Social group memberships protect against future depression, alleviate depression symptoms and prevent depression relapse
Introduction
Considerable research points to strong and consistent relationships between social connectedness and depression. For example, in a series of studies, Cacioppo et al. (Cacioppo et al., 2009, Cacioppo et al., 2010, Cacioppo et al., 2006) have demonstrated that perceived social isolation is a strong longitudinal predictor of depressive symptomatology within general community samples, even when controlling for an array of demographic and social factors that might account for such a link. Furthermore, low social support predicts poor response to depression treatment and early drop-out (Trivedi, Morris, Pan, Grannemann, & Rush, 2005) and low social functioning increases the risk of relapse (Backs-Dermott et al., 2010, George et al., 1989, Paykel et al., 1980). There is also evidence that interventions aimed at increasing social interaction can reduce depression symptoms (Cattan et al., 2005, Perese and Wolf, 2005). The association between social isolation and depression has proved to be robust, despite considerable variation in the measures that researchers use (e.g., assessing a person's number of friends, intensity of social activity, perceived loneliness; Harpham et al., 2002, Kikuchi and Coleman, 2012).
Disappointingly, however, this evidence has had little impact on the clinical practice of health professionals. General practitioners rarely question patients about their social group memberships and typically do not advise them to join more groups. Similarly, psychologists do not routinely prioritize efforts to increase patients' social support. Unfortunately too, prevailing treatments are only moderately successful in ameliorating depression (Elkin et al., 1995).
A recognized weakness of current treatment is its general failure to prevent relapse (Shea et al., 1992), as the lifetime risk of experiencing another episode of depression exceeds 80 per cent (Judd, 1997). Even among patients who receive the gold-standard treatment — comprising a combination of antidepressant medication and cognitive-behavioural therapy — 25 per cent are expected to relapse within two years (Fava, Rafanelli, Grandi, Conti, & Belluardo, 1998). Partly as a result of this, depression remains the leading cause of disability worldwide (World Health Organisation, 2012).
Clearly the gold standard can be improved, and drawing on insights from social connectedness research may provide the critical perspective needed to optimize treatment outcomes. But to do so, practitioners must be convinced of the relevance of such research. Evidence of the negative correlation between social connectedness and depression in largely non-depressed community samples may not be particularly relevant to healthcare practitioners, who work in primary healthcare environments with patients experiencing acute symptoms. There is also a need for evidence of the curative, and not only the preventative, capacity of social group membership. Put simply, can an individual who is already clinically depressed and socially isolated benefit from enhanced social connectedness? Or is it too late?
The present research addresses these questions by directly comparing the relative strength of the association between social connectedness and depression in a clinically depressed sample relative to a non-depressed sample. In doing so, it addresses a significant gap in the literature by examining the benefits of social connectedness for individuals both with and without clinical depression (as established by means of a conservative cut-off).
Importantly too, the present study addresses problems in the conceptualization of social connectedness; operationalizing this as the number of social group memberships that an individual reports that they have. This choice of measure is largely informed by research in the social identity tradition which argues that people's group memberships are an important component of their sense of self (Tajfel and Turner, 1979, Turner et al., 1987, Turner et al., 1994), and that group memberships are an important determinant of social behaviour (Levine et al., 2005, Platow et al., 2011, Platow et al., 2007).
Speaking to the importance of social identity for issues of health, a growing body of research has shown that multiple group memberships can become the basis of a ‘social cure’ (after Haslam et al., 2009, Jetten et al., 2012) by playing a protective role in recovery from a range of medical conditions, including stroke (Haslam et al., 2008) and brain injury (Jones et al., 2012). Particularly relevant to the present study is evidence from a series of small-sample survey and experimental studies (e.g., Gleibs et al., 2011, Haslam and Reicher, 2006) which shows that group membership, and the sense of social identification derived from this, is a strong predictor of depressive symptoms (Cruwys, Haslam, Dingle, Haslam, & Jetten, 2013) and a better predictor than social contact alone (Sani, Herrera, Wakefield, Boroch, & Gulyas, 2012).
As such, the benefits of social group membership are not reducible to the physical opportunities for social interaction they afford, but also stem from their capacity to furnish individuals with a more abstract sense of shared identity with others. Partly because of this, group memberships serve as instantiations of social connectedness that are at the same time both more concrete and more malleable than many other connectedness-related constructs (e.g., social support or loneliness). Accordingly, to the extent that they have been implicated in depression, group memberships seem likely to serve as a useful and realistic target for remedial intervention.
Section snippets
The present research
The aim of the present research was to explore the potential benefits of social group membership for both addressing current depression and preventing future depression. To do this, we drew on data collected for the English Longitudinal Study of Ageing (Banks et al., 2012, Marmot et al., 2013). This data source was chosen for three reasons. First, it is a large-scale, nationally representative dataset with a moderately high-risk group (i.e., older adults: Mojtabai & Olfson, 2004). Second, it
Participants
Participants were respondents in the English Longitudinal Study of Ageing (ELSA) who did not have missing data on key variables and waves of interest to the study. The ELSA sample was drawn from households previously responding to the Health Survey for England, with all respondents born before March 1952. The English Longitudinal Study of Ageing commenced in 2002–2003, constituting Wave 1, with respondents invited to participate every two years. The most recent release of data was collected in
Results
In order to test Hypothesis 1 a multiple regression analysis was conducted for both proximal and distal models. The results of this analysis are presented in Table 3. Note that the proximal model includes Waves 3 (“initial”), 4 (“subsequent”) and 5 (“final”), whereas the distal model includes Waves 2 (“initial”), 3 (“subsequent”) and 5 (“final”). The most recent waves of the dataset were used to ensure equivalency in the dependent variable across the models and to make use of the most
Discussion
This study of the relationship between social group memberships and depression revealed three key findings. First, the number of groups that an individual belongs to is a significant predictor of depression, both when measured across a two-year period (in a proximal model) and when measured across a four-year period (in a distal model). This finding is robust and holds when controlling for demographic variables, subjective health status, initial depression and initial group memberships.
Second,
Conclusion
This study has provided a strong demonstration of the power of social group memberships to protect against the development of depression, to alleviate symptoms of depression and to reduce the risk of depression relapse. Using a large sample of older adults, we tested the effects of social group membership on depression controlling for many covariates as well as initial measurement of number of groups and depression. Understood in the context of the theoretical model that they test and support,
Acknowledgement
The present data were made available through the UK Data Archive (UKDA). ELSA was developed by a team of researchers based at the National Centre for Social Research, University College London and the Institute of Fiscal Studies. The data were collected by the National Centre for Social Research. The funding is provided by the National Institute of Aging in the United States, and a consortium of UK government departments co-ordinated by the Office for National Statistics. The developers and
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