Design features of explicit values clarification methods : a systematic review

Authors: Witteman, Holly; Scherer, Laura; Gavaruzzi, Teresa; Pieterse, Arwen H.; Fuhrel-Forbis, Andrea; Dansokho, Selma Chipenda; Exe, Nicole; Kahn, Valerie C.; Feldman-Stewart, Deb; Col, Nananda; Turgeon-Fournier, Alexis; Fagerlin, Angela
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.
Document Type: Article de recherche
Issue Date: 29 January 2016
Open Access Date: 14 December 2017
Document version: AM
This document was published in: Medical decision making, Vol. 36 (4), 453-471 (2016)
Birkhäuser Boston
Alternative version: 10.1177/0272989X15626397
Collection:Articles publiés dans des revues avec comité de lecture

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