Modelling animal social networks: New solutions and future directions.

Research Highlight: Ross, C. T., McElreath, R., & Redhead, D. (2023). Modelling animal network data in R using STRAND. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.14021. One of the most important insights in ecology over the past decade has been that the social connections among animals affect a wide range of ecological and evolutionary processes. However, despite over 20 years of study effort on this topic, generating knowledge from data on social associations and interactions remains fraught with problems. Redhead et al. present an R package-STRAND-that extends the current animal social network analysis toolbox in two ways. First, they provide a simple R interfaces to implement generative network models, which are an alternative to regression approaches that draw inference by simulating the data-generating process. Second, they implement these models in a Bayesian framework, allowing uncertainty in the observation process to be carried through to hypothesis testing. STRAND therefore fills an important gap for hypothesis testing using network data. However, major challenges remain, and while STRAND represents an important advance, generating robust results continues to require careful study design, considerations in terms of statistical methods and a plurality of approaches.

Social/Sexual Networks of People Newly Diagnosed with HIV in Ibadan, Nigeria.

Young men who have sex with men (YMSM) in Nigeria are ten times more likely to be living with HIV-1 than other young men. Due to stigma and criminalization of same-sex sexual behavior, YMSM sexual networks are likely to overlap with those of the general population, leading to a generalized HIV-1 epidemic. Due to limited research on social/sexual network dynamics related to HIV-1 in Nigeria, our study focused on YMSM and sought to assess the feasibility and acceptability of collecting social and sexual network data in Network Canvas from individuals newly diagnosed with HIV-1 in Ibadan, Nigeria. The Network Canvas software was piloted at three sites in Ibadan, Nigeria to collect social/sexual network data from 151 individuals newly diagnosed with HIV-1. Our study sample included 37.7% YMSM; participants reported a mean of 2.6 social alters and 2.6 sexual alters. From the 151 egos and 634 alters, 85 potential unique individuals (194 total) were identified; 65 egos/alters were collapsed into 25 unique individuals. Our success collecting network data from individuals newly diagnosed with HIV-1 in Ibadan demonstrates clear feasibility and acceptability of the approach and the use of Network Canvas to capture and manage these data.

Social Network Characteristics Associated with More Frequent HIV and STI Prevention Conversations: The N2 Cohort Study in Chicago.

Black cisgender sexually minoritized men (SMM) and transgender women (TW) are subgroups at highest risk of HIV and sexually transmitted infections (STIs) in the US. We sought to identify factors facilitating continued conversations - social reinforcement - surrounding HIV/STI prevention among this subgroup. Participants were recruited in Chicago from 2018 to 2019 from community health spaces. Participants provided information about themselves (level 2) and ⩽5 confidants (level 1). We used multinomial multilevel modeling to identify associations with HIV/STI prevention conversation frequency. A total of 370 participants provided information on 987 confidants (mean = 2.6). We found significantly positive associations between having biweekly or more often HIV/STI prevention conversations and a confidant being a kin family member, older by 15 years or more, racially homophilous, and emotionally close. Future interventions should harness social networks by including components that consider racial homophily, respect for elders, and strong ties, in addition to applying kin family systems interventions approaches and decreasing stigma surrounding HIV/STIs.

Governance of the wildlife trade and the prevention of emerging zoonoses: a mixed methods network analysis of transnational organisations, silos, and power dynamics.

