Transitions in Social Network Types over Time among Older Adults

<b><i>Objective:</i></b> Network typology studies have identified heterogeneous types of older adults’ social networks. However, little is known about stability and change in social network types over time. We investigate transitions in social network types among older adults, aged 60 years and older, and factors associated with such transitions. <b><i>Methods:</i></b> We used data on 1,305 older adults, participating in 2 waves of a national, longitudinal survey, conducted in 2016–2017 and 2019, in Singapore. Latent transition analysis identified the distinct types of social networks and their transition patterns between the waves. Multinomial logistic regression examined the association of baseline and change in physical, functional, and mental health and baseline sociodemographic characteristics with network transitions into more diverse or less diverse types. <b><i>Results:</i></b> We found 5 social network types at both waves, representing the most to the least diverse types – diverse, unmarried and diverse, extended family, immediate family, and restricted. Between waves, about 57% of respondents retained their social network type, whereas 24% transitioned into more diverse types and 19% into less diverse types. Those who were older and less educated and those with worsening functional and mental health were more likely to transition into less diverse types versus remaining in the same type. <b><i>Discussion:</i></b> The findings capture the dynamics in social network composition among older adults in the contemporary aging society. We highlight sociodemographic and health disparities contributing to later life social network diversity.

Social network typologies of older people: A cross-national literature review

This article presents an issue narrative non-systematic review about social network typologies for the older population. We analysed 18 studies with large samples from 14 countries worldwide. The position of family ties, network composition, network size, frequency of contacts and community participation are central to social network typologization in the older population. Restricted and diverse networks emerged in typologies associated, respectively, with less and more effective social support features, and are good predictors of well-being, health, mental health, social support and social participation. Cross-nationally, there is an unequal distribution of the construction of network typologies. The different typologies, that should be culturally grounded, provide guidelines to intervention planning, inform social service providers about emerging needs and contribute to social policy debate.

Coalition-Committees as Network Interventions: Baseline Network Composition in Context of Childhood Obesity Prevention Interventions

Community coalitions can address local issues with deep, historic, and contextual understanding that enables customized implementation of evidence-based strategies. The individuals within the coalition, their partnerships, and the social context is likely an important component of unraveling the challenges of implementation so interventions reach people in need. We focus on the relevance of baseline coalition-committee network (CCN), the networks of purposely formed subcommittees within community coalitions, structure as one of the moderating, theoretical links between community coalition social networks and intervention success. We explore the baseline composition and characteristics of five CCNs at the beginning of childhood obesity prevention interventions. Using a combination of social network, multidimensional scaling, and correspondence analyses, we examine the structure and heterogeneity of five CCNs, each consisting of a core group of stakeholders in the coalition and sometimes the broader community itself. Cross-sectional analyses are used to examine the composition of coalition-committees related to network density, centralization, hierarchy, and coalition demographics and characteristics. Results indicate that CCNs are patterned in their structure and characteristics, and we discuss whether adjustments to childhood obesity prevention interventions according to baseline structure and characteristics could be advantageous for intervention implementation. Together, these findings can inform future longitudinal investigations into CCN network structure.

Forecasting under Uncertainty: How Network Composition Shapes Future-Oriented Cognition

Future migration is central to contemporary politics, but we know little of how citizens and policy-makers perceive and predict migratory trends. I analyze migration forecasting in a representative sample of the population of France, using survey data and administrative records to document differences in the accuracy of forecasting among groups of individuals. The article takes an interdisciplinary approach to future-oriented thinking, conceiving it as a distributed cognitive process, and showing that educational attainment and migratory background shape one’s ability to predict short-term trends. My analysis stresses the importance of accounting for sociodemographic characteristics and social networks in forecasting: I show that social diversity can improve predictions and extend studies based on the Delphi methodology by discussing the relevant expertise to forecast in different realms.

Myosin-driven actin-microtubule networks exhibit self-organized contractile dynamics

The cytoskeleton is a dynamic network of proteins, including actin, microtubules, and their associated motor proteins, that enables essential cellular processes such as motility, division, and growth. While actomyosin networks are extensively studied, how interactions between actin and microtubules, ubiquitous in the cytoskeleton, influence actomyosin activity remains an open question. Here, we create a network of co-entangled actin and microtubules driven by myosin II. We combine dynamic differential microscopy, particle image velocimetry, and particle tracking to show that both actin and microtubules undergo ballistic contraction with unexpectedly indistinguishable characteristics. This contractility is distinct from faster disordered motion and rupturing that active actin networks exhibit. Our results suggest that microtubules enable self-organized myosin-driven contraction by providing flexural rigidity and enhanced connectivity to actin networks. Beyond the immediate relevance to cytoskeletal dynamics, our results shed light on the design of active materials that can be precisely tuned by the network composition.

Changes in Personal Social Networks across Individuals Leaving Their Street Gang: Just What Are Youth Leaving Behind?

Despite a small but growing literature on gang disengagement and desistance, little is known about how social networks and changes in networks correspond to self-reported changes in street gang membership over time. The current study describes the personal or “ego” network composition of 228 street gang members in two east coast cities in the United States. The study highlights changes in personal network composition associated with changes in gang membership over two waves of survey data, describing notable differences between those who reported leaving their gang and fully disengaging from their gang associates, and those who reported leaving but still participate and hang out with their gang friends. Results show some positive changes (i.e., reductions) in criminal behavior and many changes toward an increase in prosocial relationships for those who fully disengaged from their street gang, versus limited changes in both criminal behavior and network composition over time for those who reported leaving but remained engaged with their gang. The findings suggest that gang intervention programs that increase access to or support building prosocial relationships may assist the gang disengagement process and ultimately buoy desistance from crime. The study also has implications for theorizing about gang and crime desistance, in that the role of social ties should take a more central role.

Order effects in PTSD network analysis: important implications for diagnostic conceptualization, treatment refinement, and research

Background For decades confirmatory factor analysis (CFA) has been the preeminent method to study the underlying structure of posttraumatic stress disorder (PTSD); however, methodological limitations of CFA have led to the emergence of other analytic approaches. In particular, network analysis has become a gold standard to investigate the structure and relationships between PTSD symptoms. A key methodological limitation, however, which has significant clinical implications, is the lack of data on the potential impact of item order effects on the conclusions reached through network analyses. Methods The current study, involving a large sample (N = 5055) of active duty army soldiers following deployment to Iraq, assessed the vulnerability of network analyses and prevalence rate to item order effects. This was done by comparing symptom networks of the DSM-IV PTSD checklist items to these same items distributed in random order. Half of the participants rated their symptoms on traditionally ordered items and half the participants rated the same items, but in random order and interspersed between items from other validated scales. Differences in prevalence rate and network composition were examined. Results The prevalence rate differed between the ordered and random item samples. Network analyses using the ordered survey closely replicated the conclusions reached in the existing network analyses literature. However, in the random item survey, network composition differed considerably. Conclusion Order effects appear to have a significant impact on conclusions reached from PTSD network analysis. Prevalence rates were also impacted by order effects. These findings have important diagnostic and clinical treatment implications.