Web Survey Bibliography
Title Dynamic Instructions in Check-All-That-Apply Questions
Year 2016
Access date 08.06.2016
Abstract
In check-all-that-apply questions, respondents are required to select all applicable responses. Although check-all-that-apply questions are one of
the most commonly used question formats in (Web) surveys, respondents often do not spend sufficient effort to thoroughly process each of the response alternatives. Instead, respondents tend to select one of the first alternatives without sufficiently considering the remaining ones, resulting in primacy effects and an overall lower number of responses then actually apply to them. On the contrary, respondents may select response alternatives that apply to them only vaguely, resulting in a considerably higher number of responses than desired. In order toensure comparability researchers often use instructions with check-all-that-apply questions that specify the number of responses desired (e.g., "Please select the three most important aspects."). However, such instructions are often overlooked or ignored by respondents. Web surveys offer the opportunity toimplement dynamic design features that possibly increase the respondents’ attention to such instructions. In this paper, we assess the effectiveness of instant feedback messages appearing once respondents start answering a question. Using a between-subjects design, the effectiveness of providing instructions either in the form of static instructions that are always visible together with the question stem (EG1), dynamic instructions that instantly appear once respondents start answering the question (EG2), or a combination of both (EG3) was assessed. Experimental conditions were evaluated compared to a control group where no instruction was provided (CG). Initial findings concerning the effectiveness of different instruction types showed that a combination of both static and dynamic instructions is most effective in obtaining the desired number of responses. Comparisons with importance ratings shed lighton the question whether respondents actually select the most important responses. In addition, response order effects were assessed in order to determine the extent of satisficing behavior in each experimental condition.
the most commonly used question formats in (Web) surveys, respondents often do not spend sufficient effort to thoroughly process each of the response alternatives. Instead, respondents tend to select one of the first alternatives without sufficiently considering the remaining ones, resulting in primacy effects and an overall lower number of responses then actually apply to them. On the contrary, respondents may select response alternatives that apply to them only vaguely, resulting in a considerably higher number of responses than desired. In order toensure comparability researchers often use instructions with check-all-that-apply questions that specify the number of responses desired (e.g., "Please select the three most important aspects."). However, such instructions are often overlooked or ignored by respondents. Web surveys offer the opportunity toimplement dynamic design features that possibly increase the respondents’ attention to such instructions. In this paper, we assess the effectiveness of instant feedback messages appearing once respondents start answering a question. Using a between-subjects design, the effectiveness of providing instructions either in the form of static instructions that are always visible together with the question stem (EG1), dynamic instructions that instantly appear once respondents start answering the question (EG2), or a combination of both (EG3) was assessed. Experimental conditions were evaluated compared to a control group where no instruction was provided (CG). Initial findings concerning the effectiveness of different instruction types showed that a combination of both static and dynamic instructions is most effective in obtaining the desired number of responses. Comparisons with importance ratings shed lighton the question whether respondents actually select the most important responses. In addition, response order effects were assessed in order to determine the extent of satisficing behavior in each experimental condition.
Access/Direct link Conference Homepage (abstract)
Year of publication2016
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography (4086)
- Respondent Processing of Rating Scales and the Scale Direction Effect ; 2016; Caporaso, A.
- The Effects of Pictorial vs. Verbal Examples on Survey Responses ; 2016; Sun, H.; Bertling, J.; Almonte, D.
- Evaluating Grid Questions for 4th Graders; 2016; Maitland, A.
- Mixing Modes: Challenges (and Tradeoffs) of Adapting a Mailed Paper Survey to the Web ; 2016; Wilkinson-Flicker, S.; McPhee, C. B.; Medway, R.; Kaiser, A.; Cutts, K.
- An Examination of How Survey Mode Affect Eligibility, Response and Health Condition Reporting Rates...; 2016; Stern, M. J.; Ghandour, R.
- Investigating Measurement Error through Survey Question Placement ; 2016; Wilson, A.; Wine, J.; Janson, N.; Conzelmann, J.; Peytcheva, E.
- Instructions in Self-administered Survey Questions: Do They Improve Data Quality or Just Make the Questionnaire...; 2016; Redline, C. D.; Zukerberg, A.; Owens, C.; Ho, A.
- Usability Testing within Agile Process; 2016; Holland, T.
- Exploring Why Web Surveys Take Longer to Complete on Smartphones than PCs: Findings from a Within-subjects...; 2016; Antoun, C.; Cernat, A.
- Making Mobile Web Surveys Accessible; 2016; Malakhoff, L.
- Association of Eye Tracking with Other Usability Metrics ; 2016; Olmsted, E. L.
- Cognitive Probing Methods in Usability Testing – Pros and Cons; 2016; Nichols, E. M.
- Grids and Online Surveys: Do More Complex Grids Induce Survey Satisficing? Evidence from the Gallup...; 2016; Wang, Me.; McCutcheon, A. L.
- Assessing the Accuracy of 51 Nonprobability Online Panels and River Samples: A Study of the Advertising...; 2016; Yang,Y.;Callegaro,M.;Yang,Y.;Callegaro,M.;Chin,K.;Yang,Y.;Villar,A.;Callegaro, M.; Chin, K.; Krosnick...
- Calculating Standard Errors for Nonprobability Samples when Matching to Probability Samples ; 2016; Lee, Ad.; ZuWallack, R. S.
- Communicating Data Use and Privacy: In-person versus Web based methods for message testing ; 2016; Clark Fobia, A.; Hunter Childs, J. E.
- User Experience and Eye-tracking: Results to Optimize Completion of a Web Survey and Website Design ; 2016; Walton, L.; Ricci, K.; Libman Barry, A.; Eiginger, C.; Christian, L. M.
