Medicine in words and numbers: a cross-sectional survey comparing probability assessment scales

General practitioners (GPs) gave assessments on and preferences for three different probability response scales: a numerical scale, a scale with only verbal labels, and a combined verbal-numerical scale we had designed ourselves. Standard analyses of variance were performed.No differences in assessments over the three response scales were found. Preferences for type of scale differed: the less experienced GPs preferred the verbal scale, the most experienced preferred the numerical scale, with the groups in between having a preference for the combined verbal-numerical scale.We conclude that all three response scales are equally suitable for supporting probability assessment. The combined verbal-numerical scale is a good choice for aiding the process, since it offers numerical labels to those who prefer numbers and verbal labels to those who prefer words, and accommodates both more and less experienced professionals.Reasoning under uncertainty is common practice in the medical field. Diagnoses and prognoses are always made in the face of uncertainty, for example about the exact pathogenic processes underlying some observed relation between symptom and disease. In addition, most diagnostic tests are not 100% reliable, resulting in uncertainty as to the true presence or absence of the disease tested for. On top of that, the effects of treatment may differ per patient and cannot be predicted with certainty. Clinical decision making is, in short, a complex task which could benefit from supporting tools.Support may for example be provided by the increasingly recommended 'threshold approach' [1]. This approach defines two thresholds. The first threshold indicates the decision boundary between no treatment and testing. If the clinician's estimate of the probability of the presence of a disease falls below this threshold, no treatment is given. The second threshold is the boundary between testing and treating. Probability estimates of the presence of a disease which fall betw