Web Survey Bibliography
Title Internet and Smartphone Coverage in a National Health Survey: Implications for Alternative Modes
Author Couper, M. P.; Kelley, J.; Axinn, W.; Guyer, H.; Wagner, J.; West, B. T.
Year 2015
Access date 22.08.2016
Abstract
The rise of Internet-enabled smartphones presents an opportunity to re-examine the issue of Internet coverage and its implications for coverage bias. While a number of papers have examined cell phone coverage and Internet coverage separately, few have looked at the possible compensatory effects of joint coverage. We added two interviewer observations (one on Internet access and the other on smartphone ownership among respondents) to the National Survey of Family Growth (NSFG) with a view to exploring the feasibility of Internet-based follow-up surveys. NSFG is a national probability survey of women and men age 15-44, using a continuous design. We examine 8 quarters (2 years) of data, from September 2012 to August 2014.
Overall, we find that 82.2% of respondent report Internet access and 76.1% report having a smartphone (estimates weighted for differential selection and nonresponse). Combined, this means that 89.4% have access to the Internet, either via traditional devices or via a smartphone. We also find some evidence of compensatory coverage when looking at key gender/race/age subgroups. For instance, while Black male teens (15-17) have the lowest rate of Internet access (74.9%) and the lowest rate of smartphone usage (58.9%), when combined 82.6% have some form of Internet access.
We propose to examine the socio-demographic correlates of Internet and smartphone (and combined) coverage (access) in this population. In addition, we propose to look at the effect of differential coverage on key estimates produced by the NSFG, related to fertility, family formation, and sexual activity. While this does not address nonresponse bias issues related to alternative modes, our paper has implications for possible coverage biases that may arise in switching to a Web-based mode of data collection, either for follow-up surveys or to replace the main face-to-face data collection.
Overall, we find that 82.2% of respondent report Internet access and 76.1% report having a smartphone (estimates weighted for differential selection and nonresponse). Combined, this means that 89.4% have access to the Internet, either via traditional devices or via a smartphone. We also find some evidence of compensatory coverage when looking at key gender/race/age subgroups. For instance, while Black male teens (15-17) have the lowest rate of Internet access (74.9%) and the lowest rate of smartphone usage (58.9%), when combined 82.6% have some form of Internet access.
We propose to examine the socio-demographic correlates of Internet and smartphone (and combined) coverage (access) in this population. In addition, we propose to look at the effect of differential coverage on key estimates produced by the NSFG, related to fertility, family formation, and sexual activity. While this does not address nonresponse bias issues related to alternative modes, our paper has implications for possible coverage biases that may arise in switching to a Web-based mode of data collection, either for follow-up surveys or to replace the main face-to-face data collection.
Access/Direct link FCSM Research Conference Homepage (Abstract) / (Full text)
Year of publication2015
Bibliographic typeConferences, workshops, tutorials, presentations
Web survey bibliography - Noncoverage & sampling (851)
- Solving the Nonresponse Problem With Sample Matching?; 2016
- HUFFPOLLSTER: Why Reaching Latinos Is A Challenge For Pollsters; 2016; Jackson, N. M.; Edwards-Levy, A.; Velencia, J.
- Predictive inference for non-probability samples: a simulation study ; 2016; Buelens, B.; Burger, J.; van den Brakel, J.
- Does the Inclusion of Non-Internet Households in a Web Panel Reduce Coverage Bias?; 2016; Eckman, S.
- Quota Controls in Survey Research.; 2016; Gittelman, S. H.; Thomas, R. K.; Lavrakas, P. J.; Lange, V.
- Scientific Surveys Based on Incomplete Sampling Frames and High Rates of Nonresponse; 2016; Fahimi, M.; Barlas, F. M.; Thomas, R. K.; Buttermore, N. R.
- Doing Surveys Online ; 2016; Toepoel, V.
- Doing Online Surveys: Zum Einsatz in der sozialwissenschaftlichen Raumforschung; 2015; Nadler, R.; Petzold, K.; Schoenduwe, R.
- Response Rates and Response Bias in Web Panel Surveys; 2015; Boyle, J.; Berman, L.; Dayton, Ja.; Fakhouri, T.; Iachan, R.; Courtright, M.; Pashupati, K.
- Characteristics of the Population of Internet Panel Members; 2015; Boyle, J; Freedner, N.; Fakhouri, T.
- Internet and Smartphone Coverage in a National Health Survey: Implications for Alternative Modes; 2015; Couper, M. P.; Kelley, J.; Axinn, W.; Guyer, H.; Wagner, J.; West, B. T.
- An Overview of Mobile CATI Issues in Europe; 2015; Slavec, A.; Toninelli, D.
- Using Mobile Phones for High-Frequency Data Collection; 2015; Azevedo, J. P.; Ballivian, A.; Durbin, W.
- Willingness of Online Access Panel Members to Participate in Smartphone Application-Based Research; 2015; Pinter, R.
- Who Has Access to Mobile Devices in an Online Opt-in Panel? An Analysis of Potential Respondents for...; 2015; Revilla, M.; Toninelli, D.; Ochoa, C.; Loewe, G.
- Who Are the Internet Users, Mobile Internet Users, and Mobile-Mostly Internet Users?: Demographic Differences...; 2015; Antoun, C.
