Decisional Conflict Scale Use over 20 Years: The Anniversary Review

Mirjam M. Garvelink, Laura Boland, Krystal Klein, Don Vu Nguyen, Matthew Menear, Hilary L. Bekker, Karen B. Eden, Annie LeBlanc, Annette M. O’Connor, Dawn Stacey and France Légaré
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Mirjam M. Garvelink: Centre de recherche sur les soins et les services de première ligne de l’Université Laval (CERSSPL-UL), Centre intégré universitaire de santé et services sociaux (CIUSSS) de la Capitale-Nationale, Québec City, QC, Canada
Laura Boland: Faculty of Health Science, University of Ottawa, Ottawa, ON, Canada
Krystal Klein: Cambia Health Solutions, Portland, OR, USA
Don Vu Nguyen: Centre de recherche sur les soins et les services de première ligne de l’Université Laval (CERSSPL-UL), Centre intégré universitaire de santé et services sociaux (CIUSSS) de la Capitale-Nationale, Québec City, QC, Canada
Matthew Menear: Centre de recherche sur les soins et les services de première ligne de l’Université Laval (CERSSPL-UL), Centre intégré universitaire de santé et services sociaux (CIUSSS) de la Capitale-Nationale, Québec City, QC, Canada
Hilary L. Bekker: Leeds Institute of Health Sciences, School of Medicine, University of Leeds, Leeds, UK (HLB)
Karen B. Eden: Pacific Northwest Evidence-Based Practice Center, Oregon Health & Science University (OHSU), Department of Medical Informatics & Clinical Epidemiology, Portland, OR, USA
Annette M. O’Connor: Faculty of Health Science, University of Ottawa, Ottawa, ON, Canada
Dawn Stacey: Faculty of Health Science, University of Ottawa, Ottawa, ON, Canada
France Légaré: Centre de recherche sur les soins et les services de première ligne de l’Université Laval (CERSSPL-UL), Centre intégré universitaire de santé et services sociaux (CIUSSS) de la Capitale-Nationale, Québec City, QC, Canada

Medical Decision Making, 2019, vol. 39, issue 4, 301-314

Abstract: Background. The Decisional Conflict Scale (DCS) measures 5 dimensions of decision making (feeling: uncertain, uninformed, unclear about values, unsupported; ineffective decision making). We examined the use of the DCS over its initial 20 years (1995 to 2015). Methods. We conducted a scoping review with backward citation search in Google Analytics/Web of Science/PubMed, followed by keyword searches in Cochrane Library, PubMed, Ovid MEDLINE, EMBASE, CINAHL, AMED, PsycINFO, PRO-Quest, and Web of Science. Eligible studies were published between 1995 and March 2015, used an original experimental/observational research design, concerned a health-related decision, and provided DCS data (total/subscales). Author dyads independently screened titles, abstracts, full texts, and extracted data. We performed narrative data synthesis. Results. We included 394 articles. DCS use appeared to increase over time. Three hundred nine studies (76%) used the original DCS, and 29 (7%) used subscales only. Most studies used the DCS to evaluate the impact of decision support interventions ( n = 238, 59%). The DCS was translated into 13 languages. Most decisions were made by people for themselves ( n = 353, 87%), about treatment ( n = 225, 55%), or testing ( n = 91, 23%). The most common decision contexts were oncology ( n = 113, 28%) and primary care ( n = 82, 20%). Conclusions. This is the first study to descriptively synthesize characteristics of DCS data. Use of the DCS as an outcome measure for health decision interventions has increased over its 20-year existence, demonstrating its relevance as a decision-making evaluation measure. Most studies failed to report when decisional conflict was measured during the decision-making process, making scores difficult to interpret. Findings from this study will be used to update the DCS user manual.

Keywords: decisional conflict scale; scoping review (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:39:y:2019:i:4:p:301-314

DOI: 10.1177/0272989X19851345

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