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Monitoring of COVID-19 Pandemic-related Psychopathology using Machine Learning
Kenneth C. Enevoldsen
Andreas Aalkjær Danielsen
Christopher Rohde
Oskar Jefsen
Kristoffer Nielbo
Søren Dinesen Østergaard
Acceso Abierto
The COVID-19 pandemic has been shown to have a major negative impact on global mental health and patients with mental illness may be particularly vulnerable. We show that developments in COVID-19 pandemic-related psychopathology among patients with mental illness can be meaningfully monitored using machine learning methods. The COVID-19 pandemic-related psychopathology was found to covary with the pandemic pressure. This correlation was, however, less pronounced during the second wave compared to the first wave of the pandemic - possibly due to habituation. Competing Interest Statement CR received the 2020 Lundbeck Foundation Talent Prize. SDO received the 2020 Lundbeck Foundation Young Investigator Prize. The remaining authors declare no conflicts of interest. Funding Statement This project is supported by an unconditional grant from the Novo Nordisk Foundation to SDO (Grant number: NNF20SA0062874). CR is supported by the Danish Diabetes Academy, funded by the Novo Nordisk Foundation (grant number NNF17SA0031406) and the Lundbeck Foundation (grant number: R358-2020-2342). OHJ is supported by the Health Research Foundation of the Central Denmark Region (grant number: R64-A3090-B1898). SDO is supported by the Lundbeck Foundation (grant numbers: R358-2020-2341 and R344-2020-1073), the Danish Cancer Society (grant number: R283-A16461), the Central Denmark Region Fund for Strengthening of Health Science (grant number: 1-36-72-4-20), the Danish Agency for Digitisation Investment Fund for New Technologies (grant number 2020-6720) and Independent Research Fund Denmark (grant number: 7016-00048B).
Epidemia COVID-19
Público en general
Versión publicada
publishedVersion - Versión publicada
Appears in Collections:Artículos científicos

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