Evidence-based practice in traditional persian medicine (TPM): a stakeholder and social network analysis.

BACKGROUND: The utilization of complementary and alternative medicine (CAM) is experiencing a global surge, accompanied by the adoption of national CAM policies in numerous countries. Traditional Persian medicine (TPM) is highly used as CAM in Iran, and the ongoing scientific evaluation of its interventions and the implementation of evidence-based medicine (EBM) encounters various barriers. Therefore, comprehending the characteristics and interactions of stakeholders is pivotal in advancing EBM within TPM policies. In this study, we utilized both classical stakeholder analysis and social network analysis to identify key stakeholders and potential communication patterns, thereby promoting EBM in TPM policy-making. METHODS: A cross-sectional nationwide stakeholder analysis was conducted in 2023 using snowball sampling. The interviews were carried out using a customized version of the six building blocks of health. Data were collected through semi-structured interviews. Stakeholders were assessed based on five factors (power, interest, influence, position, and competency). The connections and structure of the network were analyzed using degree, betweenness, closeness centrality, and modularity index to detect clusters of smaller networks. RESULTS: Among twenty-three identified stakeholders, the Ministry of Health and Medical Education (MOHME) and the Public were the most powerful and influential. The Iranian Academy of Medical Sciences was the most competent stakeholder. Social network analysis revealed a low density of connections among stakeholders. Pharmaceutical companies were identified as key connectors in the network, while the Public, supreme governmental bodies, and guilds acted as gatekeepers or brokers. The MOHME and Maraji were found to be high-ranking stakeholders based on four different centrality measures. CONCLUSION: This study identifies powerful stakeholders in the network and emphasizes the need to engage uninterested yet significant stakeholders. Recommendations include improving competence through education, strengthening international relations, and fostering stronger relationships. Engaging key connectors and gatekeepers is essential for bridging gaps in the network.

In-party love spreads more efficiently than out-party hate in online communities.

In this article, we present the findings of a comprehensive longitudinal social network analysis conducted on Twitter across four consecutive election campaigns in Spain, spanning from 2015 to 2019. Our focus is on the discernible trend of increasing partisan and ideological homogeneity within interpersonal exchanges on this social media platform, alongside high levels of networking efficiency measured through average retweeting. This diachronic study allows us to observe how dynamics of party competition might contribute to perpetuating and strengthening network ideological and partisan homophily, creating 'epistemic bubbles' in Twitter, yet showing a greater resistance to transforming them into 'partisan echo-chambers.' Specifically, our analysis reveals that the rise of a new radical right-wing party (RRP), Vox, has heightened ideological homogeneity among users across the entire ideological spectrum. However, this process has not been uniform. While users aligned with mainstream political parties consistently share content that reinforces in-party affinity, resulting in highly efficient 'epistemic bubbles,' the emergence of the RRP has given rise to a distinct group of users associated with the most extreme partisan positions, characterized by a notable proportion of out-partisan hostility content, which has fostered the creation of low-efficient 'partisan echo-chambers.'

Exploring stroke discourse on Twitter through content and network analysis among Indian users.

The study aimed to understand stroke-related Twitter conversations in India, focusing on topics, message sources, reach, and influential users to provide insights to stakeholders regarding community needs for knowledge, support, and interventions. Geo-tagged Twitter posts focusing on stroke originating from India and, spanning from November 7, 2022, to February 28, 2023, were systematically obtained via the Twitter application programming interface, using keywords and hashtags sourced through Symplur Signals. Preprocessing involved the removal of hashtags, stop words, and URLs. The Latent Dirichlet Allocation (LDA) topic model was used to identify recurring stroke-related topics, while influential users were identified through social network analysis. About half of the tweets about stroke in India were about seeking support and post-stroke bereavement sharing and had the highest reachability. Four out of 10 tweets were from the individual twitter users. Tweets on the topic risk factors, awareness and prevention (14.6%) constituted the least proportion, whereas the topic management, research, and promotion had the least retweet ratio. Twitter demonstrates significant potential as a platform for both disseminating and acquiring stroke-related information within the Indian context. The identified topics and understanding of the content of discussion offer valuable resources to public health professionals and organizations to develop targeted educational and engagement strategies for the relevant audience.

Weaving social networks from cultural similarities on the neolithisation process in the Western Mediterranean: Evolutionary trajectories using projectile tools.

In this paper, we concentrate on the neolithisation process in Mediterranean Iberia through a diachronic view (from 8600-6800 cal. BP), focusing on social interaction as a factor in articulating new cultural ties. To do this, we apply techniques centred on similarities in material culture by applying Social Network Analysis (SNA). For the first time, we point to the geometric projectiles, taking into account their recurrence in both Mesolithic and Neolithic groups as part of their characteristic hunting equipment. We hypothesise that patterns of cultural variability would express the changing flow of information between communities according to their mobility strategies (last hunter-gatherer groups), including economic and social behaviour, and that these relationships will be restructured with the arrival of the newcomer farmers and herders and their new spatial and social arrangement. The results obtained allow us to describe a connected and homogeneous Late Mesolithic network dramatically structured by the Neolithic arrival. Since then, a heterogenous pattern emerged, involving connected periods, network ruptures, and small-world phenomena. The emergence of this characteristic could support the flow of information when the network presents a clustered structure, the last probably due to regionalisation events. These diachronic dynamics fit well with demographic and socioecological trends observed from regional literature.

