Web Survey Bibliography
Title Impulsiveness, Speed and Reliability in Online Questionnaire
Author Harms, C.
Year 2016
Access date 29.04.2016
Presentation PDF (527KB)
Abstract
Relevance & Research Question: Online questionnaires offer a way to collect paradata, such as response time or mouse movements. As they require participants' behavior, personality is expected to have an influence on how the questions are answered. The present study investigates how impulsiveness influences response times in an online questionnaire. A hypothesis that found mixed evidence in the past (Moltó, Segarra & Avila, 1993; Malle & Neubauer, 1991). Further we were interested in the effect of response speed on the reliability of questionnaires. Montag & Reuter (2008) found no such link. We extend their study by using more precise client-side response times.
Methods & Data: A convenience sample of N=572 participants was recruited, mainly under-graduate students at the universities Bonn and Ulm. Participants studying psychology could receive course credit for participation. Participants completed an online questionnaire that included demographic data and two personality questionnaires (NEO-FFI, 60 items, and Barrett Impulsiveness Scale, 30 items, each in German translation). Personality items were presented in randomized order for each participant. This enabled us to measure reaction time for each item independently.
Bayesian regression analysis (Rouder & Morey, 2012; Morey & Rouder, 2015) was used to test the relationship between impulsiveness and overall completion time against a model including only age and education (Yan & Tourangeau, 2008). Reliability was measured in terms of internal consistency using Cronbach's Alpha (Cronbach, 1951).
Results:Bayesian regression analysis yielded substantial evidence for an effect of age and education on completion time against no effect (BF_10 = 7.11). Testing our hypothesized model including impulsiveness against the model including only age and educational level yielded some little evidence against our model (BF_10 = 0.18).No notable differences in internal consistency were observed in any of the scales for neither very fast nor very slow subjects. All alpha scores ranged between 0.66 and 0.84 showing acceptable to good reliability.
Added Value: Our results show that (a) impulsiveness has no impact on the time a subject needs to complete a questionnaire and that (b) the speed of completion does not impact the internal consistency of self-reports. Further studies should strengthen this evidence.
Methods & Data: A convenience sample of N=572 participants was recruited, mainly under-graduate students at the universities Bonn and Ulm. Participants studying psychology could receive course credit for participation. Participants completed an online questionnaire that included demographic data and two personality questionnaires (NEO-FFI, 60 items, and Barrett Impulsiveness Scale, 30 items, each in German translation). Personality items were presented in randomized order for each participant. This enabled us to measure reaction time for each item independently.
Bayesian regression analysis (Rouder & Morey, 2012; Morey & Rouder, 2015) was used to test the relationship between impulsiveness and overall completion time against a model including only age and education (Yan & Tourangeau, 2008). Reliability was measured in terms of internal consistency using Cronbach's Alpha (Cronbach, 1951).
Results:Bayesian regression analysis yielded substantial evidence for an effect of age and education on completion time against no effect (BF_10 = 7.11). Testing our hypothesized model including impulsiveness against the model including only age and educational level yielded some little evidence against our model (BF_10 = 0.18).No notable differences in internal consistency were observed in any of the scales for neither very fast nor very slow subjects. All alpha scores ranged between 0.66 and 0.84 showing acceptable to good reliability.
Added Value: Our results show that (a) impulsiveness has no impact on the time a subject needs to complete a questionnaire and that (b) the speed of completion does not impact the internal consistency of self-reports. Further studies should strengthen this evidence.
Access/Direct link Conference Homepage (presentation)
Year of publication2016
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography - Germany (361)
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- Approaches for Evaluating Online Survey Response Quality; 2015; Gluck, N.
- Positioning of Clarification Features in Open Frequency and Open Narrative Questions; 2015; Fuchs, M.; Metzler, A.
- A Systematic Generation of an Email Pool for Web Surveys; 2015; Silber, H.; Leibold, J.; Lischewski, J.; Schlosser, S.
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- Query on Data Collection for Social Surveys; 2014; Blanke, K., Luiten, A.
- Why Do Respondents Break Off Web Surveys and Does It Matter? Results From Four Follow-up Surveys; 2014; Rossmann, J., Blumenstiel, J. E., Steinbrecher, M.
