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. 2023 Mar 1;128(2):101-118.
doi: 10.1352/1944-7558-128.2.101.

Social Network Diversity and Mental Health Among Mothers of Individuals With Autism

Robert S Dembo  1 , Marsha R Mailick  1 , Abby E Rudolph  2 , Nick Huntington  3 , Leann Smith DaWalt  4 , Monika Mitra  5
Affiliations

Social Network Diversity and Mental Health Among Mothers of Individuals With Autism

Robert S Dembo et al. Am J Intellect Dev Disabil. .

Abstract

The present study examined the associations between networks of social relationships and psychological well-being among mothers of adolescents and adults with autism (n = 352) over a 12-year period of time. A structural equation modeling approach was used to delineate the relative impacts of network size and relationship diversity on maternal mental health, and to assess whether such effects are bidirectional. Mothers with more diverse relationships experienced reductions in depression and anxiety symptoms over time, and the psychological benefits of diversity remained after adjusting for network size. Results also suggest bidirectional links between network size, diversity, and maternal mental health. Research and clinical implications are discussed.

Keywords: adolescence; adulthood; autism spectrum disorder; mental health; mothers; social networks.

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Figures

Figure 1.
Figure 1.
Dynamic panel model for social networks predicting maternal mental health Note. Adapted from Allison et al. (2017) and Williams et al. (2018). The latent random effect is represented by α. The correlation between “Social network T4” and the “Mental health T3” ε depicts the sequential exogeneity of the social network variable: when predicting mental health, the social network variable at time t is free to correlate with the error term for mental health at any prior time point (t-1, t-2, etc.). This correlation is what allows for the possibility of a reciprocal effect, from mental health to the social network variable. To enhance readability, some of the paths and correlations are omitted, including the covariances among exogenous variables and the lagged endogenous variable. Only one correlation is drawn to depict the sequential exogeneity of social networks. The control variables included in the models are also not shown.
See this image and copyright information in PMC

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