Work, housing and friendships are core factors to feeling included.
By identifying the early signs of isolation and loneliness, support can be provided to prevent more serious mental ill-health.
In mental healthcare, simple screening tools for common conditions like depression and anxiety make it possible to diagnose people quickly and get help sooner.
A new tool developed at Orygen does the same, but for social inclusion: the F-SIM (Filia Social Inclusion Measure), developed by Dr Kate Filia and being presented in Hobart this week at the Society for Mental Health Research conference, could help to pinpoint the causes of isolation and social exclusion,
The simple test could be used by professionals such GPs, educators or community support workers to spot the early signs of social isolation so they can offer support before it develops into more serious mental illness.
“People who experience social exclusion are more likely to experience mental ill-health and people with mental ill-health are more likely to experience social exclusion,” said Kate. “It’s a negative and damaging cycle that can be challenging to break, but measuring it is the first step.”
The user-friendly tool lets people self-report their own feelings of inclusion in social relationships, housing, work, education, finances, health and wellbeing. It was developed with input from people with lived experience of mental ill-health and carers.
During 2020-21, the F-SIM tool was tested with more than 500 Australians, young and old, focusing on people who had experienced serious mental illnesses including psychosis, mood and anxiety disorders. However, the real impact could come through early detection of social exclusion and prevention of mental illness, particularly as we recover from lockdown and support programmes end.
“Our tool shows that work, housing and friendships are core factors in feeling included,” said Kate, “so programmes like Jobkeeper, the eviction moratorium and extra support we’ve all given our friends and family in lockdown probably helped to prevent some of the dire mental health consequences that many predicted.”
“As these programmes end, we need to look out for signs that people are becoming disconnected from community. If people present with early signs of mental illness, our tool could help GPs and other front-line workers identify and treat the contributing factors.”
Being able to measure and monitor social exclusion could be a game-changer in fighting the global crisis of mental health problems exacerbated by the difficult journeys we’ve all taken during the pandemic.
Prof Pat McGorry AO, Executive Director and founder of Orygen, said that new tools like the F-SIM will help us manage the growing mental health crisis.
“Early detection and support for people who are struggling with social isolation will save lives,” said Prof McGorry. “Dr Filia’s work also shows how critical housing, relationships, work and education are to positive mental health and reduction of mental ill-health, particularly for young people.”
“We need a much more visionary and holistic national mental health strategy if we are to successfully overcome the damage that COVID and other megatrends have caused to the lives and futures of young Australians.”
This work was supported by a Melbourne Research Fellowship from The University of Melbourne, with the development of the F-SIM supported through an ARC Linkage Grant.
AIMS: A disproportionate number of people with mental ill-health experience social exclusion. Appropriate measurement tools are required to progress opportunities to improve social inclusion. We have developed a novel measure, the Filia Social Inclusion Measure (F-SIM). Here we aimed to present a more concise, easy-to-use form, while retaining its measurement integrity by (i) refining the F-SIM using traditional and contemporary item-reduction techniques; and (ii) testing the psychometric properties of the reduced measure.
METHODS: Five hundred and six participants completed the F-SIM, younger and older groups of people with serious mental illness (including psychosis, mood, anxiety disorders) and same-aged community counterparts. The F-SIM was completed at baseline and 2-week follow-up, alongside other measures (including social inclusion, loneliness). The F-SIM was refined using multidimensional scaling network analysis, confirmatory factor analysis and item response theory. The psychometric evaluation included assessment of dimensionality, internal consistency, test-retest reliability, discriminant ability and construct validity.
RESULTS: The F-SIM was reduced from 135-items to 16; with 4-items in each domain of housing and neighbourhood, finances, employment and education and social participation and relationships. Psychometric properties were sound, including strong internal consistency within domains (all α > 0.85) and excellent overall (α = 0.92). Test-retest reliability was also high (γ = 0.90). Differences between groups were observed; clinical subgroups consistently reported lower levels of social inclusion compared to community counterparts.
CONCLUSIONS: The F-SIM16 is a sound, reliable, brief self-report measure of social inclusion suitable for use in clinical and research settings. It has the potential to evaluate the effectiveness of interventions, and aid in fostering targeted and personalised needs-based care.