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 - Online measurement (796)
- Tablets and Smartphones and Netbooks, Oh My! Effects of Device Type on Respondent Behavior; 2013; Ross, H., Mendelson, J., Lackey, M.
- Multi-Mode Survey Administration: Does Offering Multiple Modes at Once Depress Response Rates?; 2013; Newsome, J., Levin, K., Langetieg, P., Vigil, M., Sebastiani, M.
- Utilizing the Web in a Multi-Mode Survey; 2013; Venkataraman, L.
- Changing to a Mixed-Mode Design: The Role of Mode in Respondents’ Decisions About Participation...; 2013; Collins, D., Mitchell, M., Toomes, M.
- Internet Response for the Decennial Census – 2012 National Census Test; 2013; Reiser, C.
- Lotteries and study results in market research online panels; 2013; Goeritz, A., Luthe, S. C.
- The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study; 2013; West, B. T.
- Paradata for Coverage Research ; 2013; Eckman, S.
- Improving Surveys with Paradata: Analytic Uses of Process Information; 2013; Kreuter, F.
- A nationwide web-based freight data collection; 2013; Samimi, A., Mohammadian, A., Kawamura, K.
- Mode Matters: Evaluating Response Comparability in a Mixed-Mode Survey; 2013; Bowyer, B. T., Rogowski, J. C.
- Comparing Survey Results Obtained via Mobile Devices and Computers: An Experiment With a Mobile Web...; 2013; de Bruijne, M., Wijnant, A.
- 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.
- The E-Interview in Qualitative Research; 2013; Bampton, R., Cowton, C., Downs, Y.
- 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.
- Reducing Response Burden for Enterprises Combining Methods for Data Collection on the Internet; 2013; Vik, T.
- Measuring Wages Worldwide: Exploring the Potentials and Constraints of Volunteer Web Surveys; 2013; Steinmetz, S., Raess, D., Tijdens, K., de Pedraza, P.
- Using Web Surveys for Psychology Experiments: A Case Study in New Media Technology for Research; 2013; Peden, B. F., Tiry , A. M.
- The Distinctiveness of Online Research: Descriptive Assemblages, Unobtrusiveness, and Novel Kinds of...; 2013; Lanfrey, D.
- Sampling, Channels, and Contact Strategies in Internet Survey; 2013; Macrì, E., Tessitore, C.
- Advancing Research Methods with New Technologies; 2013; Sappleton, N.
- Data Quality in PC and Mobile Web Surveys; 2013; Mavletova, A. M.
- From mixed-mode to multiple devices. Web surveys, smartphone surveys and apps: has the respondent gone...; 2013; Callegaro, M.
- Moving an established survey online – or not?; 2013; Barber, T., Chilvers, D., Kaul, S.
- On the Use of Latent Variable Models to Detect Differences in the Interpretation of Vague Quantifiers...; 2013; Griffin, J.
- An approach to selecting online respondents; 2013; Terhanian, G.
- 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.
- Does Sample Size Still Matter?; 2013; Bakken, D. G., Bond, M.
- 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.
- 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.
- 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.
- 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.
- The fish model: What factors affect participants while filling in an online questionnaire?; 2013; Mohamed, B., Lorenz, A., Pscheida, D.
- 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.
- 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.
- 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.
- Comparison of psychometric properties of internet versions of the Marlowe-Crowne Social Desirability...; 2013; Vesteinsdottir, V., Reips, U. -D., Joinson, A. N., Porsdottir, F.
