Web Survey Bibliography
Background: Men who have sex with men (MSM) in the United States are at high risk for human immunodeficiency virus (HIV) and poor HIV related outcomes. Maps can be used to identify, quantify, and address gaps in access to HIV care among HIV-positive MSM, and tailor intervention programs based on the needs of patients being served.
Objective: The objective of our study was to assess the usability of a Google map question embedded in a Web-based survey among Atlanta-based, HIV-positive MSM, and determine whether it is a valid and reliable alternative to collection of address-based data on residence and last HIV care provider.
Methods: Atlanta-based HIV-positive MSM were recruited through Facebook and from two ongoing studies recruiting primarily through venue-based sampling or peer referral (VBPR). Participants were asked to identify the locations of their residence and last attended HIV care provider using two methods: (1) by entering the street address (gold standard), and (2) “clicking” on the locations using an embedded Google map. Home and provider addresses were geocoded, mapped, and compared with home and provider locations from clicked map points to assess validity. Provider location error values were plotted against home location error values, and a kappa statistic was computed to assess agreement in degree of error in identifying residential location versus provider location.
Results: The median home location error across all participants was 0.65 miles (interquartile range, IQR, 0.10, 2.5 miles), and was lower among Facebook participants (P<.001), whites (P<.001), and those reporting higher annual household income (P=.04). Median home location error was lower, although not statistically significantly, among older men (P=.08) and those with higher educational attainment (P=.05). The median provider location error was 0.32 miles (IQR, 0.12, 1.2 miles), and did not vary significantly by age, recruitment method, race, income, or level of educational attainment. Overall, the kappa was 0.20, indicating poor agreement between the two error measures. However, those recruited through Facebook had a greater level of agreement (κ=0.30) than those recruited through VBPR methods (κ=0.16), demonstrating a greater level of consistency in using the map question to identify home and provider locations for Facebook-recruited individuals.
Conclusions: Most participants were able to click within 1 mile of their home address and their provider’s office, and were not always able to identify the locations on a map consistently, although some differences were observed across recruitment methods. This map tool may serve as the basis of a valid and reliable tool to identify residence and HIV provider location in the absence of geocoded address data. Further work is needed to improve and compare map tool usability with the results from this study.
JMIR Homepage (Abstract) & (Full text)
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.