The lone wolf of Wall Street: the connection between isolated financial decision-making and overconfidence

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Overconfidence at the time of COVID-19: does it lead to laxer attitudes?

Background: Health education campaigns often aim to create awareness by increasing objective knowledge about pathogens, such as COVID-19. However, the present paper proposes that confidence in one's knowledge more than knowledge is a significant factor that leads to a laxer attitude toward COVID-19 and hence lower support for protective measures and reduced intention to comply with preemptive behaviors. Methods: We tested two hypotheses in three studies conducted between 2020 and 2022. In Study 1, we assessed participants’ level of knowledge and confidence, as well as attitudes toward COVID-19. In Study 2, we tested the relation between fear of COVID-19 and protective behaviors. In Study 3, we used an experimental approach to show the causal effect of overconfidence on fear of COVID-19. In addition to manipulating overconfidence and measuring fear of COVID-19, we also measured prophylactic behaviors. Results: In Study 1, more overconfident participants had a laxer attitude toward COVID-19. While knowledge had an increasing effect on worry, confidence in said knowledge significantly decreased worry about COVID-19. In Study 2, participants who were more worried about COVID-19 were more likely to engage in protective behaviors (e.g., wearing masks). In Study 3, we show that when overconfidence was experimentally diminished, fear of COVID-19 increased. The results support our claim that the effect of overconfidence on attitudes toward COVID-19 is causal in nature. Moreover, the results show that people with higher fear of COVID-19 are more likely to wear masks, use hand sanitizers, avoid crowded places or social gatherings, and get vaccinated. Conclusions: Managing adherence to public health measures is critical when it comes to highly infectious diseases. Our findings suggest that efficient information campaigns to increase adherence to public health measures should focus on calibrating people's confidence in their knowledge about COVID-19 to prevent the spread of the virus.</p

Living alone and mental health: parallel analyses in UK longitudinal population surveys and electronic health records prior to and during the COVID-19 pandemic

Background People who live alone experience greater levels of mental illness; however, it is unclear whether the COVID-19 pandemic had a disproportionately negative impact on this demographic.Objective To describe the mental health gap between those who live alone and with others in the UK prior to and during the COVID-19 pandemic.Methods Self-reported psychological distress and life satisfaction in 10 prospective longitudinal population surveys (LPSs) assessed in the nearest pre-pandemic sweep and three periods during the pandemic. Recorded diagnosis of common and severe mental illnesses between March 2018 and January 2022 in electronic healthcare records (EHRs) within the OpenSAFELY-TPP.Findings In 37 544 LPS participants, pooled models showed greater psychological distress (standardised mean difference (SMD): 0.09 (95% CI: 0.04; 0.14); relative risk: 1.25 (95% CI: 1.12; 1.39)) and lower life satisfaction (SMD: −0.22 (95% CI: −0.30; −0.15)) for those living alone pre-pandemic. This gap did not change during the pandemic. In the EHR analysis of c.16 million records, mental health conditions were more common in those who lived alone (eg, depression 26 (95% CI: 18 to 33) and severe mental illness 58 (95% CI: 54 to 62) more cases more per 100 000). For common mental health disorders, the gap in recorded cases in EHRs narrowed during the pandemic.Conclusions People living alone have poorer mental health and lower life satisfaction. During the pandemic, this gap in self-reported distress remained; however, there was a narrowing of the gap in service use.Clinical implicationsGreater mental health need and potentially greater barriers to mental healthcare access for those who live alone need to be considered in healthcare planning.</p

Impacts of the COVID-19 pandemic on deprivation-level differences in cardiovascular hospitalisations: a comparison of England and Denmark using the OpenSAFELY platform and National Registry Data

Objectives To examine the impact of the COVID-19 pandemic on deprivation-related inequalities in hospitalisations for cardiovascular disease (CVD) conditions in Denmark and England between March 2018 and December 2021.Design Time-series studies in England and Denmark.Setting With the approval of National Health Service England, we used English primary care electronic health records, linked to secondary care and death registry data through the OpenSAFELY platform and nationwide Danish health registry data.Participants We included adults aged 18 and over without missing age, sex or deprivation information. On 1 March 2020, 16 234 700 people in England and 4 491 336 people in Denmark met the inclusion criteria.Primary outcome measures Hospital admissions with the primary reason for myocardial infarction (MI), ischaemic or haemorrhagic stroke, heart failure and venous thromboembolism (VTE).Results We saw deprivation gradients in monthly CVD hospitalisations in both countries, with differences more pronounced in Denmark. Based on pre-pandemic trends, in England, there were an estimated 2608 fewer admissions than expected for heart failure in the most deprived quintile during the pandemic compared with an estimated 979 fewer admissions in the least deprived quintile. For all other outcomes, there was little variation by deprivation quintile. In Denmark, there were an estimated 1013 fewer admissions than expected over the pandemic for MI in the most deprived quintile compared with 619 in the least deprived quintile. Similar trends were seen for stroke and VTE, though absolute numbers were smaller. Heart failure admissions were similar to pre-pandemic levels with little variation by deprivation quintile.Conclusions Overall, we did not find that the pandemic substantially worsened pre-existing deprivation-related differences in CVD hospitalisations, though there were exceptions in both countries.</p

Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform

BackgroundThe COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England.MethodsIn this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020.FindingsOf 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences.InterpretationOur study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes.</p