INTRODUCTION: The wildlife trade is an important arena for intervention in the prevention of emerging zoonoses, and leading organisations have advocated for more collaborative, multi-sectoral approaches to governance in this area. The aim of this study is to characterise the structure and function of the network of transnational organisations that interact around the governance of wildlife trade for the prevention of emerging zoonoses, and to assess these network characteristics in terms of how they might support or undermine progress on these issues. METHODS: This study used a mixed methods social network analysis of transnational organisations. Data were collected between May 2021 and September 2022. Participants were representatives of transnational organisations involved in the governance of wildlife trade and the prevention of emerging zoonoses. An initial seed sample of participants was purposively recruited through professional networks, and snowball sampling was used to identify additional participants. Quantitative data were collected through an online network survey. Measures of centrality (degree, closeness, and betweenness) were calculated and the network's largest clique was identified and characterised. To understand the extent to which organisations were connected across sectors, homophily by sector was assessed using exponential random graph modelling. Qualitative data were collected through semi-structured interviews. The findings from the quantitative analysis informed the focus of the qualitative analysis. Qualitative data were explored using thematic analysis. RESULTS: Thirty-seven participants completed the network survey and 17 key informants participated in semi-structured interviews. A total of 69 organisations were identified as belonging to this network. Organisations spanned the animal, human, and environmental health sectors, among others including trade, food and agriculture, and crime. Organisation types included inter-governmental organisations, non-governmental organisations, treaty secretariats, research institutions, and network organisations. Participants emphasised the highly inter-sectoral nature of this topic and the importance of inter-sectoral work, and connections were present across existing sectors. However, there were many barriers to effective interaction, particularly conflicting goals and agendas. Power dynamics also shaped relationships between actors, with the human health sector seen as better resourced and more influential, despite having historically lower engagement than the environmental and animal health sectors around the wildlife trade and its role in emerging zoonoses. CONCLUSION: The network of transnational organisations focused on the governance of wildlife trade and the prevention of emerging zoonoses is highly multi-sectoral, but despite progress catalysed by the COVID-19 pandemic, barriers still exist for inter-sectoral interaction and coordination. A One Health approach to governance at this level, which has gained traction throughout the COVID-19 pandemic, was shared as a promising mechanism to support a balancing of roles and agendas in this space. However, this must involve agreement around equity, priorities, and clear goal setting to support effective action.

Exploring home fall events among infants and toddlers using social media information: an infodemiology study in China.

BACKGROUND: Practical interventions of fall prevention are challenging for infants and toddlers. This study aimed to explore specific details of falls that occurred at home for kids 0-3 years old using key information from social media platforms, which provided abundant data sources for fall events. METHODS: We used internet-based search techniques to collect fall events information from 2013 to 2023. The search was restricted and implemented between 1 and 12 April 2023. Online platforms included Baidu, Weibo, WeChat, TikTok, Toutiao and Little Red Book. A qualitative descriptive approach was used to analyse the fall events and major factors, including the fall event time, child age, environmental factors and behavioural characteristics of children and caregivers. RESULTS: We identified 1005 fall injury cases among infants and toddlers. Fall mechanisms included falls from household furniture (71.2%), falls from height (21.4%) and falls on the same level (7.4%). Environmental risk factors mainly consisted of not using or installing bed rails incorrectly, a gap between beds, unstable furniture, slippery ground and windows without guardrails. Behavioural factors included caregivers leaving a child alone, lapsed attention, turning around to retrieve something, misusing baby products, inadequately holding the child and falling asleep with children. Child behavioural factors included walking or running while holding an object in hand or mouth and underdeveloped walking skills. CONCLUSION: Interventions for preventing falls should be designed specifically for Chinese families, especially considering family function in the context of Chinese culture. Social media reports could provide rich information for researchers.

Quantifying relational change in community organisations participating in a Veteran suicide prevention learning collaborative: a social network analysis.

BACKGROUND: Veteran suicide remains a significant issue, as 17.5 Veterans die by suicide each day. The US Department of Veteran Affairs (VA) has implemented a robust suicide prevention program within its integrated behavioural health system. Further, the VA has increasingly contributed to suicide prevention in community settings, where a large proportion of Veterans receive health care and social services. One component integral to preventing suicide among Veterans receiving community services is ensuring that organisations are equipped with the latest evidence-based Veteran-specific suicide prevention strategies. METHODS: The Patient Safety Center of Inquiry-Suicide Prevention Collaborative piloted a Veteran suicide prevention learning collaborative in the Denver/Colorado Springs, CO region, spanning 16 months as a multimodal initiative to integrate community organisations and assist them in implementing Veteran suicide prevention strategies used within VA. Agencies completed social network analysis surveys at baseline (T1), year 1 (T2) and 16 months (T3) to examine social networks, partnerships and collaborations among community organisations and the VA over time. RESULTS: The quantity of learning collaborative relationships increased from 30 at T1 to 41 at T3 while the quality of relationships deepened over time from awareness and cooperative to more coordinated and integrated. CONCLUSION: Improvement in relationship quantity and quality facilitates community organisation engagement in collaborating to strengthen their Veteran suicide prevention programming. Learning collaboratives work with the individual organisation for intraorganisational facilitation of implementing suicide prevention strategies and engage and enhance interorganisational partnerships. This multimodal intervention can engage community organisations and provide a stronger safety net for Veterans at risk for suicide.

