Social networks and mental health: an egocentric perspective

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 (β=−0.198, p<0.001) followed by social connections (SCs) (β=0.141, p<0.001) and then social trust (ST) (β=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.

Citation

Levula, A. and Harré, M. (2016), "Social networks and mental health: an egocentric perspective", Mental Health Review Journal, Vol. 21 No. 3, pp. 161-173. https://doi.org/10.1108/MHRJ-10-2015-0029