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The longitudinal relationship between life events and loneliness in adolescence: A twin study.

Eirunn SkaugNikolai O CzajkowskiTrine WaaktaarSvenn Torgersen
Published in: Developmental psychology (2024)
The aim of the study was to examine associations between life events and self-assessed loneliness in adolescence. We used data from a Norwegian population-based twin sample including seven birth cohorts ( N = 2,879, 56% females). The participants completed self-report questionnaires three times throughout adolescence, with 2 years in between (i.e., 12-18 years old at Wave 1). By using a random intercept cross-lagged panel model (RI-CLPM), we were able to separate stable influences in the measured constructs from the within-person changes at each measurement occasion. In addition, using data from twins allowed us to examine to what degree the associations between life events and loneliness were genetic and/or environmental in nature. The results showed moderate stability of both loneliness and aggregation scores of life events throughout adolescence. The life events were assigned to clusters based on their independence (i.e., events considered dependent or independent on a person's behavior) and desirability (i.e., positive or negative). The time-stable between-person variance in all three measures, loneliness and person-dependent positive and negative life events, could almost exclusively be accounted for by genetic factors. However, as expected, also shared environmental factors influenced person-independent life events. The associations between time-stable between-person variance in loneliness and life events were small, and nearly exclusively due to shared genetic influences. Furthermore, life events do not seem to predict changes in loneliness or vice versa. In conclusion, the self-reported levels of loneliness throughout adolescence seems to be independent of life events. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Keyphrases
  • social support
  • depressive symptoms
  • emergency department
  • genome wide
  • climate change
  • big data
  • life cycle