Background: Higher social support protects people from developing mental disorders. Limited evidence is available on the mechanism through which social support plays this protective role.
Objective: To investigate the stress-buffering process of social support on depressive symptoms using a novel longitudinal dynamic symptom network approach.
Methods: A total of 4242 adult participants who completed the first two waves (from May to October 2020) of the International Covid Mental Health Survey were included in the study. Cross-lagged panel network modelling was used to estimate a longitudinal network of self-reported social support, loneliness and depressive symptoms. Standardised regression coefficients from regularised cross-lagged regressions were estimated as edge weights of the network.
Findings: The results support a unidirectional protective effect of social support on key depressive symptoms, partly mediated through loneliness: A higher number of close confidants and accessible practical help was associated with decreased anhedonia (weight=-0.033) and negative self-appraisal symptoms (weight=-0.038). Support from others was also negatively associated with loneliness, which in turn associated with decreased depressed mood (weight=0.086) and negative self-appraisal (weight=0.077). We identified a greater number of direct relationships from social support to depressive symptoms among men compared with women. Also, the edge weights from social support to depression were generally stronger in the men's network.
Conclusions: Reductions in negative self-appraisal might function as a bridge between social support and other depressive symptoms, and, thus, it may have amplified the protective effect of social support. Men appear to benefit more from social support than women.
Clinical implications: Building community-based support networks to deliver practical support, and loneliness reduction components are critical for depression prevention interventions after stressful experiences.
Keywords: COVID-19; adult psychiatry; depression & mood disorders.
© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. Published by BMJ.