Fifty Years of Connection: Characterizing the Social Network of a Primary Care Research Organization.

PURPOSE: This study marks the 50th anniversary of NAPCRG (formerly the North American Primary Care Research Group) by examining social connections among members. METHODS: This descriptive social network analysis was conducted via the Program to Analyze, Record, and Track Networks to Enhance Relationships (PARTNER) survey tool. RESULTS: Responses from 906 participants resulted in 1,721 individuals with 5,196 partner relationships. Most relationships (60%) were characterized as having an integrated level of collaboration. Many relationships led to a research paper (58%) or a grant (34%). CONCLUSIONS: This social network analysis of NAPCRG members' relationships described over 5,000 relationships, many producing publications, grants, and perceived advancements in primary care.

Analysis of the Formation of Scientific Communities in the Journal Research and Education in Nursing (2010 - 2020) and its Disciplinary Influence: an Approach from Bibliometric Analysis, Network Analysis, and Natural Language Processing.

Objective: This work sought to identify the academic communities that have shown interest and participation in the Journal Research and Education in Nursing and analyze the scientific impact generated by said journal. Methods: A bibliometric analysis was carried out, as well as social network analysis and techniques of natural language processing to conduct the research. The data was gathered and analyzed during a specific study period, covering from 2010 - 2020, for articles published in the journal, and 2010 - 2022, for articles that cited the journal within Scopus. These methods permitted performing an exhaustive evaluation of the journal's influence and reach in diverse academic and geographic contexts. Results: During the analysis, it was noted that the journal Research and Education in Nursing has had significant influence in academic and scientific communities, both nationally and internationally. Collaboration networks were detected among diverse institutions and countries, which indicates active interaction in the field of nursing research. In addition, trends and emerging patterns were identified in this field, providing a more complete view of the discipline's evolution. Conclusion: Based on the results obtained, it is concluded that the journal Research and Education in Nursing has played un fundamental role in disseminating knowledge and promoting research in nursing. The combination of Bibliometric metrics, social network analysis, and natural language processing permitted utmost comprehension of its impact in the scientific and academic community globally.

Gender dynamics and academic rank in emergency medicine collaboration networks: A social network and gender propensity analysis.

BACKGROUND: Academic productivity is bolstered by collaboration, which is in turn related to connectivity between individuals. Gender disparities have been identified in academics in terms of both academic promotion and output. Using gender propensity and network analysis, we aimed to describe patterns of collaboration on publications in emergency medicine (EM), focusing on two Midwest academic departments. METHODS: We identified faculty at two EM departments, their academic rank, and their publications from 2020 to 2022 and gathered information on their co-authors. Using network analysis, gender propensity and standard statistical analyses we assessed the collaboration network for differences between men and women. RESULTS: Social network analysis of collaboration in academic emergency medicine showed no difference in the ways that men and women publish together. However, individuals with higher academic rank, regardless of gender, had more importance to the network. Men had a propensity to collaborate with men, and women with women. The rates of gender propensity for men and women fell between the gender ratios of emergency medicine (65%/35%) and the general population (50%/50%), 59.6% and 44%, respectively, suggesting a tendency toward homophily among men. CONCLUSION: Our study aims to use network analysis and gender propensity to identify patterns of collaboration. We found that further work in the area of network analysis application to academic productivity may be of value, with a particular focus on the role of academic rank. Our methodology may aid department leaders by using the information from local analyses to identify opportunities to support faculty members to broaden and diversify their networks.

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.

The structure and function of antagonistic ties in village social networks.

Negative or antagonistic relationships are common in human social networks, but they are less often studied than positive or friendly relationships. The existence of a capacity to have and to track antagonistic ties raises the possibility that they may serve a useful function in human groups. Here, we analyze empirical data gathered from 24,770 and 22,513 individuals in 176 rural villages in Honduras in two survey waves 2.5 y apart in order to evaluate the possible relevance of antagonistic relationships for broader network phenomena. We find that the small-world effect is more significant in a positive world with negative ties compared to an otherwise similar hypothetical positive world without them. Additionally, we observe that nodes with more negative ties tend to be located near network bridges, with lower clustering coefficients, higher betweenness centralities, and shorter average distances to other nodes in the network. Positive connections tend to have a more localized distribution, while negative connections are more globally dispersed within the networks. Analysis of the possible impact of such negative ties on dynamic processes reveals that, remarkably, negative connections can facilitate the dissemination of information (including novel information experimentally introduced into these villages) to the same degree as positive connections, and that they can also play a role in mitigating idea polarization within village networks. Antagonistic ties hold considerable importance in shaping the structure and function of social networks.

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.

Psychological responses to the COVID-19 pandemic and situational impact: A network analysis in Hong Kong residents.

BACKGROUND: The COVID-19 pandemic has had situational impacts and induced various psychological responses among residents. The present study aims to analyze the network structure of psychological responses to the pandemic and their relationships with situational impact, resilience, and well-being through a network approach. METHODS: An online survey recruited 1122 residents (mean age = 32.5 years, 65.4 % female) in Hong Kong from October 2020 to October 2021. The participants completed the Mental Impact and Distress Scale: Psychological Response (MIDc-PR) and other validated measures. Gaussian graphical modeling was conducted in R to identify the central MIDc-PR symptoms and their bridge linkages with situational impact, resilience, and well-being. RESULTS: In the MIDc-PR network, the central symptoms were 'Routine' and 'Images' for Anticipation and 'