A pandemic of cognitive bias

Descriptive Norms and eHealth Use Among Older Adults: A Cross-Country Comparative Study

eHealth use enables older adults to access and manage healthcare resources, and benefits their health; however, older adults' uptake of eHealth remains low across societies. Social influences such as descriptive norms may be of critical importance in promoting the elderly's usage of eHealth. Based on the Integrative Model of Behavioral Prediction, this study investigates how descriptive norms relate to eHealth use among the elderly in China and the United States. Analysis of the combined sample (N = 1,070) showed that descriptive norms were positively related to eHealth use. Also, descriptive norms were indirectly associated with eHealth use via injunctive norms, attitudes and self-efficacy. Moderated mediation analysis indicated that these direct and indirect relationships differed across the two countries. This study highlights the important role of descriptive norms in promoting older adults' eHealth use behavior and addresses potential country differences in how the elderly respond to descriptive norms. Several important theoretical and practical implications are also discussed.

COVID-19-Associated Cognitive Biases on Pneumonia Differential Diagnosis

The coronavirus disease 2019 (COVID-19) pandemic favors cognitive biases such as anchoring and availability biases. The first refers to overvaluing some of the initial information and establishing a diagnosis too early, with resistance to future adjustments. The latter happens when diagnoses more frequently considered are regarded as more common in reality. This case, in which the correct diagnosis was delayed due to these biases, highlights the need to remain aware of them as a means toward timely diagnosis and therapeutic success of pneumonia cases. An 84-year-old woman presented with a mild non-productive cough for two months and fever. She had a history of breast carcinoma treated with radiotherapy in the previous year. Computerized tomography (CT) showed extensive bilateral consolidation foci with ground-glass-opacification areas and bilateral pleural effusion, CO-RADS 3. COVID-19 with bacterial superinfection was suspected and levofloxacin was initiated. Nasopharyngeal swab polymerase chain reaction (PCR) was carried out three times, always negative for SARS-CoV-2. As the patient remained with fever and cough, the antibiotic was escalated to piperacillin/tazobactam and then to meropenem/vancomycin. She underwent bronchofibroscopy and alveolar lavage, with negative SARS-CoV-2 PCR. The re-evaluation CT scan maintained bilateral consolidations, with an aerial bronchogram. The biopsy of pulmonary consolidation allowed the diagnosis of radiation-induced organizing pneumonia. Prednisolone was initiated and achieved clinical remission and radiological improvement. This case highlights the need to remain aware of cognitive biases both when COVID-19 is suspected or ruled out and to consider other diagnoses when there is a lack of therapeutic response.

Heuristics and biases in medical decision-making under uncertainty: The case of neuropronostication for consciousness disorders

Neuropronostication for consciousness disorders can be very complex and prone to high uncertainty. Despite notable advancements in the development of dedicated scales and physiological markers using innovative paradigms, these technical progressions are often overshadowed by factors intrinsic to the medical environment. Beyond the scarcity of objective data guiding medical decisions, factors like time pressure, fatigue, multitasking, and emotional load can drive clinicians to rely more on heuristic-based clinical reasoning. Such an approach, albeit beneficial under certain circumstances, may lead to systematic error judgments and impair medical decisions, especially in complex and uncertain environments. After a brief review of the main theoretical frameworks, this paper explores the influence of clinicians' cognitive biases on clinical reasoning and decision-making in the challenging context of neuroprognostication for consciousness disorders. The discussion further revolves around developing and implementing various strategies designed to mitigate these biases and their impact, aiming to enhance the quality of care and the patient safety.

Cognitive bias toward the Internet: The causes of adolescents' Internet addiction under parents' self-affirmation consciousness

The Internet plays a crucial part in the adolescent life. However, as a product of modernization, the Internet has brought a lifestyle different from that of our parents who tend to regard excessive exposure to the Internet as a manifestation of the adolescent Internet addiction. The cognitive bias against the Internet seem to have been arisen among the parents. Under the theoretical framework of self-efficacy and empathy, this study adopts PLS-SEM to analyze the contributing factors of the adolescent Internet addiction from the perspective of self-affirmation consciousness of parents. The result demonstrates that self-affirmation consciousness has a significant positive effect on the empathy process; the empathy process and self-affirmation have a significant positive effect on cognitive bias; and the empathy process acts as a mediator between self-affirmation and cognitive bias. To sum up, through the investigation of the causes of adolescent Internet addiction, this study explores the formation process of parents' cognitive bias toward the Internet under the influence of self-affirmation consciousness, verifying the practical effects of empathy in the process of promoting rational thinking of parents toward the Internet and adolescent Internet use, and at the same time promoting the harmonious development of parent-child relationships to a certain extent.

Nanoeconomics of Households in Lockdown Using Agent Models during COVID-19

The world is experiencing a global pandemic with COVID-19, for which few measures have proven their efficiency. Prevention through lockdown belongs to the portfolio of Non-Pharmaceutical Intervention (NPI). The implementation of a lockdown comes with a potential health care benefit balanced with an economic and human cost: people are constrained to stay in their homes. Households hence have to live together in what we call “zero-space”, which means within the walls of their flat or house. The loss of “space-domain” freedom, preventing them to move in “free” space is accompanied by a continued “time-domain” freedom with the possibility to allocate their time, and what they do with it, within the location they are not permitted to leave (with very defined exceptions). We study the microeconomics framework in such a setting, starting from the rules shaping such a “nano-market” with very few agents (the members of the household), and its consequence for nano-economic interaction. Since the behaviour of the agents is hyperconstrained in the space domain and relatively free in the time domain, behavioral economics is used to describe decisions made in the home, for the actions remaining possible during lockdown. A minimal set of rules is introduced and illustrated to describe efficiently the agents at play in this new and particular context, which has been replicated worldwide during the pandemic. Hypotheses for this model are presented and discussed, so as to allow future variations and adaptations for other specific cases with different options chosen. Such hypotheses concern agents, their interests, behaviours, and the equivalent of non-financial “nano-market transactions and contracts”.

Implicit bias in healthcare: clinical practice, research and decision making

Bias is the evaluation of something or someone that can be positive or negative, and implicit or unconscious bias is when the person is unaware of their evaluation. This is particularly relevant to policymaking during the coronavirus pandemic and racial inequality highlighted during the support for the Black Lives Matter movement. A literature review was performed to define bias, identify the impact of bias on clinical practice and research as well as clinical decision making (cognitive bias). Bias training could bridge the gap from the lack of awareness of bias to the ability to recognise bias in others and within ourselves. However, there are no effective debiasing strategies. Awareness of implicit bias must not deflect from wider socio-economic, political and structural barriers as well ignore explicit bias such as prejudice.