An exploration of the relationship of social networks with depression among older adults : a prospective study : a thesis presented in partial fulfilment of the requirements for the degree of Doctorate in Clinical Psychology at Massey University, Albany, New Zealand

Research has highlighted social integration as a protective factor against depression among older adults. This thesis aims to clarify whether specific features of social networks are particularly important, the effect of perceived connectedness on the relationship between structural social integration and depressive symptoms, and whether social integration is a longitudinal predictor of depressive symptoms among older adults. The thesis also describes the social networks and prevalence of depression among older people in New Zealand, including older Māori, of which there is limited availability of existing research. The current study utilised data taken at three waves of measurement from 3594 community-dwelling older people living in New Zealand including 172 older Māori. The relationship between components of social network structure and depression were compared using standard statistical techniques. Consistent with previous research, contact with non-family social ties was significantly and negatively associated with depressive symptoms whereas contact with family was not significantly correlated. Unlike other studies, social network size significantly predicted depressive symptoms. A series of hierarchical multivariate linear regression models indicated that, after controlling for demographics and health variables such as age, functional ability and exercise, structural integration and perceived connectedness uniquely explained between 1 and 4% of the variability in depressive symptoms. According to a multilevel model for change, social integration did not predict different trajectories of depressive symptoms over 36-months. Perceived connectedness was found to mediate 29% of the effect of structural social integration on depressive symptoms. Results highlight the relative importance of perceived connectedness in older adults’ depression. Composite measures of structural social integration in depression research with older people are indicated with the exception of items related to family ties and marital status. Measures of social integration, especially objective measures based on social network structure, may not be reliable indicators of depression risk. These findings highlight a need for further investigation into the efficacy of social interventions, especially targeting non-family ties and perceived connectedness

Digital Interventions for Mental Disorders:Key Features, Efficacy, and Potential for Artificial Intelligence Applications

Mental disorders are highly prevalent and often remain untreated. Many limitations of conventional face-to-face psychological interventions could potentially be overcome through Internet-based and mobile-based interventions (IMIs). This chapter introduces core features of IMIs, describes areas of application, presents evidence on the efficacy of IMIs as well as potential effect mechanisms, and delineates how Artificial Intelligence combined with IMIs may improve current practices in the prevention and treatment of mental disorders in adults. Meta-analyses of randomized controlled trials clearly show that therapist-guided IMIs can be highly effective for a broad range of mental health problems. Whether the effects of unguided IMIs are also clinically relevant, particularly under routine care conditions, is less clear. First studies on IMIs for the prevention of mental disorders have shown promising results. Despite limitations and challenges, IMIs are increasingly implemented into routine care worldwide. IMIs are also well suited for applications of Artificial Intelligence and Machine Learning, which provides ample opportunities to improve the identification and treatment of mental disorders. Together with methodological innovations, these approaches may also deepen our understanding of how psychological interventions work, and why. Ethical and professional restraints as well as potential contraindications of IMIs, however, should also be considered. In sum, IMIs have a high potential for improving the prevention and treatment of mental health disorders across various indications, settings, and populations. Therefore, implementing IMIs into routine care as both adjunct and alternative to face-to-face treatment is highly desirable. Technological advancements may further enhance the variability and flexibility of IMIs, and thus even further increase their impact in people’s lives in the future