You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:

- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.
- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.
- Prevention: The content covers measures to prevent the spread of COVID-19.
- Mechanism: The paragraph explains the biological mechanisms of the virus.
- Case Report: The content is a report of a COVID-19 case.
- Transmission: The paragraph discusses how COVID-19 is transmitted.
- Diagnosis: The content is about diagnosing COVID-19 in individuals.

Your classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: ["Topic1", "Topic2", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.

Article:

BACKGROUND: Corona contact tracing apps are a novel and promising measure to reduce the spread of COVID-19. They can help to balance the need to maintain normal life and economic activities as much as possible while still avoiding exponentially growing case numbers. However, a majority of citizens needs to be willing to install such an app for it to be effective. Hence, knowledge about drivers for app-uptake is crucial. OBJECTIVE: The present study aims to add to our understanding of underlying psychological factors motivating app-uptake. More specifically, we investigated the role of concern for one's own health and concern to unknowingly infect others. METHODS: A two-wave survey with N = 346 German-speaking participants from Switzerland and Germany was conducted. We measured the uptake of two decentralized contact tracing apps officially launched by governments ("Corona-Warn-App", Germany; "SwissCovid", Switzerland) as well as concerns regarding COVID-19 and control variables. RESULTS: While controlling for demographic variables as well as general attitudes towards the government and the pandemic, logistic regression analysis showed a significant effect of self-focused concerns (Odds Ratio = 1.64, P <.01). Meanwhile, concern to unknowingly infect others did not contribute significantly to the prediction of app-uptake over and above concern for one's own health (Odds Ratio = 1.01, P = .92). Longitudinal analyses replicated this pattern and showed no support for the possibility that app-uptake provokes changes in levels of concern. Testing for a curvilinear relationship, no evidence was found that "too much" concern leads to defensive reactions and reduces app-uptake. CONCLUSIONS: As one of the first studies to assess the installation of already launched corona tracing apps, our study extends our knowledge of the motivational landscape of app-uptake. Based on that, practical implications for communication strategies and app design are discussed. CLINICALTRIAL:
["Prevention"]