The common drivers of children and young people's health and wellbeing across 13 local government areas: a systems view.

BACKGROUND: System dynamics approaches, including group model building (GMB) and causal loop diagrams (CLDs), can be used to document complex public health problems from a community perspective. This paper aims to apply Social Network Analysis (SNA) methods to combine multiple CLDs created by local communities into a summary CLD, to identify common drivers of the health and wellbeing of children and young people. METHODS: Thirteen community CLDs regarding children and young people health and wellbeing were merged into one diagram involving three steps: (1) combining variable names; (2) CLD merging, where multiple CLDs were combined into one CLD with a set of unique variables and connections; (3) paring, where the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was used to generate a cut-point to reduce the number of variables and connections and to rank the overall importance of each variable in the merged CLD. RESULTS: Combining variable names resulted in 290 variables across the 13 CLDS. A total of 1,042 causal links were identified in the merged CLD. The DEMATEL analysis of the merged CLD identified 23 common variables with a net importance between 1.0 and 4.5 R + C values and 57 causal links. The variables with the highest net importance were 'mental health' and 'social connection & support' classified as high net receivers of influence within the system. CONCLUSIONS: Combining large CLDs into a simple diagram represents a generalisable model of the drivers of complex health problems.

Network development in workplace health promotion - empirically based insights from a cross-company network promoting physical activity in Germany.

BACKGROUND: In the field of health promotion, interorganisational networks are of growing relevance. However, systematic and target-oriented network management is of utmost importance for network development. The aim of this article is to report on the development of a cross-company network promoting physical activity, and to identify necessary activities and competencies for a systematic network management. METHODS: The network was systematically planned and implemented in a German technology park comprising different companies. To assess and describe the development of the network, quantitative social network analysis was conducted. To answer the question on the activities and competencies for systematic network development semi-structured interviews with participating stakeholders, and a focus group discussion with health promotion experts were conducted. The interviews were analysed deductively and inductively with the structuring content analysis method and the focus group discussion was analysed deductively by summarising key aspects of the discussion. RESULTS: Network metrics showed that the network became larger and denser during the planning phase, and stagnated during the implementation phase. As key facilitators for network development, participation of all stakeholders, a kick-off event, and the driving role of a network manager were identified. Necessary activities of the network manager were related to structural organisation, workplace health promotion offers, and cross-sectional tasks. The results suggested that not only professional and methodological competencies, but also social and self-competencies were required by the manager. CONCLUSIONS: Our study provides initial guidance regarding the activities and required competencies of an interorganisational network manager. The results are of particular relevance for the context of workplace health promotion, since a network manager can be considered as a driving role for planning and implementing a cross-company network. TRIAL REGISTRATION: The study is registered in the German Clinical Trials Register (DRKS00020956, 18/06/2020).

Implementation processes of social network interventions for physical activity and sedentary behavior among children and adolescents: a scoping review.

BACKGROUND: The characteristics of the implementation process of interventions are essential for bridging the gap between research and practice. This scoping review aims to identify the implementation process of social network interventions (SNI) to address physical activity and sedentary behaviors in children and adolescents. METHODS: The scoping review was conducted adhering to the established guidelines. The search was carried out in the ERIC, EBSCO, EMBASE, SCOPUS, and Lilacs databases in April 2023. Social network intervention studies in children and adolescents were included, addressing physical activity or sedentary behaviors. Replicability (TIDieR), applicability (PRECIS-2), and generalizability (RE-AIM) were the explored components of the implementation process. Each component was quantitatively and separately analyzed. Then, a qualitative integration was carried out using a narrative method. RESULTS: Most SNI were theoretically framed on the self-determination theory, used social influence as a social mechanism, and used the individual typology of network intervention. Overall, SNI had strong replicability, tended to be pragmatic, and three RE-AIM domains (reach, adoption (staff), and implementation) showed an acceptable level of the generalizability of findings. CONCLUSIONS: The analyzed SNI for physical activity and sedentary behaviors in adolescents tended to be reported with high replicability and were conducted pragmatically, i.e., with very similar conditions to real settings. The RE-AIM domains of reach, adoption (staff), and implementation support the generalizability of SNI. Some domains of the principles of implementation strategies of SNI had acceptable external validity (actor, action targets, temporality, dose, and theoretical justification).

