BACKGROUND: Patients often face medical decisions that involve outcomes that occur and change over time. Survival curves are a promising communication tool for patient decision support because they present information about the probability of an outcome over time in a simple graphic format. However, previous studies of survival curves did not measure comprehension, used face-to-face explanations, and focused on a VA population. METHODS: In this study, 246 individuals awaiting jury duty at the Philadelphia County Courthouse were randomized to receive one of two questionnaires. The control group received a questionnaire describing two hypothetical treatments and a graph with two survival curves showing the outcomes of each treatment. The practice group received the same questionnaire preceded by a practice exercise asking questions about a graph containing a single curve. Subjects' ability to interpret survival from a curve and ability to calculate change in survival over time were measured. RESULTS: Understanding of survival at a single point in time from a graph containing two survival curves was high overall, and was improved by the use of a single curve practice exercise. With a practice exercise, subjects were over 80% accurate in interpreting survival at a single point in time. Understanding of changes in survival over time was lower overall, and was not improved by the use of a practice exercise. With or without a practice exercise, subjects were only 55% accurate in calculating changes in survival. CONCLUSION: The majority of the general public can interpret survival at a point in time from self-administered survival curves. This understanding is improved by a single curve practice exercise. However, a significant proportion of the general public cannot calculate change in survival over time. Further research is necessary to determine the effectiveness of survival curves in improving risk communication and patient decision making.
RCT Entities:
BACKGROUND:Patients often face medical decisions that involve outcomes that occur and change over time. Survival curves are a promising communication tool for patient decision support because they present information about the probability of an outcome over time in a simple graphic format. However, previous studies of survival curves did not measure comprehension, used face-to-face explanations, and focused on a VA population. METHODS: In this study, 246 individuals awaiting jury duty at the Philadelphia County Courthouse were randomized to receive one of two questionnaires. The control group received a questionnaire describing two hypothetical treatments and a graph with two survival curves showing the outcomes of each treatment. The practice group received the same questionnaire preceded by a practice exercise asking questions about a graph containing a single curve. Subjects' ability to interpret survival from a curve and ability to calculate change in survival over time were measured. RESULTS: Understanding of survival at a single point in time from a graph containing two survival curves was high overall, and was improved by the use of a single curve practice exercise. With a practice exercise, subjects were over 80% accurate in interpreting survival at a single point in time. Understanding of changes in survival over time was lower overall, and was not improved by the use of a practice exercise. With or without a practice exercise, subjects were only 55% accurate in calculating changes in survival. CONCLUSION: The majority of the general public can interpret survival at a point in time from self-administered survival curves. This understanding is improved by a single curve practice exercise. However, a significant proportion of the general public cannot calculate change in survival over time. Further research is necessary to determine the effectiveness of survival curves in improving risk communication and patient decision making.
Authors: A M O'Connor; P Tugwell; G A Wells; T Elmslie; E Jolly; G Hollingworth; R McPherson; E Drake; W Hopman; T Mackenzie Journal: Med Decis Making Date: 1998 Jul-Sep Impact factor: 2.583
Authors: Stefan Neuner-Jehle; Oliver Senn; Odette Wegwarth; Thomas Rosemann; Johann Steurer Journal: BMC Fam Pract Date: 2011-04-05 Impact factor: 2.497