Interactive changes in depression and loneliness symptoms prior to and during the COVID-19 pandemic: A longitudinal network analysis

He Li Sun, Qinge Zhang, Tong Leong Si, Wei Bai, Pan Chen, Mei Ieng Lam, Ka In Lok, Zhaohui Su, Teris Cheung, Gabor S. Ungvari, Todd Jackson, Sha Sha, Yu Tao Xiang

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: Depression and loneliness co-occur frequently. This study examined interactive changes between depression and loneliness among older adults prior to and during the COVID-19 pandemic from a longitudinal network perspective. Methods: This network study was based on data from three waves (2016–2017, 2018–2019, and 2020) of the English Longitudinal Study of Ageing (ELSA). Depression and loneliness were measured with the eight-item version of the Center for Epidemiologic Studies Depression Scale (CESD-8) and three item version of the University of California Los Angeles (UCLA) Loneliness Scale, respectively. A network model was constructed using an Ising Model while network differences were assessed using a Network Comparison Test. Central symptoms were identified via Expected Influence (EI). Results: A total of 4,293 older adults were included in this study. The prevalence and network of depression and loneliness did not change significantly between the baseline and pre-pandemic assessments but increased significantly from the pre-pandemic assessment to during COVID-19 assessment. The central symptom with the strongest increase from pre-pandemic to pandemic assessments was "Inability to get going" (CESD8) and the edge with the highest increase across depression-loneliness symptom communities was “Lack companionship” (UCLA1) - "Inability to get going" (CESD8). Finally, “Feeling depressed” (CESD1) and “Everything was an effort" (CESD2) were the most central symptoms over the three assessment periods. Conclusions: The COVID-19 pandemic was associated with significant changes in the depression-loneliness network model. The most changed symptoms and edges could be treatment targets for reducing the risk of depression and loneliness in older adults.

Original languageEnglish
Article number115744
JournalPsychiatry Research
Volume333
DOIs
Publication statusPublished - Mar 2024

Keywords

  • Depression
  • Loneliness
  • Longitudinal network analysis

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