Challenges and Potential Solutions for Physician's Suicide risk factors in the COVID-19 Era: Psychiatric Comorbidities, Medicine Judicialization, and Burnout.

INTRODUCTION: Suicide in physicians outlines a public health problem that deserves more consideration. A recently performed meta-analysis and systematic review evaluated suicide mortality in physicians by gender and investigated several related risk factors. It showed a post-1980 suicide mortality ratio 46% higher in female physicians than women in the general population and a 33% lower risk in male physicians than men in general, despite an overall contraction in physicians' mortality rates in both genders. METHODS: This narrative review was conducted through a search and analysis of relevant articles/databases to address questions raised by the meta-analysis, and how they may be affected by COVID-19. The process included unstructured searches on physician suicide, burnout, medicine judicialization, healthcare organization and COVID-19 on Pubmed, and Google searches for relevant databases, medical society, expert and media commentaries on these topics. We focus on three factors critical to address physician suicides: epidemiological data limitations, psychiatric comorbidities, and professional overload. RESULTS: We found relevant articles on suicide reporting, physician mental health, effects of healthcare judicialization and organization on physician and patient health, and how COVID-19 may impact such factors. This review addresses information sources, underreporting/misreporting of physicians' suicide rates, inadequate diagnosis and management of psychiatric comorbidities and chronic effects on physicians' work capacity, and finally, medicine judicialization and organization failure increasing physician "burnout". We discuss these factors in general and in relation to the COVID-19 pandemic. CONCLUSIONS: We describe an overview of the above factors, discuss possible solutions, and specifically address how COVID-19 may impact such factors.

Lifestyle Behaviors, Depression, and Anxiety Among Individuals Living in Canada During the COVID-19 Pandemic.

The aim of our study was to investigate the association between lifestyle behaviors and symptoms of depression and anxiety during the COVID-19 pandemic in Canada. A web survey was conducted between July 3-August 3, 2020, across Canada. The main outcomes considered were a positive screening for depression, as evaluated by the PHQ-2 and positive screening for anxiety, as evaluated by the GAD-7. Lifestyle behaviors were assessed using the Short Multidimensional Lifestyle Inventory Evaluation-Confinement (SMILE-C), an instrument adapted for lifestyle behaviors during the COVID-19 pandemic. The total sample size included 404 participants, of which 24.3% had a positive screen for depression, 20.5% for anxiety, and 15.5% for both. We found significant differences in SMILE-C scores between individuals with a positive and individuals with a negative screen for depression (P < .001). Likewise, there were significant differences in SMILE-C scores between individuals with a positive and individuals with a negative screen for anxiety (P < .001). We found an association between unhealthy lifestyle behaviors and symptoms of depression and anxiety during the COVID-19 lockdown in Canada. The findings highlight the importance of lifestyle medicine (LM) education and targeted lifestyle interventions to promote healthy behaviors and help reduce the burden of mental disorders.

Effective recommendations towards healthy routines to preserve mental health during the COVID-19 pandemic.

OBJECTIVE: To assess the adherence to a set of evidence-based recommendations to support mental health during the coronavirus disease 2019 (COVID-19) pandemic and its association with depressive and anxiety symptoms. METHODS: A team of health workers and researchers prepared the recommendations, formatted into three volumes (1: COVID-19 prevention; 2: Healthy habits; 3: Biological clock and sleep). Participants were randomized to receive only Volume 1 (control), Volumes 1 and 2, Volumes 1 and 3, or all volumes. We used a convenience sample of Portuguese-speaking participants over age 18 years. An online survey consisting of sociodemographic and behavioral questionnaires and mental health instruments (Patient Health Questionnaire-9 [PHQ-9] and Generalized Anxiety Disorder-7 [GAD-7]) was administered. At 14 and 28 days later, participants were invited to complete follow-up surveys, which also included questions regarding adherence to the recommendations. A total of 409 participants completed the study - mostly young adult women holding university degrees. RESULTS: The set of recommendations contained in Volumes 2 and 3 was effective in protecting mental health, as suggested by significant associations of adherence with PHQ-9 and GAD-7 scores (reflecting anxiety and depression symptoms, respectively). CONCLUSION: The recommendations developed in this study could be useful to prevent negative mental health effects in the context of the pandemic and beyond.

Lifestyle predictors of depression and anxiety during COVID-19: a machine learning approach.

INTRODUCTION: Recent research has suggested an increase in the global prevalence of psychiatric symptoms during the COVID-19 pandemic. This study aimed to assess whether lifestyle behaviors can predict the presence of depression and anxiety in the Brazilian general population, using a model developed in Spain. METHODS: A web survey was conducted during April-May 2020, which included the Short Multidimensional Inventory Lifestyle Evaluation (SMILE) scale, assessing lifestyle behaviors during the COVID-19 pandemic. Depression and anxiety were examined using the PHQ-2 and the GAD-7, respectively. Elastic net, random forest, and gradient tree boosting were used to develop predictive models. Each technique used a subset of the Spanish sample to train the models, which were then tested internally (vs. the remainder of the Spanish sample) and externally (vs. the full Brazilian sample), evaluating their effectiveness. RESULTS: The study sample included 22,562 individuals (19,069 from Brazil, and 3,493 from Spain). The models developed performed similarly and were equally effective in predicting depression and anxiety in both tests, with internal test AUC-ROC values of 0.85 (depression) and 0.86 (anxiety), and external test AUC-ROC values of 0.85 (depression) and 0.84 (anxiety). Meaning of life was the strongest predictor of depression, while sleep quality was the strongest predictor of anxiety during the COVID-19 epidemic. CONCLUSIONS: Specific lifestyle behaviors during the early COVID-19 epidemic successfully predicted the presence of depression and anxiety in a large Brazilian sample using machine learning models developed on a Spanish sample. Targeted interventions focused on promoting healthier lifestyles are encouraged.