Random sampling of alters from networks: A promising direction in egocentric network research

Advancing the Measurement of Social Functioning in Schizophrenia: Applications of Egocentric Social Network Analysis

People with schizophrenia face challenges with forming and maintaining social relationships, often resulting in poor social functioning. Commonly used measures of social functioning provide broad information relating to social relationships, but they do not adequately capture information regarding network structure and characteristics of network members. One method that can assess these more detailed aspects of social networks and provide a more comprehensive understanding of social functioning deficits is egocentric social network analysis (SNA). SNA is a scientific discipline that uses principles of network science and graph theory to analyze social relations quantitatively. Even though some types of SNA have been applied in prior schizophrenia studies, its application as a framework to measure social functioning has been extremely limited. Therefore, this article aims to formally introduce SNA and select quantitative SNA metrics, including measures of network composition, structure, homophily, and centrality, to schizophrenia researchers as novel ways of measuring components of social functioning. To demonstrate the application of SNA, we provide illustrative examples of the SNA metrics and graphical diagrams of social networks for two individuals with schizophrenia.

Diversity, integration, and variability of intergenerational relationships in old age: New insights from personal network research

Relationships between family members from different generations have long been described as a source of solidarity and support in aging populations and, more recently, as a potential risk factor for COVID-19 contagion. Personal or egocentric network research offers a powerful kit of conceptual and methodological tools to study these relationships, but this has not yet been employed to its full potential in the literature. We investigate the heterogeneity, social integration, and individual correlates of intergenerational relationships in old age analyzing highly granular data on the personal networks of 230 older adults (2747 social ties) from a local survey in one of the areas of the world at the forefront of global aging trends (northern Italy). Using information on different layers in broad egocentric networks and on the structure of connectivity among the social contacts of aging people, we propose multiple conceptualizations and measures of intergenerational connectedness. Results show that intergenerational relationships are strongly integrated, but also highly diverse and variable, in older adults' social networks. Different types of intergenerational ties exist in different network layers, with various relational roles, degrees of tie strength, and patterns of association with individual and tie characteristics. We discuss how new and existing personal network data can be leveraged to consider novel questions and hypotheses about intergenerational relationships in contemporary aging families.

Advances and innovations in methods for collecting egocentric network data

This article reviews recent methodological research that bears on the collection of egocentric network data. It begins with background on setting egocentric network boundaries and principal types of instruments that obtain information about such networks. It then discusses innovations in data collection and studies of data quality. The bulk of these address questions about "name generator" instruments that obtain information about the alters and relationships in a subject's network. Among topics receiving substantial attention in recent research are mitigation of respondent burden, interviewer effects, survey mode, and the performance of name generators in longitudinal studies. Potentially fruitful innovations supplement conventional question-and-answer surveys with visual elements that promise to better engage respondents and reduce the demands that name generator-based data collection poses. We close by highlighting both accomplishments of this body of research and some open issues.

Informal Support Networks of Tanzanians With Chronic Diseases: Predictors of Support Provision and Treatment Adherence

Objectives: To examine the role of NCD patients' social ties as informal caregivers and whether receiving their support is associated with engagement in care. Methods: NCD outpatients (N2 = 100) in rural Tanzania completed a cross-sectional questionnaire to characterize the support role of their social ties (N1 = 304). Bivariate analyses explored predictors of social support and whether social support is associated with engagement in care. Results: This study found that 87% of participants had health insurance, yet 25% received financial support for financing healthcare. Patient gender, age and marital status were found to be important predictors of social support, with NCD-related disability and disease severity being predictive to a lesser degree. Monthly receipt of both material and non-material support were associated with increased odds of adherence to prescribed medications. Conclusion: These findings indicate that patients' social ties play an important role in filling the gaps in formal social health protection and incur substantial costs by doing so. The instrumental role of even non-material social support in promoting engagement in care deserves greater attention when developing policies for improving this population's engagement in care.