Mindfulness as a Protective Factor Against Increased Tobacco and Alcohol Use in Hospital Workers Following the First COVID-19-Related Lockdown: a Study in Southern France.

COVID-19-related national lockdowns worldwide have had repercussions on people's well-being and have led to increased substance use. Mindfulness has previously been associated with reduced psychological distress and benefits in terms of addictive behaviors. We aimed to assess whether dispositional mindfulness protected against increased tobacco and alcohol use in hospital workers after France's first lockdown started. All workers in two French hospitals were contacted by email to participate in an online survey. Three hundred eighty-five workers answered. We ran two separate logistic regression models to test for associations between the level of dispositional mindfulness and both increased tobacco and alcohol use, after adjusting for affect deterioration. Dispositional mindfulness was associated with a lower likelihood of increased tobacco (adjusted odds ratio (AOR) [95% CI] 0.71 [0.51; 0.99], p = 0.046) and alcohol (0.66 [0.50; 0.87], p = 0.004) use. The effect of mindfulness on tobacco use was partially mediated by affect deterioration. Dispositional mindfulness appeared to be a protective factor against lockdown-related tobacco and alcohol use increases in French hospital workers.

Psychological Distress and Tobacco Use Among Hospital Workers During COVID-19.

Background and Aims: This work aims to assess the impact of the COVID-19 pandemic on hospital workers' psychological parameters and attitudes toward substance use, before and during the French COVID-19 lockdown. Methods: An online survey was proposed to the staff of the University Hospital of Nice and Sainte-Marie psychiatric hospital in France from May 18 to June 6, 2020 assessing changes in daily habits, psychological distress and changes in substance use, including smoking. Results: A total of 702 respondents (80.3% female) filled out the survey. Overall, most of the workers reported increased stress, irritability, sadness, decreased motivation, and a worse quality of sleep after the beginning of the COVID-19 lockdown. Additionally, hospital workers who were more likely to use tobacco during the COVID-19 lockdown reported increased sadness (OR = 1.23, p < 0.001), loss of motivation (OR = 0.86, p < 0.05), alcohol consumption (OR = 3.12, p < 0.001), lower incomes (OR = 1.69, p < 0.05), living alone (OR = 1.77, p < 0.001) and doing less physical activity (OR = 0.36, p < 0.001). Conclusion: During the first lockdown, significant psychological changes (sadness, distress, irritability) associated with changes in tobacco use and physical activity were reported. Such results should encourage hospital leaders to implement dedicated policies to better accompany hospital workers' psychological distress.

On the True Number of COVID-19 Infections: Effect of Sensitivity, Specificity and Number of Tests on Prevalence Ratio Estimation.

In this paper, a formula for estimating the prevalence ratio of a disease in a population that is tested with imperfect tests is given. The formula is in terms of the fraction of positive test results and test parameters, i.e., probability of true positives (sensitivity) and the probability of true negatives (specificity). The motivation of this work arises in the context of the COVID-19 pandemic in which estimating the number of infected individuals depends on the sensitivity and specificity of the tests. In this context, it is shown that approximating the prevalence ratio by the ratio between the number of positive tests and the total number of tested individuals leads to dramatically high estimation errors, and thus, unadapted public health policies. The relevance of estimating the prevalence ratio using the formula presented in this work is that precision increases with the number of tests. Two conclusions are drawn from this work. First, in order to ensure that a reliable estimation is achieved with a finite number of tests, testing campaigns must be implemented with tests for which the sum of the sensitivity and the specificity is sufficiently different than one. Second, the key parameter for reducing the estimation error is the number of tests. For a large number of tests, as long as the sum of the sensitivity and specificity is different than one, the exact values of these parameters have very little impact on the estimation error.