This summary follows the order in which data appeared in the report. We start with individual personal networks, findings from interviews with organisation leaders and practitioners and insights from two case studies. We have found:
l Three types of personal networks of people with SMI were generated by k-cluster analysis, which we carried out in order to understand heterogeneity within, and similarities between, people in our sample in terms of network characteristics: diverse and active; family and stable; formal and sparse. These incorporated dimensions of people, place and activity, an approach that was broader than measuring social ties alone.
l Only a few factors in our data set explained variance in network type, and the significant factors found could potentially be altered: living alone or not; housing status; formal education; and long-term sickness or disability. These are hard factors to change but deserve attention. Network type differed significantly by diagnosis but, when it was controlled for other factors, diagnosis did not explain variance; though participants with a schizophrenia/psychosis diagnosis had significantly fewer social ties than other diagnostic groups, 42% of this group had diverse and active network types.
l There were some key observations about network types:
¢ Diverse and active networks had higher numbers of people, place and activity connections. Those with these networks had the highest proportion of new connections and the highest network satisfaction. Qualitative analysis found active management of connections, resources and network opportunities but that big was not always better. Diversity and variety could be associated with enhanced personal well-being and more durable networks, but for some people connectedness caused stress and distress. Manageable routines were important and stigma featured prominently; as networks diversified, the potential for mental health discrimination increased.
¢ Family and stable networks had the highest access to social capital and health resources, but lower levels of activity and place connection than diverse and active networks. Participants with these networks spent most of their time at home but tended to live with others. Qualitative analysis found high levels of social support and building blocks for wellness and recovery through family connections; however, such support could restrict access to social capital and well-being resources. Reciprocal relationships were highly valued.
¢ Formal and sparse networks were significantly smaller with lower access to social capital and health resources, poorer functioning and well-being. They were the least active, having fewer friends, family and wider contacts, and practitioner contacts were more dominant. Qualitative analysis found mental illness featured most strongly in these networks framing decisions and experiences. We found agency in some of these networks, despite limited resources, and potential building blocks for recovery; others needed help identifying potential opportunities. Sparse networks were sometimes considered beneficial for supporting individual well-being. Strength was also gained from identities developed away from diagnostic labels and there were signs of resilience and determination to move on from mental illness. These networks also revealed the resentment that some people feel when relying on practitioners to support mental health and well-being.
l Role of practitioners within current networks of people with SMI varied. We found more than one in five participants named a practitioner within their inner circle of emotional closeness and they formed a portion of social contacts in all network types: formal and sparse networks 33%; diverse and active networks 20%; family and stable networks 12%. Practitioners tended to complement rather than replace informal network contacts, and had a role too in larger networks, but did not replace social or health capital where this was missing from informal ties. This was consistent with practitioner accounts that their role was not to provide social support but to encourage clients towards‘taking control’ (IDSW59, occupational therapist) to build networks and recovery:‘we will very much walk alongside someone, you know, I haven’t got the magical key for someone to recover–it’s what their recovery means to them’(IDSW67, team leader).
l We investigated social capital among the study population. The mean social capital score was 14.2, which was higher overall than other studies of mental health social capital, but lower than the general population, and there was variation across network type and between study sites. In the schizophrenia/ psychosis group it was 11.6, in the bipolar group 16.6. We found social capital and health resources to be provided primarily by close informal ties such as family and friends and less so from wider and practitioner contacts overall, although they were more prominent in networks lacking informal social support. Importantly, those who lacked family and friends had lower resources overall. We noted that connections to activities including employment and place were important providing gateways to social ties.
l The social networks in our study population had a mean of 19.9 contacts, ranging from 5 to 64 contacts. However, formal and sparse networks had only 12.4 contacts on average. Our data suggest it was the type of relationship (close relationships) rather than the number which was most important for resource exchange.
l The qualitative interviews helped us to explore heterogeneity within the study population. We found individual agency across all network types and surface tensions, including relationships with
practitioners or families; dealing with the impact of stigma; and employment and financial frustrations. The value of connectedness, countering the risk of isolation and loneliness, within personal networks for supporting recovery was evident, shaping identity, providing meaning to life and sense of
belonging, gaining access to new resources, structuring routines and helping individuals‘move on’in their recovery journey.
l Managing a personal network was a complex interplay of personal and external factors. Evidence showed how relationships, places and activities in networks could be used to build new network connections, and withdrawal was also a strategy. Identities were closely bound to activities and roles. Participants acknowledged their own responsibility to develop their networks– ‘it is down to me’ (Eleanor, SUSW38);‘It’s all down to me’(Neil, SUSW26)–and it was also evident that practitioners have an important role in assisting the process.
l Networks in London showed more bridging capital properties, with higher numbers of wider contacts and access to more diverse relationships and place types. These networks had fewer family contacts and lower social capital.
