Non-binary gender, vulnerable populations and mental health during the COVID-19 pandemic: Data from the COVID-19 MEntal health inTernational for the general population (COMET-G) study.

BACKGROUND: The COVID-19 pandemic has brought significant mental health challenges, particularly for vulnerable populations, including non-binary gender individuals. The COMET international study aimed to investigate specific risk factors for clinical depression or distress during the pandemic, also in these special populations. METHODS: Chi-square tests were used for initial screening to select only those variables which would show an initial significance. Risk Ratios (RR) were calculated, and a Multiple Backward Stepwise Linear Regression Analysis (MBSLRA) was followed with those variables given significant results at screening and with the presence of distress or depression or the lack of both of them. RESULTS: The most important risk factors for depression were female (RR = 1.59-5.49) and non-binary gender (RR = 1.56-7.41), unemployment (RR = 1.41-6.57), not working during lockdowns (RR = 1.43-5.79), bad general health (RR = 2.74-9.98), chronic somatic disorder (RR = 1.22-5.57), history of mental disorders (depression RR = 2.31-9.47; suicide attempt RR = 2.33-9.75; psychosis RR = 2.14-10.08; Bipolar disorder RR = 2.75-12.86), smoking status (RR = 1.15-5.31) and substance use (RR = 1.77-8.01). The risk factors for distress or depression that survived MBSLRA were younger age, being widowed, living alone, bad general health, being a carer, chronic somatic disorder, not working during lockdowns, being single, self-reported history of depression, bipolar disorder, self-harm, suicide attempts and of other mental disorders, smoking, alcohol, and substance use. CONCLUSIONS: Targeted preventive interventions are crucial to safeguard the mental health of vulnerable groups, emphasizing the importance of diverse samples in future research. LIMITATIONS: Online data collection may have resulted in the underrepresentation of certain population groups.

Somatic multicomorbidity and disability in patients with psychiatric disorders in comparison to the general population: a quasi-epidemiological investigation in 54,826 subjects from 40 countries (COMET-G study).

BACKGROUND: The prevalence of medical illnesses is high among patients with psychiatric disorders. The current study aimed to investigate multi-comorbidity in patients with psychiatric disorders in comparison to the general population. Secondary aims were to investigate factors associated with metabolic syndrome and treatment appropriateness of mental disorders. METHODS: The sample included 54,826 subjects (64.73% females; 34.15% males; 1.11% nonbinary gender) from 40 countries (COMET-G study). The analysis was based on the registration of previous history that could serve as a fair approximation for the lifetime prevalence of various medical conditions. RESULTS: About 24.5% reported a history of somatic and 26.14% of mental disorders. Mental disorders were by far the most prevalent group of medical conditions. Comorbidity of any somatic with any mental disorder was reported by 8.21%. One-third to almost two-thirds of somatic patients were also suffering from a mental disorder depending on the severity and multicomorbidity. Bipolar and psychotic patients and to a lesser extent depressives, manifested an earlier (15-20 years) manifestation of somatic multicomorbidity, severe disability, and probably earlier death. The overwhelming majority of patients with mental disorders were not receiving treatment or were being treated in a way that was not recommended. Antipsychotics and antidepressants were not related to the development of metabolic syndrome. CONCLUSIONS: The finding that one-third to almost two-thirds of somatic patients also suffered from a mental disorder strongly suggests that psychiatry is the field with the most trans-specialty and interdisciplinary value and application points to the importance of teaching psychiatry and mental health in medical schools and also to the need for more technocratically oriented training of psychiatric residents.

Results of the COVID-19 mental health international for the health professionals (COMET-HP) study: depression, suicidal tendencies and conspiracism.

