Can Social Resources Explain the Limitations in the Activities of Daily Living of Older Adults Classified by the Phenotype of Physical Frailty?

The objective is to investigate the mediating roles of living alone and personal network in the relationship between physical frailty and activities of daily living (ADL) limitations among older adults. 2271 individuals were classified as vulnerable (pre-frail or frail) or robust. Mediating variables were living alone and personal network. Katz Index and Lawton-Brody scale were used to assess ADL. Mediating effects were analyzed with beta coefficients from linear regression models using the bootstrapping method. Mediation analysis showed significant mediating effects of living alone (β = .011; 95% CI = .004; .018) and personal network (β = .005; 95% CI = .001; .010) on the relationship between physical frailty and basic ADL limitations. Mediation effects of living alone and personal network on the relationship between physical frailty and instrumental ADL limitations were β = −.074 (95% CI=−.101; −.046) and β = −.044 (95% CI = −.076; −.020), respectively. Physically vulnerable older adults who lived alone or had poor personal network were more dependent on basic and instrumental ADL.

Relational Agency of University Teachers of Chinese as a Second Language: A Personal Network Perspective

Relational agency is pivotal for understanding how language teachers seek and utilize relational resources in different contexts and grow to be agents of change amid various educational challenges. This study explored how three university teachers of Chinese as a second language (CSL) enacted their relational agency to enhance their research capacity and sustain their professional development. Data on their personal network development was collected through concentric circle interviews, life-history interviews and written reflections over three months. Thematic analysis was adopted for iterative coding and interpretation of the data. The findings revealed that teachers’ personal networks provided them with value guidance, emotional support and academic support, which exerted differential levels of impact on them to make agentic choices and actions. The study suggests that personal network analysis may serve as a suitable theoretical lens to achieve a multi-layered understanding of relational agency. The study also calls for more efforts to create learning opportunities and spaces in the relational context for teachers to build their career as agentic academics in language teacher education and development programs.

Revisiting Small- and Medium-Sized Enterprises’ Innovation and Resilience during COVID-19: The Tourism Sector

Every day, companies are exposed to various risks arising from their environment, and small and medium enterprises (SMEs) are the most affected. This study emphasizes innovation and resilience as the starting points to understand how SMEs are influenced by external factors which are independent of the managers’ will. To date, we have seen several extreme factors that have conditioned businesses and entrepreneurs of these types of companies, such as the financial crisis of 2008. However, last year, in 2020, we saw the beginning of a worldwide pandemic: COVID-19. Thus, this research seeks to understand the extent to which this pandemic influenced the resilience and innovation of SMEs in the tourism area. Thus, eight hypotheses were raised based on four independent variables: access to finance, risk taking, working conditions, and personal network. The study of these variables was developed from an online questionnaire and in-depth interviews. After analyzing the results, it is possible to infer that the COVID-19 pandemic resulted in consequences never observed in previous crises, to such an extent that the study showed that: (1) a company’s network positively influences its resilience; (2) risk taking influences innovation and resilience of these SMEs.

Social reference cues can reduce misinformation sharing behaviour on social media

Misinformation on social media is a key challenge to effective and timely public health responses. Existing mitigation measures include flagging misinformation or providing links to correct information but have not yet targeted social processes. Here, we examine whether providing balanced social reference cues in addition to flagging misinformation leads to reductions in sharing behavior. In 3 field experiments (N=817, N=322, and N=278) on Twitter, we show that highlighting which content others within the personal network share and, more importantly, not share combined with misinformation flags significantly and meaningfully reduces the amount of misinformation shared (Study 1-3). We show that this reduction is driven by change in injunctive social norms (Study 2) but not social identity (Study 3). Social reference cues, combined with misinformation flags, are feasible and scalable means to effectively curb sharing misinformation on social media.

Structural Embeddedness in Transnational Social Fields: Personal Networks, International (Im)Mobilities, and the Migratory Capital Paradox

In this article we focus on individuals’ structural embeddedness in transnational social fields (TSFs) and examine how this is related to patterns of international mobility. The main argument is that the structure of TSFs matters for (im)mobility trajectories, and thus all actors (migrants, non‐migrants, and returnees) need to be examined as a whole to obtain a deeper understanding of the role of social networks in processes of transnational mobility. Taking the case of Romanian migrants in Spain as a TSF connecting their place of origin (Dâmbovița in Romania) with their destination (Castelló in Spain), we analyze survey data for 303 migrants, non‐migrants, and returnees, sampled through an RDS‐like binational link‐tracing design. We then categorize types of personal network using an international mobility scale to assess the degree of structural embeddedness in the TSF. An important contribution is the rigorous operationalization of TSF and assessment of the level of migratory capital of each individual. Our results reveal that migratory capital is not always linked positively with high mobility patterns and that its role is strongly related to the overall composition and structure of the TSF.

