Efficacy of a decision support intervention for reducing decisional conflict in patients with elevated serum prostate-specific antigen: A randomized controlled trial

Decision aids for people facing health treatment or screening decisions

BACKGROUND

Patient decision aids are interventions designed to support people making health decisions. At a minimum, patient decision aids make the decision explicit, provide evidence-based information about the options and associated benefits/harms, and help clarify personal values for features of options. This is an update of a Cochrane review that was first published in 2003 and last updated in 2017.

OBJECTIVES

To assess the effects of patient decision aids in adults considering treatment or screening decisions using an integrated knowledge translation approach.

SEARCH METHODS

We conducted the updated search for the period of 2015 (last search date) to March 2022 in CENTRAL, MEDLINE, Embase, PsycINFO, EBSCO, and grey literature. The cumulative search covers database origins to March 2022.

SELECTION CRITERIA

We included published randomized controlled trials comparing patient decision aids to usual care. Usual care was defined as general information, risk assessment, clinical practice guideline summaries for health consumers, placebo intervention (e.g. information on another topic), or no intervention.

DATA COLLECTION AND ANALYSIS

Two authors independently screened citations for inclusion, extracted intervention and outcome data, and assessed risk of bias using the Cochrane risk of bias tool. Primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were attributes related to the choice made (informed values-based choice congruence) and the decision-making process, such as knowledge, accurate risk perceptions, feeling informed, clear values, participation in decision-making, and adverse events. Secondary outcomes were choice, confidence in decision-making, adherence to the chosen option, preference-linked health outcomes, and impact on the healthcare system (e.g. consultation length). We pooled results using mean differences (MDs) and risk ratios (RRs) with 95% confidence intervals (CIs), applying a random-effects model. We conducted a subgroup analysis of 105 studies that were included in the previous review version compared to those published since that update (n = 104 studies). We used Grading of Recommendations Assessment, Development, and Evaluation (GRADE) to assess the certainty of the evidence.

MAIN RESULTS

This update added 104 new studies for a total of 209 studies involving 107,698 participants. The patient decision aids focused on 71 different decisions. The most common decisions were about cardiovascular treatments (n = 22 studies), cancer screening (n = 17 studies colorectal, 15 prostate, 12 breast), cancer treatments (e.g. 15 breast, 11 prostate), mental health treatments (n = 10 studies), and joint replacement surgery (n = 9 studies). When assessing risk of bias in the included studies, we rated two items as mostly unclear (selective reporting: 100 studies; blinding of participants/personnel: 161 studies), due to inadequate reporting. Of the 209 included studies, 34 had at least one item rated as high risk of bias. There was moderate-certainty evidence that patient decision aids probably increase the congruence between informed values and care choices compared to usual care (RR 1.75, 95% CI 1.44 to 2.13; 21 studies, 9377 participants). Regarding attributes related to the decision-making process and compared to usual care, there was high-certainty evidence that patient decision aids result in improved participants' knowledge (MD 11.90/100, 95% CI 10.60 to 13.19; 107 studies, 25,492 participants), accuracy of risk perceptions (RR 1.94, 95% CI 1.61 to 2.34; 25 studies, 7796 participants), and decreased decisional conflict related to feeling uninformed (MD -10.02, 95% CI -12.31 to -7.74; 58 studies, 12,104 participants), indecision about personal values (MD -7.86, 95% CI -9.69 to -6.02; 55 studies, 11,880 participants), and proportion of people who were passive in decision-making (clinician-controlled) (RR 0.72, 95% CI 0.59 to 0.88; 21 studies, 4348 participants). For adverse outcomes, there was high-certainty evidence that there was no difference in decision regret between the patient decision aid and usual care groups (MD -1.23, 95% CI -3.05 to 0.59; 22 studies, 3707 participants). Of note, there was no difference in the length of consultation when patient decision aids were used in preparation for the consultation (MD -2.97 minutes, 95% CI -7.84 to 1.90; 5 studies, 420 participants). When patient decision aids were used during the consultation with the clinician, the length of consultation was 1.5 minutes longer (MD 1.50 minutes, 95% CI 0.79 to 2.20; 8 studies, 2702 participants). We found the same direction of effect when we compared results for patient decision aid studies reported in the previous update compared to studies conducted since 2015.

