Holly O Witteman1,2,3, Teresa Gavaruzzi4, Laura D Scherer5, Arwen H Pieterse6, Andrea Fuhrel-Forbis7, Selma Chipenda Dansokho2, Nicole Exe7,8, Valerie C Kahn7,8, Deb Feldman-Stewart9, Nananda F Col10, Alexis F Turgeon3,11, Angela Fagerlin7,8,12,13. 1. Department of Family and Emergency Medicine, Faculty of Medicine, Laval University, Quebec City, Quebec, Canada (HOW) 2. Office of Education and Continuing Professional Development, Faculty of Medicine, Laval University, Quebec City, Quebec, Canada (HOW, SCD) 3. Public Health and Optimal Health Practices Research Axis, Research Centre of the CHU de Québec, Quebec City, Quebec, Canada (HOW, AFT) 4. Department of Developmental Psychology and Socialization, University of Padova, Italy (TG) 5. Department of Psychological Sciences, University of Missouri, Columbia, Missouri, USA (LDS) 6. Department of Medical Decision Making, Leiden University Medical Center, Leiden, the Netherlands (AHP) 7. Dutch Cancer Society, the Netherlands (AHP)Center for Bioethics and Social Sciences in Medicine, University of Michigan, Ann Arbor, Michigan, USA (AF-F, NE, VCK, AF) 8. Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA (NE, VCK, AF) 9. Division of Cancer Care and Epidemiology, Cancer Research Institute, Queen's University, Kingston, Ontario, Canada (DF-S) 10. Department of Oncology, Queen's University, Kingston, Ontario, Canada (DF-S)Shared Decision Making Resources, Georgetown, Maine, USA (NFC) 11. Department of Anesthesiology, Division of Critical Care, Faculty of Medicine, Laval University, Quebec City, Quebec, Canada (AFT) 12. Ann Arbor Center for Clinical Management Research, Ann Arbor, Michigan, USA (AF) 13. Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA (AF).
Abstract
BACKGROUND: Diverse values clarification methods exist. It is important to understand which, if any, of their design features help people clarify values relevant to a health decision. PURPOSE: To explore the effects of design features of explicit values clarification methods on outcomes including decisional conflict, values congruence, and decisional regret. DATA SOURCES: MEDLINE, all EBM Reviews, CINAHL, EMBASE, Google Scholar, manual search of reference lists, and expert contacts. STUDY SELECTION: Articles were included if they described the evaluation of 1 or more explicit values clarification methods. DATA EXTRACTION: We extracted details about the evaluation, whether it was conducted in the context of actual or hypothetical decisions, and the results of the evaluation. We combined these data with data from a previous review about each values clarification method's design features. DATA SYNTHESIS: We identified 20 evaluations of values clarification methods within 19 articles. Reported outcomes were heterogeneous. Few studies reported values congruence or postdecision outcomes. The most promising design feature identified was explicitly showing people the implications of their values, for example, by displaying the extent to which each of their decision options aligns with what matters to them. LIMITATIONS: Because of the heterogeneity of outcomes, we were unable to perform a meta-analysis. Results should be interpreted with caution. CONCLUSIONS: Few values clarification methods have been evaluated experimentally. More research is needed to determine effects of different design features of values clarification methods and to establish best practices in values clarification. When feasible, evaluations should assess values congruence and postdecision measures of longer-term outcomes.
BACKGROUND: Diverse values clarification methods exist. It is important to understand which, if any, of their design features help people clarify values relevant to a health decision. PURPOSE: To explore the effects of design features of explicit values clarification methods on outcomes including decisional conflict, values congruence, and decisional regret. DATA SOURCES: MEDLINE, all EBM Reviews, CINAHL, EMBASE, Google Scholar, manual search of reference lists, and expert contacts. STUDY SELECTION: Articles were included if they described the evaluation of 1 or more explicit values clarification methods. DATA EXTRACTION: We extracted details about the evaluation, whether it was conducted in the context of actual or hypothetical decisions, and the results of the evaluation. We combined these data with data from a previous review about each values clarification method's design features. DATA SYNTHESIS: We identified 20 evaluations of values clarification methods within 19 articles. Reported outcomes were heterogeneous. Few studies reported values congruence or postdecision outcomes. The most promising design feature identified was explicitly showing people the implications of their values, for example, by displaying the extent to which each of their decision options aligns with what matters to them. LIMITATIONS: Because of the heterogeneity of outcomes, we were unable to perform a meta-analysis. Results should be interpreted with caution. CONCLUSIONS: Few values clarification methods have been evaluated experimentally. More research is needed to determine effects of different design features of values clarification methods and to establish best practices in values clarification. When feasible, evaluations should assess values congruence and postdecision measures of longer-term outcomes.
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