Web Survey Bibliography
Title The Effect of Respondent Commitment on Response Quality in Two Online Surveys
Author Cibelli Hibben, K.
Year 2017
Access date 08.09.2017
Abstract Answering questions completely, accurately and honestly is not always the top priority for survey respondents. To the extent that the inaccuracy in survey responses is due to insufficient effort by respondents, it might help to directly ask respondents to try harder and elicit an explicit agreement from them to do so. The rationale for this technique is that agreeing or stating one's intention to behave in a certain way commits a person to carry out the terms of the agreement. Charles Cannell and his associates pioneered this technique in the late1970s and the results were promising. Existing studies found that respondents in the commitment condition (vs. control) showed the following: significantly more mentions to open-ended items, number of health conditions, amount reported for food and drink consumed, higher mean score on reported precise-to-day index for health events, checking outside sources, and sensitive reporting (Oksenberg et al., 1977a; Oksenberg et al., 1977b). Similar results for commitment were observed in a telephone survey (Miller & Cannell, 1982). In an experimental web survey, Conrad et al. (under review) found commitment to improve response accuracy particularly among respondents with a college education or more (results for the lower education groups were not significant) and that only a very small percentage of respondents refused to make the commitment (1%).While promising, much of this research was conducted decades ago, in interviewer administered modes, with limited measures of data quality.
The proposed paper presents results from two web-based studies examining the effect commitment. The first study measures the effect of commitment – “yes” or “no” – in an online labor force survey. The experiment was embedded in a survey conducted by the Institute for Labor Market and Occupational Research (Institut für Arbeitsmarkt und Berurfsforschung (IAB)) in Germany fielded in December 2014 – January 2015. The second study measures the effect of asking respondents to commit to engaging in several specific response behaviors that seem likely promote data quality, such as reading the questions carefully, and trying to be as precise as possible, in an online survey of the parents of child patients at University of Michigan (UM) Health System. It was fielded in March – May 2016. Both studies examine the effect of commitment on response accuracy as verified in administrative records – previous studies evaluating commitment have only used indirect measures of accuracy – in addition to reducing satisficing behaviors, item nonresponse, and socially desirable reporting.
Both studies produced mixed results for the overall effect of commitment. However, in Study 1 there were some particularly promising results for those who committed versus those who were invited to commit but did not, and in Study 2 for those who committed to all of the requested response behaviors versus those who committed to engage in only a few. Overall, the results offer insights into the underlying level of motivation of web survey respondents, such as their willingness to look up information in records, and raise challenging practical questions about how such techniques might be used in production surveys.
The proposed paper presents results from two web-based studies examining the effect commitment. The first study measures the effect of commitment – “yes” or “no” – in an online labor force survey. The experiment was embedded in a survey conducted by the Institute for Labor Market and Occupational Research (Institut für Arbeitsmarkt und Berurfsforschung (IAB)) in Germany fielded in December 2014 – January 2015. The second study measures the effect of asking respondents to commit to engaging in several specific response behaviors that seem likely promote data quality, such as reading the questions carefully, and trying to be as precise as possible, in an online survey of the parents of child patients at University of Michigan (UM) Health System. It was fielded in March – May 2016. Both studies examine the effect of commitment on response accuracy as verified in administrative records – previous studies evaluating commitment have only used indirect measures of accuracy – in addition to reducing satisficing behaviors, item nonresponse, and socially desirable reporting.
Both studies produced mixed results for the overall effect of commitment. However, in Study 1 there were some particularly promising results for those who committed versus those who were invited to commit but did not, and in Study 2 for those who committed to all of the requested response behaviors versus those who committed to engage in only a few. Overall, the results offer insights into the underlying level of motivation of web survey respondents, such as their willingness to look up information in records, and raise challenging practical questions about how such techniques might be used in production surveys.
Access/Direct link Conference Homepage (abstract) / (presentation)
Year of publication2017
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography (345)
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- Web-Based Survey Methodology; 2017; Wright, K. B.
- Handbook of Research Methods in Health Social Sciences; 2017; Liamputtong, P.
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- Achieving Strong Privacy in Online Survey; 2017; Zhou, Yo.; Zhou, Yi.; Chen, S.; Wu, S. S.
- Measuring Subjective Health and Life Satisfaction with U.S. Hispanics; 2017; Lee, S.; Davis, R.
- The Effect of Respondent Commitment on Response Quality in Two Online Surveys; 2017; Cibelli Hibben, K.
- In search of best practices; 2017; Kappelhof, J. W. S.; Steijn, S.
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- Comparing Twitter and Online Panels for Survey Recruitment of E-Cigarette Users and Smokers; 2016; Guillory, J.; Kim, A.; Murphy, J.; Bradfield, B.; Nonnemaker, J.; Hsieh, Y. P.
- Web based health surveys: Using a Two Step Heckman model to examine their potential for population health...; 2016; Morrissey, K.; Kinderman, P.; Pontin, E.; Tai, S.; Schwannauer, M.
- “Better do not touch” and other superstitions concerning melanoma: the cross-sectional web...; 2016; Gajda, M.; Kamińska-Winciorek, G.; Wydmański, J.; Tukiendorf, A.
- Methods for Evaluating Respondent Attrition in Web-Based Surveys; 2016; Hochheimer, C. J.; Sabo, R. T.; Krist, A. H.; Day, T.; Cyrus, J.; Woolf, S. H.