When Spatial Dimension Matters: Comparing Personal Network Characteristics in Different Segregated Areas

Living in segregated areas with concentrated neighbourhood poverty negatively affects the quality of life, including the availability of local jobs, access to services, and supportive social relationships. However, even with similar neighbourhood poverty levels, the degree and structure of spatial separation vary markedly between such areas. We expected that the level of spatial segregation aggravates the social exclusion of its inhabitants by negatively affecting their social capital. To test this hypothesis, we identified three low‐income neighbourhoods with high poverty rates (78%) in a medium‐sized town in Hungary, with different levels of integration in the city (based on characteristics such as the degree of spatial separation, infrastructure, and availability of services). The three neighbourhoods were located in two areas of differing degrees of integration in the fabric of the city: fully integrated, semi‐integrated (integrated into the surrounding residential area but isolated from the city), and non‐integrated. 69% of the 394 households in these areas were represented in our sample (one respondent per household). We interviewed respondents regarding the size and composition of their personal networks. Our results, which also distinguished between Roma and non‐Roma inhabitants, showed that those living in the spatially more integrated area not only have the largest and most diverse networks but seem to have a strong, “bonding‐based” cohesive community network as well. Even the non‐Roma who live there have ethnically heterogeneous—in other words—Roma network members. The disintegrated area, on the other hand, is characterised by both spatial and social isolation.

A Privilege not a Choice: Transnational Support Networks of Asylum Seekers and Expatriates

The article explores how different factors shape migrants’ transnational social fields and support networks through a comparative study of two different groups of migrants—asylum seekers and expatriates—in Budapest, Hungary. To do so, the study employs a parallel mixed‐methods social network design by combining personal network data with qualitative data based on interviews and ethnographic fieldwork with thirty‐three migrants in the aftermath of the 2015 refugee crisis. The article presents three key findings: First, it finds that asylum seekers’ and expatriates’ networks differ on several key characteristics, as asylum seekers’ close personal networks are less efficient, smaller in size, and show a remarkable lack of friendship and transnational support ties. Second, it also finds that asylum seekers have limited access to social support and, especially so, to financial and emotional support. Lastly, using multi‐level models, the article also demonstrates how migrants’ legal status and the transnationality of their support ties affect their access to financial support, as well as how their gender and legal status shape their access to emotional support. These findings illustrate how migrants’ individual opportunity structures affect their transnational practices alongside their access to social support, while also highlighting the importance of several individual and contextual factors which contribute to the diverse integration processes of migrants.

Personal Network Inference Unveils Heterogeneous Immune Response Patterns to Viral Infection in Children with Acute Wheezing

Human rhinovirus (RV)-induced exacerbations of asthma and wheeze are a major cause of emergency room presentations and hospital admissions among children. Previous studies have shown that immune response patterns during these exacerbations are heterogeneous and are characterized by the presence or absence of robust interferon responses. Molecular phenotypes of asthma are usually identified by cluster analysis of gene expression levels. This approach however is limited, since genes do not exist in isolation, but rather work together in networks. Here, we employed personal network inference to characterize exacerbation response patterns and unveil molecular phenotypes based on variations in network structure. We found that personal gene network patterns were dominated by two major network structures, consisting of interferon-response versus FCER1G-associated networks. Cluster analysis of these structures divided children into subgroups, differing in the prevalence of atopy but not RV species. These network structures were also observed in an independent cohort of children with virus-induced asthma exacerbations sampled over a time course, where we showed that the FCER1G-associated networks were mainly observed at late time points (days four–six) during the acute illness. The ratio of interferon- and FCER1G-associated gene network responses was able to predict recurrence, with low interferon being associated with increased risk of readmission. These findings demonstrate the applicability of personal network inference for biomarker discovery and therapeutic target identification in the context of acute asthma which focuses on variations in network structure.