Female social dynamics as viewed from grooming networks in the Central Himalayan Langur (Semnopithecus schistaceus).

Enhanced survival and reproduction are associated with an individual's direct and indirect social connections with members of a group. Yet, the role of these connections is little known in a vast range of primate species. We studied female Central Himalayan Langur (CHL) to investigate the link between four specific attributes (dominance rank, age, genetic relatedness, and the presence of females carrying infants) and a female's direct and indirect social relationships. By analyzing grooming networks, we revealed different behavioral strategies: high-ranking females form relationships with many females (high degree), whereas females with dependent infants have strong relationships (high strength and eigenvector). Subadult females are important individuals that hold the social network together (high betweenness), while an immigrant female strategy is to integrate herself into the group by forming strong bonds with females who themselves have strong bonds (high eigenvector). Our study sheds light on how behavioral strategies shape female CHL grooming networks, which may help them to secure fitness and survival advantages.

Social network analysis for medical narcotics in South Korea: focusing on patients and healthcare organizations.

BACKGROUND: Medical narcotics must be administered under medical supervision because of their potential for misuse and abuse, leading to more dangerous and addictive substances. The control of medical narcotics requires close monitoring to ensure that they remain safe and effective. This study proposes a methodology that can effectively identify the overprescription of medical narcotics in hospitals and patients. METHODS: Social network analysis (SNA) was applied to prescription networks for medical narcotics. Prescription data were obtained from the Narcotics Information Management System in South Korea, which contains all data on narcotic usage nationwide. Two-mode networks comprising hospitals and patients were constructed based on prescription data from 2019 to 2021 for the three most significant narcotics: appetite suppressants, zolpidem, and propofol. Two-mode networks were then converted into one-mode networks for hospitals. Network structures and characteristics were analyzed to identify hospitals suspected of overprescribing. RESULTS: The SNA identified hospitals that overprescribed medical narcotics. Patients suspected of experiencing narcotic addiction seek treatment in such hospitals. The structure of the network was different for the three narcotics. While appetite suppressants and propofol networks had a more centralized structure, zolpidem networks showed a less centralized but more fragmented structure. During the analysis, two types of hospitals caught our attention: one with a high degree, meaning that potential abusers have frequently visited the hospital, and the other with a high weighted degree, meaning that the hospital may overprescribe. For appetite suppressants, these two types of hospitals matched 84.6%, compared with 30.0% for propofol. In all three narcotics, clinics accounted for the largest share of the network. Patients using appetite suppressants were most likely to visit multiple locations, whereas those using zolpidem and propofol tended to form communities around their neighborhoods. CONCLUSIONS: The significance of this study lies in its analysis of nationwide narcotic use reports and the differences observed across different types of narcotics. The social network structure between hospitals and patients varies depending on the composition of the medical narcotics. Therefore, these characteristics should be considered when controlling medication with narcotics. The results of this study provide guidelines for controlling narcotic use in other countries.

The Influence of Joe Wicks on Physical Activity During the COVID-19 Pandemic: Thematic, Location, and Social Network Analysis of X Data.

