Amendment nr. 1 to: Preregistration nr. 1 of “DynaCORE-C: The DynaMORE cross-sectional survey study on psychological resilience to the mental health consequences of the Corona crisis”: study description, major hypotheses, initial variables and analysis plan, published 01/04/2020 on osf.io/r6btn by Veer et al.: “Second interim analysis”
Creators: name: Kalisch, Raffael
name: Veer, Ilya
name: Yuen, Kenneth
name: Hendler, Talma
name: Myin-Germeys, Inez
name: Walter, Henrik
name: Riepenhausen, Antje
Publisher: name: Open Science Framework
Year: 2022
Subjects: subject: Medicine and Health Sciences
subject: Social and Behavioral Sciences

description: 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.