The role of self-compassion in loneliness during the COVID-19 pandemic: a group-based trajectory modelling approach

Robin Wollast, David A. Preece, Mathias Schmitz, Alix Bigot, James J. Gross, Olivier Luminet

    Research output: Contribution to journalArticlepeer-review

    5 Citations (Web of Science)

    Abstract

    Research has suggested an increase in loneliness during the COVID-19 pandemic, but much of this work has been cross-sectional, making causal inferences difficult. In the present research, we employed a longitudinal design to identify loneliness trajectories within a period of twelve months during the COVID-19 pandemic in Belgium (N = 2106). We were particularly interested in the potential protective role of self-compassion in these temporal dynamics. Using a group-based trajectory modelling approach, we identified trajectory groups of individuals following low (11.0%), moderate-low (22.4%), moderate (25.7%), moderate-high (31.3%), and high (9.6%) levels of loneliness. Findings indicated that younger people, women, and individuals with poor quality relationships, high levels of health anxiety, and stress related to COVID-19, all had a higher probability of belonging to the highest loneliness trajectory groups. Importantly, we also found that people high in two of the three facets of self-compassion (self-kindness and common humanity) had a lower probability of belonging to the highest loneliness trajectory groups. Ultimately, we demonstrated that trajectory groups reflecting higher levels of loneliness were associated with lower life satisfaction and greater depressive symptoms. We discuss the possibility that increasing self-compassion may be used to promote better mental health in similarly challenging situations.

    Original languageEnglish
    Pages (from-to)103-119
    Number of pages17
    JournalCognition and Emotion
    Volume38
    Issue number1
    DOIs
    Publication statusPublished - 2024

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