Design, Implementation, and Preliminary Evaluation of a Web-Based Health Risk Calculator

Through "health risk calculator" websites, Internet users can obtain personalized and interactive predictions about health risks. While it seems appropriate to provide laypersons with educational health information, prior research emphasizes the importance of understanding behavioral responses when communicating risk information. In order to systematically explore and analyze these relationships in the context of online health information, a new diabetes risk calculator website was developed to serve as an intervention in which the presence of personalization and interactive feedback could be manipulated for randomized experimentation. The website was integrated with pre- and post-intervention surveys in order to assess users in terms of information usage and risk perceptions. In two preliminary experiments, there was a small, unexpected negative impact of personalization on multiple measures of information usage. The implications of these results are discussed in the context of improving the presentation of online risk information for practical and experimental evaluation purposes.

[1]  Rema Padman,et al.  The Impact Of Web-Based Diabetes Risk Calculators On Information Processing and Risk Perceptions , 2008, AMIA.

[2]  John G. Lynch,et al.  Interactive Home Shopping: Consumer, Retailer, and Manufacturer Incentives to Participate in Electronic Marketplaces , 1997 .

[3]  Robert A Rizza,et al.  Progression From Newly Acquired Impaired Fasting Glucose to Type 2 Diabetes , 2007, Diabetes Care.

[4]  David M Eddy,et al.  Archimedes: a trial-validated model of diabetes. , 2003, Diabetes care.

[5]  Elena Karahanna,et al.  Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage , 2000, MIS Q..

[6]  W. Klein,et al.  Objective standards are not enough: affective, self-evaluative, and behavioral responses to social comparison information. , 1997, Journal of personality and social psychology.

[7]  Christopher K. Hsee,et al.  Risk as Feelings , 2001, Psychological bulletin.

[8]  S. Chaiken Heuristic versus systematic information processing and the use of source versus message cues in persuasion. , 1980 .

[9]  Elizabeth Sillence,et al.  Health Websites that people can trust - the case of hypertension , 2007, Interact. Comput..

[10]  S. Dunwoody,et al.  Proposed model of the relationship of risk information seeking and processing to the development of preventive behaviors. , 1999, Environmental research.

[11]  John Vergo,et al.  A user-centered design approach to personalization , 2000, CACM.

[12]  G. Colditz,et al.  Colon Cancer: Risk Perceptions and Risk Communication , 2004, Journal of health communication.

[13]  W. Klein,et al.  Dispositional, Unrealistic, and Comparative Optimism: Differential Relations with the Knowledge and Processing of Risk Information and Beliefs about Personal Risk , 2002 .

[14]  Sharon Dunwoody,et al.  Studying Heuristic‐Systematic Processing of Risk Communication , 2003, Risk analysis : an official publication of the Society for Risk Analysis.

[15]  F. Bull,et al.  Understanding how people process health information: a comparison of tailored and nontailored weight-loss materials. , 1999, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.

[16]  Izak Benbasat,et al.  The Effects of Personalizaion and Familiarity on Trust and Adoption of Recommendation Agents , 2006, MIS Q..

[17]  Matthew W Kreuter,et al.  Tailored and targeted health communication: strategies for enhancing information relevance. , 2003, American journal of health behavior.

[18]  Franziska Marquart,et al.  Communication and persuasion : central and peripheral routes to attitude change , 1988 .