Predicting downstream effects of high decisional conflict: Meta-analyses of the decisional conflict scale

Background. The Decisional Conflict Scale (DCS) is a useful clinical tool in assessing the health care consumers' decisional needs. However, the exact predictive ability of the DCS is unknown. Objective. To examine the DCS as a proxy measure for patients' knowledge level and as a predictor of downstream effects of high decisional conflict, specifically, decision delay, discontinuance of chosen option, and decisional regret. Design. Meta-analyses with individual data from 10 clinical trials using the following statistics: descriptive statistics, correlation analysis and logistic regression. Results. Patients' knowledge deficit has a fair association with the uninformed subscale of the DCS (OR 3.10; 95% CI 1.58-6.05). Patients' decisional delay has a very strong association with the DCS (OR 23.81; 4.66-121.51). Patients' discontinuance of chosen treatment has a varied association with the DCS, very strong for change from status quo (OR 59.37; 4.09-861.05) and fair for change from active treatment (OR 3.39; 1.42-8.00). Patients' decisional regret has a strong association with the DCS (OR 5.52; 3.35-9.12). Conclusion. When clinicians assess a patient's decisional conflict after counselling, and they find the decisional conflict is low, they can be reasonably assured that the likelihood of downstream decision delay, change from the status quo, or decisional regret will be low. However, low scores on the uninformed scale do not guarantee the patient is well informed; they need to validate the patients' understanding with some follow-up questions. Moreover, the likelihood of discontinuing active treatment even with low decisional conflict is also a possibility