Resilience is closely related to mental health and well-being. Identifying risk groups with lower resilience and the variables associated with resilience informs preventive approaches. Previous research on resilience patterns in the general population is heterogeneous, and comprehensive large-scale studies are needed. The aim of our study is to examine sociodemographic and social correlates of resilience in a large population-based sample. We examined 4795 participants from the LIFE-Adult-Study. Assessments included resilience (RS-11), social support (ESSI), and social network (LSNS), as well as the sociodemographic variables age, gender, marital status, education, and occupation. The association of resilience with sociodemographic and social correlates was examined using linear regression analyses. Higher resilience was associated with female gender, married marital status, high education, and full-time occupation. Social support and social network were positively associated with resilience. Our results implicate that resilience is related to various sociodemographic variables. Social variables seem to be particularly important for resilience. We identified risk groups with lower resilience, which should be given special attention by public health policies, especially in times of crisis. Reducing loneliness and promoting social connectedness may be promising ways to build resilience in the general population.

Background: As a new and effective support option, e-mental health interventions can be useful in complementing treatment in mental health care. To date, little is known about how health care providers use these programs to treat patients with mental illnesses in Germany. The present study aims to examine the use of and experiences with e-mental health interventions from the point of view of different types of health care providers for patients with mental illnesses. Methods: Data from a cross-sectional survey of routine care health care providers in Germany in 2021 were analysed. In this survey, data were collected from n = 107 general practitioners (GPs), n = 114 specialist doctors, n = 102 psychotherapists, and n = 102 inpatient clinicians. Assessments included professional use of digital media, as well as knowledge, use and experiences regarding e-mental health interventions in care of people with mental illness. Results: In the total sample of n = 425, 65.6% (n = 279) were female. The study participants had an average age of 47.7 years (SD = 11.0) and their average work experience was 20.0 years (SD = 11.1). Overall, the majority (83.8%, n = 353) had heard of e-mental health interventions, but few felt well informed. Only 28.5% (n = 121) had already used e-mental health interventions for treatment support. The most commonly recommended e-mental health interventions in the sample were deprexis (39.7%, n = 48), moodgym (24.8%, n = 30), and iFightDepression (22.3%, n = 27). The use was predominantly considered to be helpful and satisfactory. Insufficient knowledge about e-mental health interventions and lack of informational materials for patients were reported as relevant barriers to the use of e-mental health interventions. Conclusions: E-mental health interventions can be a useful support option, but they are rarely used in the treatment of patients with mental illnesses. There is a need to disseminate information specific to the various types of health care providers. Tailored implementation strategies need to be developed in order to capitalize on the potential of effective e-mental health interventions and to improve health care for patients with mental illnesses.

Resilience describes a good adaptation to adversity. Strengthening resilience is a promising approach in the prevention of mental health problems. Yet, research on the association of resilience with mental health symptoms in the general population is scarce. The aim of our study is to examine comprehensively the association of resilience with depressive symptoms, anxiety, and perceived stress in a large population-based sample. We analyzed data of n = 3762 participants from the follow-up assessment of the LIFE-Adult-Study, a population-based cohort study in Leipzig. Assessments included resilience (RS-11), depressive symptoms (CES-D), anxiety (GAD-7), and perceived stress (PSQ). The association of resilience with mental health symptoms was examined via multiple linear regression analyses. In our analyses, higher resilience predicted less mental health problems and contributed significantly to the explained variance in mental health outcomes. Women, individuals with previous mental disorders, and those without employment had higher mental health symptoms. Resilience is closely associated with mental health problems in the general population. Vulnerable groups should be targeted with public health measures. Strengthening resilience is a promising approach in the large-scale prevention of mental disorders.

Little is known about resilience in old age and its manifestation during the COVID-19 pandemic. This study aims to estimate the prevalence of high resilience in the German old age population. We further examine the socio-demographic correlates and whether high resilience reflects on older adults’ perception of the threat posed by COVID-19. The data were derived from a representative telephone survey of n = 1005 older adults (≥65 years) during the first COVID-19 lockdown. Assessments included socio-demographic variables, the perceived threat of COVID-19, and high resilience (Brief Resilience Scale; cutoff: ≥4.31). The association between high resilience and threat from COVID-19 was analyzed using ordinal logistic regression. The study sample had a mean age (SD) of 75.5 (7.1) years, and n = 566 (56.3%) were female. The estimated prevalence of high resilience was 18.7% (95% CI = [16.3; 21.2]). High resilience was more prevalent in the younger age group and participants with higher education levels. High resilience was significantly associated with a lower perception of threat from COVID-19. The results of the representative survey in the German old age population showed that one out of five adults aged 65 years and older had high resilience. Older adults with high resilience tended to feel less threatened by COVID-19. Further research on resilience in old age is needed to support vulnerable groups in the context of care.

(1) Background: There is a fundamental shift in healthcare toward shared decision making (SDM). This study explores SDM from the perspective of individuals affected by mental illness and their family members and investigates factors which promote and hinder the process. (2) Methods: We conducted N = 15 telephone interviews (n = 4 adults affected by mental illness, n = 5 family members, n = 6 both applicable, the majority reporting experiences with affective and anxiety disorders). Data were recorded, transcribed, and analyzed according to procedures established by Mayring. (3) Results: Individuals affected by mental illness and their family members have a strong desire to be involved in treatment decisions and to participate in finding a diagnosis. Often these stakeholders are denied the opportunity to participate; sometimes enabling behaviors impede participation. The stigmatization of mental illnesses is a major barrier. There are also structural barriers to SDM within the healthcare system. Peer support, self-help associations, and psychosocial counseling services are important to empowering individuals and promoting SDM. (4) Conclusions: SDM has the potential to improve the quality of mental healthcare. Barriers can be mitigated and new approaches for interventions in the psychiatric sector have been identified. This study has also shown the importance of understanding SDM as a process that should begin at the diagnostic phase.