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- Title
Shared Decision-Making in Cardiovascular Risk Factor Management: A Systematic Review and Meta-Analysis.
- Authors
Elias, Sabrina; Chen, Yuling; Liu, Xiaoyue; Slone, Sarah; Turkson-Ocran, Ruth-Alma; Ogungbe, Bunmi; Thomas, Sabena; Byiringiro, Samuel; Koirala, Binu; Asano, Reiko; Baptiste, Diana-Lyn; Mollenkopf, Nicole L.; Nmezi, Nwakaego; Commodore-Mensah, Yvonne; Himmelfarb, Cheryl R. Dennison
- Abstract
Key Points: Question: To what extent is shared decision-making (SDM) used in interventions aimed at improving cardiovascular risk factor management, and how does SDM affect decisional outcomes, cardiovascular risk factors, and health behaviors? Findings: In this systematic review and meta-analysis of 57 randomized clinical trials that included 88 578 patients on SDM interventions for cardiovascular risk management and 1341 clinicians, SDM interventions were associated with a slight decrease in decisional conflict and an improvement in hemoglobin A1c levels with substantial heterogeneity. Meaning: These findings may help advance the field of SDM interventions for cardiovascular risk management. This systematic review and meta-analysis examines the use and outcomes of shared decision-making in interventions to enhance management of cardiovascular risk factors. Importance: The effect of shared decision-making (SDM) and the extent of its use in interventions to improve cardiovascular risk remain unclear. Objective: To assess the extent to which SDM is used in interventions aimed to enhance the management of cardiovascular risk factors and to explore the association of SDM with decisional outcomes, cardiovascular risk factors, and health behaviors. Data Sources: For this systematic review and meta-analysis, a literature search was conducted in the Medline, CINAHL, Embase, Cochrane, Web of Science, Scopus, and ClinicalTrials.gov databases for articles published from inception to June 24, 2022, without language restrictions. Study Selection: Randomized clinical trials (RCTs) comparing SDM-based interventions with standard of care for cardiovascular risk factor management were included. Data Extraction and Synthesis: The systematic search resulted in 9365 references. Duplicates were removed, and 2 independent reviewers screened the trials (title, abstract, and full text) and extracted data. Data were pooled using a random-effects model. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline. Main Outcomes and Measures: Decisional outcomes, cardiovascular risk factor outcomes, and health behavioral outcomes. Results: This review included 57 RCTs with 88 578 patients and 1341 clinicians. A total of 59 articles were included, as 2 RCTs were reported twice. Nearly half of the studies (29 [49.2%]) tested interventions that targeted both patients and clinicians, and an equal number (29 [49.2%]) exclusively focused on patients. More than half (32 [54.2%]) focused on diabetes management, and one-quarter focused on multiple cardiovascular risk factors (14 [23.7%]). Most studies (35 [59.3%]) assessed cardiovascular risk factors and health behaviors as well as decisional outcomes. The quality of studies reviewed was low to fair. The SDM intervention was associated with a decrease of 4.21 points (95% CI, −8.21 to −0.21) in Decisional Conflict Scale scores (9 trials; I2 = 85.6%) and a decrease of 0.20% (95% CI, −0.39% to −0.01%) in hemoglobin A1c (HbA1c) levels (18 trials; I2 = 84.2%). Conclusions and Relevance: In this systematic review and meta-analysis of the current state of research on SDM interventions for cardiovascular risk management, there was a slight reduction in decisional conflict and an improvement in HbA1c levels with substantial heterogeneity. High-quality studies are needed to inform the use of SDM to improve cardiovascular risk management.
- Subjects
GLYCOSYLATED hemoglobin; RESEARCH funding; CINAHL database; CONFLICT (Psychology); CARDIOVASCULAR diseases risk factors; DECISION making; EVALUATION of medical care; META-analysis; DESCRIPTIVE statistics; SYSTEMATIC reviews; MEDLINE; HEALTH behavior; MEDICAL databases; CONFIDENCE intervals; DATA analysis software
- Publication
JAMA Network Open, 2024, Vol 7, Issue 3, pe243779
- ISSN
2574-3805
- Publication type
Article
- DOI
10.1001/jamanetworkopen.2024.3779