IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i23p12677-d692794.html
   My bibliography  Save this article

Impact of Longitudinal Social Support and Loneliness Trajectories on Mental Health during the COVID-19 Pandemic in France

Author

Listed:
  • Sandy Laham

    (Social Epidemiology Research Team, Institut Pierre Louis d’Épidémiologie et de Santé Publique, Sorbonne Université, INSERM U1136, 75012 Paris, France)

  • Leticia Bertuzzi

    (Social Epidemiology Research Team, Institut Pierre Louis d’Épidémiologie et de Santé Publique, Sorbonne Université, INSERM U1136, 75012 Paris, France)

  • Séverine Deguen

    (Social Epidemiology Research Team, Institut Pierre Louis d’Épidémiologie et de Santé Publique, Sorbonne Université, INSERM U1136, 75012 Paris, France
    Department of Environmental and Occupational Health, EHESP School of Public Health, 35043 Rennes, France)

  • Irwin Hecker

    (Social Epidemiology Research Team, Institut Pierre Louis d’Épidémiologie et de Santé Publique, Sorbonne Université, INSERM U1136, 75012 Paris, France)

  • Maria Melchior

    (Social Epidemiology Research Team, Institut Pierre Louis d’Épidémiologie et de Santé Publique, Sorbonne Université, INSERM U1136, 75012 Paris, France)

  • Martina Patanè

    (World Health Organization Collaborating Center for Research and Dissemination of Psychological Interventions, Department of Clinical, Neuro- and Developmental Psychology, Amsterdam Public Health Institute, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands)

  • Irene Pinucci

    (World Health Organization Collaborating Center for Research and Dissemination of Psychological Interventions, Department of Clinical, Neuro- and Developmental Psychology, Amsterdam Public Health Institute, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands)

  • Marit Sijbrandij

    (World Health Organization Collaborating Center for Research and Dissemination of Psychological Interventions, Department of Clinical, Neuro- and Developmental Psychology, Amsterdam Public Health Institute, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands)

  • Judith van der Waerden

    (Social Epidemiology Research Team, Institut Pierre Louis d’Épidémiologie et de Santé Publique, Sorbonne Université, INSERM U1136, 75012 Paris, France)

Abstract

(1) Background: Little is known about how the COVID-19 pandemic has impacted social support and loneliness over time and how this may predict subsequent mental health problems. This study aims to determine longitudinal trajectories of social support and loneliness in the French general population during the first year of the COVID-19 pandemic and study whether variations in these trajectories are associated with symptoms of depression and anxiety; (2) Methods: Analyses were based on data from 681 French participants in the international COVID-19 Mental Health Study (COMET) study, collected at four periods of time between May 2020 and April 2021. Group-based trajectory modelling (GBTM) was used to determine social support and loneliness trajectories. Associations between the identified trajectories and symptoms of depression and anxiety, measured with the Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder scale (GAD-7), were tested through multivariate linear regression models; (3) Results: Social support trajectories revealed four stable groups: ‘poor’ (17.0%), ‘moderate’ (42.4%), ‘strong’ (35.4%) and ‘very strong’ (5.1%). Loneliness trajectories also identified four groups: ‘low stable’ (17.8%), ‘low rising’ (40.2%), ‘moderate stable’ (37.6%) and ‘high rising’ (5.0%). Elevated symptoms of depression were associated with poor social support as well as all identified loneliness trajectories, while high levels of anxiety were associated with moderate stable and high rising loneliness trajectories; (4) Conclusions: High and increasing levels of loneliness are associated with increased symptoms of depression and anxiety during the pandemic. Interventions to address loneliness are essential to prevent common mental health problems during the pandemic and afterwards.

Suggested Citation

  • Sandy Laham & Leticia Bertuzzi & Séverine Deguen & Irwin Hecker & Maria Melchior & Martina Patanè & Irene Pinucci & Marit Sijbrandij & Judith van der Waerden, 2021. "Impact of Longitudinal Social Support and Loneliness Trajectories on Mental Health during the COVID-19 Pandemic in France," IJERPH, MDPI, vol. 18(23), pages 1-15, December.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12677-:d:692794
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/23/12677/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/23/12677/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    2. Yanmengqian Zhou & Erina L. MacGeorge & Jessica Gall Myrick, 2020. "Mental Health and Its Predictors during the Early Months of the COVID-19 Pandemic Experience in the United States," IJERPH, MDPI, vol. 17(17), pages 1-19, August.
    3. Yeli Wang & Monica Palanichamy Kala & Tazeen H Jafar, 2020. "Factors associated with psychological distress during the coronavirus disease 2019 (COVID-19) pandemic on the predominantly general population: A systematic review and meta-analysis," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-27, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jordi Miró & Elisabet Sánchez-Rodríguez & M. Carme Nolla & Rui M. Costa & J. Pais-Ribeiro & Alexandra Ferreira-Valente, 2022. "The Role of Resilience, Happiness, and Social Support in the Psychological Function during the Late Stages of the Lockdown in Individuals with and without Chronic Pain," IJERPH, MDPI, vol. 19(11), pages 1-10, May.

