A clustering approach to segmenting users of internet-based risk calculators.

BACKGROUND: Risk calculators are widely available Internet applications that deliver quantitative health risk estimates to consumers. Although these tools are known to have varying effects on risk perceptions, little is known about who will be more likely to accept objective risk estimates. OBJECTIVE: To identify clusters of online health consumers that help explain variation in individual improvement in risk perceptions from web-based quantitative disease risk information. METHODS: A secondary analysis was performed on data collected in a field experiment that measured people's pre-diabetes risk perceptions before and after visiting a realistic health promotion website that provided quantitative risk information. K-means clustering was performed on numerous candidate variable sets, and the different segmentations were evaluated based on between-cluster variation in risk perception improvement. RESULTS: Variation in responses to risk information was best explained by clustering on pre-intervention absolute pre-diabetes risk perceptions and an objective estimate of personal risk. Members of a high-risk overestimater cluster showed large improvements in their risk perceptions, but clusters of both moderate-risk and high-risk underestimaters were much more muted in improving their optimistically biased perceptions. CONCLUSIONS: Cluster analysis provided a unique approach for segmenting health consumers and predicting their acceptance of quantitative disease risk information. These clusters suggest that health consumers were very responsive to good news, but tended not to incorporate bad news into their self-perceptions much. These findings help to quantify variation among online health consumers and may inform the targeted marketing of and improvements to risk communication tools on the Internet.

Why some are perceived as more confident and more insecure, more reckless and more cautious, more trusting and more suspicious, than others: enriched and impoverished options in social judgment.

In line with the principle of compatibility, when making social judgments, people tend to focus on personality attributes compatible with the trait under consideration. Better known, or enriched, personages are more likely to present attributes that are compatible with a particular trait than are personages about whom little is known. As a result, enriched personages are more likely to have various, sometimes even conflicting, traits attributed to them. This hypothesis is supported by a number of studies that compare the frequency with which some people are chosen as being better described by opposite trait adjectives than are others. Celebrities more often have both of a pair of opposing adjectives ascribed to them than do less well known figures. Similarly, subjects judge themselves to be better described by either of a pair of opposite adjectives than is a person who is relatively unknown in their lives. The implications for social judgment and for everyday decisions are discussed.

Communicating foodborne disease risk.

The food industry, like many others, has a risk communication problem. That problem is manifested in the public's desire to know the truth about outbreaks of foodborne diseases; ongoing concern about the safety of foods, additives, and food-processing procedures; and continued apathy regarding aspects of routine food hygiene. If these concerns are addressed in a coherent and trustworthy way, the public will have better and cheaper food. However, sloppy risk communication can itself cause public health damage. Because citizens are ill-equipped to discriminate among information sources, the food industry as a whole bears responsibility for the successes and failures of its individual members. We review risk communication research and practice for their application to the food industry.

Decision-making theory and HIV disease.

AIDS: AIDS treatment is sophisticated and complex, requiring difficult decisions about when to begin treatment, how aggressively to treat the infection, and which alternative therapies to pursue. Health care professionals need to be able to calculate risks and to help patients weigh their treatment options. Ideally, clinicians should present all options and discuss why they advocate some and not others. Unconventional treatments should also receive attention, because a patient may lend more credibility to options he or she believes is being purposefully concealed. Treatment decisions can be turned into a formula by estimating the good or bad value of each possible outcome of an action, multiplying that figure by the outcome's probability, and adding up the products from all the outcomes. Even if the person does not wish to base a decision on the formula, they have at least given careful consideration to all the issues. Creating a record of the decision-making process can also help ease regret caused by hindsight or outcome bias.^ieng