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Med Decis Making. 2016 May;36(4):453-71. doi: 10.1177/0272989X15626397. Epub 2016 Jan 29.

Design Features of Explicit Values Clarification Methods: A Systematic Review.

Author information

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
Population Health and Optimal Health Practices Unit, Research Center of the CHU de Québec, Québec City, Québec, Canada (HOW, AFT)
4
Department of Psychological Sciences, University of Missouri, Columbia, MO, USA (LDS)
5
Department of Developmental Psychology and Socialization, University of Padova, Italy (TG)
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, MI, USA (AF-F, NE, VCK, AF)
8
Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA (NE, VCK, AF)
9
Department of Oncology, Queen's University, Kingston, Ontario, Canada (DF-S)
10
Shared Decision Making Resources, Georgetown, ME, USA (NFC)
11
University of New England, Biddeford, ME, USA (NFC)
12
Department of Anesthesiology and Critical Care Medicine, Division of Critical Care Medicine, Laval University, Quebec City, Quebec, Canada (AFT)
13
VA Ann Arbor Center for Clinical Management Research, Ann Arbor, MI, USA (AF)
14
Department of Psychology, University of Michigan, Ann Arbor, Michigan, USA (AF).

Abstract

BACKGROUND:

Values clarification is a recommended element of patient decision aids. Many different values clarification methods exist, but there is little evidence synthesis available to guide design decisions.

PURPOSE:

To describe practices in the field of explicit values clarification methods according to a taxonomy of design features.

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 1 or more explicit values clarification methods.

DATA EXTRACTION:

We extracted data about decisions addressed; use of theories, frameworks, and guidelines; and 12 design features.

DATA SYNTHESIS:

We identified 110 articles describing 98 explicit values clarification methods. Most of these addressed decisions in cancer or reproductive health, and half addressed a decision between just 2 options. Most used neither theory nor guidelines to structure their design. "Pros and cons" was the most common type of values clarification method. Most methods did not allow users to add their own concerns. Few methods explicitly presented tradeoffs inherent in the decision, supported an iterative process of values exploration, or showed how different options aligned with users' values.

LIMITATIONS:

Study selection criteria and choice of elements for the taxonomy may have excluded values clarification methods or design features.

CONCLUSIONS:

Explicit values clarification methods have diverse designs but can be systematically cataloged within the structure of a taxonomy. Developers of values clarification methods should carefully consider each of the design features in this taxonomy and publish adequate descriptions of their designs. More research is needed to study the effects of different design features.

KEYWORDS:

clarify; decision aids; decision making; design; preferences; shared decision making; values; values clarification; values clarification exercise; values clarification method

PMID:
26826032
DOI:
10.1177/0272989X15626397
[Indexed for MEDLINE]

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