fact that drop offs plateau near the half-way point is important to consider to reduce the overall drop off amount. It is also important to ensure that the respondent be offered some incentive to stay with a questionnaire within the first five minutes of opening the questionnaire. This could reduce the drop off rate significantly. Further analysis of the nature of questions and formatting of questions merit additional examination to locate other predictors of drop off.
Conference Homepage (abstract)
Web Survey Bibliography (6390)
- Using mobile devices to access the realities of youth: How identification with society influences political...; 2013; Smith, M.
- On the Use of Latent Variable Models to Detect Differences in the Interpretation of Vague Quantifiers...; 2013; Griffin, J.
- Managing mobile research: How it's different and why it matters; 2013; Kachhi-Jiwani, D., Tucker, J., Wilding-Brown, L.
- An approach to selecting online respondents; 2013; Terhanian, G.
- 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.
- 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.
- Do I Have Your Full Attention?; 2013; Cape, P. J.
- Does Sample Size Still Matter?; 2013; Bakken, D. G., Bond, M.
- 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.
- Internet-Based Recruitment to a Depression Prevention Intervention: Lessons From the Mood Memos Study...; 2013; Morgan, A. J., Jorm, A. F., Mackinnon, A. 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.
- 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.
- A standard for test reliability in group research; 2013; Ellis, J. L.
- 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.
- The comparison of road safety survey answers between web-panel and face-to-face; Dutch results of SARTRE...; 2013; Goldenbeld, C., de Craen, S.
- 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.
- 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.
- Consolidation and Standardization of Survey Operations at a Decentralized Federal Statistical Agency; 2013; Nealon, J., Gleaton, E.
- 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.
- Clarifying Categorical Concepts in a Web Survey.; 2013; Redline, C. D.
- Using Online and Paper Surveys - The Effectiveness of Mixed-Mode Methodology for Populations Over 50; 2013; De Bernardo, D. H., Curtis, A.
- The fish model: What factors affect participants while filling in an online questionnaire?; 2013; Mohamed, B., Lorenz, A., Pscheida, 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.
- Technical and methodological meta-information on current practices in online research: A full population...; 2013; Burger, C., Stieger, S.
- 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.
- Measuring wages via a volunteer web survey – a cross-national analysis of item nonresponse; 2013; Steinmetz, S., Annmaria, B.
- 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.
- 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.
- Measuring working conditions in a volunteer web survey; 2013; de Pedraza, P., Villacampa, A.
- Sampling online communities: using triplets as basis for a (semi-) automated hyperlink web crawler.; 2013; Veny, Y.
- Prison break: Releasing offline experiments from methodological constraints by transforming them into...; 2013; Förstel, H., Manthei, K., Mohnen, A., Berger, G.
- Comparison of psychometric properties of internet versions of the Marlowe-Crowne Social Desirability...; 2013; Vesteinsdottir, V., Reips, U. -D., Joinson, A. N., Porsdottir, F.
- Why are you leaving me?? - Personality predictors of answering drop out in an online-study; 2013; Thielsch, M., Nestler, S., Back, M.
- Propensity Score Weighting – Can Personality Adjust for Selectivity?; 2013; Glantz, A., Greszki, R.

