How is loneliness related to anxiety and depression: A population‐based network analysis in the early lockdown period

Marcin Owczarek, Emma Nolan, Mark Shevlin, Sarah Butter, Thanos Karatzias, Orla McBride, Jamie Murphy, Frederique Vallieres, Richard Bentall, Anton Martinez, Philip Hyland

Research output: Contribution to journalArticlepeer-review

Abstract

High risk of mental health problems is associated with loneliness resulting from social distancing measures and “lockdowns” that have been imposed globally due to the COVID‐19 pandemic. This study explores the interconnectedness of loneliness, anxiety and depression on a symptom level using network analysis. A representative sample of participants (N = 1041), who were of at least 18 years of age, was recruited from the Republic of Ireland (ROI). Loneliness, anxiety and depression were assessed using validated instruments. Network analysis was used to identify the network structure of loneliness, anxiety and depression. Loneliness was found to be largely isolated from anxiety and depression nodes in the network. Anxiety and depression were largely interconnected. “Trouble relaxing,” “feeling bad about oneself” and “not being able to stop or control worrying” were suggested as the most influential nodes of the network. Despite the expectation that loneliness would be implicated more robustly in the anxiety and depression network of symptoms, the results suggest loneliness as a distinct construct that is not interwoven with anxiety and depression.
Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalInternational Journal of Psychology
Early online date6 May 2022
DOIs
Publication statusE-pub ahead of print - 6 May 2022

Bibliographical note

© 2022 The Authors. International Journal of Psychology published by John Wiley & Sons Ltd on behalf of International Union of Psychological Science.

Keywords

  • Regular Empirical Article
  • Regular Empirical Articles
  • Anxiety
  • Depression
  • Loneliness

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