Web Survey Bibliography
Relevance & Research Question: Optimizing online questionnaires for certain browsers not only raises the risk of loosing respondents but also may bias the sample composition. In their GOR paper on the low-tech principle, Buchanan and Reips (2001) found that more educated users were more likely to turn JavaScript off. Furthermore, respondents using Mac OS scored higher on the personality trait Openness to Experience than users of Windows OS. This study focuses on the question if these differences still hold, ten years later and with a sample of experienced Internet users.
Methods & Data: The questionnaire was a Big Five personality inventory. Following the low-tech principle, participation was possible with any Web browser.
Results: Overall, 2.6% of all participants (N = 358) had JavaScript disabled. Male respondents were more likely to have JavaScript disabled than female respondents, chi^2(1, N = 344) = 11.64, p = .001, odds ratio = 15.6. Mac users scored higher on Openness (e.g., “I enjoy hearing new ideas”) than Windows users, F(1, 294) = 12.14, p = .001, eta^2 = .040. Furthermore, respondents using Macs scored lower on Agreeableness (e.g., “I am interested in other people”) than users of Windows, F(1, 294) = 9,02, p = .003, eta^2 = .030. Within respondents running Windows Extraversion (e.g., “I am the life of the party”) was slightly higher for users of the Internet Explorer in comparison to users of Firefox, F(1, 277) = 4.13, p = .043, eta^2 = .015. Finally, there was a tendency that respondents with JavaScript deactivated scored lower on Openness than respondents with this technology activated, F(1, 312) = 3.05, p = .082, eta^2 = .010.
Added Value: The present study confirms and extends the results from Buchanan and Reips (2001). A questionnaire exclusively optimized for certain OSs or browsers can seriously bias the psychological and demographical sample composition. In the present study restricting participation to respondents with JavaScript enabled would have reduced the number of male participants. Overall, it is recommended either to refrain from using complex technologies or to implement alternative low-tech versions of questionnaires as fallback.
GOR Homepage (abstract)
Web Survey Bibliography - 2012 (526)
- WebSM Study: Overview of Features of Software Packages: SurveyMonkey, QuestionPro, FluidSurveys, Wufoo...; 2012; Cehovin, G.; Vehovar, V.
- WebSM Study: Speed and efficiency of online survey tools; 2012; Cehovin, G.; Vehovar, V.
- Worldwide online research spending; 2012
- What we can learn from unintentional mobile respondents; 2012; Peterson, G.
- Using paradata to explore item-level response times in surveys; 2012; Couper, M. P., Kreuter, F.
- Using multivariate statistics, 6th Edition; 2012; Tabachnick, B. G., Fidell, L. S.
- Unintentional mobile respondents; 2012; Peterson, G.
- Tracking preference expression (DNT); 2012
- The smartphone psychology manifesto; 2012; Miller, G.
- The rise of the "connected viewer"; 2012; Smith, A., Boyles, J. L.
- The practice of social research; 2012; Babbie, E. R.
- The integration of facebook into class management: an exploratory study; 2012; Chou, P. N.
- The effects of item saliency and question design on measurement error in a self-administered survey; 2012; Stern, M. J., Smyth, J. D., Mendez, J.
- The cross platform report. Q2 -2012 - US; 2012
- Speed (necessarily) doesn’t kill: A new way to detect survey satisficing; 2012; Garland, P. et al.
- Smartphone ownership update: September 2012; 2012; Rainie, L.
- Sensitive topics in PC Web and mobile web surveys: Is there a difference?; 2012; Mavletova, A. M., Couper, M. P.
- Selection bias of internet panel surveys: A comparison with a paper-based survey and national governmental...; 2012; Tsuboi, S. et al.
- Screenwise panel: Frequently Asked Questions; 2012
- Research company spotlight - Mobile surveys; 2012
- Redeveloping the research section of Meningitis UK's website — A case study report; 2012; Witt, J. et al.
- Quality in market research. From theory to practice. 2nd Edition; 2012; Harding, D., Jackson, P.
- Participation of mobile users in traditional online studies; 2012; Jue, A.
- Online survey statistics for the mobile future. Updated with Q3 2012 data; 2012
- Ofcom technology tracker Wave 3; 2012
- Ofcom technology tracker Wave 2; 2012
- Not just playing around; 2012; Ewing, T.
- Norme di qualita' Assirm (Assirm quality rules]; 2012
- NBCU enlists Google, ComScore to track multiscreen Olympics viewing; 2012; Spangler, T.
- MRS Guidelines for online reseach; 2012
- More dirty little secrets of online panel research.; 2012
- Mobile email opens report 2nd half 2011; 2012
- Metering mobile usage. Insights from global Arbitron mobile trends panel; 2012; Verkasalo, H.
- Media tracker; 2012
- Measuring the quality of governmental websites in a controlled versus an online setting with the ‘...; 2012; Elling, S. et al.
- Measuring modern media consumption; 2012; Arini, N.
- ISO 20252. Market, opinion and social research-Vocabulary and service requirements, 2nd Edition; 2012
- Is „chapterisation“ a viable alternative to traditional progress indicators ?; 2012; Spicer, R., Dowling, Z.
- Internet use in households and by individual in 2012. Eurostat Statistics in Focus 50/2012; 2012; Seybert, H.
- Internet access - Households and individuals, 2012 part 2; 2012
- Internet access - Households and individuals, 2012; 2012
- Guide to social science data preparation. Best practice throughout the data life cycle; 2012
- Google et Médiamétrie créent une audience bimédia; 2012; Gonzales, P.
- GMI Pinnacle; 2012
- Global market research 2012; 2012
- Flowing with the mainstream. Is mobile market research finally living up to the hype?; 2012; Townsend, L.
- Explaining rising nonresponse rates in cross-sectional surveys; 2012; Brick, J. M., Williams, D.
- Eurobarometer Special surveys: Special Eurobarometer 381; 2012
- Online Surveys 2.0; 2012; Elferink, R.
- The Impact of Academic Sponsorship on Online Survey Dropout Rates; 2012; Allen, P. J., Roberts, L. D.
