IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2022i1p494-d1017699.html
   My bibliography  Save this article

What Is the Role of Psychological Factors in Long COVID Syndrome? Latent Class Analysis in a Sample of Patients Recovered from COVID-19

Author

Listed:
  • Giuseppe Craparo

    (Faculty of Human and Social Sciences, Kore University of Enna, 94100 Enna, Italy
    These authors contributed equally to this work.)

  • Valentina Lucia La Rosa

    (Department of Educational Sciences, University of Catania, 95124 Catania, Italy
    These authors contributed equally to this work.)

  • Elena Commodari

    (Department of Educational Sciences, University of Catania, 95124 Catania, Italy)

  • Graziella Marino

    (IRCCS—Referral Cancer Center of Basilicata (CROB), 85028 Rionero in Vulture, Italy)

  • Michela Vezzoli

    (Department of Psychology, University of Milano-Bicocca, 20126 Milan, Italy)

  • Palmira Faraci

    (Faculty of Human and Social Sciences, Kore University of Enna, 94100 Enna, Italy)

  • Carmelo Mario Vicario

    (Department of Cognitive Sciences, Psychology, Education and Cultural Studies, University of Messina, 98122 Messina, Italy)

  • Gabriella Serena Cinà

    (Department of Psychology, U.O.C., Azienda Sanitaria Provinciale Trapani, 91100 Trapani, Italy)

  • Morena Colombi

    (#LongCovid Facebook Group, 00118 Rome, Italy)

  • Giuseppe Arcoleo

    (Pneumology Unit, Cervello Hospital, 90146 Palermo, Italy)

  • Maria Severino

    (Associazione Orizzonti Onlus, 90121 Palermo, Italy)

  • Giulia Costanzo

    (Faculty of Human and Social Sciences, Kore University of Enna, 94100 Enna, Italy)

  • Alessio Gori

    (Department of Health Sciences, University of Florence, 50121 Florence, Italy)

  • Ernesto Mangiapane

    (Associazione Orizzonti Onlus, 90121 Palermo, Italy)

Abstract

Background : This study aimed to identify clusters of long COVID-19 symptoms using latent class analysis and investigate the psychological factors involved in the onset of this syndrome. Method: Five hundred and six subjects recovering from COVID-19 completed a series of standardized questionnaires to evaluate the personality traits, alexithymia, and post-traumatic stress. Results : Five classes were identified: Brain fog (31.82%), No symptoms (20.95%), Sensory disorders (18.77%), Breath impairment (17.59%), and Multiple disorders (10.87%). Women reported post-COVID-19 respiratory symptoms and multiple disorders to a greater extent than men. Hospitalized subjects were more likely to report persistent symptoms after COVID-19 than asymptomatic or home-treated subjects. Antagonism, hyperarousal, and difficulty identifying emotions significantly predicted post COVID-19 symptoms. Conclusions : These findings open new questions for research on long COVID-19 and how states of emotional dysregulation can alter the physiological processes of the body and contribute to the onset of organic pathologies.

