Networks of pandemic-specific stressors, risk factors, and clinical symptoms: A comparison between women and men during the early phase of the COVID-19 pandemic.

BACKGROUND: During the COVID-19 pandemic, female gender was a robust factor associated with mental health problems. This study aimed to investigate associations between pandemic-related risk factors, stressors, and clinical symptoms, with special reference to gender and possible differential gender effects. METHODS: Participants were recruited from June to September 2020 through an online survey (ESTSS ADJUST study). Women (N = 796) and men (N = 796) were matched on age, education, income, and living community. Symptoms of depression (PHQ-9), anxiety (PHQ-4), adjustment disorder (ADNM-8), and PTSD (PC-PTSD-5) and different risk factors including pandemic-specific stressors (PaSS) were assessed. Separate network analyses for men and women were conducted and compared followed by a joint network analysis including gender. RESULTS: The networks of women and men did not differ in their structure (M = 0.14, p = .174) or strength of associations (S = 1.22, p = .126). Few relationships differed significantly between genders e.g., the connection between burden through work-related problems and anxiety was stronger in women. In the joint network, single factors were related to gender e.g., men felt more burdened through work-related problems and women through conflicts at home. LIMITATIONS: We cannot imply causal relationships due to the cross-sectional data of our study. The findings cannot be generalized as the sample is not representative. CONCLUSION: Men and women seem to show comparable networks of risk factors, stressors, and clinical symptoms, although differences in individual connections and in levels of clinical symptoms and burdens were found.

Profiles of risk factors for depressive and anxiety symptoms during the COVID-19 pandemic: A latent class analysis

The COVID-19 pandemic has caused a high burden in the general population. The exposure to an accumulation of risk factors, as opposed to a single risk, may have been associated with higher levels of depressive and anxiety symptoms during the pandemic. This study aimed to (1) identify subgroups of individuals with distinct constellations of risk factors during the COVID-19 pandemic and (2) investigate differences in levels of depressive and anxiety symptoms. German participants (N = 2,245) were recruited between June-September 2020 through an online survey (ADJUST study). Latent class analysis (LCA) and multiple group analyses (Wald-tests) were conducted to identify profiles of risk factors and examine differences in symptoms of depression (PHQ-9) and anxiety (GAD-2). The LCA included 14 robust risk factors of different domains, e.g., sociodemographic (e.g., age), health-related (e.g., trauma), and pandemic-related (e.g., reduced income) factors. The LCA identified three risk profiles: High sociodemographic risk (11.7%), high social and moderate health-related risk (18.0%), and low general risk (70.3%). Individuals with high sociodemographic risk reported significantly higher symptom levels of depression and anxiety than the remaining groups. A better understanding of risk factor profiles could help to develop targeted prevention and intervention programs during pandemics.

Profiles of risk factors for depressive and anxiety symptoms during the COVID-19 pandemic: A latent class analysis.

The COVID-19 pandemic has caused a high burden in the general population. The exposure to an accumulation of risk factors, as opposed to a single risk, may have been associated with higher levels of depressive and anxiety symptoms during the pandemic. This study aimed to (1) identify subgroups of individuals with distinct constellations of risk factors during the COVID-19 pandemic and (2) investigate differences in levels of depressive and anxiety symptoms. German participants (N = 2245) were recruited between June-September 2020 through an online survey (ADJUST study). Latent class analysis (LCA) and multiple group analyses (Wald-tests) were conducted to identify profiles of risk factors and examine differences in symptoms of depression (PHQ-9) and anxiety (GAD-2). The LCA included 14 robust risk factors of different domains, for example, sociodemographic (e.g., age), health-related (e.g., trauma), and pandemic-related (e.g., reduced income) factors. The LCA identified three risk profiles: High sociodemographic risk (11.7%), high social and moderate health-related risk (18.0%), and low general risk (70.3%). Individuals with high sociodemographic risk reported significantly higher symptom levels of depression and anxiety than the remaining groups. A better understanding of risk factor profiles could help to develop targeted prevention and intervention programs during pandemics.

Coping profiles and differences in well-being during the COVID-19 pandemic: A latent profile analysis.

During the current COVID-19 pandemic, people need to cope with multiple stressors which may affect their well-being. This study aimed (1) to identify latent coping profiles in the German general population, and (2) to investigate differences between these profiles in well-being. In total, N = 2326 German participants were recruited as part of the European Society of Traumatic Stress Studies (ESTSS) ADJUST study from June to September 2020 using an online survey. Coping strategies were assessed using the Brief-COPE and the Pandemic Coping Scale; well-being was assessed using the WHO-5 Well-Being Index. Coping profiles were identified using latent profile analysis; differences between profiles were examined using the automatic BCH method and multiple group analyses. Five coping profiles were identified that included different types and numbers of coping strategies: (1) High functional coping (17.84%), (2) Moderate functional coping (40.63%), (3) High functional and religious coping (9.07%), (4) Low functional coping (22.06%), (5) Moderate functional and dysfunctional coping (10.40%). The identified profiles significantly differed in well-being (χ2  = 503.68, p <0.001). Coping profiles indicating high functional coping were associated with greater well-being compared to coping profiles indicating low (χ2  = 82.21, p <0.001) or primarily dysfunctional (χ2  = 354.33, p <0.001) coping. These results provide insight into how people differ in their coping strategies when dealing with stressors in an early phase of the COVID-19 pandemic. The study indicates higher levels of well-being in coping profiles with more frequent use of functional strategies. To promote well-being in the general population, it might be beneficial to train functional coping strategies in appropriate interventions that are associated with increased well-being.