Web Survey Bibliography
Over the last ten years the number of people using the Internet for health information and advice has grown rapidly. Many people trust the information and advice they find online although this trust may be misplaced. Indeed in a systematic meta-analysis of health website evaluations, 70% of studies concluded that quality is a problem on the Internet (Eysenbach et al., 2002). In the face of such variable quality, how do health consumers decide whether or not to trust the information and advice they find online? To address this question a review of Internet health use over the last ten years has been instigated with the intention of examining the attitudes and behaviour of online health consumers at 5 year intervals. This paper reports on the findings of that decade in e-health.
In the year 2000 a large scale questionnaire was developed to assess online trust across a number of domains including health (Briggs et al., 2002). The data from the questionnaire was used to develop a staged model of trust. This model noted that design factors and visual appeal appeared to be strong predictors of early rejection and mistrust of a health website whilst content features such as source credibility and personalisation appeared to be more predictive of trust and selection.
In 2005 the researchers sampled online health consumers again with two main objectives. Firstly, to generate an updated picture of the online health landscape, providing information on the kinds of websites people were accessing and the types of information they were seeking. Secondly, to build upon the original staged model of trust and so increase understanding of the process by which trust perceptions are translated into relevant behaviour. To these ends a revised trust questionnaire was developed reflecting the importance of both design and social identity issues. In addition questions specific to e-health (notably perceived threat, coping, and information checking and corroboration) were included. As predicted, these variables added to the ability of the model to predict variance in both trust and readiness to act upon the advice provided by the site. The results of the 2005 questionnaire data showed that women were still the predominant users of the Internet for health advice but that the sites they were seeking had changed from 2000. A key difference between the 2005 and 2000 data was the rise in use of ‘less regulated’ health sites (Sillence et al., 2006). These sites were typically run by individual ‘experts’ and marked the growing interest in Patient Experience (PEx) material online. This interest was reflected in the 2011 revised questionnaire which included items designed to measure the exposure to and importance of PEx material. The preliminary findings indicate that whilst PEx material predicts whether or not people like the site it negatively predicts their trust perceptions and has no bearing on their subsequent actions.
Collectively the findings of this 10 year study provide valuable insights into the design of trustworthy health websites, our understanding of the process between trust and behavioural outcomes and the provision of PEx websites. This should be of interest to researchers, health practitioners, providers and policy makers.
Social Science Research Network (abstract) / (full text)
Web Survey Bibliography (6797)
- Survey Reminder Method Experiment: An Examination of Cost Efficiency and Reminder Mode Salience in the...; 2013; Anderson, M., Rogers, B., CyBulski, K., Hall, J. W., Alderks, C. E., Milazzo-Sayre, L.
- Using Qualitative and Quantitative Testing to Improve Hispanic Response Rates for Online Surveys; 2013; Pens, Y., Gentry, R. J.
- The Use of Email, Text Messages, and Facebook to Increase Response Rates Among Adolescents in a Longitudinal...; 2013; Fleeman, A., Francis, K., Henderson, T., Woodford, M., Jani, M.
- Use of Smart Phones/Text Messaging to Increase Response Rates; 2013; DuBray, P.
- Designing Surveys for Tablets and Smartphones; 2013; Lakhe, S., Nichols, E. M., Olmsted, M. G., King, T.
- Tablets as Data Entry Interfaces – Solving Data Cleaning and Transcription Issues During Data...; 2013; Costall, A.
- Effects of Response Format on Measurement of Readership; 2013; Thomas, R. K., Cobb, C. L., Baim, J.
- Potential Impact of Modifying the Fielding Time of a Web-Based Survey; 2013; Baum, H. M., Chandonnet, A.
- How Representative are Google Consumer Surveys?: Results From an Analysis of a Google Consumer Survey...; 2013; Krishnamurty, P., Tanenbaum, E., Stern, M. J.
- One Drink or Two: Does Quantity Depicted in an Image Affect Web Survey Responses?; 2013; Charoenruk, N., Stange, M.
- A Comparison Between Screen/Follow Item Format and Yes/No Item Format on a Multi-Mode Federal Survey; 2013; Hernandez,S. J., Arakelyan, S. N., Welch, V. E.
- Using Multiple Modes in Follow-Up Contacts in Random-Digit Dialing Surveys; 2013; Chowdhury, P. P.