- Estimated-control Calibrated Estimates from Nonprobability Surveys; 2016; Dever, J. A.
- Decomposing Selection Effects in Non-probability Samples ; 2016; Mercer, A. W.; Keeter, S.; Kreuter, F.
- The Effect of Emphasizing the Web Option in a Mixed-mode Establishment Survey ; 2016; O'Brien, J.; Rajapaksa, S.; Schafer, B.; Langetieg, P.
- A Multi-phase Exploration Into Web-based Panel Respondents: Assessing Differences in Recruitment, Respondents...; 2016; Redlawsk, D.; Rogers, K.; Borie-Holtz, D.
- Effect of Clarifying Instructions on Response to Numerical Open-ended Questions in Self-administered...; 2016; Kumar Chaudhary, A.; Israel, G. D.
- Exploring the Feasibility of Using Facebook for Surveying Special Interest Populations ; 2016; Lee, C.; Jang, S.
- National Estimates of Sexual Minority Women Alcohol Use through Web Based Respondent Driven Sampling...; 2016; Farrell Middleton, D.; Iachan, R.; Freedner-Maguire, N.; Trocki, K.; Evans, C.
- Bringing Fair Market Rent Surveys into the 21st Century – Evaluating the Effectiveness of MSG...; 2016; Dayton, J.; Brassell, T.; Cooper, V.; Dion, R.; Williams, R.
- Measuring Survey Behavior of Smartphone Users; 2016; Luks, S.; Phillips, R.
- Practical Considerations for Using Vignettes to Evaluate Survey Items ; 2016; Steiger, D. M.; Williams, Do.; Edwards, W. S.; Cantor, D.; Truman, J.
- Using Web Panels to Quantify the Qualitative: The National Center for Health Statistics Research and...; 2016; Scanlon, P. J.
- Impact of Field Period Length in the Estimates of Sexual Victimization in a Web-based Survey of College...; 2016; Berzofsky, M.; Peterson, K.; Shook-Sa, B. E.; Lindquist, C.; Krebs, C.
- Longitudinal Online Ego-centric Social Network Data Collection with EgoWeb 2.0 ; 2016; Amin, A.; Kennedy, D.
- Influences on Item Response Times in a Multinational Web Survey ; 2016; Phillips, B. T.; Kolenikov, S.; Howard Ecklund, E.; Ackermann, A.; Brulia, A.
- QR Codes for Survey Access: Is It Worth It?; 2016; Allen, L.; Marlar, J.
- An Exploration of the Relationship between Usability Testing and Data Verification ; 2016; Langer Tesfaye, C.; Kurmlavage, V.
- Beyond the Survey: Improving Data Insights and User Experience with Mobile Devices ; 2016; Graham, P.; Lew, G.
- User Experience Considerations for Contextual Product Surveys on Smartphones ; 2016; Sedley, A.; Mueller, H.
- The Differential Effect of Mobile-friendly Surveys on Data Quality; 2016; Horwitz, R.
- Embedding Survey Questions within Non-research Mobile Apps: A Method for Collecting High-quality Data...; 2016; Bapna, V.; Antoun, C.
- Does Changing Monetary Incentive Schemes in Panel Studies Affect Cooperation? A Quasi-experiment on...; 2016; Schaurer, I.; Bosnjak, M.
- Survey Mode and Mail Method: A Practical Experiment in Survey Fielding for a Multi-round Survey ; 2016; Sullivan, B. D.; Duda, N.; Bogen, K.; Clusen, N. A.; Wakar, B.; Zhou, H.
- Web Probing for Question Evaluation: The Effects of Probe Placement ; 2016; Fowler, S.; Willis, G. B.; Moser, R. P.; Townsend, R. L. M.; Maitland, A.; Sun, H.; Berrigan, D.
- Early-bird Incentives: Results From an Experiment to Determine Response Rate and Cost Effects ; 2016; De Santis, J.; Callahan, R.; Marsh, S.; Perez-Johnson, I.
- Using Cash Incentives to Help Recruitment in a Probability Based Web Panel: The Effects on Sign Up Rates...; 2016; Krieger, U.
- Assessing Changes in Coverage Bias of Web Surveys a s Internet Access Increases in the United States...; 2016; Sterrett, D.; Malato, D.; Benz, J.; Tompson, T.; English, N.
- Timing is Everything: Discretely Discouraging Mobile Survey Response through the Timing of Email Contacts...; 2016; Richards, A.; C.; Shook-Sa, B. E.; C.; Berzofsky, M.; Smith, A. C.
- Dynamic Instructions in Check-All-That-Apply Questions ; 2016; Kunz, T.; Fuchs, M.
- Patterns of Unit and Item Nonresponse in a Multinational Web Survey ; 2016; Ackermann, A.; Howard Ecklund, E.; Phillips, B. T.; Brulia, A.
- Debunking Myths About the Quality of Industry and O ccupation Data Collected Through Self-administered...; 2016; Hurwitz, F. I.; Stein, J.; Skaff, A. L.
- Desktops, Tablets and Phones, Oh My! Device Prefere nce for Web Based Surveys ; 2016; Schy, S.; Ghirardelli, A.; Morrison, H.
- Assessing Potential Bias in Respondent-driven Incident Based Data from a Web Survey of College Students...; 2016; Peterson, K.; Berzofsky, M.; Shook-Sa, B. E.; Krebs, C.; Lindquist, C.
- Making Connections on the Internet: Online Survey Panel Communications ; 2016; Libman Barry, A.; Eiginger, C.; Walton, L.; Ricci, K.