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- Instant Interactive Feedback in Grid Questions: Reminding Web Survey; 2014; Kunz, T., Fuchs, M.
- What Does the Satisfaction with Democracy Measure Mean to Respondents in Different Countries? How Cross...; 2014; Behr, D., Braun, M.
- Determinants of the starting rate and the completion rate in online panel studies; 2014; Goeritz, A.
- Assessing representativeness of a probability-based online panel in Germany; 2014; Struminskaya, B., Kaczmirek, L., Schaurer, I., Bandilla, W.
- The Influence of the Answer Box Size on Item Nonresponse to Open-Ended Questions in a Web Survey; 2014; Zuell, C., Menold, N., Koerber, S.
- Does the Choice of Header Images influence Responses? Findings from a Web Survey on Students’...; 2014; Barth, A.
- Using Paradata to Predict and to Correct for Panel Attrition in a Web-based Panel Survey; 2014; Rossmann, J., Gummer, T.
- Offline Households in the German Internet Panel; 2014; Bossert, D., Holthausen, A., Krieger, U.
- Which fieldwork method for what target group? How to improve response rate and data quality; 2014; Wulfert, T., Woppmann, A.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Improving cheater detection in web-based randomized response using client-side paradata; 2014; Dombrowski, K., Becker, C.
- Interest Bias – An Extreme Form of Self-Selection?; 2014; Cape, P. J., Reichert, K.
- Increasing data quality in online surveys 4.1; 2014; Hoeckel, H.
- Moving answers with the GyroScale: Using the mobile device’s gyroscope for market research purposes...; 2014; Luetters, H., Kraus, M., Westphal, D.
- Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information...; 2014; Schweiger, S., Oeberst, A., Cress, U.
- Undisclosed Privacy: The Effect of Privacy Rights Design on Response Rates; 2014; Haer, R., Meidert, N.
- The Effect of Benefit Wording on Consent to Link Survey and Administrative Records in a Web Survey; 2014; Sakshaug, J. W., Kreuter, F.
- GESIS Panel: Sample and Recruitment; 2014
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- Incentives on demand in a probability-based online panel: redemption and the choice between pay-out...; 2014; Schaurer, I., Struminskaya, B., Kaczmirek, L.
- Responsive designed web surveys; 2014; Dreyer, M., Reich, M., Schwarzkopf, K.
- Extra incentives for extra efforts – impact of incentives for burdensome tasks within an incentivized...; 2014; Schreier, J. H., Biethahn, N., Drewes, F.
- Innovation for television research - online surveys via HbbTV. A new technology with fantastic opportunities...; 2014; Herche, J., Adler, M.
- Asking Sensitive Questions: An Evaluation of the Randomized Response Technique Versus Direct Questioning...; 2013; Wolter, F.; Preisendoerfer, P.
- Respondent Choice of Survey Mode; 2013; Fuchs, M.
- Development and validation of a single- item scale for the relative assessment of physical attractiveness...; 2013; Lutz, J.; Kemper, C. J.; Beierlein, C.; etc.
- Accounting for the Effects of Data Collection Method Application to the International Tobacco Control...; 2013; Thompson, M. E.; Huang, Y. C.; Boudreau, C.; Fong, G. T.; van den Putte, B.; Nagelhout, G. E.; Willemsen...
- The Short-term Campaign Panel of the German Longitudinal Election Study 2009. Design, Implementation...; 2013; Steinbrecher, M., Rossmann, J.
- Too Fast, Too Straight, Too Weird: Post Hoc Identification of Meaningless Data in Internet ; 2013; Leiner, D. J.
- The Digital Divide in Europe; 2013; Zillien, N.; Marr, M.
- The Recruitment of the Access Panel of German Official Statistics from a Large Survey in 2006: Empirical...; 2013; Amarov, B.; Rendtel, U.
- Online, face-to-face and telephone surveys—Comparing different sampling methods in wine consumer...; 2013; Szolnoki, G., Hoffmann, D.
- Where does the Fair Trade price premium go? Confronting consumers' request with reality; 2013; Langen, N., Adenaeuer, L.