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Decisional Conflict Scale Findings among Patients and Surrogates Making Health Decisions: Part II of an Anniversary Review.

Mirjam Marjolein GarvelinkLaura BolandKrystal KleinDon Vu NguyenMatthew MenearHilary L BekkerKaren B EdenAnnie LeBlancAnnette M O'ConnorShi Wu WenFrance Légaré
Published in: Medical decision making : an international journal of the Society for Medical Decision Making (2019)
Background. We explored decisional conflict as measured with the 16-item Decisional Conflict Scale (DCS) and how it varies across clinical situations, decision types, and exposure to decision support interventions (DESIs). Methods. An exhaustive scoping review was conducted using backward citation searches and keyword searches. 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. Dyads independently screened titles/abstracts and full texts, and extracted data. We performed narrative syntheses and calculated average or median DCS scores. Results. We included 246 articles reporting on 253 studies. DCS scores ranged from 2.4 to 89.6 out of 100. Highest baseline DCS scores were for care planning (30.5 ± 12.8, median = 30.9) and treatment decisions (30.5 ± 14.6, median = 28.0), in contexts of primary care (33.8 ± 19.8), obstetrics/gynecology (28.8 ± 10.4), and geriatrics (32.6 ± 10.7). Baseline scores were high among decision makers who were ill (29.5 ± 13.8, median = 27.2) or making decisions for themselves (29.7 ± 14.8, median = 26.9). Total DCS scores <25 out of 100 were associated with implementing decisions. Without DESIs, DCS scores tended to increase shortly after decision making (>37.4). After DESI use, DCS scores decreased short-term but increased or remained the same long-term (>6 months). Conclusions. DCS scores were highest at baseline and decreased after decision making. DESIs decreased decisional conflict immediately after decision making. The largest improvements after DESIs were in decision makers who were ill, male, or made decisions for themselves. Meta-analyses focusing on decision types, contexts, and interventions could inform hypotheses about the expected effects of DESIs, the best timing for measurement, and interpretation of DCS scores.
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