The structure of social support: a multilevel analysis of the personal networks of people with severe mental disorders.

BACKGROUND: For psychiatric service users suffering from severe mental disorders, the social support provided by personal social networks is essential for living a meaningful life within the community. However, the importance of the support received depend on the relations between the providers of social support. Yet this hasn't been addressed in the literature so far for people with severe mental disorders. This article seeks to investigate how characteristics of service users with severe mental disorders, their social contacts, and the pattern of relationships between those contacts influence the distribution and provision of social support to people with severe mental disorders. METHODS: We collected personal network data relating to 380 psychiatric service users from a random sample of health care providers in Belgium. We computed various measures of the structure of those networks and of the position of support persons within those networks. We conducted a multilevel analysis of the importance of the support provided by each support persons. RESULTS: The results show that the more central a support person was in the network of a service user, the more important his or her support was considered to be by the service user. Also, the denser the network in which a support person was embedded, the less important was the support he or she offers, but only for hospitalised service users. CONCLUSION: These finding highlight the collective dimension of social support. We discuss the implications for the organisation of mental health care.

Implementation of a computer-assisted face-to-face intervention for mapping the social support networks of patients with severe mental illness in routine clinical practice: Analysis of the appropriateness and acceptability of the intervention.

BACKGROUND: Social support is a key dimension of personal recovery for patients with severe mental disorders. Although clinicians and health professionals should monitor the social support resources of patients in order to provide effective treatment, no specific tool or intervention exist for that purpose. Egonet is a computer-assisted intervention for health and social services that enables the mapping, assessment and fostering of patients' social support networks. AIMS: This paper describes the intervention and evaluates the appropriateness and acceptability of its implementation in a clinical setting. METHOD: We described the computer-assisted intervention. We used a questionnaire to assess how appropriate and acceptable clinicians found a preliminary version to be. We also collected patients' level of satisfaction with their social support networks before and after the intervention and carried out qualitative interviews. RESULTS: Egonet is made up of four components: (1) a computer-assisted interview for mapping social networks, (2) a remote data server, (3) a data-mining module and (4) a customisable reporting tool. Egonet was implemented for 232 patients by 91 clinicians from five services. The intervention was perceived by clinicians as appropriate and useful for clinical practice, although it was noted that considerable effort was required to obtain its benefits. Patients were slightly more satisfied with their social support after the intervention than before, and expressed the opinion that more attention should be paid to the social support network. CONCLUSIONS: EGONET is appropriate and acceptable for use in work related to the social support networks of patients with psychiatric disorders.

The personal social network of psychiatric service users.

BACKGROUND: For psychiatric service users, the personal social network offers resources such as behavioural guidance, social support, and coherence of care delivery. So far, most research on the subject has assessed the availability of these resources using size and composition measures. However, the availability of network resources also depends on the cohesion of the relationships between network members, a topic that is rarely addressed in the literature. AIMS: In this article, we aim to describe the cohesion of psychiatric service users' networks. METHOD: We carried out a personal network survey and collected data on the social networks of 380 service users recruited in outpatient and inpatient services in Belgium. We used an ego-network mapping technique. The data were analysed using several structural metrics describing size, composition, and cohesion. We carried out analysis of variance (ANOVA) in relation to residential status, level of education, psychiatric history, and psychosocial functioning and analysed three cohesion indicators (density, fragmentation, and centralisation) with regression analyses. RESULTS: Personal social networks were small and not very cohesive. Most were composed of a dense subgroup as well as several isolated network members. The analyses revealed that highly educated psychiatric service users had more fragmented networks, while users living in independent accommodation had less dense networks. Density and fragmentation were not associated with the severity of psychosocial functioning, whereas centralisation was. CONCLUSIONS: The low level of cohesion may indicate that service users aim to access multiple and diverse social resources and that better-off service users are more successful at doing so. On the whole, however, these personal social networks were fragile, because they contained a high number of isolated network members. Finally, it could be beneficial for professionals to pay special attention to the central persons within the networks of psychiatric service users.

Social support network and continuity of care: an ego-network study of psychiatric service users.

PURPOSE: For severely mentally ill (SMI) users, continuity of care requires consistency between the supports provided by the members of their social support network. However, we know little about their network cohesion and its association with continuity of care. We set out to investigate this association and hypothesised that it would depend on the severity of the user's situation and on his/her living arrangements. METHODS: We conducted face-to-face interviews with 380 SMI users recruited in outpatient and inpatient mental health services in three areas in Belgium. Data regarding users' social networks were collected using an ego-network mapping technique and analysed with social network analysis. The cohesion indicators were density (frequency of connections between network members), centralisation (having a small number of central people), and egobetweenness (the user's centrality in his/her own network). Participants' perception of continuity of care was measured by the Alberta Continuity of Services Scale. RESULTS: Results show that cohesion indicators were associated with continuity of care only for users with high-severity problems, regardless of their living arrangements. The numbers of network members, professionals, and services in the network were all negatively associated with continuity of care for all the users. CONCLUSIONS: Satisfactory continuity of care requires fewer professionals or services in a user's network and a dense network for users with the most severe problems. This implies that those providing care must not only be able to increase cohesion within a network, but also to adapt their interventions to support the transition to a different, individualised network structure when severity decreases.