Distress, loneliness, and mental health during the COVID-19 pandemic: Test of the extension of the Evolutionary Theory of Loneliness

Franziska Maria Keller, Christina Derksen, Lukas Kötting, Alina Dahmen, Sonia Lippke, Franziska Maria Keller, Christina Derksen, Lukas Kötting, Alina Dahmen, Sonia Lippke

Abstract

COVID-19 restrictions such as lockdowns or quarantines may increase the risk for social isolation and perceived loneliness. The mechanisms can be modeled by Cacioppo's Evolutionary Theory of Loneliness (ETL), which predicts that a lack of perceived social connectedness may lead, in the long-term, to mental and physical health consequences. However, the association between COVID-19 pandemic distress, mental health, and loneliness is not sufficiently understood. The present longitudinal study examined the relationship between distress and depression, and the mediating effects of anxiety and loneliness in a German rehabilitation sample (N = 403) at two timepoints (≤6 weeks pre-rehabilitation; ≥12 weeks post-rehabilitation; mean time between T1 and T2 was 52 days). Change scores between T1 and T2 were examined for the variables COVID-19 Peritraumatic Distress Index (CPDI), anxiety, loneliness, and depression. The results of the serial mediation analysis indicated that anxiety and loneliness were able to explain the relationship between distress and depression with 42% of variance in depression accounted for. Findings extend research on the relationship between COVID-19 and mental health by considering anxiety and loneliness as sustaining factors of depressive symptoms, thus, successfully applying the ETL. Results stress the necessity to consider anxiety and loneliness in the treatment or prevention of depression.

Keywords: anxiety; depressive symptoms; psychosomatic rehabilitation patients; serial mediation.

Conflict of interest statement

The authors declare no conflict of interest.

© 2022 The Authors. Applied Psychology: Health and Well-Being published by John Wiley & Sons Ltd on behalf of International Association of Applied Psychology.

Figures

FIGURE 1
FIGURE 1
Theoretical model of the serial mediation model. Note: The serial mediation model contains six path coefficients (a1, a2, a3, b1, b2, c′) and the total effect (c). Note. IV = independent variable, DV = dependent variable, M1 = mediator 1, M2 = mediator 2
FIGURE 2
FIGURE 2
Longitudinal serial mediation model for COVID‐19 Peritraumatic Distress Index (CPDI), symptoms of anxiety, loneliness, and symptoms of depression in N = 342 rehabilitation patients. Note. The model is controlled for age, gender, education, and ICD‐10 diagnosis. Reported coefficients are standardized betas coefficients, in brackets is the total effect; * p < .05; ** p < .01 (see Figure B2 for the full sample)
FIGURE B2
FIGURE B2
Validating the longitudinal serial mediation model COVID‐19 Peritraumatic Distress Index (CPDI), symptoms of anxiety, loneliness, and symptoms of depression with N = 651 rehabilitation patients (retaining dropouts by means of missing imputation). Note. The model is controlled for age, gender, education, ICD‐10 diagnosis. Reported coefficients are standardized betas coefficients, in brackets is the total effect; ** p < .01 With regard to the present serial mediation path model, three possible indirect effects were examined: (1) the total indirect path from CPDI to symptoms of depression through symptoms of anxiety and loneliness which was significant; (2) the specific indirect path through symptoms of anxiety which was not significant (ß = .107, 95% CI [0.063, 0.154]); (3) and the specific indirect path through loneliness (ß = .115, 95% CI [0.077, 0.156]), which was also significant

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