The ZPID lockdown measures dataset for Germany.

Autor/inn/en	Steinmetz, Holger; Batzdorfer, Veronika; Scherhag, Julian; Bosnjak, Michael
Institution	Leibniz-Institut für Psychologie (ZPID)
Titel	The ZPID lockdown measures dataset for Germany.
Quelle	Trier: ZPID (2022), 14 S. PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Reihe	ZPID Science Information Online. 20(1)
Beigaben	Literaturangaben; Tabellen
Sprache	englisch
Dokumenttyp	online; Monographie
DOI	10.23668/psycharchives.6679
Schlagwörter	Datenerhebung; Deutschland; Auswirkung; Datenerhebung; Maßnahme; Bundesland; Pandemie; COVID-19; Pandemie; Bundesland; Gesellschaftliches Leben; Auswirkung; Einschränkung; Maßnahme; COVID-19; Deutschland
Abstract	The outbreak of the COVID-19 pandemic has prompted the German government and the 16 German federal states to announce a variety of public health measures in order to suppress the spread of the coronavirus. These non-pharmaceutical measures intended to curb transmission rates by increasing social distancing (i.e., diminishing interpersonal contacts) which restricts a range of individual behaviors. These measures span moderate recommendations such as physical distancing, up to the closures of shops and bans of gatherings and demonstrations. The implementation of these measures are not only a research goal for themselves but have implications for behavioral research conducted in this time (e.g., in form of potential confounder biases). Hence, longitudinal data that represent the measures can be a fruitful data source. The presented data set contains data on 16 governmental measures across the 16 German federal states. In comparison to existing datasets, the data set at hand is a fine-grained daily time series tracking the effective calendar date, introduction, extension, or phase-out of each respective measure. Based on self-regulation theory, measures were coded whether they did not restrict, partially restricted or fully restricted the respective behavioral pattern. The time frame comprises March 08, 2020 until October 31, 2021. The project is an open-source, ongoing project with planned continued updates in regular (approximately quarterly) intervals. This release note presents the background, dataset structure and coding rules of the dataset. (Orig.).
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2023/1