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Loneliness and Well-Being in Children and Adolescents during the COVID-19 Pandemic: A Systematic Review.

Ann H FarrellIrene VitoroulisMollie ErikssonTracy Vaillancourt
Published in: Children (Basel, Switzerland) (2023)
Concerns have been raised about the loneliness and well-being of children and adolescents during the COVID-19 pandemic. The extent to which the ongoing pandemic has impacted loneliness and the association between loneliness and well-being is unclear. Therefore, a systematic review of empirical studies on the COVID-19 pandemic was conducted to examine the (1) prevalence of loneliness in children and adolescents, (2) associations between loneliness and indicators of well-being, and (3) moderators of these associations. Five databases (MEDLINE, Embase, PsycInfo, Web of Science, ERIC) were searched from 1 January 2020 to 28 June 2022 and 41 studies met our inclusion criteria (cross-sectional: n = 30; longitudinal: n = 11; registered on PROSPERO: CRD42022337252). Cross-sectional prevalence rates of pandemic loneliness varied, with some finding that over half of children and adolescents experienced at least moderate levels of loneliness. Longitudinal results reflected significant mean increases in loneliness compared to pre-pandemic levels. Cross-sectional results indicated that higher levels of loneliness were significantly associated with poorer well-being, including higher depression symptoms, anxiety symptoms, gaming addiction, and sleep problems. Longitudinal associations between loneliness and well-being were more complex than cross-sectional associations, varying by assessment timing and factors in the statistical analyses. There was limited diversity in study designs and samples, preventing a thorough examination of moderating characteristics. Findings highlight a broader challenge with child and adolescent well-being that predates the pandemic and the need for future research to examine underrepresented populations across multiple timepoints.
Keyphrases
  • cross sectional
  • social support
  • sars cov
  • depressive symptoms
  • coronavirus disease
  • mental health
  • risk factors
  • public health
  • young adults
  • machine learning