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Related Experiment Video

Updated: Mar 26, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

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

Holly O Witteman1,2,3, Laura D Scherer4, Teresa Gavaruzzi5

  • 1Department of Family and Emergency Medicine, Faculty of Medicine, Laval University, Quebec City, Quebec, Canada (HOW)

Medical Decision Making : an International Journal of the Society for Medical Decision Making
|January 31, 2016
PubMed

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Summary
This summary is machine-generated.

Patient decision aids often use values clarification, but design evidence is scarce. This study catalogs 98 methods, revealing common practices and areas for improvement in designing effective decision support tools.

Area of Science:

  • Patient decision making
  • Health behavior
  • Health services research

Background:

  • Values clarification is crucial for patient decision aids.
  • Existing methods for values clarification lack synthesized evidence for design guidance.

Purpose of the Study:

  • To systematically describe explicit values clarification methods.
  • To categorize methods based on a taxonomy of design features.

Main Methods:

  • Searched multiple databases (MEDLINE, CINAHL, EMBASE, etc.) and references.
  • Included articles describing explicit values clarification methods.
  • Extracted data on decision context, theoretical basis, and 12 design features.

Main Results:

Keywords:
clarifydecision aidsdecision makingdesignpreferencesshared decision makingvaluesvalues clarificationvalues clarification exercisevalues clarification method

Related Experiment Videos

Last Updated: Mar 26, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
10:39

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Published on: August 29, 2025

1.3K
  • Identified 98 explicit values clarification methods across 110 articles.
  • Most methods focused on cancer or reproductive health decisions, often with binary choices.
  • Common methods like 'pros and cons' often lacked user-specific concerns, tradeoff explanations, or alignment with user values.

    • Conclusions:

    • Values clarification methods exhibit diverse designs that can be classified using a taxonomy.
    • Developers should consider all taxonomy design features and publish detailed descriptions.
    • Further research is needed to evaluate the impact of different design features on patient decision-making.