Monitoring of COVID-19 Pandemic-related Psychopathology using Machine Learning

Kenneth Enevoldsen; Andreas Aalkjær Danielsen; Christopher Rohde; Oskar Hougaard Jefsen; Kristoffer Laigaard Nielbo; Søren Dinesen Østergaard

Monitoring of COVID-19 Pandemic-related Psychopathology using Machine Learning

Kenneth Enevoldsen^*, Andreas Aalkjær Danielsen, Christopher Rohde, Oskar Hougaard Jefsen, Kristoffer Laigaard Nielbo, Søren Dinesen Østergaard

^*Corresponding author af dette arbejde

Publikation: Working paper/Preprint › Preprint

Abstract

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.

Originalsprog	Engelsk
Udgiver	medRxiv
Status	Udgivet - 2021

Adgang til dokumentet

https://www.medrxiv.org/content/10.1101/2021.07.13.21259962v1

2 Tidsskriftartikel

Psychological well-being and symptoms of depression and anxiety across age groups during the second wave of the COVID-19 Pandemic in Denmark
Vistisen, H. T., Sønderskov, K. M., Dinesen, P. T. & Østergaard, S. D., 9 dec. 2021, I: Acta Neuropsychiatrica. 33, 6, s. 331-334 4 s.
Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

9 Citationer (Scopus)
The PSYchiatric Clinical Outcome Prediction (PSYCOP) cohort: Leveraging the potential of electronic health records in the treatment of mental disorders
Hansen, L., Enevoldsen, K. C., Bernstorff, M., Nielbo, K. L., Danielsen, A. A. & Østergaard, S. D., 9 dec. 2021, I: Acta Neuropsychiatrica. 33, 6, s. 323 - 330 8 s.
Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review
10 Citationer (Scopus)

Citationsformater

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abstract = "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.",

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author = "Kenneth Enevoldsen and Danielsen, {Andreas Aalkj{\ae}r} and Christopher Rohde and Jefsen, {Oskar Hougaard} and Nielbo, {Kristoffer Laigaard} and {\O}stergaard, {S{\o}ren Dinesen}",

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AU - Enevoldsen, Kenneth

AU - Danielsen, Andreas Aalkjær

AU - Rohde, Christopher

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AU - Nielbo, Kristoffer Laigaard

AU - Østergaard, Søren Dinesen

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AB - 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.

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KW - COVID-19

M3 - Preprint

BT - Monitoring of COVID-19 Pandemic-related Psychopathology using Machine Learning

PB - medRxiv

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Monitoring of COVID-19 Pandemic-related Psychopathology using Machine Learning

Abstract

Adgang til dokumentet

Fingeraftryk

Publikation

Psychological well-being and symptoms of depression and anxiety across age groups during the second wave of the COVID-19 Pandemic in Denmark

The PSYchiatric Clinical Outcome Prediction (PSYCOP) cohort: Leveraging the potential of electronic health records in the treatment of mental disorders

Citationsformater