BACKGROUND:  Social media (SM) was essential in promoting physical activity during the COVID-19 pandemic, especially among people confined to their homes. Joe Wicks, a fitness coach, became particularly popular on SM during this time, posting daily workouts that millions of people worldwide followed. OBJECTIVE:  This study aims to investigate the influence of Joe Wicks on SM and the impact of his content on physical activity levels among the public. METHODS:  We used NodeXL Pro (Social Media Research Foundation) to collect data from X (formerly Twitter) over 54 days (March 23, 2020, to May 15, 2020), corresponding to the strictest lockdowns in the United Kingdom. We collected 290,649 posts, which we analyzed using social network analysis, thematic analysis, time-series analysis, and location analysis. RESULTS:  We found that there was significant engagement with content generated by Wicks, including reposts, likes, and comments. The most common types of posts were those that contained images, videos, and text of young people (school-aged children) undertaking physical activity by watching content created by Joe Wicks and posts from schools encouraging pupils to engage with the content. Other shared posts included those that encouraged others to join the fitness classes run by Wicks and those that contained general commentary. We also found that Wicks' network of influence was extensive and complex. It contained numerous subcommunities and resembled a broadcast network shape. Other influencers added to engagement with Wicks via their networks. Our results show that influencers can create networks of influence that are exhibited in distinctive ways. CONCLUSIONS: Our study found that Joe Wicks was a highly influential figure on SM during the COVID-19 pandemic and that his content positively impacted physical activity levels among the public. Our findings suggest that influencers can play an important role in promoting public health and that government officials should consider working with influencers to communicate health messages and promote healthy behaviors. Our study has broader implications beyond the status of fitness influencers. Recognizing the critical role of individuals such as Joe Wicks in terms of health capital should be a critical area of inquiry for governments, public health authorities, and policy makers and mirrors the growing interest in health capital as part of embodied and digital experiences in everyday life.

Twitter Analysis of Health Care Workers' Sentiment and Discourse Regarding Post-COVID-19 Condition in Children and Young People: Mixed Methods Study.

BACKGROUND: The COVID-19 pandemic has had a significant global impact, with millions of cases and deaths. Research highlights the persistence of symptoms over time (post-COVID-19 condition), a situation of particular concern in children and young people with symptoms. Social media such as Twitter (subsequently rebranded as X) could provide valuable information on the impact of the post-COVID-19 condition on this demographic. OBJECTIVE: With a social media analysis of the discourse surrounding the prevalence of post-COVID-19 condition in children and young people, we aimed to explore the perceptions of health care workers (HCWs) concerning post-COVID-19 condition in children and young people in the United Kingdom between January 2021 and January 2022. This will allow us to contribute to the emerging knowledge on post-COVID-19 condition and identify critical areas and future directions for researchers and policy makers. METHODS: From a pragmatic paradigm, we used a mixed methods approach. Through discourse, keyword, sentiment, and image analyses, using Pulsar and InfraNodus, we analyzed the discourse about the experience of post-COVID-19 condition in children and young people in the United Kingdom shared on Twitter between January 1, 2021, and January 31, 2022, from a sample of HCWs with Twitter accounts whose biography identifies them as HCWs. RESULTS: We obtained 300,000 tweets, out of which (after filtering for relevant tweets) we performed an in-depth qualitative sample analysis of 2588 tweets. The HCWs were responsive to announcements issued by the authorities regarding the management of the COVID-19 pandemic in the United Kingdom. The most frequent sentiment expressed was negative. The main themes were uncertainty about the future, policies and regulations, managing and addressing the COVID-19 pandemic and post-COVID-19 condition in children and young people, vaccination, using Twitter to share scientific literature and management strategies, and clinical and personal experiences. CONCLUSIONS: The perceptions described on Twitter by HCWs concerning the presence of the post-COVID-19 condition in children and young people appear to be a relevant and timely issue and responsive to the declarations and guidelines issued by health authorities over time. We recommend further support and training strategies for health workers and school staff regarding the manifestations and treatment of children and young people with post-COVID-19 condition.

A statistical approach for assessing cyber risk via ordered response models.

Proper evaluation of the risk associated to a cyber attack is a crucial aspect for many companies. There is an increasing need to plan for and implement effective ways to address cyber security, data security, and privacy protection. Estimating the risk of a successful cyber attack is an important issue, since this type of threat is proliferating and thus poses increasing danger to companies and the customers who use their services. While quantitative loss data are rarely available, it is possible to obtain a qualitative evaluation on an ordinal scale of severity of cyber attacks from experts of the sector. Hence, it is natural to apply order response models for the analysis of cyber risk. In particular, we rely on cumulative link models. We explain the experts' assessment of the severity of a cyber attack as a function of a set of explanatory variables describing the characteristics of the attack under consideration. A measure of diffusion of the effects of the attacks obtained via the use of a network structure is also incorporated into the set of explanatory variables of the model. Along with the description of the methodology, we present a detailed analysis of a real data set that includes information on serious cyber attacks occurred worldwide in the period 2017-2018.

