The four weeks before lockdown during the COVID-19 pandemic in Germany: a weekly serial cross-sectional survey on risk perceptions, knowledge, public trust and behaviour, 3 to 25 March 2020.

BackgroundDuring the COVID-19 pandemic, public perceptions and behaviours have had to adapt rapidly to new risk scenarios and radical behavioural restrictions.AimTo identify major drivers of acceptance of protective behaviours during the 4-week transition from virtually no COVID-19 cases to the nationwide lockdown in Germany (3-25 March 2020).MethodsA serial cross-sectional online survey was administered weekly to ca 1,000 unique individuals for four data collection rounds in March 2020 using non-probability quota samples, representative of the German adult population between 18 and 74 years in terms of age × sex and federal state (n = 3,910). Acceptance of restrictions was regressed on sociodemographic variables, time and psychological variables, e.g. trust, risk perceptions, self-efficacy. Extraction of homogenous clusters was based on knowledge and behaviour.ResultsAcceptance of restrictive policies increased with participants' age and employment in the healthcare sector; cognitive and particularly affective risk perceptions were further significant predictors. Acceptance increased over time, as trust in institutions became more relevant and trust in media became less relevant. The cluster analysis further indicated that having a higher education increased the gap between knowledge and behaviour. Trust in institutions was related to conversion of knowledge into action.ConclusionIdentifying relevant principles that increase acceptance will remain crucial to the development of strategies that help adjust behaviour to control the pandemic, possibly for years to come. Based on our findings, we provide operational recommendations for health authorities regarding data collection, health communication and outreach.

PsychOpen CAMA: Publication of community-augmented meta-analyses in psychology.

To enable optimal decision-making based on the best evidence available, open syntheses are called for. To make data accessible and comprehensible even for decision-makers without proficient knowledge in meta-analysis, a graphical user interface (GUI) provides flexible data visualizations including interpretation aids. Moreover, due to a growing number of research findings, efficient and easy updating of meta-analyses is crucial to prevent waste in research. One label for a concept to meet these needs is community-augmented meta-analysis (CAMA). The research community at the one hand feeds the data repository of a CAMA with new data and on the other hand benefits from easy access to data and meta-analyses on a GUI. PsychOpen CAMA has been released recently to serve the psychological research community as a whole by covering a broad scope of potential research domains. PsychOpen CAMA relies on a web application with an OpenCPU server for the R calculations. To achieve interoperability of different datasets with the analysis functions used in PsychOpen CAMA, a template for meta-analytic data and machine-readable metadata are used. In the future, the automation of workflows, flexibility of analysis options, and the scope of the platform will be further developed by making use of synergies with other resources and tools at ZPID. The article provides an overview on the rationale for the necessity of open syntheses and the CAMA approach, as well as a presentation of the architecture, user interface, functionalities and future challenges of PsychOpen CAMA.