Abstract
Purpose - The purpose of this paper is to examine the relationship between egocentric social networks and mental health (MH) outcomes. The authors aim to develop a theoretical framework for understanding this association and to test whether social network factors add any further explanatory power to MH outcomes.
Design/methodology/approach - Data for this study were drawn from the Household, Income and Labour Dynamics in Australia survey (n = 14,756). The authors used hierarchical multiple regression technique to test this hypothesis and using the Akaike information criterion (AIC) the authors identified the best fit model.
Findings - The results of this study shows that social network measures do add considerable explanatory power to MH with social isolation (SI) having the highest influence (beta = -0.198, p < 0.001) followed by social connections (SCs) (beta = 0.141, p < 0.001) and then social trust (ST) (beta = 0.071, p < 0.001). The AIC best fit model included all the social network predictors however it excluded physical functioning which contributed very little.
Originality/value - This study shows that social network factors play a significant role in predicting MH outcomes. In particular, SI was a more significant predictor of MH than SC. However, ST played a relatively minor role in predicting MH scores. These findings have practical implications and applications for the design of policy initiatives aimed at improving MH outcomes.