- Optimizing the Decennial Census for Mobile – A Case Study; 2015; Nichols, E. M.; Hawala, E. O.; Horwitz, R.; Bentley, M.
- App vs. Web for Surveys of Smartphone Users: Experimenting with mobile apps for signal-contingent experience...; 2015; McGeeney, K.; Keeter, S.; Igielnik, R.; Smith, A.; Rainie, L.
- On the Go: How Mobile Participants Affect Survey Results; 2015; Barlas, F. M.; Thomas, R. K.
- Variance Estimation for Surveys from Internet Panels ; 2015; Rivers, D.
- Sensitivity Analysis of Bias of Estimates from Web Surveys with Nonrandomized Panel Selection; 2015; Beresovsky, V.
- Detecting Fraud in a Survey Sample Recruited Online; 2015; Brown, D.; Dever, J. A.; Augustson, E.; Squiers, L.
- On Climbing Stairs Many Steps at a Time: The New Normal in Survey Methodology; 2015; Dillman, D. A.
- Mobile Research Methods: Opportunities and challenges of mobile research methodologies. ; 2015; Toninelli, D. (Ed.); Pinter, R.; de Pedraza, P.
- Explorations in Non - Probability Sampling Using the Web; 2015; Brick, J. M.
- On Bias Adjustments for Web Surveys; 2015; Fan, L.; Lou, W.; Landsman, V.
- Web panel surveys – a challenge for official statistics; 2015; Svensson, J.
- Estimation with Non-probability Surveys and the Question of External Validity; 2015; Dever, J. A.; Valliant, R. L.
- Can Non-full-probability Internet Surveys Yield Useful Data? A Comparison with Full-probability Face...; 2015; Simmons, A.D.; Bobo, L. D.
- The Cathie Marsh lecture: What does the failure of the polls tell us about the future of survey research...; 2015; Sturgis, P., Matheson, J.
- Hidden Populations, Online Purposive Sampling, and External Validity: Taking off the Blindfold; 2015; Barrat, M. J.; Ferris, J. A.; Lenton, S.
- Mixed Mode Design Considerations; 2015; Hupp, A.
- Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys 2015; 2015
- Analysis of four recruitment methods for obtaining normative data through a Web-based questionnaire:...; 2015; Nolte, M. T.; Shauver, M. J.; Chung, K. C.
- Doing online research involving university students with disabilities: Methodological issues; 2015; De Cesarei, A.; Baldaro, B.
- Understanding Society Innovation Panel Wave 7: Results from Methodological Experiments; 2015; Blom, A. G.; Burton, J.; Booker, C. L.; Cernat, A.; Fairbrother, M.; Jaeckle, A.; Kaminska, O.; Keusch...
- Correcting for non-response bias in contingent valuation surveys concerning environmental non-market...; 2015; Bonnichsen, O.; Boye Olsen, S.
- An Introduction to Survey Research; 2015; Cowles, E. L.; Nelson, E.
- HUFFPOLLSTER: Pollsters Debate If Modern Surveys Can Be Trusted; 2015; Blumenthal, M.; Edwards-Levy, A.; Velencia, J.
- Using Internet to Recruit Immigrants with Language and Culture Barriers for Tobacco and Alcohol Use...; 2015; Carlini, B. H.; Safioti, L.; Rue, T. C.; Miles, L.
- Online Recruitment Methods for Web-Based and Mobile Health Studies: A Review of the Literature; 2015; Lane, T. S.; Armin, J.; Gordon, Ju. S.
- iTunes Song-Gifting is a Low-Cost, Efficient Recruitment Tool to Engage High-Risk MSM in Internet Research...; 2015; Holland, C. M.; Ritchie, N. D.; Du Bois, S. N.
- Comparing the Similarity of Responses Received from Studies in Amazon’s Mechanical Turk to Studies...; 2015; Bartneck, C.; Duenser, A.; Moltchanova, E.; Zawieska, K.
- Recruiting Online: Lessons From a Longitudinal Survey of Contraception and Pregnancy Intentions of Young...; 2015; Harris, M. L.; Loxton, D.; Wigginton, B.; Lucke, J. C.
- Recruiting for addiction research via Facebook; 2015; Thornton, L. K.; Harris, K.; Baker, A.; Johnson, M.; Kay-Lambkin, F. J.
- Can a non-probabilistic online panel achieve question quality similar to that of the European Social...; 2015; Revilla, M.; Saris, W. E.; Loewe, G.; Ochoa, C.
- Innovative Recruitment Using Online Networks: Lessons Learned From an Online Study of Alcohol and Other...; 2015; Bauermeister, J. A.; Zimmerman, M. A.; Johns, M. M.; Glowacki, P. F.; Stoddard, S. A.; Volz, E. M.
- Probabilistic Web Survey Methodology in Education Centers: An Example in Spanish Schools; 2015; Tapia, J. A., Menendez, J. A.
- Understanding Participation in a Web-Based Measurement Burst Design: Response Metrics and Predictors...; 2015; Griffin, J., Patrick, M. E.
- Facebook as a Tool for Respondent Tracing; 2015; Schneider, S. J., Burke-Garcia, A., Thomas, G.