Individual Value Clarification Methods Based on Conjoint Analysis: A Systematic Review of Common Practice in Task Design, Statistical Analysis, and Presentation of Results

Marieke G.M. Weernink, Janine A. van Til, Holly O. Witteman, Liana Fraenkel and Maarten J. IJzerman
Additional contact information
Marieke G.M. Weernink: Department of Health Technology and Services Research, MIRA—Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, the Netherlands
Janine A. van Til: Department of Health Technology and Services Research, MIRA—Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, the Netherlands
Holly O. Witteman: Department of Family and Emergency Medicine, Office of Education and Professional Development, Laval University, Quebec City, QC, Canada
Liana Fraenkel: School of Medicine, Yale University, New Haven, CT, USA
Maarten J. IJzerman: Department of Health Technology and Services Research, MIRA—Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, the Netherlands

Medical Decision Making, 2018, vol. 38, issue 6, 746-755

Abstract: Background. There is an increased practice of using value clarification exercises in decision aids that aim to improve shared decision making. Our objective was to systematically review to which extent conjoint analysis (CA) is used to elicit individual preferences for clinical decision support. We aimed to identify the common practices in the selection of attributes and levels, the design of choice tasks, and the instrument used to clarify values. Methods. We searched Scopus, PubMed, PsycINFO, and Web of Science to identify studies that developed a CA exercise to elicit individual patients’ preferences related to medical decisions. We extracted data on the above-mentioned items. Results. Eight studies were identified. Studies included a fixed set of 4–8 attributes, which were predetermined by interviews, focus groups, or literature review. All studies used adaptive conjoint analysis (ACA) for their choice task design. Furthermore, all studies provided patients with their preference results in real time, although the type of outcome that was presented to patients differed (attribute importance or treatment scores). Among studies, patients were positive about the ACA exercise, whereas time and effort needed from clinicians to facilitate the ACA exercise were identified as the main barriers to implementation. Discussion. There is only limited published use of CA exercises in shared decision making. Most studies resembled each other in design choices made, but patients received different feedback among studies. Further research should focus on the feedback patients want to receive and how the CA results fit within the patient–physician dialogue.

Keywords: conjoint analysis; adaptive conjoint analysis; clinical decision making; shared decision making; values clarification methods; values clarification exercises (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X18765185 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:38:y:2018:i:6:p:746-755

DOI: 10.1177/0272989X18765185

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().