Web Survey Bibliography
BACKGROUND:
E-cigarettes have rapidly increased in popularity in recent years, driven, at least in part, by marketing and word-of-mouth discussion on Twitter. Given the rapid proliferation of e-cigarettes, researchers need timely quantitative data from e-cigarette users and smokers who may see e-cigarettes as a cessation tool. Twitter provides an ideal platform for recruiting e-cigarette users and smokers who use Twitter. Online panels offer a second method of accessing this population, but they have been criticized for recruiting too few young adults, among whom e-cigarette use rates are highest.
OBJECTIVE:
This study compares effectiveness of recruiting Twitter users who are e-cigarette users and smokers who have never used e-cigarettes via Twitter to online panelists provided by Qualtrics and explores how users recruited differ by demographics, e-cigarette use, and social media use.
METHODS:
Participants were adults who had ever used e-cigarettes (n=278; male: 57.6%, 160/278; age: mean 34.26, SD 14.16 years) and smokers (n=102; male: 38.2%, 39/102; age: mean 42.80, SD 14.16 years) with public Twitter profiles. Participants were recruited via online panel (n=190) or promoted tweets using keyword targeting for e-cigarette users (n=190). Predictor variables were demographics (age, gender, education, race/ethnicity), e-cigarette use (eg, past 30-day e-cigarette use, e-cigarette puffs per day), social media use behaviors (eg, Twitter use frequency), and days to final survey completion from survey launch for Twitter versus panel. Recruitment method (Twitter, panel) was the dependent variable.
RESULTS:
Across the total sample, participants were recruited more quickly via Twitter (incidence rate ratio=1.30, P=.02) than panel. Compared with young adult e-cigarette users (age 18-24 years), e-cigarette users aged 25 to 34 years (OR 0.01, 95% CI 0.00-0.60, P=.03) and 35 to 44 years (OR 0.01, 95% CI 0.00-0.51, P=.02) were more likely to be recruited via Twitter than panel. Smokers aged 35 to 44 years were less likely than those aged 18 to 24 years to be recruited via Twitter than panel (35-44: OR 0.03, 95% CI 0.00-0.49, P=.01). E-cigarette users who reported a greater number of e-cigarette puffs per day were more likely to be recruited via Twitter than panel compared to those who reported fewer puffs per day (OR 1.12, 95% CI 1.05-1.20, P=.001). With each one-unit increase in Twitter usage, e-cigarette users were 9.55 times (95% CI 2.28-40.00, P=.002) and smokers were 4.91 times (95% CI 1.90-12.74, P=.001) as likely to be recruited via Twitter than panel.
CONCLUSIONS:
Twitter ads were more time efficient than an online panel in recruiting e-cigarette users and smokers. In addition, Twitter provided access to younger adults, who were heavier users of e-cigarettes and Twitter. Recruiting via social media and online panel in combination offered access to a more diverse population of participants.
Web survey bibliography - Marketing/business (336)
- Achieving Strong Privacy in Online Survey; 2017; Zhou, Yo.; Zhou, Yi.; Chen, S.; Wu, S. S.
- Where, When, How and with What Do Panel Interviews Take Place and Is the Quality of Answers Affected...; 2017; Niebruegge, S.
- Is There a Future for Surveys; 2017; Miller, P. V.
- Mobile Research im Kontext der digitalen Transformation; 2017; Friedrich-Freksa, M.
- Virtual reality meets sensory research; 2017; Depoortere, L.
- Online customer journey analysis: a data science toolbox; 2017; Bonnay, D.
- 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.
- Statistical Design for Online Experiments Across Desktops, Tablets, Smartphones (and Maybe Wearable...; 2016; Qian, P.; Sadeghi, S.; Arora, N. K.
- FocusVision 2015 Annual MR Technology Report; 2016; Macer, T., Wilson, S.
- The Effects of a Delayed Incentive on Response Rates, Response Mode, Data Quality, and Sample Bias in...; 2016; McGonagle, K., Freedman, V. A.
- A look at the unique data-gathering process behind the Harvard Impact Study; 2016; Vitale, J.
- Are sliders too slick for surveys?; 2016; Buskirk, T. D.
- Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk; 2016; Berinsky, A.; Huber, G. A.; Lenz, G. S.
- Web-based versus Paper-based Survey Data: An Estimation of Road Users’ Value of Travel Time Savings...; 2016; Kato, H.; Sakashita, A.; Tsuchiya, Tak.
- An Examination of Opposing Responses on Duplicated Multi-Mode Survey Responses; 2016; Djangali, A.
- Scientific Surveys Based on Incomplete Sampling Frames and High Rates of Nonresponse; 2016; Fahimi, M.; Barlas, F. M.; Thomas, R. K.; Buttermore, N. R.