Faculty members as academic knowledge brokers in Iran's health sector: a social network analysis study.

BACKGROUND: Interaction between researchers and policymakers is an essential factor to facilitate the evidence-informed policymaking. One of the effective ways to establish this relationship and promote evidence-informed policymaking is to employ people or organizations that can play the role of knowledge brokers. This study aims to analyze the communication network and interactions between researchers and policymakers in Iran's health sector and identify key people serving as academic knowledge brokers. METHODS: This study was a survey research. Using a census approach, we administered a sociometric survey to faculty members in the health field in top ten Iranian medical universities to construct academic-policymaker network using social network analysis method. Network maps were generated using UCINET and NetDraw software. We used Indegree Centrality, Outdegree Centrality, and Betweenness Centrality indicators to determine knowledge brokers in the network. RESULTS: The drawn network had a total of 188 nodes consisting of 94 university faculty members and 94 policymakers at three national, provincial, and university levels. The network comprised a total of 177 links, with 125 connecting to policymakers and 52 to peers. Of 56 faculty members, we identified four knowledge brokers. Six policymakers were identified as key policymakers in the network, too. CONCLUSIONS: It seems that the flow of knowledge produced by research in the health field in Iran is not accomplished well from the producers of research evidence to the users of knowledge. Therefore, it seems necessary to consider incentive and support mechanisms to strengthen the interaction between researchers and policymakers in Iran's health sector.

Social Dynamics of Advice-Seeking: A Network Analysis of Two Residency Programs.

Phenomenon: Residents interact with their peers and supervisors to ask for advice in response to complicated situations occurring during patient care. To provide a deeper understanding of workplace learning, this study explores the structure and dynamics of advice-seeking networks in two residency programs. Approach: We conducted a survey-based social network study. To develop the survey, we conducted focus group discussions and identified three main categories of advice: factual knowledge, clinical reasoning, and procedural skills. We invited a total of 49 emergency medicine and psychiatry residents who had completed at least six months of their training, to nominate their supervisors and peer residents, as their sources of advice, from a roster. Participants identified the number of occasions during the previous month that they turned to each person to seek advice regarding the three broad categories. We calculated the density, centrality, and reciprocity measures for each advice category at each department. Findings: The response rates were 100% (n = 21) and 85.7% (n = 24) in the emergency medicine and psychiatry departments, respectively. The advice network of emergency medicine residents was denser, less hierarchical, and less reciprocated compared to the psychiatry residents' network. In both departments, PGY-1s were the top advice-seekers, who turned to PGY-2s, PGY-3s, and supervisors for advice. The "procedural skills" network had the lowest density in both departments. There was less overlap in the sources of advice for different advice types in the psychiatry department, implying more selectivity of sources. Insights: Complex social structures and dynamics among residents vary by discipline and level of seniority. Program directors can develop tailored educational interventions informed by their departments' specific network patterns to promote a timely and effective advice-seeking culture which in turn, could lead to optimally informed patient care.

The coevolution of bullying and friendship networks.

The coevolution of bullying and friendship networks and the moderating effects of classroom bullying popularity norms were examined in a sample of 965 students (52.1% boys) in 22 fourth- and fifth-grade classes. Longitudinal social network analysis showed that children were more likely to bully their friends' victims (bully influence effect) and to be bullied by their friends' bullies (victim influence effect); two children bullying the same child were likely to be friends (bully selection effect), and two victims bullied by the same child were likely to be friends (victim selection effect). Bullying popularity norms served as moderators, and the bully selection effect was significant weaker in the context of low bullying popularity norms. This study adds understanding of bullying as a group process and provides implications for preventing school bullying.

Applying Social Network Theory to Vaping in High School: Implications for Person-Centered Intervention.