    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. Aidan Bodner & Leo Ruhl & Emily Barr & Arti Shridhar & Shayna Skakoon-Sparling & Kiffer George Card, 2022. "The Impact of Working from Home on Mental Health: A Cross-Sectional Study of Canadian Worker’s Mental Health during the Third Wave of the COVID-19 Pandemic," IJERPH, MDPI, vol. 19(18), pages 1-15, September.
    2. Noémi Kreif & Richard Grieve & Iván Díaz & David Harrison, 2015. "Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1213-1228, September.
    3. Abhilash Bandam & Eedris Busari & Chloi Syranidou & Jochen Linssen & Detlef Stolten, 2022. "Classification of Building Types in Germany: A Data-Driven Modeling Approach," Data, MDPI, vol. 7(4), pages 1-23, April.
    4. Fumiya Tanji & Yuki Kodama, 2021. "Prevalence of Psychological Distress and Associated Factors in Nursing Students during the COVID-19 Pandemic: A Cross-Sectional Study," IJERPH, MDPI, vol. 18(19), pages 1-10, October.
    5. Boonstra Philip S. & Little Roderick J.A. & West Brady T. & Andridge Rebecca R. & Alvarado-Leiton Fernanda, 2021. "A Simulation Study of Diagnostics for Selection Bias," Journal of Official Statistics, Sciendo, vol. 37(3), pages 751-769, September.
    6. Sana Malik & Melissa Bessaha & Kathleen Scarbrough & Jessica Younger & Wei Hou, 2023. "Self-Reported Depression and Anxiety among Graduate Students during the COVID-19 Pandemic: Examining Risk and Protective Factors," Sustainability, MDPI, vol. 15(8), pages 1-16, April.
    7. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    8. Liangyuan Hu & Lihua Li, 2022. "Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series," IJERPH, MDPI, vol. 19(23), pages 1-13, December.
    9. Norah Alyabs & Sy Han Chiou, 2022. "The Missing Indicator Approach for Accelerated Failure Time Model with Covariates Subject to Limits of Detection," Stats, MDPI, vol. 5(2), pages 1-13, May.
    10. Feldkircher, Martin, 2014. "The determinants of vulnerability to the global financial crisis 2008 to 2009: Credit growth and other sources of risk," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 19-49.
    11. Ida Kubiszewski & Kenneth Mulder & Diane Jarvis & Robert Costanza, 2022. "Toward better measurement of sustainable development and wellbeing: A small number of SDG indicators reliably predict life satisfaction," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(1), pages 139-148, February.
    12. Georges Steffgen & Philipp E. Sischka & Martha Fernandez de Henestrosa, 2020. "The Quality of Work Index and the Quality of Employment Index: A Multidimensional Approach of Job Quality and Its Links to Well-Being at Work," IJERPH, MDPI, vol. 17(21), pages 1-31, October.
    13. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.
    14. Esef Hakan Toytok & Sungur Gürel, 2019. "Does Project Children’s University Increase Academic Self-Efficacy in 6th Graders? A Weak Experimental Design," Sustainability, MDPI, vol. 11(3), pages 1-12, February.
    15. J M van Niekerk & M C Vos & A Stein & L M A Braakman-Jansen & A F Voor in ‘t holt & J E W C van Gemert-Pijnen, 2020. "Risk factors for surgical site infections using a data-driven approach," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-14, October.
    16. Joost R. Ginkel, 2020. "Standardized Regression Coefficients and Newly Proposed Estimators for $${R}^{{2}}$$R2 in Multiply Imputed Data," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 185-205, March.
    17. Lara Jehi & Xinge Ji & Alex Milinovich & Serpil Erzurum & Amy Merlino & Steve Gordon & James B Young & Michael W Kattan, 2020. "Development and validation of a model for individualized prediction of hospitalization risk in 4,536 patients with COVID-19," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-15, August.
    18. Matthew Carli & Mary H. Ward & Catherine Metayer & David C. Wheeler, 2022. "Imputation of Below Detection Limit Missing Data in Chemical Mixture Analysis with Bayesian Group Index Regression," IJERPH, MDPI, vol. 19(3), pages 1-17, January.
    19. Gerko Vink & Laurence E. Frank & Jeroen Pannekoek & Stef Buuren, 2014. "Predictive mean matching imputation of semicontinuous variables," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(1), pages 61-90, February.
    20. Tsai, Tsung-Han, 2016. "A Bayesian Approach to Dynamic Panel Models with Endogenous Rarely Changing Variables," Political Science Research and Methods, Cambridge University Press, vol. 4(3), pages 595-620, September.

    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:18:y:2021:i:23:p:12677-:d:692794. 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.