Reframe the data to improve decision-making
People in one study rated a disease that kills 1,286 people out of every 10,000 as more dangerous than one that kills 24.14% of the population (Yamagishi, 1997). But in fact, it’s about half as dangerous.
Why? The way you present, or frame, the information changes the way people — even experts — perceive it.
“If you tell someone that something will happen to one out of 10 people, they think, ‘Well, who’s the one?’” Paul Slovic, a University of Oregon psychologist, told Money.
Trying to help readers make a complex decision? Reframe the data so people can more easily see its meaning. Here’s how:
1. Choose frequencies, not probabilities.
People process frequencies (2 out of 100) better than percentages (2%) (Kaplan, 1986). Frequencies are effective because they:
- Demonstrate the importance of data. People weigh frequencies as more important than percentages when making decisions (Lipkus, Samsa and Rimer, 2001).
- Help people make better choices. In one study, faculty members and students at the Harvard Medical School made much better decisions when they received information about diseases and symptoms in the form of frequencies instead of probabilities (Huffrage, Lindsey, Hertwig and Gigerenzer, 2000).
- Help even experts see the situation more clearly. Forensic psychiatrists and psychologists judged a patient’s risk of being violent as much greater when it was communicated as a frequency instead of a probability (Slivic, Monahan and MacGregor, 2000).
2. Frame as a loss (or gain).
Give readers new ways to think about information by highlighting the potential gain or loss. You can frame your data as:
- Mortality vs. survival rates. The effect of dying seems to be greater when it is framed as a mortality rate of 10% than when it is framed as a survival rate of 90%. And both patients and doctors found surgery less attractive than radiation therapy when risk information was presented in terms of mortality rather than survival, despite surgery having better long-term prospects (McNeil, Pauker and Sox, 1986).
- Risk vs. reward. Consumers understood information much better, valued it more and gave it more weight in decision-making when it was framed as a loss or risk than as a reward. So “protect yourself from problems in health plans” is more effective than “get the best quality” (Hibbard, Harris-Kojetin, Mullen, Lubalin and Garfinkel, 2000).
- Loss vs. gain. In six out of seven studies, framing information as a loss was more effective than as a gain in communicating prevention, detection and treatment (Edwards, Elwyn, Covey, Matthews and Pill, 2001).
- Consider the message within the frame. Framing your message as a loss is more effective when promoting screening. Framing it as a gain is more effective when promoting prevention (Rothman, Martino, Bedell, Detweiler and Salovey, 1999).
3. Generalize a little.
In order to be as “correct” as possible, communicators often include too much information — six decimal points of precision, for instance, or data about confidence intervals.
But that actually makes important details harder to suss out. As a result, people weigh this information lower when making a decision (Hsee, 1996). So, for instance, offer an average point estimate (a score of 8) instead of a more correct one (7 to 9).
But don’t pile on the data.
To help people make better decisions, reframe the data — don’t just offer more data.___
Source: Judith H. Hibbard and Ellen Peters, “Supporting Informed Consumer Health Care Decisions: Data Presentation Approaches that Facilitate the Use of Information in Choice,” Annual Review of Public Health, 2003, Vol. 24, pp. 413-33