Social capital, interconnected with the tight-knit bonds within marginalised groups, could deter help-seeking. Knowledge and attitudes towards help and help-seeking, shaped by past experiences and network cultures, influenced help-seeking and contributed to a cautious and selective approach.
4/4

Social/relational influences identified included: fear of losing social capital, the risks of high bonding capital, service providers as social capital, selective help-seeking, trust and network culture.
3/4

Paper reviews the 27 papers around mental health/substance use help-seeking by adults experiencing (non-demographic) marginalisation and used social capital or social network analysis (#SNA)
2/4

Congratulations. Well done.

And secondly, Research Fellow in Evidence Review and Synthesis of Community Interventions
my.corehr.com/pls/shurecru...

Here's a good one from Danielle Pillet-Shore.
onlinelibrary.wiley.com/doi/10.1111/...

They are great to use in teaching. Students like hearing the author discuss the paper and it improves the flow of a lecture as well.

Overall, the book brings together ideas from social stratification, social network analysis and social inequalities to argue that looking at the occupations of pairs of individuals (such as partners, or friends) can aid our understanding of important social processes. (14/14)

(12) Conclusion argues that effects of homophily around social stratification position are important in the reproduction of inequality (13/14)

(11) Exploiting Non-standard Dimension Scores and Network Structures in the Analysis of Social Interactions Between Occupations looks at other forms of homophily in people's connections and breaks down the analysis to explore differences between subgroups (12/14)

(10) Social Interactions and Educational Inequality provides an intersectional approach to examing the role of education in occupational stratification (11/14)

(9) Occupational-Level Residuals and Distributional Parameters explores other meaningful approaches using pairs of occupations, including random effects modelling (10/14)

(8) Social Network Analysis of Occupational Connections converts those occupations which are commonly linked into a network to explore how stratification patterns can be observed and meaningfully compared (9/14)

(7) Networked Occupations looks at which occupations tend to connect more often than we would imagine if randomly distributed - this shows the effect of stratification in a slightly different way to Social Interaction Distance approaches (8/14)

(6) Constructing CAMSIS Scales provides the recipe (and #Stata syntax) for creating a scheme from data on pairs of occupations, managing the data and dealing with pseudo-diagonals (pairings which do not reflect the stratification structure) (7/14)

(5) Evaluating CAMSIS scales explores the characteristics of #CAMSIS (and #HISCAM) schemes between countries, drawing on consistencies we commonly see, and how differences often uncover important contours of that society (6/14)

(4) #CAMSIS and the Analysis of Social Interaction Distance provides the theoretical underpinning of how studying combinations of occupations can produce a valid and nuanced stratification scheme of the position of each individual occupation (5/14)

(3) Measures of Social Stratification provides an overview of ways of measuring stratification, exploring the different forms of occupational, social class, geographical, income and #GBCS style approaches (4/14)