Purpose/Background Observational studies show an association between nightmares and suicide. Prazosin is proposed as a nightmare treatment. This pilot, randomized clinical trial tested whether treatment of nightmares with prazosin would reduce suicidal ideas in suicidal posttraumatic stress disorder (PTSD) patients. Methods/Procedures Twenty adult, suicidal PTSD patients with nightmares were blindly and randomly assigned 1:1 to escalating doses of prazosin versus placebo at bedtime only for 8 weeks. All participants had comorbid mood disorders and received stable doses of mood disorder medication. Outcomes of interest were measured weekly and included severity of suicidal ideation, nightmares, PTSD, insomnia, and depression. Longitudinal mixed-effects models assessed change in outcomes over time. Findings/Results All psychometric measures improved over 8 weeks. However, nighttime measures of nightmares and insomnia showed significantly less improvement in the prazosin group, whereas there was no significant change in daytime measures of suicidal ideation and daytime-only PTSD symptoms. Two patients required emergency psychiatric hospitalization, but there were no suicide attempts and no deaths. Implications/Conclusions This study confirmed an effect of nighttime-only prazosin on nighttime symptoms of insomnia and nightmares in suicidal PTSD patients who are experiencing nightmares. Surprisingly, the effect was in the direction opposite of what we expected. Furthermore, prazosin showed no signal on daytime measures including suicidal ideation. The results do not support a larger study of nighttime-only prazosin in suicidal PTSD patients but leave open the possibility of benefit from daytime administration of prazosin.

Camouflage-breaking is a special case of visual search where an object of interest, or target, can be hard to distinguish from the background even when in plain view. We have previously shown that naive, non-professional subjects can be trained using a deep learning paradigm to accurately perform a camouflage-breaking task in which they report whether or not a given camouflage scene contains a target. But it remains unclear whether such expert subjects can actually detect the target in this task, or just vaguely sense that the two classes of images are somehow different, without being able to find the target per se. Here, we show that when subjects break camouflage, they can also localize the camouflaged target accurately, even though they had received no specific training in localizing the target. The localization was significantly accurate when the subjects viewed the scene as briefly as 50 ms, but more so when the subjects were able to freely view the scenes. The accuracy and precision of target localization by expert subjects in the camouflage-breaking task were statistically indistinguishable from the accuracy and precision of target localization by naive subjects during a conventional visual search where the target ‘pops out’, i.e., is readily visible to the untrained eye. Together, these results indicate that when expert camouflage-breakers detect a camouflaged target, they can also localize it accurately.

When making decisions under uncertainty, human subjects do not always act as rational decision makers, but often resort to one or more mental “shortcuts”, or heuristics, to arrive at a decision. How do such “top-down” processes affect real-world decisions that must take into account empirical, “bottom-up” sensory evidence? Here we use recognition of camouflaged objects by expert viewers as an exemplar case to demonstrate that the effect of heuristics can be so strong as to override the empirical evidence in favor of heuristic information, even though the latter is random. We provided the viewers a random number that we told them was the estimate of a drone reconnaissance system of the probability that the visual image they were about to see contained a camouflaged target. We then showed them the image. We found that the subjects’ own estimates of the probability of the target in the image reflected the random information they were provided, and ignored the actual evidence in the image. However, when the heuristic information was not provided, the same subjects were highly successful in finding the target in the same set of images, indicating that the effect was solely attributable to the availability of heuristic information. Two additional experiments confirmed that this effect was not idiosyncratic to camouflage images, visual search task, or the subjects’ prior training or expertise. Together, these results demonstrate a novel aspect of the interaction between heuristics and sensory information during real-world decision making, where the former can be strong enough to veto the latter. This ‘heuristic vetoing’ is distinct from the vetoing of sensory information that occurs in certain visual illusions.

Many studies have shown that using a computer-aided detection (CAD) system does not significantly improve diagnostic accuracy in radiology, possibly because radiologists fail to interpret the CAD results properly. We tested this possibility using screening mammography as an illustrative example. We carried out two experiments, one using 28 practicing radiologists, and a second one using 25 non-professional subjects. During each trial, subjects were shown the following four pieces of information necessary for evaluating the actual probability of cancer in a given unseen mammogram: the binary decision of the CAD system as to whether the mammogram was positive for cancer, the true-positive and false-positive rates of the system, and the prevalence of breast cancer in the relevant patient population. Based only on this information, the subjects had to estimate the probability that the unseen mammogram in question was positive for cancer. Additionally, the non-professional subjects also had to decide, based on the same information, whether to recall the patients for additional testing. Both groups of subjects similarly (and significantly) overestimated the cancer probability regardless of the categorical CAD decision, suggesting that this effect is not peculiar to either group. The misestimations were not fully attributable to causes well-known in other contexts, such as base rate neglect or inverse fallacy. Non-professional subjects tended to recall the patients at high rates, even when the actual probably of cancer was at or near zero. Moreover, the recall rates closely reflected the subjects’ estimations of cancer probability. Together, our results show that subjects interpret CAD system output poorly when only the probabilistic information about the underlying decision parameters is available to them. Our results also highlight the need for making the output of CAD systems more readily interpretable, and for providing training and assistance to radiologists in evaluating the output.

When making decisions under uncertainty, people in all walks of life, including highly trained medical professionals, tend to resort to using ‘mental shortcuts’, or heuristics. Anchoring-and-adjustment (AAA) is a well-known heuristic in which subjects reach a judgment by starting from an initial internal judgment (‘anchored position’) based on available external information (‘anchoring information’) and adjusting it until they are satisfied. We studied the effects of the AAA heuristic during diagnostic decision-making in mammography. We provided practicing radiologists (N = 27 across two studies) a random number that we told them was the estimate of a previous radiologist of the probability that a mammogram they were about to see was positive for breast cancer. We then showed them the actual mammogram. We found that the radiologists’ own estimates of cancer in the mammogram reflected the random information they were provided and ignored the actual evidence in the mammogram. However, when the heuristic information was not provided, the same radiologists detected breast cancer in the same set of mammograms highly accurately, indicating that the effect was solely attributable to the availability of heuristic information. Thus, the effects of the AAA heuristic can sometimes be so strong as to override the actual clinical evidence in diagnostic tasks.