Ce travail traite du réseau social de connaissance des personnes diabétiques et de leurs proches en rapport à l’utilisation des plantes médicinales, dans la localité de Korhogo. Il est question d’analyser le système de transmission des connaissances thérapeutiques traditionnelles du diabète. Ainsi, nous nous sommes proposés d’exposer la perception du malade et de son réseau quant à l’utilisation des plantes, d’identifier l’accessibilité de ces plantes et les méthodes utilisées dans le traitement traditionnel du diabète et enfin de décrire le mode de transmission de ces connaissances thérapeutiques traditionnelles utilisées dans le traitement du diabète. C’est par une approche mixte que nous avons vérifié ces hypothèses. Au terme de cette étude, il ressort que le système de transmission des connaissances thérapeutiques traditionnelles à Korhogo est fonction d’un réseau social qui influence les perceptions des malades quant à l’utilisation des plantes, et ce à travers un mode de transmission informel et pourtant impactant.

From foraging societies to online communities, human social networks exhibit striking structural regularities, characterized by densely connected local communities linked by bridging ties. However, it remains in question how these small-world patterns emerge alongside demographic processes and changes. Here, we provide a baseline investigation into the dynamics of both kin and non-kin social systems in response to the AIDS epidemic in a poorer, rural South African region. We combine multiple datasets to construct population-scale inter-household social networks from 2000 to 2016. Leveraging a quasi-experimental approach, we find that families are more likely to form distant, potentially non-kin ties following a mortality event. Coupled with increases in both network clustering and efficiency among close kin and distant ties, our findings suggest that the observed small-worldness in contemporary societies may be closely tied to the diversity of social connectivity in the wake of key demographic events.

Purpose: Assess how central community health worker (CHW) training institutions in Illinois facilitate access to standardized training opportunities and associated benefits or obscure persistent marginality in training practices.

Methods: A statewide survey asked CHWs (n=450) to name organizations where they received training and questions about their work per national efforts to standardize CHW training. A projected CHW network, with edges inferred from shared trainings, was analyzed for centrality metrics, core-periphery, and community structure. Further analyses removed high degree training institutions prior to projection of the network. Removal of the single highest degree institution resulted in a 72% decrease in network density but a 67% increase in average betweenness. Emergent analyses will use geographic networks to identify spatial clustering and bottlenecks in transportation infrastructure affecting CHWs and compare networks to non-network core-periphery characteristics using survey data.

Contributions: Community health workers are non-clinical agents of health equity, facilitating access to care, navigation of insurance, and addressing social determinants of health in vulnerable communities. Initial findings indicate that structural support of a few highly central training institutions may have generated an artificially large and dense core of CHWs in Illinois, while obscuring functional training communities and gatekeepers. Ongoing analyses will contribute to social network literature by validating or contraindicating the use of unipartite projections of training networks to represent access to core trainings and associated benefits and support training interventions themselves by assessing if and how amplification of core training institutions serves to standardize and unify CHW skills and opportunities across the state.

The rising use of marijuana among young adults has drawn increasing attention from researchers, leading to a surge in studies examining its effects, risks, and patterns of consumption. However, much of this research focuses on marijuana in isolation, overlooking its role within the broader network of substance use. A key question remains unanswered: Is marijuana replacing other drugs, strengthening connections between substances, or creating a more distinct pattern of use? Understanding these shifts is crucial, as substance use rarely occurs in isolation but rather within an interconnected system. Traditional analyses fail to capture these dynamics, highlighting the need for a network-based approach to better inform intervention strategies.

In this study, we used repeated national cross-sectional surveys of university students to examine the evolving structure of drug use networks. Using mixed graphical models, we constructed substance use networks at each time point, analyzing global metrics, such as density, average path length, clustering coefficient, and modularity, to assess shifts in connectivity and community structure. Additionally, we explored node-level measures, including weighted degree, betweenness, closeness, and eigenvector centrality, to determine how patterns of co-use have changed over time. Our primary aim was to assess whether marijuana use has not only increased but also whether its position in the substance use network has shifted, indicating changes in its role within polysubstance patterns.

We used repeated cross-sectional survey data from Colombian university students (2009: n = 7,803; 2012: n = 9,876; 2016: n = 9,805; 2023: n = 11,065), collected by the Colombian government. Mixed Graphical Models were used to estimate conditional dependencies between substances at each time point. Global network metrics (density, average path length, clustering coefficient, modularity) were computed to assess overall connectivity and community structure, while node-level measures (weighted degree, betweenness, closeness, eigenvector centrality) were used to examine marijuana’s changing role within the network. Networks were visualized using ggraph in R.

Descriptive results indicate a decline in lifetime prevalence of alcohol and tobacco use, while the use of ecstasy, tranquilizers, and marijuana has increased. Network analyses reveal that overall connectivity has remained high (density = 0.86–0.89), while the network has become more compact over time, as indicated by a decreasing average path length (from 0.53 in 2009 to 0.36 in 2023). At the substance level, partial correlations indicate that marijuana’s connections with other drugs have strengthened in recent years, reflecting its increasing prevalence. Centrality measures further highlight marijuana’s growing role within the network, even as alcohol and tobacco continue to serve as foundational substances in polysubstance use.

These findings suggest that while the overall substance use network remains highly interconnected, marijuana has become a more integral component of polysubstance patterns. This shift underscores the need for prevention and intervention strategies that account for marijuana’s evolving role in the broader drug use landscape.

The rapid ageing of the population has increased the demand for both healthcare and long-term care, creating an urgent need for caregivers. However, the capacity of the social services to address this issue is limited, making the role of informal caregivers essential. Furthermore, it is evident that informal caregivers require social support to ensure their own wellbeing, fundamental for them to persevere in the caregiving role.

The objectives of the present research, the analysis for which is currently underway, are twofold: first, to explore, using the novel technique qualitative comparative analysis (QCA), how the social networks of informal caregivers affect their wellbeing; second, to highlight how different methodological approaches, namely social network analysis, qualitative methods and QCA, can be combined to obtain in-depth knowledge about the wellbeing of informal caregivers.

The data originate from a nationwide mixed-methods study conducted in Italy and funded by the Recovery and Resilience Plan, which commenced in 2024 and is scheduled to conclude in 2025. The study comprised 30 caregivers, and their social network data were collected through online interviews utilizing a name generator, name interpreter and name interrelator. Information regarding their wellbeing was collected via an online dyadic interview method. The dyads were composed of caregivers and their supporters (e.g. spouses, other relatives or friends). QCA is applied to identify which social network conditions (e.g. size of the social network support, density and reciprocity) affect the wellbeing of informal caregivers.