AUTHORS' CONCLUSIONS

Compared to usual care, across a wide variety of decisions, patient decision aids probably helped more adults reach informed values-congruent choices. They led to large increases in knowledge, accurate risk perceptions, and an active role in decision-making. Our updated review also found that patient decision aids increased patients' feeling informed and clear about their personal values. There was no difference in decision regret between people using decision aids versus those receiving usual care. Further studies are needed to assess the impact of patient decision aids on adherence and downstream effects on cost and resource use.

Efficacy of a Decision Support Intervention on Decisional Conflict Related to Hepatocellular Cancer Treatment: A Randomized Controlled Trial

The purpose of this study was to investigate the efficacy of decision support intervention on treatment knowledge, decision self-efficacy, decisional conflict, and decision satisfaction in patients with hepatocellular cancer. The study was a randomized controlled trial. In all, 69 patients with hepatocellular carcinoma (HCC) were recruited and randomly assigned to a decision support group or a control group. Data were collected at baseline, post-test, and follow-up using self-report questionnaires. After controlling for baseline scores, the between-group difference (95% confidence interval [CI]) for treatment-related knowledge in post-test scores was 11.9 (6.1, 17.8). After controlling for baseline scores, the between-group difference (95% CI) for decisional conflict was -7.0 (-12.0, -2.0). There was no statistically significant between-group difference in decision self-efficacy and decision satisfaction. Findings supported the efficacy of decision support intervention to improve treatment knowledge and reduce decisional conflict but had no significant effect on decision self-efficacy and decision satisfaction in patients with HCC.

Decisional Conflict About Kidney Failure Treatment Modalities Among Adults With Advanced CKD

Rationale & Objective

Choosing from multiple kidney failure treatment modalities can create decisional conflict, but little is known about this experience before decision implementation. We explored decisional conflict about treatment for kidney failure and its associated patient characteristics in the context of advanced chronic kidney disease (CKD).

Study Design

Cross-sectional study.

Setting & Participants

Adults (N = 427) who had advanced CKD, received nephrology care in Pennsylvania-based clinics, and had no history of dialysis or transplantation.

Predictors

Participants' sociodemographic, physical health, nephrology care/knowledge, and psychosocial characteristics.

Outcomes

Participants' results on the Sure of myself; Understand information; Risk-benefit ratio; Encouragement (SURE) screening test for decisional conflict (no decisional conflict vs decisional conflict).

Analytical Approach

We used multivariable logistic regression to quantify associations between aforementioned participant characteristics and decisional conflict. We repeated analyses among a subgroup of participants at highest risk of kidney failure within 2 years.

Results

Most (76%) participants reported treatment-related decisional conflict. Participant characteristics associated with lower odds of decisional conflict included complete satisfaction with patient-kidney team treatment discussions (OR, 0.16; 95% CI, 0.03-0.88; P = 0.04), attendance of treatment education classes (OR, 0.38; 95% CI, 0.16-0.90; P = 0.03), and greater treatment-related decision self-efficacy (OR, 0.97; 95% CI, 0.94-0.99; P < 0.01). Sensitivity analyses showed a similarly high prevalence of decisional conflict (73%) and again demonstrated associations of class attendance (OR, 0.26; 95% CI, 0.07-0.96; P = 0.04) and decision self-efficacy (OR, 0.95; 95% CI, 0.91-0.99; P = 0.03) with decisional conflict.

Limitations

Single-health system study.

Conclusions

Decisional conflict was highly prevalent regardless of CKD progression risk. Findings suggest efforts to reduce decisional conflict should focus on minimizing the mismatch between clinical practice guidelines and patient-reported engagement in treatment preparation, facilitating patient-kidney team treatment discussions, and developing treatment education programs and decision support interventions that incorporate decision self-efficacy-enhancing strategies.

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.