The Representation of Mortality Statistics and the Perceived Importance of Causes of Death

Abstract

This study investigated how different methods of presenting mortality statistics may influence subjective impressions of the importance of a given cause of death. Subjects were 214 students from the fifth year of a comprehensive school (average age 15). Each subject rated one of six causes of death on a scale labeled "extremely minor-extremely major cause of death" before and after receiving accurate information concerning the number of deaths per annum in the United Kingdom resulting from the cause in question. This information was presented in one of five forms: (a) a statement of what proportion of all deaths resulted from the specified cause; (b) a statement of what percentage of all deaths were so caused; (c) a pie chart representing the proportion pictorially; (d) a bar chart representing the proportion pictorially; and (e) a statement of absolute number of deaths from the specified cause without information on total number of deaths from all causes combined. Analysis showed that subjects discriminated between the different causes both before and after presentation of the information but their ratings were imperfectly calibrated with actual frequencies. Also, the changes in ratings following the information depended significantly on the mode of presentation. Except when subjects were told the absolute frequency, the changes were in the direction of decrease in perceived importance. This decrease was most marked in the bar chart and pie chart conditions. The data are interpreted in relation to the literature on statistical inference processes and on judgmental contrast.

Women's preferences and consultants' communication of risk in consultations about familial breast cancer: impact on patient outcomes

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“…Some studies have suggested that the number and format of risk figures given have influence on the accuracy of the risk. [27][28][29] Framing, which has been found to be influential in the clinical context, 30 31 is not relevant here as risk is almost always framed in terms of having a mutation or developing cancer.…”

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The Hurricane Decision Simulator: A Tool for Marine Forces in New Orleans to Practice Operations Management in Advance of a Hurricane

“…People often do not process probabilistic information well (Tversky et al 1982), and their interpretation of probabilities depends on how the information is presented (Ibrekk and Morgan 1987, Harding et al 1982, Halpern et al 1989.…”