Assessing the effectiveness of social network interventions for adults with a diagnosis of mental health problems: a systematic review and narrative synthesis of impact.

ABSTRACT

BACKGROUND: Social connections have been linked to the genesis and amelioration of mental health problems and thus have potential therapeutic value. PURPOSE: To identify the current evidence base, assess risk of bias and synthesise findings on the effectiveness of social network interventions for people with mental health problems. METHODS: Electronic databases (MEDLINE, Embase, PsycINFO, CINAHL, Cochrane Library, Web of Science, Scopus) and grey literature databases were systematically searched from inception to October 2021 using free text syntax combining synonyms for 'mental health problems' and 'social network interventions'. Articles were eligible for inclusion if they reported data from randomised controlled trials on the effectiveness of interventions designed to improve social networks for adults (18+) with mental health problems. Papers were independently reviewed for inclusion with conflicts resolved through consensus. Included papers were quality assessed and data extracted and synthesized narratively. Risk of bias was assessed using the Cochrane Risk of Bias Tool. RESULTS: Nine studies randomising 2226 participants were included. Four focused on those with a diagnosis of schizophrenia or psychosis, one on major depressive disorder and four included all types of mental health diagnoses. The current evidence base is of unclear quality. However, interventions which focused on supporting social activities appear to hold the most promise for enhancing social networks. Data on cost-effectiveness and research acceptability were limited, but suggest the potential economic feasibility of and acceptability for evaluating these interventions. CONCLUSION: There is emerging evidence that social network interventions can be effective in improving social connections for people with mental health problems. However, further evaluations with robust methodological approaches are required to inform evidence-based recommendations for health services.