Diagnostic Bias in the COVID-19 Pandemic: A Series of Short Cases.

During the COVID-19 pandemic, healthcare systems have faced unprecedented pressures. One challenge has been to promptly recognise non-COVID-19 conditions. Cognitive bias due to the availability heuristic may cause difficulties in reaching the correct diagnosis. Confirmation bias may also affect imaging interpretation. We report three cases with an alternative final diagnosis in whom COVID-19 was initially suspected: (a) Pneumocystis jirovecii pneumonia with unrecognised HIV infection; (b) pulmonary lymphangitis carcinomatosis; and (c) ST elevation myocardial infarction causing acute pulmonary oedema. To help mitigate bias, there is no substitute for thoughtful clinical assessment and critical appraisal when evaluating new information and formulating the differential diagnosis. LEARNING POINTS: The availability heuristic during the recent pandemic may lead to cognitive bias in favour of COVID-19 diagnosis and delayed recognition of other conditions, especially in patients presenting with similar non-specific features.Confirmation bias towards COVID-19 can also affect the interpretation of pulmonary imaging which is central to the investigation of cases with suspected pneumonitis.Diagnostic bias can be mitigated by recognition and allowing time for a thorough clinical history and methodical examination of the patients.

Number 19: Another Victim of the COVID-19 Pandemic?

Conscious selection is the mental process by which lottery players select numbers nonrandomly. In this paper, we show that the number 19, which has been heard, read, seen, and googled countless times since March 2020, has become significantly less popular among Belgian lottery players after the World Health Organization named the disease caused by the coronavirus SARS-CoV-2 "COVID-19". We argue that the reduced popularity of the number 19 is due to its negative association with the COVID-19 pandemic. Our study triangulates evidence from field data from the Belgian National Lottery and survey data from a nationally representative sample of 500 Belgian individuals. The field data indicate that the number 19 has been played significantly less frequently since March 2020. However, a potential limitation of the field data is that an unknown proportion of players selects numbers randomly through the "Quick Pick" computer system. The survey data do not suffer from this limitation and reinforce our previous findings by showing that priming an increase in the salience of COVID-19 prior to the players' selection of lottery numbers reduces their preference for the number 19. The effect of priming is concentrated amongst those with high superstitious beliefs, further supporting our explanation for the reduced popularity of the number 19 during the COVID-19 pandemic.

Availability Bias and the COVID-19 Pandemic: A Case Study of Legionella Pneumonia.

Cognitive biases, such as the availability heuristic or availability bias, can inadvertently affect patient outcomes. These biases may be magnified during times of heightened awareness of a particular disease. Failure to identify cognitive biases when managing patients during the coronavirus disease 2019 (COVID-19) pandemic can delay the institution of the right treatment option and result in poor health outcomes. We present a case of delayed diagnosis of Legionella pneumonia due to COVID-19-related availability bias. We discuss some methods to mitigate the effects of this bias and the importance of challenging trainees to recognize these pitfalls in medical training.

Risk Perception in a Real-World Situation (COVID-19): How It Changes From 18 to 87 Years Old.

Studies on age-related differences in risk perception in a real-world situation, such as the recent COVID-19 outbreak, showed that the risk perception of getting COVID-19 tends to decrease as age increases. This finding raised the question on what factors could explain risk perception in older adults. The present study examined age-related differences in risk perception in the early stages of COVID-19 lockdown, analyzing variables that can explain the differences in perception of risk at different ages. A total of 1,765 adults aged between 18 and 87 years old completed an online survey assessing perceived risk severity and risk vulnerability of getting COVID-19, sociodemographic status, emotional state, experience relating to COVID-19, and physical health status. Results showed that the older the participants, the lower the perceived vulnerability to getting COVID-19, but the higher the perceived severity. Different predictors explain the perception of risk severity and vulnerability at different ages. Overall, self-reported anxiety over the pandemic is a crucial predictor in explaining risk perceptions in all age groups. Theoretical and practical implications of the empirical findings are discussed.