Featured research (2)
Patients' beliefs about the effectiveness of their treatments are key to the success of any intervention. However, since these beliefs are usually formed by sequentially accumulating evidence in the form of the covariation between the treatment use and the symptoms, it is not always easy to detect when a treatment is actually working. In Experiments 1 and 2, we presented participants with a contingency learning task in which a fictitious treatment was actually effective to reduce the symptoms of fictitious patients. However, the base-rate of the symptoms was manipulated so that, for half of participants, the symptoms were very frequent before the treatment, whereas for the rest of participants, the symptoms were less frequently observed. Although the treatment was equally effective in all cases according to the objective contingency between the treatment and healings, the participants' beliefs on the effectiveness of the treatment were influenced by the base-rate of the symptoms, so that those who observed frequent symptoms before the treatment tended to produce lower judgments of effectiveness. Experiment 3 showed that participants were probably basing their judgments on an estimate of effectiveness relative to the symptom base-rate, rather than on contingency in absolute terms. Data and materials are publicly available at the Open Science Framework: https://osf.io/emzbj/
Phishing is a form of electronic fraud in which attackers attempt to steal sensitive information by posing as a legitimate entity. To maintain the attack unnoticed, phishers typically use fake sites that accurately mimic real ones. However, there are usually subtle visual discrepancies between these spoof sites and their legitimate counterparts that may help Internet users to identify their deceptive nature. Among all the potential visual cues, we choose to focus on typography, because it is often hard for phishers to use exactly the same font as in the original website. Thus, Experiment 1 assessed the effectiveness of visual discrimination training to help people detect typographical discrepancies between fake and legitimate websites. Results showed higher sensitivity to differences when undergraduate students were previously trained with easier versions of the discrimination task (i.e., involving more noticeable differences in typography) than when they were trained with the difficult target discrimination from the start (easy-to-hard effect). These results were replicated with a broader and more representative sample of anonymous Internet users in Experiment 2. Implications for the design of strategies to prevent electronic fraud are discussed.