INTRODUCTION: The current study aimed to investigate the rates of anxiety, clinical depression, and suicidality and their changes in health professionals during the COVID-19 outbreak. MATERIALS AND METHODS: The data came from the larger COMET-G study. The study sample includes 12,792 health professionals from 40 countries (62.40% women aged 39.76 ± 11.70; 36.81% men aged 35.91 ± 11.00 and 0.78% non-binary gender aged 35.15 ± 13.03). Distress and clinical depression were identified with the use of a previously developed cut-off and algorithm, respectively. STATISTICAL ANALYSIS: Descriptive statistics were calculated. Chi-square tests, multiple forward stepwise linear regression analyses, and Factorial Analysis of Variance (ANOVA) tested relations among variables. RESULTS: Clinical depression was detected in 13.16% with male doctors and 'non-binary genders' having the lowest rates (7.89 and 5.88% respectively) and 'non-binary gender' nurses and administrative staff had the highest (37.50%); distress was present in 15.19%. A significant percentage reported a deterioration in mental state, family dynamics, and everyday lifestyle. Persons with a history of mental disorders had higher rates of current depression (24.64% vs. 9.62%; p < 0.0001). Suicidal tendencies were at least doubled in terms of RASS scores. Approximately one-third of participants were accepting (at least to a moderate degree) a non-bizarre conspiracy. The highest Relative Risk (RR) to develop clinical depression was associated with a history of Bipolar disorder (RR = 4.23). CONCLUSIONS: The current study reported findings in health care professionals similar in magnitude and quality to those reported earlier in the general population although rates of clinical depression, suicidal tendencies, and adherence to conspiracy theories were much lower. However, the general model of factors interplay seems to be the same and this could be of practical utility since many of these factors are modifiable.

Students' mental health during the pandemic: results of the observational cross-sectional COVID-19 MEntal health inTernational for university Students (COMET-S) study.

Introduction: The aim of the study was to search rates of depression and mental health in university students, during the COVID-19 pandemic. Materials and methods: This is an observational cross-sectional study. A protocol gathering sociodemographic variables as well as depression, anxiety and suicidality and conspiracism was assembled, and data were collected anonymously and online from April 2020 through March 2021. The sample included 12,488 subjects from 11 countries, of whom 9,026 were females (72.2%; aged 21.11 ± 2.53), 3,329 males (26.65%; aged 21.61 ± 2.81) and 133 "non-binary gender" (1.06%; aged 21.02 ± 2.98). The analysis included chi-square tests, correlation analysis, ANCOVA, multiple forward stepwise linear regression analysis and Relative Risk ratios. Results: Dysphoria was present in 15.66% and probable depression in 25.81% of the total study sample. More than half reported increase in anxiety and depression and 6.34% in suicidality, while lifestyle changes were significant. The model developed explained 18.4% of the development of depression. Believing in conspiracy theories manifested a complex effect. Close to 25% was believing that the vaccines include a chip and almost 40% suggested that facemask wearing could be a method of socio-political control. Conspiracism was related to current depression but not to history of mental disorders. Discussion: The current study reports that students are at high risk for depression during the COVID-19 pandemic and identified specific risk factors. It also suggested a role of believing in conspiracy theories. Further research is important, as it is targeted intervention in students' groups that are vulnerable both concerning mental health and conspiracism.

The effect of different degrees of lockdown and self-identified gender on anxiety, depression and suicidality during the COVID-19 pandemic: Data from the international COMET-G study.

INTRODUCTION: During the COVID-19 pandemic various degrees of lockdown were applied by countries around the world. It is considered that such measures have an adverse effect on mental health but the relationship of measure intensity with the mental health effect has not been thoroughly studied. Here we report data from the larger COMET-G study pertaining to this question. MATERIAL AND METHODS: During the COVID-19 pandemic, data were gathered with an online questionnaire from 55,589 participants from 40 countries (64.85% females aged 35.80 ± 13.61; 34.05% males aged 34.90±13.29 and 1.10% other aged 31.64±13.15). Anxiety was measured with the STAI, depression with the CES-D and suicidality with the RASS. Distress and probable depression were identified with the use of a previously developed cut-off and algorithm respectively. STATISTICAL ANALYSIS: It included the calculation of Relative Risk (RR), Factorial ANOVA and Multiple backwards stepwise linear regression analysis RESULTS: Approximately two-thirds were currently living under significant restrictions due to lockdown. For both males and females the risk to develop clinical depression correlated significantly with each and every level of increasing lockdown degree (RR 1.72 and 1.90 respectively). The combined lockdown and psychiatric history increased RR to 6.88 The overall relationship of lockdown with severity of depression, though significant was small. CONCLUSIONS: The current study is the first which reports an almost linear relationship between lockdown degree and effect in mental health. Our findings, support previous suggestions concerning the need for a proactive targeted intervention to protect mental health more specifically in vulnerable groups.

