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Probability Discounting and Cardiovascular Risk: The Effect of Side-Effect Severity and Framing
An expectation of healthcare delivery is that patients can make informed decisions about whether and how to treat chronic health conditions. Decisions are complex because treatment is not always 100% effective and side effects can occur without a beneficial outcome. It is important, therefore, to un...
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Published in: | The Psychological record 2017-06, Vol.67 (2), p.169-179 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | An expectation of healthcare delivery is that patients can make informed decisions about whether and how to treat chronic health conditions. Decisions are complex because treatment is not always 100% effective and side effects can occur without a beneficial outcome. It is important, therefore, to understand the drivers of individual choices about whether to accept a treatment, particularly, how people respond to the probabilities of being well or unwell with or without the treatment. The current project investigated this using a probability discounting framework. Participants indicated whether they would take a drug that reduced their chance of having a heart attack or a stroke from a baseline probability that varied across trials. We told participants that they would always experience a side effect and manipulated its severity (i.e. either frequent headaches or persistent cold hands and feet). We also manipulated whether probabilities were framed negatively—in terms of heart attack or stroke—or positively—in terms of continued good heart health. We observed systematic discounting as a function of probability of heart attack or stroke without treatment. Discounting was shallower when the side effect was less severe. There was no significant effect of framing at the group level. Overall, probability discounting offers a useful approach to investigating the drivers of decisions about whether to accept medical treatment. |
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ISSN: | 0033-2933 2163-3452 |
DOI: | 10.1007/s40732-017-0243-2 |