TY - JOUR
T1 - Decisional Conflict Scale Use over 20 Years
T2 - The Anniversary Review
AU - Garvelink, Mirjam M.
AU - Boland, Laura
AU - Klein, Krystal
AU - Nguyen, Don Vu
AU - Menear, Matthew
AU - Bekker, Hilary L.
AU - Eden, Karen B.
AU - LeBlanc, Annie
AU - O’Connor, Annette M.
AU - Stacey, Dawn
AU - Légaré, France
N1 - Funding Information:
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 (MMG, DVN, MM, FL); Pacific Northwest Evidence-Based Practice Center, Oregon Health & Science University (OHSU), Department of Medical Informatics & Clinical Epidemiology, Portland, OR, USA (KBE); Cambia Health Solutions, Portland, OR, USA (KK); Leeds Institute of Health Sciences, School of Medicine, University of Leeds, Leeds, UK (HLB); Faculty of Health Science, University of Ottawa, Ottawa, ON, Canada (AMO, DSLB); Ottawa Hospital Research Institute, Ottawa, ON, Canada (DSLB); and Department of Family Medicine and Emergency Medicine, Université Laval, Quebec City, QC, Canada (FL). The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This scoping review is funded by the Tier 1 Canada Research Chair in Shared Decision-Making and Knowledge Translation at Université Laval. Mirjam M. Garvelink is supported by a postdoctoral fellowship from the Canadian Institutes of Health Research (CIHR), funding reference number MFE-140842. Registration number: CRD42014013556.
Publisher Copyright:
© The Author(s) 2019.
PY - 2019/5/1
Y1 - 2019/5/1
N2 - 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.
AB - 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.
KW - decisional conflict scale
KW - scoping review
UR - http://www.scopus.com/inward/record.url?scp=85066826911&partnerID=8YFLogxK
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U2 - 10.1177/0272989X19851345
DO - 10.1177/0272989X19851345
M3 - Review article
C2 - 31142194
AN - SCOPUS:85066826911
SN - 0272-989X
VL - 39
SP - 301
EP - 314
JO - Medical Decision Making
JF - Medical Decision Making
IS - 4
ER -