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The first interim analysis of the data set, preregistered on 01/04/2020 (osf.io/r6btn) and published as a preprint on 22/04/2020 (psyarxiv.com/4z62t/), has confirmed the main effects hypotheses H1 to H9 about resilience factors as well as the mediation hypotheses H10 and H11 in a sample of the first 5000 European respondents providing complete survey data. In particular, our primary hypothesis about positive appraisal style as a resilience factor (H1) was tested positively. Regularized regression analysis identified positive appraisal specifically of the consequences of the Corona crisis (PAC, see H9) as the strongest resilience factor. The data used for the analysis were acquired between 22/03/2020 (start of data collection) and 01/04/2020, that is, during a time window when measures of quarantine, social distancing, or curfew were already in place in many European countries. This amendment describes the plan for the second interim analysis, in which we will use the data acquired from study start on 22/03/2020 until 19/04/2020, that is, before the date (20/04/2020) when several of the European countries most strongly represented in our sample started to loosen the movement and contact restrictions. Thereby, we intend to obtain a complete picture of resilience factors during the most intense phase of the lockdown in response to the first wave of the pandemic. The independent and dependent variables, the main effects and mediation hypotheses H1 to H11, and the design plan remain identical (see sections 4 and 5 of the preregistration nr. 1). We will also use the same analysis methods (hypothesis testing with multiple regression and mediation analyses and combined regularized regression analysis) to determine the relative strengths of the hypothesized resilience factors (see section 7 of the preregistration). The considerably larger sample size than in the first interim analysis allows us to also perform exploratory subgroup analyses. In particular, we will here explore if and how the covariates age, gender, country of residence, education, household income, and past or present mental health diagnosis moderate the effects of the resilience factors (as formulated in the main effects hypotheses H1 to H9) on resilience. To this end, we will calculate additional multiple regression analyses, separately for each resilience factor (as above), and there introduce the interaction term of the resilience factor with the given covariate. We will then plot and interpret the resulting pattern of effect estimates that correspond to the main hypotheses for each level of the covariate. See section 6 of this amendment. Thereby, these subgroup analyses will shed first light on a) whether the hypothesized main effects H1 to H9 generalize across subgroups and b) whether subgroups differ in their main effect sizes. If effects generalize across subgroups, that is, if they are positive at all levels of a covariate (a), the identified resilience factors can be considered potentially valid in the broader population from which the current sample was drawn. If there are pronounced subgroup differences in a covariate (b), this would yield valuable information on which resilience factors might be the most promising targets of preventive interventions in different subgroups. These interaction analyses will be complemented with combined regularized regression analyses at each of the covariate levels, to learn more about which appear to be the strongest resilience factors in each subgroup.

Supplemental material, sj-docx-1-emr-10.1177_17540739221114642 for Positive Cognitive Reappraisal in Stress Resilience, Mental Health, and Well-Being: A Comprehensive Systematic Review by Antje Riepenhausen, Carolin Wackerhagen, Zala C. Reppmann, Hans-Christian Deter, Raffael Kalisch, Ilya M. Veer and Henrik Walter in Emotion Review

Supplemental material, sj-docx-1-emr-10.1177_17540739221114642 for Positive Cognitive Reappraisal in Stress Resilience, Mental Health, and Well-Being: A Comprehensive Systematic Review by Antje Riepenhausen, Carolin Wackerhagen, Zala C. Reppmann, Hans-Christian Deter, Raffael Kalisch, Ilya M. Veer and Henrik Walter in Emotion Review

The SARS-CoV-2 pandemic is not only a threat to physical health but is also having severe impacts on mental health. Although increases in stress-related symptomatology and other adverse psycho-social outcomes, as well as their most important risk factors have been described, hardly anything is known about potential protective factors. Resilience refers to the maintenance of mental health despite adversity. To gain mechanistic insights about the relationship between described psycho-social resilience factors and resilience specifically in the current crisis, we assessed resilience factors, exposure to Corona crisis-specific and general stressors, as well as internalizing symptoms in a cross-sectional online survey conducted in 24 languages during the most intense phase of the lockdown in Europe (22 March to 19 April) in a convenience sample of N = 15,970 adults. Resilience, as an outcome, was conceptualized as good mental health despite stressor exposure and measured as the inverse residual between actual and predicted symptom total score. Preregistered hypotheses (osf.io/r6btn) were tested with multiple regression models and mediation analyses. Results confirmed our primary hypothesis that positive appraisal style (PAS) is positively associated with resilience (p

Background The current Corona pandemic is not only a threat to physical health. First data from China and Europe indicate that symptoms of anxiety and depression and perceptions of stress rise significantly as a consequence of the pandemic. There are also anecdotal reports of increased domestic violence, divorce, and suicide rates. Hence, the Corona crisis is also a mental health crisis. There is urgent need for knowledge about factors that can protect mental health (resilience factors) in this world-wide crisis, which is different in nature from other crises that have so far been studied in resilience research. Methods Potential resilience factors, exposure to Corona-specific and general stressors, as well as internalizing symptoms were assessed online in N=5000 adult Europeans. Resilience, as an outcome, was conceptualized as good mental health despite stressor exposure and measured as the inverse residual between actual and predicted symptom total score. Preregistered hypotheses (osf.io/r6btn) were tested with multiple regression models and mediation analyses. Results Results confirmed our primary hypothesis that positive appraisal style (PAS) is positively associated with resilience (p

Funder: State of Rhineland-Palatinate, Germany (MARP program, DRZ program, Leibniz Institute for Resilience Research), The SARS-CoV-2 pandemic is not only a threat to physical health but is also having severe impacts on mental health. Although increases in stress-related symptomatology and other adverse psycho-social outcomes, as well as their most important risk factors have been described, hardly anything is known about potential protective factors. Resilience refers to the maintenance of mental health despite adversity. To gain mechanistic insights about the relationship between described psycho-social resilience factors and resilience specifically in the current crisis, we assessed resilience factors, exposure to Corona crisis-specific and general stressors, as well as internalizing symptoms in a cross-sectional online survey conducted in 24 languages during the most intense phase of the lockdown in Europe (22 March to 19 April) in a convenience sample of N = 15,970 adults. Resilience, as an outcome, was conceptualized as good mental health despite stressor exposure and measured as the inverse residual between actual and predicted symptom total score. Preregistered hypotheses (osf.io/r6btn) were tested with multiple regression models and mediation analyses. Results confirmed our primary hypothesis that positive appraisal style (PAS) is positively associated with resilience (p < 0.0001). The resilience factor PAS also partly mediated the positive association between perceived social support and resilience, and its association with resilience was in turn partly mediated by the ability to easily recover from stress (both p < 0.0001). In comparison with other resilience factors, good stress response recovery and positive appraisal specifically of the consequences of the Corona crisis were the strongest factors. Preregistered exploratory subgroup analyses (osf.io/thka9) showed that all tested resilience factors generalize across major socio-demographic categories. This research identifies modifiable protective factors that can be targeted by public mental health efforts in this and in future pandemics.