Customized versus conventional video counseling for peritoneal dialysis decision-making in patients with stage 5 chronic kidney disease under a PD-first policy: a randomized controlled study

Shared decision-making in advanced kidney disease: a scoping review

OBJECTIVES

To provide a comprehensive overview of interventions that support shared decision-making (SDM) for treatment modality decisions in advanced kidney disease (AKD). To provide summarised information on their content, use and reported results. To provide an overview of interventions currently under development or investigation.

DESIGN

The JBI methodology for scoping reviews was followed. This review conforms to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) checklist.

DATA SOURCES

MEDLINE, Embase, Web of Science, Cochrane Library, Emcare, PsycINFO, PROSPERO and Academic Search Premier for peer-reviewed literature. Other online databases (eg, clinicaltrials.gov, OpenGrey) for grey literature.

ELIGIBILITY FOR INCLUSION

Records in English with a study population of patients >18 years of age with an estimated glomerular filtration rate <30 mL/min/1.73 m2. Records had to be on the subject of SDM, or explicitly mention that the intervention reported on could be used to support SDM for treatment modality decisions in AKD.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently screened and selected records for data extraction. Interventions were categorised as prognostic tools (PTs), educational programmes (EPs), patient decision aids (PtDAs) or multicomponent initiatives (MIs). Interventions were subsequently categorised based on the decisions they were developed to support.

RESULTS

One hundred forty-five interventions were identified in a total of 158 included records: 52 PTs, 51 EPs, 29 PtDAs and 13 MIs. Sixteen (n=16, 11%) were novel interventions currently under investigation. Forty-six (n=46, 35.7%) were reported to have been implemented in clinical practice. Sixty-seven (n=67, 51.9%) were evaluated for their effects on outcomes in the intended users.

CONCLUSION

There is no conclusive evidence on which intervention is the most efficacious in supporting SDM for treatment modality decisions in AKD. There is a lot of variation in selected outcomes, and the body of evidence is largely based on observational research. In addition, the effects of these interventions on SDM are under-reported.

Decision coaching for people making healthcare decisions

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.