- Adapting Labour Force Survey questions from interviewer-administered modes for web self-completion in...; 2015; Betts, P.; Cubbon, B.
- Internet Panels, Professional Respondents, and Data Quality; 2015; Matthijsse, S.; De Leeuw, E. D.; Hox, J.
- Are they willing to use the web? First results of a possible switch from PAPI to CAPI/CAWI in an establishment...; 2015; Ellguth, P.; Kohaut, S.
- GreenBook Research Industry Trends Report; 2015; Murphy, L. (Ed.)
- The role of gamification in better accessing reality and hence increasing data validity ; 2015; Bailey, P.; Kernohan, H.; Pritchard, G.
- Rewarding the Truth; 2015; Puleston, J.
- Impact of raising awareness of respondents on the measurement quality in a web survey; 2015; Revilla, M.
- Email subject lines and response rates to invitations to participate in a web survey and a face-to-face...; 2015; Sappleton, N.; Lourenco, F.
- 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.
- Mode Effects in Mixed-Mode Economic Surveys: Insights from a Randomized Experiment; 2015; Hsu, J. W.; McFall, B. H.
- Web-based survey, calibration, and economic impact assessment of spending in nature based recreation; 2015; Paudel, K. P., Devkota, N., Gyawali, B.
- The Influence of Answer Box Format on Response Behavior on List-Style Open-Ended Questions; 2014; Keusch, F.
- Improving Survey Response Rates in Online Panels Effects of Low-Cost Incentives and Cost-Free Text Appeal...; 2014; Pedersen, M. J., Nielsen, C. V.
- Matrix versus paging designs in a brand attribution task; 2014; Conrad, F. G., McCullough, W., Nishimura, R.
- Internet-Based Surveys: Methodological Issues; 2014; Albaum, G., Brockett, P., Golden, L., Han, V., Roster, C. A., Smith, S. M., Wiley, J. B.
- Use of a Google Map Tool Embedded in an Internet Survey Instrument: Is it a Valid and Reliable Alternative...; 2014; Dasgupta, S., Vaughan, A. S., Kramer, M. R., Sanchez, T. H., Sullivan, P. S.
- Sequential or Simultaneous Multi-Mode? Results from Two Large Surveys of Electric Utility Consumers; 2014; Jackson, C., Ledoux, C.
- Targeting the bias – the impact of mass media attention on sample composition and representativeness...; 2014; Steinmetz, S., Oez, F., Tijdens, K. G.
- Exploring selection biases for developing countries - is the web a promising tool for data collection...; 2014; Tijdens, K. G., Steinmetz, S.
- Measuring the very long, fuzzy tail in the occupational distribution in web-surveys; 2014; Tijdens, K. G.
- Moving answers with the GyroScale: Using the mobile device’s gyroscope for market research purposes...; 2014; Luetters, H., Kraus, M., Westphal, D.
- Clicking vs. Dragging: Different Uses of the Mouse and Their Implications for Online Surveys; 2014; Sikkel, D., Steenbergen, R., Gras, S.
- Innovation for television research - online surveys via HbbTV. A new technology with fantastic opportunities...; 2014; Herche, J., Adler, M.
- Online mobile surveys in Italy: coverage and other methodological challenges; 2014; Poggio, T.
- How Sliders Bias Survey Data; 2013; Sellers, R.
- Survey Research Response Rates: Internet Technology vs. Snail Mail ; 2013; Lanier, P. A., Tanner, J. R., Totaro, M. W., Gradnigo, G.
- The impact of New Zealand's 2008 prohibition of piperazine-based party pills on young people'...; 2013; Sheridan, J., Dong, C. Y., Butler, R., Barnes, J.
- How well do volunteer web panel surveys measure sensitive behaviours in the general population, and...; 2013; Erens, B., Burkill, S., Copas, A., Couper, M. P., Conrad, F.
- Effects of Gamification on Participation and Data Quality in a Real-World Market Research Domain ; 2013; Cechanowicz, J., Gutwin, C., Brownell, B., Goodfellow, L.
- Ideal participants in online market research: Lessons from closed communities; 2013; Heinze, A., Ferneley, E., Child, P.
- Online, face-to-face and telephone surveys—Comparing different sampling methods in wine consumer...; 2013; Szolnoki, G., Hoffmann, D.
- Where does the Fair Trade price premium go? Confronting consumers' request with reality; 2013; Langen, N., Adenaeuer, L.
- Customer satisfaction in Web 2.0 and information technology development; 2013; Sharma, G., Baoku, L.
- Research staff and public engagement: a UK study; 2013; Davies, S.