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Howard, Michelle; Bansback, Nick; Tan, Amy; Klein, Doug; Bernard, Carrie; Barwich, Doris; Dodek, Peter M.; Nijjar, Aman; Heyland, Daren K.

BioMed Central

Background: Decisions about care options and the use of life-sustaining treatments should be informed by a person’s values and treatment preferences. The objective of this study was to examine the consistency of ratings of the importance of the values statements and the association between values statement ratings and the patient’s expressed treatment preference. Methods: We conducted a multi-site survey in 20 family practices. Patients aged 50 and older self-completed a questionnaire assessing the importance of eight values (rated 1 to 10), and indicated their preference for use of life-sustaining treatment (5 options). We compared correlations among values to a priori hypotheses based on whether the value related to prolonging or shortening life, and examined expected relationships between importance of values and the preference option for life-sustaining treatment. Results: Eight hundred ten patients participated (92% response rate). Of 24 a priori predicted correlations among values statements, 14 were statistically significant but nearly all were negligible in their magnitude and some were in the opposite direction than expected. For example, the correlation between importance of being comfortable and suffering as little as possible and the importance of living as long as possible should have been inversely correlated but was positively correlated (r = 0.08, p = 0.03). Correlations between importance of values items and preference were negligible, ranging from 0.03 to 0.13. Conclusions: Patients may not recognize that trade-offs in what is most important may be needed when considering the use of treatments. In the context of preparation for decision-making during serious illness, decision aids that highlight these trade-offs and connect values to preferences more directly may be more helpful than those that do not.

Text

2017-12-06

Attribution 4.0 International (CC BY 4.0)

http://hdl.handle.net/2429/63849

BMC Medical Informatics and Decision Making. 2017 Dec 06;17(1):164

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