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Design Features of Explicit Values Clarification Methods

Author

Listed:
  • Holly O. Witteman
  • Laura D. Scherer
  • Teresa Gavaruzzi
  • Arwen H. Pieterse
  • Andrea Fuhrel-Forbis
  • Selma Chipenda Dansokho
  • Nicole Exe
  • Valerie C. Kahn
  • Deb Feldman-Stewart
  • Nananda F. Col
  • Alexis F. Turgeon
  • Angela Fagerlin

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.

Suggested Citation

  • Holly O. Witteman & Laura D. Scherer & Teresa Gavaruzzi & Arwen H. Pieterse & Andrea Fuhrel-Forbis & Selma Chipenda Dansokho & Nicole Exe & Valerie C. Kahn & Deb Feldman-Stewart & Nananda F. Col & Ale, 2016. "Design Features of Explicit Values Clarification Methods," Medical Decision Making, , vol. 36(4), pages 453-471, May.
  • Handle: RePEc:sae:medema:v:36:y:2016:i:4:p:453-471
    DOI: 10.1177/0272989X15626397
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    References listed on IDEAS

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    1. Linzer, Drew A. & Lewis, Jeffrey B., 2011. "poLCA: An R Package for Polytomous Variable Latent Class Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i10).
    2. Pieterse, Arwen H. & de Vries, Marieke & Kunneman, Marleen & Stiggelbout, Anne M. & Feldman-Stewart, Deb, 2013. "Theory-informed design of values clarification methods: A cognitive psychological perspective on patient health-related decision making," Social Science & Medicine, Elsevier, vol. 77(C), pages 156-163.
    3. Gaston, Christine M. & Mitchell, Geoffrey, 2005. "Information giving and decision-making in patients with advanced cancer: A systematic review," Social Science & Medicine, Elsevier, vol. 61(10), pages 2252-2264, November.
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    Cited by:

    1. Nananda F. Col & Andrew J. Solomon & Vicky Springmann & Calvin P. Garbin & Carolina Ionete & Lori Pbert & Enrique Alvarez & Brenda Tierman & Ashli Hopson & Christen Kutz & Idanis Berrios Morales & Car, 2018. "Whose Preferences Matter? A Patient-Centered Approach for Eliciting Treatment Goals," Medical Decision Making, , vol. 38(1), pages 44-55, January.
    2. Laura D. Scherer & Jeffrey T. Kullgren & Tanner Caverly & Aaron M. Scherer & Victoria A. Shaffer & Angela Fagerlin & Brian J. Zikmund-Fisher, 2018. "Medical Maximizing-Minimizing Preferences Predict Responses to Information about Prostate-Specific Antigen Screening," Medical Decision Making, , vol. 38(6), pages 708-718, August.
    3. Bo Min Jeon & Su Hyun Kim & Soo Jung Lee, 2018. "Decisional conflict in end‐of‐life cancer treatment among family surrogates: A cross‐sectional survey," Nursing & Health Sciences, John Wiley & Sons, vol. 20(4), pages 472-478, December.
    4. Marieke G.M. Weernink & Janine A. van Til & Holly O. Witteman & Liana Fraenkel & Maarten J. IJzerman, 2018. "Individual Value Clarification Methods Based on Conjoint Analysis: A Systematic Review of Common Practice in Task Design, Statistical Analysis, and Presentation of Results," Medical Decision Making, , vol. 38(6), pages 746-755, August.

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