- Question order sensitivity of subjective well-being measures: focus on life satisfaction, self-rated...; 2016; Lee, S.; McClain, C.; Webster, N.; Han, S.
- Using Visual Analogue Scales in eHealth: Non-Response Effects in a Lifestyle Intervention; 2016; Kuhlmann, T.; Reips, U.-D.; Wienert, J.; Lippke, S.
- A Case Study on the Use of Propensity Score Adjustments with Web Survey Data; 2016; Parsons, V.
- Using official surveys to reduce bias of estimates from nonrandom samples collected by web surveys; 2016; Beresovsky, V.; Dorfman, A.; Rumcheva, P.
- A Feasibility Study of Recruiting and Maintaining a Web Panel of People with Disabilities; 2016; Chandler, J.
- Exploration of Methods for Blending Unconventional Samples with Traditional Probability Samples; 2016; Gellar, J.; Zhou, H.; D.; Sinclair, M. D.
- Evaluation of mode equivalence of the MSKCC Bowel Function Instrument, LASA Quality of Life, and Subjective...; 2016; Bennett, A. V.; Keenoy, K.; Shouery, M.; Basch, E.; Temple, L. K.
- Population Survey Features and Response Rates: A Randomized Experiment; 2016; Guo, Y.; Kopec, J.; Cibere, J.; Li, L. C.; Goldsmith, C. H.
- Web Health Monitoring Survey: A New Approach to Enhance the Effectiveness of Telemedicine Systems ; 2016; Romano, M. F.; Sardella, M. V.; Alboni, F.
- Question order sensitivity of subjective well-being measures: focus on life satisfaction, self-rated...; 2016; Lee, S.; McClain, C.; Webster, N.; Han, S.
- Facebook, Twitter, & Qr codes: An exploratory trial examining the feasibility of social media mechanisms...; 2016; Gu, L. L.; Skierkowski, D.; Florin, P.; Friend, K.; Ye, Y.
- Helping respondents provide good answers in Web surveys; 2016; Couper, M. P.; Zhang, C.
- The Effects of a Delayed Incentive on Response Rates, Response Mode, Data Quality, and Sample Bias in...; 2016; McGonagle, K., Freedman, V. A.
- Feature phones no barrier to conducting an effective conjoint study ; 2016; de Rooij, R.; Dossin, R.
- Patient preference: a comparison of electronic patient-completed questionnaires with paper among cancer...; 2016; Martin, P.; Brown, M.C.; Espin‐Garcia, O.; Cuffe, S.; Pringle, D.; Mahler, M.; Villeneuve, J.;...
- Detecting Insufficient Effort Responding with an Infrequency Scale: Evaluating Validity and Participant...; 2016; Huang, J. L.; Bowling, N. A.; Liu, Me.; Li, Yu.
- On-line life history calendar and sensitive topics: A pilot study; 2016; Morselli, D.; Berchtold, A.; Granell, J.-C. S.; Berchtold, And.
- An experiment comparing grids and item-by-item formats in web surveys completed through PCs and smartphones...; 2016; Revilla, M.; Toninelli, D.; Ochoa, C.
- Assessing the Effects of Participant Preference and Demographics in the Usage of Web-based Survey Questionnaires...; 2016; Mlikotic, R.; Parker, B.; Rajapakshe, R.
- Improving Inpatient Surveys: Web-Based Computer Adaptive Testing Accessed via Mobile Phone QR Codes; 2016; Chien, T. S.; Lin, W.S.
- Comparing online and telephone survey results in the context of a skin cancer prevention campaign evaluation...; 2016; Hollier, L.P.; Pettigrew, S.; Slevin, T.; Strickland, M.; Minto, C.
- Collecting Data from mHealth Users via SMS Surveys: A Case Study in Kenya; 2016; Johnson, D.
- Effect of a Post-paid Incentive on Response to a Web-based Survey; 2016; Brown, J. A.; Serrato, C. A.; Hugh, M.; Kanter, M. H.; A.; Spritzer, K. L.; Hays, R. D.
- Reducing Underreports of Behaviors in Retrospective Surveys: The Effects of Three Different Strategies...; 2016; Lugtig, P. J.; Glasner, T.; Boeve, A.
- Quantifying Under- and Overreporting in Surveys Through a Dual-Questioning-Technique Design. ; 2016; de Jong , M.; Fox, J.-P.; Steenkamp, J. - B. E. M.
- Take the money and run? Redemption of a gift card incentive in a clinician survey. ; 2016; Chen, J. S.; Sprague, B. L.; Klabunde, C. N.; Tosteson, A. N. A.; Bitton, A.; Onega, T.; MacLean, C....
- Creation and Usability Testing of a Web-Based Pre-Scanning Radiology Patient Safety and History Questionnaire...; 2016; Robinson, T. J.; DuVall, S.; Wiggins III, R
- A multi-group analysis of online survey respondent data quality: Comparing a regular USA consumer panel...; 2016; Golden, L.; Albaum, G.; Roster, C. A.; Smith, S. M.
- The effect of email invitation elements on response rate in a web survey within an online community; 2016; Petrovcic, A.; Petric, G.; Lozar Manfreda, K.
- Quota Controls in Survey Research.; 2016; Gittelman, S. H.; Thomas, R. K.; Lavrakas, P. J.; Lange, V.
- Internet-administered Health-related Quality of Life Questionnaires Compared With Pen and Paper in an...; 2016; Nitikman, M.; Mulpuri, K.; Reilly, C. W.