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 (6476)
- Smartphone Apps and User Engagement: Collecting Data in the Digital Era; 2012; Link, M. W.
- Snowball Sampling in Online Social Networks; 2012; Raissi, M., Ackland, R.
- The Use of Facebook as a Locating and Contacting Tool; 2012; McCarthy, T.
- How Often Do You Use the App with a Bird on It? Exploring Differences in Survey Completion Times, Primacy...; 2012; Buskirk, T. D.
- Data quality of questions sensitive to social-desirability bias in web surveys; 2012; Lozar Manfreda, K., Zajc, N., Berzelak, N., Vehovar, V.
- Online Questionnaires: Development of ‘basic requirements’; 2012; Tries, S., Blanke, K.
- Social research in online context: methodological reflections on web surveys from a case study; 2012; Pandolfini, V.
- Efficacy of a health-related Facebook social network site on health-seeking behaviors; 2012; Woolley, P., Peterson, M.
- Methods for eliminating skip statements from questionnaire logic; 2012; Canvanough Spencer, S.
- The war against unengaged online respondents; 2012; Gittelman, S. H., Trimarchi, E.
- Qualitatively Speaking: The five absolute, no-excuse must-dos for online qualitative researchers; 2012; Rossow, A.
- By the Numbers: Lessons for using online panels in B2B research; 2012; Elsner, N.
- Improving Survey Website Usability ; 2012; Vannette, D.
- Specialized Tools for Measuring Past Events ; 2012; Belli, R. F.
- Transparency, Access and the Credibility of Survey Research; 2012; Lupia, A.
- Experience Sampling and Ecological Momentary Assessment; 2012; Stone, A.
- Can Microtargeting Improve Survey Sampling? An Assessment of Accuracy and Bias in Consumer File Marketing...; 2012; Pasek, J.
- Anonymity and Confidentiality; 2012; Tourangeau, R.
- Cognitive Evaluation of Survey Instruments: State of the Science (Art?) and Future Directions; 2012; Willis, G. B.
- Oh, Just One More Thing … Leveraging “Leave-Behinds” in Data Collection; 2012; Link, M. W.
- Can Offcial Records Correct Errors in Turnout Self-reports?; 2012; Berent, M., Krosnick, J. A., Lupia, A.
- Paradata; 2012; Kreuter, F.
- Computation of Survey Weights: Bridging Theory and Practice; 2012; Debell, M.
- Optimizing Response Rates; 2012; Brick, J. M.
- Modes of Data Collection; 2012; Tourangeau, R.
- The Use and Effects of Incentives in Surveys; 2012; Singer, E.
- Probability vs. Non-probability Methods; 2012; Langer, G,
- Improving Question Design to Maximize Reliability and Validity; 2012; Krosnick, J. A.
- Respondent Attrition vs Data Attrition and Their Reduction; 2012; Olsen, R. J.
- Survey Interviewing: Deviations from the Script; 2012; Schaeffer, N. C.
- Sampling for Single and Multi-Mode Surveys using Address-Based Sampling; 2012; O'Muircheartaigh, C.
- What Human Language Technology can do for you (and vice versa); 2012; Liberman, M.
- Proxy Reporting; 2012; Cobb, C. L.
- The Impact of Survery Nonresponse on Survey Accuracy; 2012; Keeter, S.
- How accurate are surveys of objective phenomena?; 2012; Chang, L. C., Krosnick, J. A.
- An Empirical Investigation of the Role of the Email Contact in Web Survey Response Rates; 2012; Hsu, H.-Y., Lai, Y.-H., Chin, H.-Y.
- Measure the response burden in the Swedish Intrastat system; 2012; Weideskog, F.
- Mode and non-response effects and their treatment; 2012; Chrysanthopoulos, S., Georgostathi, A.
- What can be said about quality in the Central Population Register based on a self-completion survey...; 2012; Falnes-Dalheim, E., Pedersen, H. E.
- Improving the quality of complex surveys: The case of the EU Labour Force Survey ; 2012; van der Valk, J.
- Pros and cons of Internet based User Satisfaction Surveys; 2012; Consoli, A., Matsulevits, L.
- The re-engineering of the Structural Earnings survey process: Mixed - Mode data collection and new E...; 2012; Cardinaleschi, S., De Santis, S., Rocci, F., Spinelli, V.
- Between demand and reality: Ensuring efficiency and quality in pretesting questionnaires; 2012; Sattelberger, S., Blanke, K.
- How to provide high data quality in online-questionnaires: Setting guidelines in design; 2012; Tries, S., Nebel, S., Blanke, K.
- Boosting Web pick-up Rates by referring to Compliance Principles ; 2012; Falnes-Dalheim, E., Haraldsen, G., Sundvoll, A.
- Choosing a Data Collection Approach: Mixed Mode Design Experiences in Statistics Finland; 2012; Taskinen, P., Kiianmaa, N.
- Ebook readings jumps, print book reading declines; 2012; Rainie, L., Duggan, M.
- Does mentioning "Some People" and "Other People" in an opinion question improve...; 2012; Yeager, D. S., Krosnick, J. A.
- Digital Divides: A connectivity continuum for the United States. Data from the 2011 Current Population...; 2012; File, T.
- Developments and the impact of smart technology; 2012; Macer, T.