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Prevalence and Predictors of Long COVID in Patients Accessing a National Digital Mental Health Service

Author

Listed:
  • Lauren G. Staples

    (MindSpot Clinic, MQ Health, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia)

  • Olav Nielssen

    (MindSpot Clinic, MQ Health, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia)

  • Blake F. Dear

    (MindSpot Clinic, MQ Health, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia)

  • Madelyne A. Bisby

    (MindSpot Clinic, MQ Health, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia)

  • Alana Fisher

    (MindSpot Clinic, MQ Health, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia)

  • Rony Kayrouz

    (MindSpot Clinic, MQ Health, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia)

  • Nickolai Titov

    (MindSpot Clinic, MQ Health, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia)

Abstract

MindSpot is a national mental health service that provides assessments and treatment to Australian adults online or via telephone. Since the start of 2020, questions related to the mental health impacts of COVID-19 have been routinely administered. The objective of the current study is to report the prevalence and predictors of self-reported “long COVID” in patients completing an assessment at the MindSpot Clinic between 5 September 2022 and 7 May 2023 ( n = 17,909). Consistent with the World Health Organization definition, we defined long COVID as the occurrence of ongoing physical or mental health symptoms three months after a COVID-19 infection. We conducted a descriptive univariate analysis of patients who reported: no COVID-19 diagnosis ( n = 6151); a current or recent (within 3 months) COVID-19 infection ( n = 2417); no symptoms three months post-COVID-19 infection ( n = 7468); or COVID-related symptoms at least three months post-infection (n = 1873). Multivariate logistic regression was then used to compare patients with and without symptoms three months post-COVID to identify potential predictors for long COVID. The prevalence of long COVID was 10% of the total sample (1873/17909). Patients reporting symptoms associated with long COVID were older, more likely to be female, and more likely to be depressed and report a reduced ability to perform their usual tasks. Sociodemographic factors, including cultural background, education, and employment, were examined. These results provide evidence of the significant prevalence of symptoms of long COVID in people using a national digital mental health service. Reporting outcomes in an Australian context and in specific sub-populations is important for public health planning and for supporting patients.

Suggested Citation

  • Lauren G. Staples & Olav Nielssen & Blake F. Dear & Madelyne A. Bisby & Alana Fisher & Rony Kayrouz & Nickolai Titov, 2023. "Prevalence and Predictors of Long COVID in Patients Accessing a National Digital Mental Health Service," IJERPH, MDPI, vol. 20(18), pages 1-8, September.
  • Handle: RePEc:gam:jijerp:v:20:y:2023:i:18:p:6756-:d:1239300
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    References listed on IDEAS

    as
    1. Lauren G. Staples & Nick Webb & Lia Asrianti & Shane Cross & Daniel Rock & Rony Kayrouz & Eyal Karin & Blake F. Dear & Olav Nielssen & Nickolai Titov, 2022. "A Comparison of Self-Referral and Referral via Primary Care Providers, through Two Similar Digital Mental Health Services in Western Australia," IJERPH, MDPI, vol. 19(2), pages 1-13, January.
    2. Ben King & Omolola E. Adepoju & LeChauncy Woodard & Abiodun O. Oluyomi & Xiaotao Zhang & Christopher I. Amos & Hoda Badr, 2023. "The Effects of COVID-19 Lockdown on Social Connectedness and Psychological Distress in U.S. Adults with Chronic Diseases," IJERPH, MDPI, vol. 20(13), pages 1-14, June.
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