Psychopathology and Resilience Following Strict COVID-19 Lockdowns in Hubei, China: Examining Person- and Context-Level Predictors for Longitudinal Trajectories

In Hubei, China, where the COVID-19 epidemic first emerged, the government has enforced strict quarantine and lockdown measures. Longitudinal studies suggest that the impact of adverse events on psychological adjustment is highly heterogenous. To better understand protective and risk factors that predict longitudinal psychopathology and resilience following strict COVID-19 lockdowns, this study used unsupervised machine learning to identify half-year longitudinal trajectories (April, June, August, and October, 2020) of three mental health outcomes (depression, anxiety, and PTSD) among a sample of Hubei residents (N = 326), assessed a broad range of person- and context-level predictors, and applied LASSO logistic regression, a supervised machine learning approach, to select best predictors for trajectory memberships of resilience and chronic psychopathology. Across outcomes, most individuals remained resilient. Models with both person- and context-level predictors showed excellent predictive accuracy, except for models predicting chronic anxiety. The person-level models showed either good or excellent predictive accuracy. The context-level models showed good predictive accuracy for depression trajectories but were only fair in predicting trajectories of anxiety and PTSD. Overall, the most critical person-level predictors were worry, optimism, fear of COVID, and coping flexibility, whereas important context-level predictors included features of stressful life events, community satisfaction, and family support. This study identified clinical patterns of response to COVID-19 lockdowns and used a combination of risk and protective factors to accurately differentiate these patterns. These findings have implications for clinical risk identifications and interventions in the context of potential trauma.

Gender Differences in the Association Between Cataract and Mental Health in Adults With Diabetes: A Cross-Sectional Analysis From the Spanish National Health Survey 2017

Objective: This study aimed to explore gender differences in the associations between cataracts and self-reported depression and chronic anxiety in Spanish adults with diabetes.Methods: Cross-sectional data from the Spanish Health Survey 2017 were analyzed. Inclusion criterion was a positive response to the question “Have you ever been diagnosed with diabetes?” Diabetes, cataracts, depression and chronic anxiety were based on self-reported lifetime diagnosis. Multivariable logistic regression was conducted to assess the association between cataracts and depression or anxiety among respondents with diabetes, stratifying by gender.Results: Out of a total 23,089 respondents, 2,266 people self-reported suffering from diabetes (50.2% women; average age 69.7 ± 12.7 years; age range 15-98 years). In people with diabetes, the presence of cataracts was associated with significantly higher odds for depression (OR = 1.655; 95% CI = 1.295-2.115). Gender-stratified analyses showed that only women with cataracts were significantly associated with higher odds for depression (OR = 1.762; 95% CI = 1.307-2.374) and chronic anxiety (OR = 1.519; 95% CI = 1.067-2.163).Conclusion: Cataracts are a significant risk factor for depression and chronic anxiety in Spanish women with diabetes, but not in men. Women with both diabetes and cataracts require assessment for depression and chronic anxiety, and possibly earlier interventions in order to reduce the potential risk of further mental health complications.

Self-Management in Anxiety and Depression: A Psychometric Evaluation of a Questionnaire

Objective: To examine the underlying factor structure and psychometric properties of the Assessment of Self-management in Anxiety and Depression (ASAD) questionnaire, which was specifically designed for patients with (chronic) anxiety and depressive disorders. Moreover, this study assesses whether the number of items in the ASAD can be reduced without significantly reducing its precision.Methods: The ASAD questionnaire was completed by 171 participants across two samples: one sample comprised patients with residual anxiety or depressive symptoms, while the other consisted of patients who have been formally diagnosed with a chronic anxiety or depressive disorder. All participants had previously undergone treatment. Both exploratory (EFA) and confirmatory factor analyses (CFA) were conducted. Internal consistency and test–retest reliability were also assessed.Results: Both EFA and CFA indicated three solid factors: Seeking support, Daily life strategies and Taking ownership [Comparative Fit Index = 0.80, Tucker Lewis Index = 0.78, Root Mean Square Error of Approximation = 0.09 (CI 0.08–1.00), Standardized Root Mean Square Residual = 0.09 (χ2 = 439.35, df = 168)]. The ASAD was thus reduced from 45 items to 21 items, which resulted in the ASAD-Short Form (SF). All sub-scales had a high level of internal consistency (> α = 0.75) and test–retest reliability (ICC > 0.75).Discussion: The first statistical evaluation of the ASAD indicated a high level of internal consistency and test–retest reliability, and identified three distinctive factors. This could aid patients and professionals’ assessment of types of self-management used by the patient. Given that this study indicated that the 21-item ASAD-SF is appropriate, this version should be further explored and validated among a sample of patients with (chronic or partially remitted) anxiety and depressive disorders. Alongside this, to increase generalizability, more studies are required to examine the English version of the ASAD within other settings and countries.

