BACKGROUND: Being confronted with uncertainty in the context of health-related judgments and decision making can give rise to the occurrence of systematic biases. These biases may detrimentally affect lay persons and health experts alike. Debiasing aims at mitigating these negative effects by eliminating or reducing the biases. However, little is known about its effectiveness. This study seeks to systematically review the research on health-related debiasing to identify new opportunities and challenges for successful debiasing strategies.
METHODS: A systematic search resulted in 2748 abstracts eligible for screening. Sixty-eight articles reporting 87 relevant studies met the predefined inclusion criteria and were categorized and analyzed with regard to content and quality. All steps were undertaken independently by 2 reviewers, and inconsistencies were resolved through discussion.
RESULTS: The majority of debiasing interventions ( n = 60) was at least partially successful. Optimistic biases ( n = 25), framing effects ( n = 14), and base rate neglects ( n = 10) were the main targets of debiasing efforts. Cognitive strategies ( n = 36) such as "consider-the-opposite" and technological interventions ( n = 33) such as visual aids were mainly tested. Thirteen studies aimed at debiasing health care professionals' judgments, while 74 interventions addressed the general population. Studies' methodological quality ranged from 26.2% to 92.9%, with an average rating of 68.7%.
DISCUSSION: In the past, the usefulness of debiasing was often debated. Yet most of the interventions reviewed here are found to be effective, pointing to the utility of debiasing in the health context. In particular, technological strategies offer a novel opportunity to pursue large-scale debiasing outside the laboratory. The need to strengthen the transfer of debiasing interventions to real-life settings and a lack of conceptual rigor are identified as the main challenges requiring further research.
}, year = {2018}, journal = {Med Decis Making}, volume = {38}, pages = {3-13}, month = {12/2018}, issn = {1552-681X}, doi = {10.1177/0272989X17716672}, language = {eng}, }