Suggested Citation

  • Giuseppe Craparo & Valentina Lucia La Rosa & Elena Commodari & Graziella Marino & Michela Vezzoli & Palmira Faraci & Carmelo Mario Vicario & Gabriella Serena Cinà & Morena Colombi & Giuseppe Arcoleo &, 2022. "What Is the Role of Psychological Factors in Long COVID Syndrome? Latent Class Analysis in a Sample of Patients Recovered from COVID-19," IJERPH, MDPI, vol. 20(1), pages 1-14, December.
  • Handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:494-:d:1017699
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/1/494/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/20/1/494/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Linzer, Drew A. & Lewis, Jeffrey B., 2011. "poLCA: An R Package for Polytomous Variable Latent Class Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i10).
    2. Callard, Felicity & Perego, Elisa, 2021. "How and why patients made Long Covid," Social Science & Medicine, Elsevier, vol. 268(C).
    3. Md. Saiful Islam & Most. Zannatul Ferdous & Ummay Soumayia Islam & Abu Syed Md. Mosaddek & Marc N. Potenza & Shahina Pardhan, 2021. "Treatment, Persistent Symptoms, and Depression in People Infected with COVID-19 in Bangladesh," IJERPH, MDPI, vol. 18(4), pages 1-16, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Matthew Whitaker & Joshua Elliott & Marc Chadeau-Hyam & Steven Riley & Ara Darzi & Graham Cooke & Helen Ward & Paul Elliott, 2022. "Persistent COVID-19 symptoms in a community study of 606,434 people in England," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Adrian O’Hagan & Arthur White, 2019. "Improved model-based clustering performance using Bayesian initialization averaging," Computational Statistics, Springer, vol. 34(1), pages 201-231, March.
    3. Aline Riboli Marasca & Maurício Scopel Hoffmann & Anelise Reis Gaya & Denise Ruschel Bandeira, 2021. "Subjective Well-Being and Psychopathology Symptoms: Mental Health Profiles and their Relations with Academic Achievement in Brazilian Children," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 14(3), pages 1121-1137, June.
    4. Lisa Blaydes, 2023. "Assessing the Labor Conditions of Migrant Domestic Workers in the Arab Gulf States," ILR Review, Cornell University, ILR School, vol. 76(4), pages 724-747, August.
    5. Jindřich Špička & Zdeňka Náglová, 2022. "Consumer segmentation in the meat market - The case study of Czech Republic," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(2), pages 68-77.
    6. Nicholas T. Davis & Kirby Goidel & Yikai Zhao, 2021. "The Meanings of Democracy among Mass Publics," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(3), pages 849-921, February.
    7. Irfan Ullah & Md. Saiful Islam & Sajjad Ali & Hashaam Jamil & Muhammad Junaid Tahir & Aatik Arsh & Jaffer Shah & Sheikh Mohammed Shariful Islam, 2021. "Insufficient Physical Activity and Sedentary Behaviors among Medical Students during the COVID-19 Lockdown: Findings from a Cross-Sectional Study in Pakistan," IJERPH, MDPI, vol. 18(19), pages 1-10, September.
    8. Turner, Melody & Beckwith, Helen & Spratt, Tanisha & Vallejos, Elvira Perez & Coughlan, Barry, 2023. "The #longcovid revolution: A reflexive thematic analysis," Social Science & Medicine, Elsevier, vol. 333(C).
    9. Carter, Virginia & Derudder, Ben & Henríquez, Cristián, 2021. "Assessing local governments’ perception of the potential implementation of biophilic urbanism in Chile: A latent class approach," Land Use Policy, Elsevier, vol. 101(C).
    10. Arjan S. Gosal & Janine A. McMahon & Katharine M. Bowgen & Catherine H. Hoppe & Guy Ziv, 2021. "Identifying and Mapping Groups of Protected Area Visitors by Environmental Awareness," Land, MDPI, vol. 10(6), pages 1-14, May.
    11. Assem Abu Hatab & Padmaja Ravula & Swamikannu Nedumaran & Carl-Johan Lagerkvist, 2022. "Perceptions of the impacts of urban sprawl among urban and peri-urban dwellers of Hyderabad, India: a Latent class clustering analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(11), pages 12787-12812, November.
    12. Jacqueline A. Krysa & Sidney Horlick & Kiran Pohar Manhas & Katharina Kovacs Burns & Mikayla Buell & Maria J. Santana & Kristine Russell & Elizabeth Papathanassoglou & Chester Ho, 2023. "Accessing Care Services for Long COVID Sufferers in Alberta, Canada: A Random, Cross-Sectional Survey Study," IJERPH, MDPI, vol. 20(15), pages 1-14, July.
    13. Martin Eling & David Pankoke, 2016. "Costs and Benefits of Financial Regulation: An Empirical Assessment for Insurance Companies," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 41(4), pages 529-554, October.
    14. Sunil Kumar & Zakir Husain & Diganta Mukherjee, 2015. "Assessing Consistency of Consumer Confidence Data using Dynamic Latent Class Analysis," Papers 1509.01215, arXiv.org.
    15. Lorena Charrier & Paola Berchialla & Paola Dalmasso & Alberto Borraccino & Patrizia Lemma & Franco Cavallo, 2019. "Cigarette Smoking and Multiple Health Risk Behaviors: A Latent Class Regression Model to Identify a Profile of Young Adolescents," Risk Analysis, John Wiley & Sons, vol. 39(8), pages 1771-1782, August.
    16. Raphaela Grafiadeli & Heide Glaesmer & Birgit Wagner, 2022. "Loss-Related Characteristics and Symptoms of Depression, Prolonged Grief, and Posttraumatic Stress Following Suicide Bereavement," IJERPH, MDPI, vol. 19(16), pages 1-10, August.
    17. Daniel L. Oberski, 2016. "A Review of Latent Variable Modeling With R," Journal of Educational and Behavioral Statistics, , vol. 41(2), pages 226-233, April.
    18. Guangchao Feng, 2014. "Estimating intercoder reliability: a structural equation modeling approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(4), pages 2355-2369, July.
    19. Giorgio Eduardo Montanari & Marco Doretti & Maria Francesca Marino, 2022. "Model-based two-way clustering of second-level units in ordinal multilevel latent Markov models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(2), pages 457-485, June.
    20. Bradley D. Custer & Hope O. Akaeze, 2021. "A Typology of State Financial Aid Grant Programs Using Latent Class Analysis," Research in Higher Education, Springer;Association for Institutional Research, vol. 62(2), pages 175-205, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:494-:d:1017699. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.