The Mannheim Corona Study - Design, Implementation and Data Quality
SFB 884, University of Mannheim, Germany
Relevance & Research Question:
The outbreak of COVID-19 has sparked a sudden demand for fast, frequent, and accurate data on the societal impact of the pandemic. To meet this demand quickly and efficiently, within days of the first containment measures in Germany in March 2020, we set up the Mannheim Corona Study (MCS), a rotating panel survey with daily data collection on the basis of the long-standing probability-based online panel infrastructure of the German Internet Panel (GIP). In a team effort, our research group was able to inform political decision makers and the general public with key information to understand the social and economic developments from as early as March 2020 as well as advance social scientific knowledge through in-depth interdisciplinary research.
Methods & Data:
This presentation gives insights into the MCS methodology and study design. We will provide a detailed account of how we adapted the GIP to create the MCS and describe the daily data collection, processing, and communication routines that were the cornerstones of our MCS methodology. In addition, we will provide insights into the necessary preconditions that allowed us to react so quickly and set up the MCS so early in the pandemic. Furthermore, we will discuss the quality of the MCS data in terms of the development of response rates as well as sample representativeness across the course of the MCS study period.
Our results show how the German Internet Panel could be transformed in an agile measurement tool in times of crisis. Participation rates were stable over the 16 weeks of data collection. Data quality indicators such as the Average Absolute Relative Bias comparing key survey indicators to German Mikozensus show stable low deviation from benchmark.
In this presentation we demonstrate how an existing research infrastructure can be quickly transformed in an instrument to measure important societal change or crisis events.
Tracking and driving behaviour with survey and metered data: The influence of incentives on the uptake of a COVID-19 contact tracing app
Relevance & Research Question:
Tracing the chain of infections is a substantial part of the strategy against SARS-CoV-2. But how is the German Corona Tracing App (CWA) used? Who are the users? Could uptake be boosted by just informing the population? Or are monetary incentives more effective? We study these questions by combining survey with passively metered behavioral data. The passive metering not only measures app usage more accurately but helps also to understand sensitive behaviour that is affected by social desirability.
Methods & Data:
100+ days (June to September 2020) survey with 2,500 participants; 1,100 participants of the passive tracking panel, which measures the usage of the CWA
3 wave survey:
• Baseline. Random assignment to 2 informational treatments and a control group
• Re-measurement of attitudes and behaviour. Assign to 3 monetary treatments and a control group
• Last measurement
The control group contains not only surveyed respondents but also part of the metered panel that was not interviewed.
First, we provide evidence on covariates linked with app usage. We observe higher usage rates among people who are already well informed and adhere to public health guidelines. Furthermore, a higher proportion of higher educated, digitally competent and older people are using the app, as well as those who report to trust the government. We can show the impact of information treatments on uptake is negligible, whereas small financial offers increase app usage substantially.
Due to the app’s privacy-by-default approach, individual-level determinants of usage have been difficult to identify. This study provides important behavioral evidence and highlights the advantage of passive data to measure potential socially desirable behaviour, as well as complex over-time behaviour which is difficult to report. It also shows how such data can be combined with an experimental design to evaluate the effects of possible policy interventions. While the nature of the online access panel prohibits strong conclusions about overall usage rates in the population of interest (smartphone users, whose mobile phones are technically compatible with the tracing app are anyway virtually impossible to sample from), conditional usage rates across different demographic and behavioral groups are informative about app usage.
Are people more likely to listen to experts than authorities during Covid-19 crisis? The case of crisis communication on Twitter during the covid-19 pandemic in Germany
1c3 team, Germany; 2sine - Süddeutsches Institut für empirische Sozialforschung e.V. | sine-Institut gGmbH, Germany
Relevance & Research Question:
The worldwide spread of the Covid-19 virus has led to an increased need for information related to the pandemic. Social media plays an important role in the population's search for information.
Both authorities and Covid-19 experts use Twitter to directly share their own statements and opinions with the Twitter community – unfiltered and independently from traditional media. Little is known on the twitter communication behavior of these players. This study aims to analyze characteristics and differences of both authorities and experts regarding the Covid-19 virus communication on Twitter.
Methods & Data: The evaluation is carried out using sentiment analysis and quantitative text analysis. Tweets from 40 German experts (n = 18) and public health authorities (n = 22) are analyzed between January 2020 and January 2021. For the analysis 35,645 relevant tweets covering Covid-19 topics have been identified. This study is commissioned by the Federal Office for Radiation Protection in Germany.
Results: First findings show that experts (58,6%) have 1.4 times more followers and tweet more often about Covid-19 than authorities (41,4%). Due to a much broader range of topics authorities tweet significantly more about non-Covid-19 topics in 2020 than experts do. Another important finding shows that Covid-19 tweets replicates the Covid-19 cases-curve including a lower Twitter activity during the summer of 2020. Regarding the structural, content and style elements of crisis communication tweets remarkable differences are revealed. While Covid-19 tweets of authorities are obviously designed to follow the known rules of successful social media communication with a higher rate of structural elements like hashtags, URLs and images, experts’ tweets are much plainer. Contrary, experts address their followers more directly via style elements such as use of first or second person than authorities do. Overall, Covid-19 tweets of experts are exceedingly more successful compared to authorities which is shown by a mean retweet rate that is 7 times that of authorities.
Added Value: The results of this study provide not only insights into risk and crisis communication during the Covid-19 pandemic, but also helpful conclusions for future (health) crisis situations, particularly for communication between authorities and the population.
Targeted communication in weather warnings: An experimental approach
1LINK Institut, Switzerland; 2MeteoSchweiz, Switzerland
Relevance & Research Question: Weather warnings, risk communication
Weather warnings inform the public about potentially dangerous weather events so that they can take precautionary measures to avoid harm and damages. However, weather warnings are often not user-oriented, which leads to poor understanding and low compliance rate. The present study focuses on the question, which elements of a warning message are the most important to influence risk perception and intended behavioural change.
Methods & Data: Vignette experiment, implicit associations, Web survey experiment
Using a single association test in a survey vignette experiment with 2000 Swiss citizens from all three language regions, we focus on implicit associations that citizens have, or do not have, when they see a warning message with varying elements (physical values, impact information, behavioural recommendations, warning level and labelling of the warning level). We test for associations with different concepts that play a role in the pre-decisional process of a warning response (e.g. personal relevance, risk perception). The experimental setup allows us to test for causal relationships between the different elements of a warning message and the intended behavioural response. Measuring the implicit associations enables us to better understand the first reactions triggered by the warning elements and how that impacts intended behavior.
Results: Multi-level analyses
Results show that risk and relevance have to be addressed unconsciously for weather warnings to impact the intention to act. The emphasis on behavioural recommendations and potential effects in weather warnings have a wake-up call character. In a nutshell, people need to know to what extent the weather can have an impact on their well-being and what they can do to protect themselves.
Added Value: Targeted communication to the public
First, by conducting a survey vignette experiment in combination with the single association test, we apply an experimental setup, which will open the black box of the perception of targeted communication. Second, the results add direct practical value as they inform the development of user-oriented weather warnings.Finally, the study contributes to research on risk perception and communication by providing a further insight to the cognitive process that underlies the decision to take protective actions