University students' mental health amidst the COVID-19 pandemic in Georgia.

AIMS: We aimed to identify the prevalence of anxiety, depression, and suicidality and identify relevant risk and protecting factors among university students during the COVID-19 pandemic in Georgia. MATERIALS AND METHODS: We conducted an anonymous online survey (n = 984, convenience sample by approaching all universities in Georgia and some student organizations) using valid instruments (e.g., STAI to assess anxiety, CES-D for depression, and RASS to assess suicidality). We calculated frequencies and prevalence and applied regression analysis and Chi-square tests to identify risk and protecting factors. FINDINGS: Respondents' mental health had been significantly affected (with a high prevalence of depression (46.7%) and anxiety (79%)) during the pandemic (which coincided with political turmoil and caused an economic crisis) in Georgia. Some of the critical factors affecting mental health were: female sex (p = .000), bad general health condition (anxiety p = .001, depression p = .004), finances (anxiety and depression p < .001), reduced physical activity (anxiety p < .001, depression p = .014), and a history of self-harming (suicidality p < .001). Less family conflicts (anxiety and depression p < .05), absence of nightmares (anxiety and depression p < .001), moderate or low fears of COVID-19 (anxiety p < .001), and lower substance use (anxiety p = .023) were among the potentially protective factors. International students coped better, despite vulnerability. Medical students had a lower risk of depression. CONCLUSIONS: In the complex socioeconomic context, mental health of students in Georgia suffered a lot during the COVID-19 pandemic, requiring thorough planning and delivery of student support services in higher educational institutions during and after the pandemic.

Climate rather than economic variables might have caused increase in US homicide but not suicide rates during the Great Depression.

BACKGROUND: It is widely believed that during the Great Depression (1929-1933) there was a rise in suicidal rates which was causally related to the increase in unemployment. There are no studies on the effect the Great Depression had on homicidal rates METHODS: The data concerning suicide, homicide, economic and climatic variables for the years 1900-1940 for the whole of the US were gathered from the US Center for Disease Control, the Maddison Project, the National Bureau of Economic Research and the National Climatic Data Center. Time Series Analysis was performed. RESULTS: The results are inconclusive on the role of economic factors but preclude any role of climate on suicidal rates during the years 1900-1940 in the US. Suicidal rates might have a 24-years periodicity, however much longer time series are needed to confirm this. On the contrary they strongly suggest an effect of higher temperatures on homicidal rates after 1922. CONCLUSIONS: The results of the current study suggest a direct and clear effect of climate (higher temperatures) on the increasing homicidal rates in the US after 1922 but failed to establish a causal relationship between suicide rates and economic or climate variables. These should be considered together with increasing concerns on the possible effect of climate change on mental health.

Mental health and conspirasism in health care professionals during the spring 2020 COVID-19 lockdown in Greece.

INTRODUCTION: The aim of the study was to investigate mental health and conspiracy theory beliefs concerning COVID-19 among health care professionals (HCPs). MATERIAL AND METHODS: During lockdown, an online questionnaire gathered data from 507 HCPs (432 females aged 33.86 ± 8.63 and 75 males aged 39.09 ± 9.54). STATISTICAL ANALYSIS: A post-stratification method to transform the study sample was used; descriptive statistics were calculated. RESULTS: Anxiety and probable depression were increased 1.5-2-fold and were higher in females and nurses. Previous history of depression was the main risk factor. The rates of believing in conspiracy theories concerning the COVID-19 were alarming with the majority of individuals (especially females) following some theory to at least some extend. CONCLUSIONS: The current paper reports high rates of depression, distress and suicidal thoughts in the HCPs during the lockdown, with a high prevalence of beliefs in conspiracy theories. Female gender and previous history of depression acted as risk factors, while the belief in conspiracy theories might act as a protective factor. The results should be considered with caution due to the nature of the data (online survey on a self-selected but stratified sample).

