Health professionals prefer to communicate risk-related numerical information using “1-in-X” ratios
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AuthorSirota, Miroslav; Juanchich, Marie; Petrova, Dafina; García-Retamero, Rocío; Walasek, Lukasz; Bhatia, Sudeep
Format preference“1-in-X” effect“1-in-X” ratioSubjective probabilityRisk communication
Sirota, Miroslav, Juanchich, Marie, Petrova, Dafina, Garcia-Retamero, Rocio, Walasek, Lukasz and Bhatia, Sudeep. (2017) Health professionals prefer to communicate risk-related numerical information using “1-in-X” ratios. Medical Decision Making. PREPRINT [http://hdl.handle.net/10481/52767]
Previous research showed that format effects such as the “1-in-X” effect – whereby “1-in-X” ratios lead to a higher perceived probability than “N-in-N*X” ratios – alter perceptions of medical probabilities. We do not know, however, how prevalent this effect is in practice – whether health professionals often use “1-in-X” ratios. We assembled four different sources of evidence, involving experimental work and corpus studies, to examine the use of “1-in-X” and other numerical formats quantifying probability. Our results revealed that the use of “1-in-X” ratios is prevalent and that health professionals prefer this format compared with other numerical formats (i.e., the “N-in-N*X”, %, and decimal formats). In Study 1, UK family physicians preferred to communicate prenatal risk using a “1-in-X” ratio (80.4%, n = 131) across different risk levels and regardless of patients’ numeracy levels. In Study 2, a sample from the UK adult population (n = 203), reported that most GPs (60.6%) preferred to use “1-in-X” ratios compared with other formats. In Study 3, “1-in-X” ratios were the most commonly used format in a set of randomly sampled drug leaflets describing the risk of side effects (100%, n = 94). In Study 4, the “1-in-X” format was the most commonly used numerical expression of medical probabilities or frequencies on the UK’s NHS website (45.7%, n = 2,469 sentences). The prevalent use of “1-in-X” ratios magnifies the chances of increased subjective probability. Further research should establish clinical significance of the “1-in-X” effect.