Background: Decision coaching is non-directive support delivered by a healthcare provider to help patients prepare to actively participate in making a health decision. 'Healthcare providers' are considered to be all people who are engaged in actions whose primary intent is to protect and improve health (e.g. nurses, doctors, pharmacists, social workers, health support workers such as peer health workers). Little is known about the effectiveness of decision coaching.
Objectives: To determine the effects of decision coaching (I) for people facing healthcare decisions for themselves or a family member (P) compared to (C) usual care or evidence-based intervention only, on outcomes (O) related to preparation for decision making, decisional needs and potential adverse effects.
Search Methods: We searched the Cochrane Library (Wiley), Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE (Ovid), Embase (Ovid), PsycINFO (Ovid), CINAHL (Ebsco), Nursing and Allied Health Source (ProQuest), and Web of Science from database inception to June 2021.
Selection Criteria: We included randomised controlled trials (RCTs) where the intervention was provided to adults or children preparing to make a treatment or screening healthcare decision for themselves or a family member. Decision coaching was defined as: a) delivered individually by a healthcare provider who is trained or using a protocol; and b) providing non-directive support and preparing an adult or child to participate in a healthcare decision. Comparisons included usual care or an alternate intervention. There were no language restrictions.
Data Collection And Analysis: Two authors independently screened citations, assessed risk of bias, and extracted data on characteristics of the intervention(s) and outcomes. Any disagreements were resolved by discussion to reach consensus. We used the standardised mean difference (SMD) with 95% confidence intervals (CI) as the measures of treatment effect and, where possible, synthesised results using a random-effects model. If more than one study measured the same outcome using different tools, we used a random-effects model to calculate the standardised mean difference (SMD) and 95% CI. We presented outcomes in summary of findings tables and applied GRADE methods to rate the certainty of the evidence.
Main Results: Out of 12,984 citations screened, we included 28 studies of decision coaching interventions alone or in combination with evidence-based information, involving 5509 adult participants (aged 18 to 85 years; 64% female, 52% white, 33% African-American/Black; 68% post-secondary education). The studies evaluated decision coaching used for a range of healthcare decisions (e.g. treatment decisions for cancer, menopause, mental illness, advancing kidney disease; screening decisions for cancer, genetic testing). Four of the 28 studies included three comparator arms. For decision coaching compared with usual care (n = 4 studies), we are uncertain if decision coaching compared with usual care improves any outcomes (i.e. preparation for decision making, decision self-confidence, knowledge, decision regret, anxiety) as the certainty of the evidence was very low. For decision coaching compared with evidence-based information only (n = 4 studies), there is low certainty-evidence that participants exposed to decision coaching may have little or no change in knowledge (SMD -0.23, 95% CI: -0.50 to 0.04; 3 studies, 406 participants). There is low certainty-evidence that participants exposed to decision coaching may have little or no change in anxiety, compared with evidence-based information. We are uncertain if decision coaching compared with evidence-based information improves other outcomes (i.e. decision self-confidence, feeling uninformed) as the certainty of the evidence was very low. For decision coaching plus evidence-based information compared with usual care (n = 17 studies), there is low certainty-evidence that participants may have improved knowledge (SMD 9.3, 95% CI: 6.6 to 12.1; 5 studies, 1073 participants). We are uncertain if decision coaching plus evidence-based information compared with usual care improves other outcomes (i.e. preparation for decision making, decision self-confidence, feeling uninformed, unclear values, feeling unsupported, decision regret, anxiety) as the certainty of the evidence was very low. For decision coaching plus evidence-based information compared with evidence-based information only (n = 7 studies), we are uncertain if decision coaching plus evidence-based information compared with evidence-based information only improves any outcomes (i.e. feeling uninformed, unclear values, feeling unsupported, knowledge, anxiety) as the certainty of the evidence was very low.
Authors' Conclusions: Decision coaching may improve participants' knowledge when used with evidence-based information. Our findings do not indicate any significant adverse effects (e.g. decision regret, anxiety) with the use of decision coaching. It is not possible to establish strong conclusions for other outcomes. It is unclear if decision coaching always needs to be paired with evidence-informed information. Further research is needed to establish the effectiveness of decision coaching for a broader range of outcomes.
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http://dx.doi.org/10.1002/14651858.CD013385.pub2 | DOI Listing |
J Funct Morphol Kinesiol
December 2024
Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers Sciences and Technologies, 75013 Paris, France.
The handstand is an exercise performed in many sports, either for its own sake or as part of physical training. Unlike the upright bipedal standing posture, little is known about the sagittal alignment and balance of the spine during a handstand, which may hinder coaching and reduce the benefits of this exercise if not performed correctly. The purpose of this study was to quantify the sagittal alignment and balance of the spine during a handstand using radiographic images to characterize the strategies employed by the spino-pelvic complex during this posture.
View Article and Find Full Text PDFFront Health Serv
December 2024
School of Social Work, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Background: Professionals who provide implementation support in human service systems describe relationships as being critical to support evidence use; however, developing trusting relationships are not strongly featured in implementation science literature. The aims of this study were to (a) assess the feasibility and acceptability of a theory-driven training and coaching approach for building trusting relationships among members of an implementation team who were supporting the implementation of an evidence-informed program in a public child welfare system in the United States and (b) gauge the initial efficacy of the approach in terms of the development of trusting relationships and subsequent implementation outcomes.
Methods: Consistent with a convergent mixed-methods approach, we collected both quantitative and qualitative data to address our research questions.
BMC Med Inform Decis Mak
December 2024
School of Pharmacy, University of Washington, 1959 NE Pacific Street, Box 357630, Seattle, WA, 98195, USA.
Background: Interactive artificial intelligence tools such as ChatGPT have gained popularity, yet little is known about their reliability as a reference tool for healthcare-related information for healthcare providers and trainees. The objective of this study was to assess the consistency, quality, and accuracy of the responses generated by ChatGPT on healthcare-related inquiries.
Methods: A total of 18 open-ended questions including six questions in three defined clinical areas (2 each to address "what", "why", and "how", respectively) were submitted to ChatGPT v3.
PLoS One
December 2024
Department of Basic Education, Jiangsu Shipping College, Nantong, China.
Incorporating fuzzy logic-based models into sports prediction has generated significant interest due to the intricate nature of athletic events and the many factors influencing their outcomes. This study evaluates the effectiveness of fuzzy logic-based models in predicting sports event outcomes using a hybrid CRITIC-VIKOR approach. The objective is to improve the accuracy and reliability of sports predictions by addressing the complexity and uncertainty inherent in sports data.
View Article and Find Full Text PDFRev Panam Salud Publica
December 2024
The University of the West Indies at Cave Hill Bridgetown, Saint Michael Barbados The University of the West Indies at Cave Hill, Bridgetown, Saint Michael, Barbados.
The CaribData project, funded by the Inter-American Development Bank and implemented by The University of the West Indies, aims to enhance data-handling, -sharing and reuse capabilities in the Caribbean. The project focuses on four main objectives: developing an online data-handling platform, creating a sustainable training and mentoring program, launching a data communication initiative and conducting data availability audits. To evaluate its progress, CaribData integrates two implementation science frameworks, RE-AIM (for Reach, Effectiveness, Adoption, Implementation, Maintenance) and the Consolidated Framework for Implementation Research.
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