BACKGROUND: Presentation of information using survival or mortality (i.e., incidence) curves offers a potentially powerful method of communication because such curves provide information about risk over time in a relatively simple graphic format. However, the effect of framing as survival versus mortality on understanding and treatment choice is not known. METHODS: In this study, 451 individuals awaiting jury duty at the Philadelphia City Courthouse were randomized to receive 1 of 3 questionnaires: (1) survival curves, (2) mortality curves, or (3) both survival and mortality curves. Each questionnaire included a brief description of a hypothetical treatment decision, survival curve graphs and/or mortality curve graphs presenting the outcome of the treatment, and questions measuring understanding of the information contained in the graphs and preference for undergoing treatment. After completing a brief practice exercise, participants were asked to answer questions assessing their ability to interpret single points on a curve and the difference between curves, and then to decide whether they would choose to undergo preventive surgery for 3 different scenarios in which the benefit of surgery varied. RESULTS: Participants who received only survival curves or who received both survival and mortality curves were significantly more accurate in answering questions about the information than participants who received only mortality curves (P < 0.05). For 2 of the 3 treatment presentations, participants who received only mortality curves were significantly less likely to prefer preventive surgery than participants who received survival curves only or both survival and mortality curves (P < 0.05). The effect of framing on understanding was greatest among participants with less than a college education and among non-Caucasian participants. CONCLUSION: Framing graphic risk information as chance of death over time results in lower levels of understanding and less interest in preventive surgery than framing as chance of survival over time.
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BACKGROUND: Presentation of information using survival or mortality (i.e., incidence) curves offers a potentially powerful method of communication because such curves provide information about risk over time in a relatively simple graphic format. However, the effect of framing as survival versus mortality on understanding and treatment choice is not known. METHODS: In this study, 451 individuals awaiting jury duty at the Philadelphia City Courthouse were randomized to receive 1 of 3 questionnaires: (1) survival curves, (2) mortality curves, or (3) both survival and mortality curves. Each questionnaire included a brief description of a hypothetical treatment decision, survival curve graphs and/or mortality curve graphs presenting the outcome of the treatment, and questions measuring understanding of the information contained in the graphs and preference for undergoing treatment. After completing a brief practice exercise, participants were asked to answer questions assessing their ability to interpret single points on a curve and the difference between curves, and then to decide whether they would choose to undergo preventive surgery for 3 different scenarios in which the benefit of surgery varied. RESULTS:Participants who received only survival curves or who received both survival and mortality curves were significantly more accurate in answering questions about the information than participants who received only mortality curves (P < 0.05). For 2 of the 3 treatment presentations, participants who received only mortality curves were significantly less likely to prefer preventive surgery than participants who received survival curves only or both survival and mortality curves (P < 0.05). The effect of framing on understanding was greatest among participants with less than a college education and among non-Caucasian participants. CONCLUSION: Framing graphic risk information as chance of death over time results in lower levels of understanding and less interest in preventive surgery than framing as chance of survival over time.
Authors: K Viswanath; Rebekah H Nagler; Cabral A Bigman-Galimore; Michael P McCauley; Minsoo Jung; Shoba Ramanadhan Journal: Cancer Epidemiol Biomarkers Prev Date: 2012-10 Impact factor: 4.254