l Networks in the SW showed more features of bonding capital, with close family and friend ties and dense interconnected lives. Challenges for practitioners lay in working with individuals who had networks where family ties were negative or absent.
l Service providers were keen to promote a recovery-focused approach but we found a distance
between recovery policy and practice. In particular, the social aspects of supporting SMI get overlooked in the health-care system. In a demanding and changing context, strategic multiagency collaboration was seen as crucial; however, we found limited organisational partnerships or collaborations. l Health-care and third-sector practitioners, including GPs and psychiatrists, recognised social factors
were important in recovery but reported system-level barriers (workload, administrative bureaucracy, limited contact time with clients) in addressing these issues. Skilled care co-ordinators acknowledged the importance of network development, and many reported they used to do more in past roles, but currently did not believe they had enough time to focus sufficiently on‘the social’.
l We suggest the CHN approach provides a useful‘way in’to working with people with SMI to develop personal networks, emphasising meaningful people, places and activities. Using a person-centred networking approach is supportive of recovery-focused practice in that it helps to identify varying levels of agency in people with SMI, from limited engagement to active evaluative and future-forming strategies, as well as addressing barriers to change.
Discussion
The CHN study argues that network development should be seen as an integral part of recovery for people with SMI, through encouraging increased connections and engagement in meaningful activities.8 Working within an individual’s personal network could help services to emphasise a person-centred and strength-focused approach that the recovery approach advocates.41,42The importance of employment for people with SMI245was supported in our data, with those in employment having increased social capital. Those working tended to have diverse and active networks, and this included people with schizophrenia/ psychosis. Research has found that people with SMI, and particularly schizophrenia, tend to have low rates of employment.12Our data showed that any activities leading towards work (volunteering, education, part-time or full-time work), which meant people were not categorised as long-term sick or disabled, were beneficial for building diverse networks which helped build social capital.
We found evidence that social networks for this population were larger, more diverse and more socially integrated today than those found in the TAPS study following deinstitutionalisation policies of community care in the 1990s.3–5However, many of our participants remained isolated in formal and sparse networks with low activity levels and our population overall had lower perceived social support than in the general population.245There is a serious concern that selection bias, likely to have occurred as part of our low recruitment rates, might mean that the population we studied was more connected than an average population of individuals with SMI.
Mapping the structure of networks has allowed us to understand how social capital and health resources were accessed. We found networks with both bonding117and bridging118capital. It seemed that a mixture of each was healthiest; our diverse and active, and family and stable networks had some elements of both. Our social capital scores were slightly higher than other SMI populations198but lower than the general population.123Lower access to resources may be a vulnerability factor for mental ill-health, or a result of social withdrawal due to mental illness, or the relationship may work in both directions;123our study cannot draw any conclusions on the direction of observed relationships. However, access to resources was important for the provision of support and had wider benefits, such as helping people attain goals such as gaining employment through informal contacts.246Our data suggested more needed to be done to help individuals build their social capital.
The qualitative insights we present highlight the importance of understanding the meaning of network characteristics51and show how networks were often managed through agency of individuals and others,80 which also applied to networks we have described as formal and sparse. The level of agency that people could draw on varied, underlining the heterogeneity of this population. Networks were actively managed in terms of segregation of components, removal of negative ties and mental health disclosure, the latter linking to the impact of mental health stigma.32,227Network configuration also seemed to reflect what was coherent and manageable for the individual.47Understanding why networks are the way they were, without an assumption that they need to stay that way, may not always reveal new information for the practitioner but visual network mapping may offer new ways of conversing and understanding the meaning of connections, to plan goals holistically. We suggest the systematic collation of network data would provide a useful framework for planning interventions and setting person-centred outcomes.
Our population has poorer well-being202and functioning201than the general population, while our limited data on hospitalisation for physical health issues reflects the poor physical health of this population, and the need for greater attention on the part of services to improve it.58We heard varying views from participants about antipsychotic medication: it kept mental health symptoms stable and allowed networks to be (re)built; conversely the side effects of medication could make maintaining active networks difficult. The breadth of physical activities and interests found in our activity data suggests how this might be achieved: supporting individuals to increase engagement in activities of interest to them, as well as identifying local community spaces where these activities can be engaged in, while addressing potential barriers, facilitates greater social contact and connectedness, and enhances personal well-being.
Finally, we believe our study’s approach and findings support current government mental health policy and theNo Health without Mental Healthstrategy.30,40Our data were closely aligned to the objective in this strategy that people with mental illness should have a‘greater ability to manage their own lives, stronger social relationships, a greater sense of purpose, the skills they need for living and working, improved chances in education, better employment rates and a suitable and stable place to live’(p. 21).30A modified CHN approach offers potential insights into how to meet these policy aims, addressing inequalities in mental health, physical health, stigma, social inclusion and quality of life for people with SMI.