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.

Psychosocial characteristics of candidates for implantable pain devices: validation of an assessment model.

Aim: To provide a detailed profile of Veteran and community patients with chronic pain who completed preprocedural psychological evaluations for implantable pain devices. Patients & methods: A total of 157 candidates completed a preimplantable pain device evaluation between June 2018 and October 2019 with a pain psychologist that included a structured interview, elicitation of patient-centered goals for the implantable device, and psychometric testing. Results: Candidates demonstrated moderate to high rates of sleep impairment (73%), depressive symptoms (62%), anxiety symptoms (61%), pain catastrophizing (37%), cognitive impairment screen (30%) and somatic symptoms (24%). Conclusion: Candidates for implantable pain devices report high rates of mood, sleep and cognitive impairment, reinforcing the value of preprocedural psychological evaluations.