- Tablets and Smartphones and Netbooks, Oh My! Effects of Device Type on Respondent Behavior; 2013; Ross, H., Mendelson, J., Lackey, M.
- Impacts of Unit Nonresponse in a Recontact Study of Youth; 2013; Mendelson, J., Viera Jr., L.
- Multi-Mode Survey Administration: Does Offering Multiple Modes at Once Depress Response Rates?; 2013; Newsome, J., Levin, K., Langetieg, P., Vigil, M., Sebastiani, M.
- Responsive Design for Web Panel Data Collection; 2013; Bianchi, A., Biffignandi, S.
- Utilizing the Web in a Multi-Mode Survey; 2013; Venkataraman, L.
- Changing to a Mixed-Mode Design: The Role of Mode in Respondents’ Decisions About Participation...; 2013; Collins, D., Mitchell, M., Toomes, M.
- Comparing the Effects of Mode Design on Response Rate, Representativeness, and Cost Per Complete in...; 2013; Tully, R.
- Internet Response for the Decennial Census – 2012 National Census Test; 2013; Reiser, C.
- The Effects of Pushing Web in a Mixed-Mode Establishment Data Collection; 2013; Ellis, C.
- Using Web Ex to Conduct Usability Testing of an On-Line Survey Instrument; 2013; Stettler, K.
- Effects of Lotteries on Response Behavior in Online Panels; 2013; Goeritz, A., Luthe, S. C.
- Lotteries and study results in market research online panels; 2013; Goeritz, A., Luthe, S. C.
- The Effects of Errors in Paradata on Weighting Class Adjustments: A Simulation Study; 2013; West, B. T.
- Using Paradata to Study Response to Within-Survey Requests; 2013; Sakshaug, J. W.
- Paradata for Coverage Research ; 2013; Eckman, S.
- Improving Surveys with Paradata: Analytic Uses of Process Information; 2013; Kreuter, F.
- Theory of adaptation or survival of the fittest?; 2013; Cavallaro, K.
- The smart(phone) way to collect survey data; 2013; Stapleton, C.
- Online Fundraising Essentials, Second Edition; 2013; Stevenson, S. C.
- Tips for Evaluating Online Effectiveness; 2013; Stevenson, S. C.
- The Digital Divide: The internet and social inequality in international perspective; 2013; Ragnedda, M., Muschert, G.
- Ten questions to ask your online survey provider; 2013; Williams, D.
- Survey quality prediction system 2.0; 2013
- Practical tools for designing and weighting survey samples; 2013; Valliant, R. L., Daver, J. A., Kreuter, F.
- Paradata in web surveys; 2013; Callegaro, M.
- Report Of The AAPOR Task Force On Non-probability sampling; 2013; Baker, R. P., Brick, J. M., Bates, N., Battaglia, M. P., Couper, M. P., Dever, J. A., Gile, K. J., Tourangeau...
- Incentive effects; 2013; Goeritz, A.
- A nationwide web-based freight data collection; 2013; Samimi, A., Mohammadian, A., Kawamura, K.
- Mode Matters: Evaluating Response Comparability in a Mixed-Mode Survey; 2013; Bowyer, B. T., Rogowski, J. C.
- Comparing Survey Results Obtained via Mobile Devices and Computers: An Experiment With a Mobile Web...; 2013; de Bruijne, M., Wijnant, A.
- Cognitive Probes in Web Surveys: On the Effect of Different Text Box Size and Probing Exposure on Response...; 2013; Behr, D., Bandilla, W., Kaczmirek, L., Braun, M.
- The E-Interview in Qualitative Research; 2013; Bampton, R., Cowton, C., Downs, Y.
- Methodological Considerations of Qualitative Email Interviews; 2013; Nehls, K.
- Best Practice in Online Survey Research with Sensitive Topics; 2013; Kays, K., Keith, T. L., Broughal, M. T.
- Research Intentions are Nothing without Technology: Mixed-Method Web Surveys and the Coberen Wall of...; 2013; Ganassali, S., Rodriguez-Santos, C.
- Reducing Response Burden for Enterprises Combining Methods for Data Collection on the Internet; 2013; Vik, T.
- Measuring Wages Worldwide: Exploring the Potentials and Constraints of Volunteer Web Surveys; 2013; Steinmetz, S., Raess, D., Tijdens, K., de Pedraza, P.
- Using Web Surveys for Psychology Experiments: A Case Study in New Media Technology for Research; 2013; Peden, B. F., Tiry , A. M.