Abstract

PurposeLoneliness increased during the COVID-19 pandemic and social distancing guidelines, potentially exacerbating negative cognitions about pain. The present study investigated the longitudinal relationship between loneliness, assessed during the early weeks of the pandemic, and pain catastrophizing, assessed after living in the pandemic for approximately 1 year, among chronic pain patients. We also examined whether severity of depressive symptoms mediated this association.MethodsThis prospective longitudinal study recruited individuals with chronic pain (N=93) from Massachusetts using an online convenience sampling method via the platform Rally. Participants completed an initial survey early after the onset of social distancing (4/28/20–6/17/20; Time 1) and a follow-up survey 1 year later (5/21/21–6/7/21; Time 2). Participants completed validated assessments of loneliness (T1), pain catastrophizing (T2), and depression (T2). Spearman correlations and Mann–Whitney U-tests were used to explore associations among psychosocial, pain, and participant characteristics. A mediation analysis was conducted to test whether the association between loneliness and pain catastrophizing was mediated by depression.ResultsParticipants had a mean age of 40.6 years and were majority female (80%) and White (82%). Greater loneliness was associated with subsequent higher pain catastrophizing (b=1.23, 95% CI [0.03, 2.44]). Mediation analysis showed a significant indirect effect (b=0.57, 95% CI [0.10, 1.18) of loneliness (T1) on catastrophizing (T2) through depression (T2) while accounting for several important covariates. The direct effect of loneliness on catastrophizing was no longer significant when depression was included in the model (b=0.66, 95% CI [−0.54, 1.87]).ConclusionFindings suggest that greater loneliness during the pandemic was associated with higher pain catastrophizing 1 year later, and severity of depression after living in the pandemic mediated this association. As loneliness, depression, and catastrophizing can all be modified with behavioral interventions, understanding the temporal associations among these variables is important for the employment of future empirically supported treatments.

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