Results of the COVID-19 mental health international for the general population (COMET-G) study.

INTRODUCTION: There are few published empirical data on the effects of COVID-19 on mental health, and until now, there is no large international study. MATERIAL AND METHODS: During the COVID-19 pandemic, an online questionnaire gathered data from 55,589 participants from 40 countries (64.85% females aged 35.80 ± 13.61; 34.05% males aged 34.90±13.29 and 1.10% other aged 31.64±13.15). Distress and probable depression were identified with the use of a previously developed cut-off and algorithm respectively. STATISTICAL ANALYSIS: Descriptive statistics were calculated. Chi-square tests, multiple forward stepwise linear regression analyses and Factorial Analysis of Variance (ANOVA) tested relations among variables. RESULTS: Probable depression was detected in 17.80% and distress in 16.71%. A significant percentage reported a deterioration in mental state, family dynamics and everyday lifestyle. Persons with a history of mental disorders had higher rates of current depression (31.82% vs. 13.07%). At least half of participants were accepting (at least to a moderate degree) a non-bizarre conspiracy. The highest Relative Risk (RR) to develop depression was associated with history of Bipolar disorder and self-harm/attempts (RR = 5.88). Suicidality was not increased in persons without a history of any mental disorder. Based on these results a model was developed. CONCLUSIONS: The final model revealed multiple vulnerabilities and an interplay leading from simple anxiety to probable depression and suicidality through distress. This could be of practical utility since many of these factors are modifiable. Future research and interventions should specifically focus on them.

Self-reported changes in anxiety, depression and suicidality during the COVID-19 lockdown in Greece.

INTRODUCTION: There are only a few published empirical data on COVID-19's effects on the mental health. MATERIAL AND METHODS: During lockdown, an online questionnaire registered demographic, health data, previous psychiatric history, current anxiety, depression and suicidality, believing in conspiracy theories and other domains. Data from 3399 persons were used (81.08% females; aged 34.02 ± 9.72 and 18.27% males; aged 36.38±10.33). Distress and clinical depression were identified with the use of cut-off and a previously developed algorithm respectively. STATISTICAL ANALYSIS: A post-stratification method was used; descriptive statistics were calculated. Chi-square tests, multiple forward stepwise linear regression analyses and Factorial Analysis of Variance (ANOVA) tested relations among variables. RESULTS: Clinical depression was present in 9.31% of the stratified sample, while 8.5% had severe distress; increased anxiety was present in more than 45%. Suicidal thoughts increased in 10.40% and decreased in 4.42%. Beliefs in conspiracy theories were widely prevalent; at least half of cases were following various misconceptions. A model for the development of depression was created with general health status, previous history of depression, self-harm and suicidal attempts, family responsibility, economic change, and age acting as risk factors, while keeping a daily routine, pursuing religiousness/spirituality, and believing in conspiracy theories acting as protective factors. CONCLUSIONS: The model developed here revealed multiple vulnerabilities and an interplay leading from simple anxiety to clinical depression and suicidality through distress. This could be of practical utility since most of these factors are modifiable. Future research, as well as interventions, should focus specifically on them.

Factors determining different death rates because of the COVID-19 outbreak among countries.

BACKGROUND: During the coronavirus disease 2019 (COVID-19) pandemic, all European countries were hit, but mortality rates were heterogenous. The aim of the current paper was to identify factors responsible for this heterogeneity. METHODS: Data concerning 40 countries were gathered, concerning demographics, vulnerability factors and characteristics of the national response. These variables were tested against the rate of deaths per million in each country. The statistical analysis included Person correlation coefficient and Forward Stepwise Linear Regression Analysis (FSLRA). RESULTS: The FSLRA results suggested that 'days since first national death for the implementation of ban of all public events' was the only variable significantly contributing to the final model, explaining 44% of observed variability. DISCUSSION: The current study suggests that the crucial factor for the different death rates because of COVID-19 outbreak was the fast implementation of public events ban. This does not necessarily mean that the other measures were useless, especially since most countries implemented all of them as a 'package'. However, it does imply that this is a possibility and focused research is needed to clarify it, and is in accord with a model of spreading where only a few superspreaders infect large numbers through prolonged exposure.