Web Survey Bibliography
Title Behavioral Intention Measurement: International Findings
Source RC33 6th International Conference on Social Science Methodology: Recent Developments and Applications in Social Research Methodology, 2004
Access date 16.09.2004
Abstract There are a variety of measures of behavioural intention, though little empirical attention has been directed to determine if one form of measurement might be any better than any other. In one of the few experiments on behavioural intention measurement, Thomas and Behnke (2004) found that unipolar intention scales had greater concurrent validity with behavioural measures than bipolar measures and that 5 response categories led to maximal validity (when comparing scales ranging from 2 to 11 categories). The study reported here sought to extend these findings to international measurement. In an online survey, we administered a survey to over 22,000 respondents in 8 different countries and in 5 different language versions. Respondents were asked how often they engaged in each of 10 behaviours in the past 30 days (e.g. exercising vigorously, attending a religious service, eating chocolate) and then were asked to indicate how likely they would be to engage in each behaviour in the next 30 days. The respondents were randomly assigned to a behavioural intention measure that was either unipolar (Not at all likely – Extremely likely) or bipolar (Very unlikely – Very likely). In addition, respondents were assigned a scale that was made up of either 2, 3, 4, 5, 6, or 7 response categories. In general, increasing the number of response categories was associated with higher validity for both unipolar and bipolar scales, though no increase in validity was noted with more than 5 response categories for the unipolar scale and more than 6 response categories for the bipolar scale. In addition, we found that across nations and languages, the unipolar scale led to superior criterionrelated validity with 5 response categories.
Bibliographic typeConferences, workshops, tutorials, presentations
Year of publication2004
Web Survey Bibliography - Terhanian, G. (31)
- An approach to selecting online respondents; 2013; Terhanian, G.
- Thinking Differently About How to Select Respondents for Surveys; 2012; Terhanian, G., Bremer, J.
- A Smarter Way to Select Respondents for Surveys; 2012; Terhanian, G., Bremer, J.
- Beyond the Blank-Canvas Approach ; 2010; Terhanian, G.
- Response Formats in Cross-cultural Comparisons in Web-based Surveys; 2009; Thomas, R. K.l, Terhanian, G., Funke, F.
- Changing times, changing modes: The future of public opinion polling?; 2008; Terhanian, G.
- Parallel Phone and Web-based Interviews: Effects of Sample and Weighting on Comparability and Validity...; 2008; Thomas, R. K., Krane, D., Taylor, H., Terhanian, G.
- Truth in measurement: Comparing Web Based interviewing Techniques; 2007; Couper, M. P., Terhanian, G., Bremer, J., Thomas, R. K.
- The Best of Intentions: Response Format Effects on Measures of Behavioral lntention ; 2007; Thomas, R. K., Klein, J. D., Behnke, C. S., Terhanian, G.
- Attitude Measurement in Phone and Online Surveys: Can Different Modes and Samples Yield Similar Results...; 2006; Thomas, R. K., Krane, D., Taylor, H., Terhanian, G.
- Multi-Mode Research and Data Linkage. Theoretical and Practical Advice; 2005; Terhanian, G.
- Comparing data from online and face-to-face surveys; 2005; Duffy, C., Smith, K., Terhanian, G., Bremer, J.
- Creative Applications of Selection Bias Modelling in Market Research; 2005; Terhanian, G., Bremer, J.
- Measuring television viewership through a multi-method approach; 2004; Terhanian, G., Bremer, J., Delaney, T. F., Thomas, R. K.
- Behavioral Intention Measurement: International Findings; 2004; Thomas, R. K., Terhanian, G., Bayer, L. R.
- Propensity Score Matching as a Bias Correction Method for Internet-based Studies; 2004; Bremer, J., Terhanian, G., Strange, P.
- Not Sure About "Don't Know"?: Effects of Response Choice in Mixed Mode Surveys; 2002; Terhanian, G., Thomas, R. K., Bremer, J., Smith, R.
- The record of internet-based opinion polls in predicting the results of 72 races in the November 2000...; 2001; Taylor, H., Bremer, J., Overmeyer, C., Siegel, J.W., Terhanian, G.
- Touchdown! Online polling scores big in November 2000; 2001; Terhanian, G., Bremer, J., Overmeyer, C., Siegel, J.W., Taylor, H.
- Using Internet polling to forecast the 2000 elections; 2001; Terhanian, G., Taylor, H., Bremer, J., Overmeyer, C., Siegel, J.W.
- Exploiting analytical advances. Minimizing the biases associated with Internet-based surveys of non-...; 2001; Terhanian, G., Thomas, R. K., Bremer, J., Smith, R.
- How To Ensure the Accuracy Of Internet Research; 2001; Terhanian, G.
- Reducing Error Associated with Non-Probability Sampling through Propensity Scores: Evidence from Election...; 2001; Terhanian, G., Marcus, S., Bremer, J., Smith, R.
- The Accuracy of Harris Interactive's Pre-Election Polls of 2000; 2001; Terhanian, G., Taylor, H., Bremer, J., Siegel, J.W., Smith, R.
- A Propensity Score Adjustment for Selection Bias in Online Surveys; 2000; Bremer, J., Terhanian, G., Smith, R.
- Advance to the Next Level: Online Methodologies and Best Practices; 2000; Terhanian, G.
- How To Produce Credible, Trustworthy Information Through Internet-Based Survey Research; 2000; Terhanian, G.
- Understanding Online Research: Lessons from the Harris Poll Online; 1999; Terhanian, G.
- Beyond Questions: Influences on Web Survey Testing; 1999; Terhanian, G., Jeavons, A.
- Heady Days Are Here Again. Online polling is rapidly coming of age; 1999; Taylor, H., Terhanian, G.
- Understanding the Online Population: Lessons from the Harris Poll and the Harris Poll Online; 1999; Black, G. S., Terhanian, G.