Risk communication in the context of clinical research

• Main Authors: Paulo NADANOVSKY (Author), Luciane Rezende COSTA (Author), Ana Paula Pires dos SANTOS (Author)
• Format: Book
• Published: Sociedade Brasileira de Pesquisa Odontológica, 2020-08-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1807-3107; 10.1590/1807-3107bor-2020.vol34.0078
• Keywords: Risk Assessment; Risk Management; Evidence-Based Practice; Dentistry; RK1-715
• Source: Brazilian Oral Research, Vol 34, Iss suppl 2 (2020)

Abstract Physicians and dentists usually make clinical decisions and recommendations without a clear understanding of the meaning of the numbers regarding the accuracy of diagnostic tests and the efficacy of treatments. This critical review aimed to identify problems in the communication of diagnostic test accuracy and treatment benefits and to suggest strategies to improve risk communication in these contexts. Most clinical decisions are taken under uncertainty. Health professionals cannot predict the outcome in one individual patient. This uncertainty invites these professionals to make decisions based on heuristics, which gives rise to several cognitive biases. Cognitive biases are automatic and unconscious, so how is it possible to mitigate their undesirable effects on risk interpretation in the context of clinical practice? Some forms of risk communication reinforce cognitive bias, while others weaken them. Maybe one of the most difficult obstacles to overcome is the difficulty to think with numbers. This difficulty probably arises from a mismatch of ancestral adaptations of the brain having to deal with modern environments, which are quite different from the ancestral ones. There are two quite common, but bad, forms of risk communication: the conditional probability and the relative risk reduction or efficacy. People, including physicians and dentists, are confused with this kind of information. The main methods discovered so far to facilitate a clearer understanding are to emphasize the base rates of the events and to use absolute numbers, that is to use natural frequencies, instead of percentages and conditional probabilities.