Digital interventions to promote psychological resilience: a systematic review and meta-analysis.

Societies are exposed to major challenges at an increasing pace. This underscores the need for preventive measures such as resilience promotion that should be available in time and without access barriers. Our systematic review summarizes evidence on digital resilience interventions, which have the potential to meet these demands. We searched five databases for randomized-controlled trials in non-clinical adult populations. Primary outcomes were mental distress, positive mental health, and resilience factors. Multilevel meta-analyses were performed to compare intervention and control groups at post-intervention and follow-up assessments. We identified 101 studies comprising 20,010 participants. Meta-analyses showed small favorable effects on mental distress, SMD = -0.24, 95% CI [-0.31, -0.18], positive mental health, SMD = 0.27, 95% CI [0.13, 0.40], and resilience factors, SMD = 0.31, 95% CI [0.21, 0.41]. Among middle-aged samples, older age was associated with more beneficial effects at follow-up, and effects were smaller for active control groups. Effects were comparable to those of face-to-face interventions and underline the potential of digital resilience interventions to prepare for future challenges.

Interrelations of resilience factors and their incremental impact for mental health: insights from network modeling using a prospective study across seven timepoints.

Resilience can be viewed as trajectory of stable good mental health or the quick recovery of mental health during or after stressor exposure. Resilience factors (RFs) are psychological resources that buffer the potentially negative effects of stress on mental health. A problem of resilience research is the large number of conceptually overlapping RFs complicating their understanding. The current study sheds light on the interrelations of RFs in the face of the COVID-19 pandemic as a use case for major disruptions. The non-preregistered prospective study assessed a sample of 1275 German-speaking people from February 2020 to March 2021 at seven timepoints. We measured coping, hardiness, control beliefs, optimism, self-efficacy, sense of coherence (SOC), sense of mastery, social support and dispositional resilience as RFs in February 2020, and mental health (i.e., psychopathological symptoms, COVID-19-related rumination, stress-related growth) at all timepoints. Analyses used partial correlation network models and latent growth mixture modeling (LGMM). Pre-pandemic RFs were strongly interrelated, with SOC being the most central node. The strongest associations emerged between coping using emotional support and social support, SOC and sense of mastery, and dispositional resilience and self-efficacy. SOC and active coping were negatively linked. When we examined RFs as predictors of mental health trajectories, SOC was the strongest predictor of psychopathological symptoms and rumination, while trajectories of stress-related growth were predicted by optimism. Subsequent network analyses, including individual intercepts and slopes from LGMM, showed that RFs had small to moderate associations with intercepts but were unrelated to slopes. Our findings provide evidence for SOC playing an important role in mental distress and suggest further examining SOC's incremental validity. However, our results also propose that RFs might be more important for stable levels of mental health than for adaptation processes over time. The differential associations for negative and positive outcomes support the use of multidimensional outcomes in resilience research.

The Perceived Stress Scale 2&2: a two-factorial German short version of the Perceived Stress Scale.

Background: Stress is among the leading causes for diseases. The assessment of subjectively perceived stress is essential for resilience research. While the Perceived Stress Scale (PSS) is a widely used questionnaire, a German short version of the scale is not yet available. In the current study, we developed such a short version using a machine learning approach for item reduction to facilitate the simultaneous optimization of multiple psychometric criteria. Method: We recruited 1,437 participants from an online panel, who completed the German long version of the PSS along with measures of mental health and resilience. An ant-colony-optimization algorithm was used to select items, taking reliability, and construct validity into account. Findings on validity were visualized by psychological network models. Results: We replicated a bifactor structure for the long version of the PSS and derived a two-factor German short version of the PSS with four items, the PSS-2&2. Its factors helplessness and self-efficacy showed differential associations with mental health indicators and resilience-related factors, with helplessness being mainly linked to mental distress. Conclusion: The valid and economic short version of the PSS lends itself to be used in future resilience research. Our findings highlight the importance of the two-factor structure of the PSS short versions and challenge the validity of commonly used one-factor models. In cases where the general stress factor is of interest, researchers should use the longer versions of the PSS that allow for the interpretation of total scores, while the PSS-2&2 allows of an economic assessment of the PSS factors helplessness and self-efficacy.