BACKGROUND: Peer influence on risky behavior is particularly potent in adolescence and varies by gender. Smoking prevention programs focused on peer-group leaders have shown great promise, and a social influence model has proven effective in understanding adult smoking networks but has not been applied to adolescent vaping until 2023. This work aims to apply a social influence model to analyze vaping by gender in a high school network. METHODS: A high school's student body was emailed an online survey asking for gender, age, grade level, vape status, and the names of three friends. Custom Java and MATLAB scripts were written to create a directed graph, compute centrality measures, and perform Fisher's exact tests to compare centrality measures by demographic variables and vape status. RESULTS: Of 192 students in the school, 102 students responded. Students who vape were in closer-knit friend groups than students who do not vape (p < .05). Compared to males who vape, females who vape had more social ties to other students who vape, exhibiting greater homophily (p < .01). Compared to females who do not vape, females who vape were in closer-knit friend groups (p < .05) and had more ties to other students who vape (p < .01). CONCLUSION: Differences in vaping by social connectedness and gender necessitate school and state policies incorporating the social aspect of vaping in public health initiatives. Large-scale research should determine if trends can be generalized across student bodies, and more granular studies should investigate differences in motivations and social influence by demographic variables to individualize cessation strategies.

Utilising qualitative data for social network analysis in disaster research: opportunities, challenges, and an illustration.

An abundance of unstructured and loosely structured data on disasters exists and can be analysed using network methods. This paper overviews the use of qualitative data in quantitative social network analysis in disaster research. It discusses two types of networks, each with a relevant major topic in disaster research-that is, (i) whole network approaches to emergency management networks and (ii) personal network approaches to the social support of survivors-and four usable forms of qualitative data. This paper explains five opportunities afforded by these approaches, revolving around their flexibility and ability to account for complex network structures. Next, it presents an empirical illustration that extends the authors' previous work examining the sources and the types of support and barrier experienced by households during long-term recovery from Hurricane (Superstorm) Sandy (2012), wherein quantitative social network analysis was applied to two qualitative datasets. The paper discusses three challenges associated with these approaches, related to the samples, coding, and bias.

Care complexity, perceptions of complexity and preferences for interprofessional collaboration: an analysis of relationships and social networks in paediatrics.

BACKGROUND: In the context of increasingly intricate healthcare systems, professionals are compelled to collaborate within dynamically changing interprofessional teams. Moreover, they must adapt these collaborative processes to effectively and efficiently manage the evolving complexity of care needs. It remains unclear how professionals determine care complexity and relate this complexity to their preferences for interprofessional collaboration (IPC). This study investigated the relationships between care complexity, professionals' perceived complexity and IPC preferences, and examined the variation in individual and team characteristics of IPC-practices across different levels of complexity in paediatric care. METHODS: In an online questionnaire, 123 healthcare professionals working at an academic tertiary children's hospital scored their perceptions of complexity and preferences for IPC. They also selected family and various professions as members of the interprofessional (IP-) team based on thirteen patient cases. We employed conjoint analysis to systematically model the complexity of case descriptions across the five domains of the International Classification of Functioning, Disability and Health (ICF). Additionally, we applied social network analysis to identify important professions, crucial connectors and influential professions in the IP-team, and to describe the cohesiveness of IP-teams. RESULTS: Modelled case complexity, professionals' perceived complexity and IPC preferences were positively associated. We found large inter-individual variations in the degree of these associations. Social network analysis revealed that the importance and influence of professions was more equally distributed when case complexity increased. Depending on the context and complexity of the case, different professions (e.g. medical doctors, social professionals, extramural professionals) were considered to be more crucial connectors within the IP-team. Furthermore, team cohesion was positively associated with modelled and perceived care complexity. CONCLUSIONS: In conclusion, our study contributes to the existing knowledge by integrating task-specific insights and broadening the use of conjoint and social network analysis in the context of IPC. The findings substantiate the contingency theory that relates characteristics of IPC to care complexity, offering quantified insights into how IP-teams adapt to situational needs. This understanding of relationships and variations within IPC holds crucial implications for designing targeted interventions in both clinical and health profession education contexts. Consequently, it contributes to advancements in healthcare systems.