Prospective predictors of risk and resilience trajectories during the early stages of the COVID-19 pandemic: a longitudinal study

Background. The COVID-19 pandemic is a rapidly evolving stressor with significant mental health consequences. We aimed to delineate distinct anxiety-response trajectories during the early stages of the pandemic and to identify baseline risk and resilience factors as predictors of anxiety responses. Methods. Using a crowdsourcing website, we enrolled 1,362 participants, primarily from the United States (n = 1064) and Israel (n = 222) over three time-points from April-September 2020. We used latent growth mixture modeling to identify anxiety trajectories over time. Group comparison and multivariate regression models were used to examine demographic and risk and resilience factors associated with class membership. Results. A four-class model provided the best fit. The resilient trajectory (stable low anxiety) was the most common (n = 961, 75.08%), followed by chronic anxiety (n = 149, 11.64%), recovery (n = 96, 7.50%) and delayed anxiety (n = 74, 5.78%). While COVID-19 stressors did not differ between trajectories, resilient participants were more likely to be older, living with another person and to report higher income, more education, fewer COVID-19 worries, better sleep quality, and more dispositional resilience factors at baseline. Multivariate analyses suggested that baseline emotion regulation capabilities and low conflictual relationships uniquely distinguished participants in distinct trajectories. Conclusions. Consistent with prior resilience research following major adversities, a majority of individuals showed stable low levels of low anxiety in response to the COVID-19 pandemic. Knowledge about dispositional resilience factors may prospectively inform mental health trajectories early in the course of ongoing adversity.

ANXIETY AND DEPRESSION AFFECTING QUALITY OF LIFE DURING COVID-19 IN IT SECTOR WORKERS, DUE TO WORK FROM HOME

Background- Everyone has anxiety from time to time, but chronic anxiety can interfere with your quality of life. Depression is a mood disorder that involves a persistent feeling of sadness and loss of interest.Major life events,such as bereavement or the loss of a job,can lead to depression. Aim & Objectives:- The objective of this study was to demonstrate that anxiety and depression has a significant affect on QOL during covid-19 in IT sector workers due to work from home . Study Design-An survey design study was conducted. Methods-: Written consent from participants was taken.Qol was assessed by the Qol scale,Hamilton anxiety scale and patient health questionnaire (degree of depression severity).Statistical analysis was done . Result – There was mild correlation between the severity of anxiety and depression but also There was no correlation between QoL. Conclusion – It was seen that there was increase in Anxiety and Depression due to the external environmental factors but it didn't affect the Quality of life.

Lamotrigine Reduces Stress Symptoms of Chronic Anxiety in the Times of the Covid-19 Natural Catastrophe-A Case Report

The SARS-CoV-2 pandemic has been a worldwide chronic, stress-inducing natural catastrophe associated with increased emotional challenging. Patients with Post-traumatic stress disorder (PTSD), self-injury behavior, and obesity are predisposed to aggravation of their symptoms at this time, requiring new therapeutic approaches to balance their disrupted neuro-hormonal stress axis. Here we present our observations of an off-label treatment with lamotrigine in an adolescent girl with PTSD, self-injury behavior, and obesity. Lamotrigine was an efficacious pharmaceutical intervention that helped the patient deal with chronic stress and associated anxiety. The results are discussed based on our previous basic research outcomes in animals and humans that focused on the glutamate-cortisol circuits within the limbic brain.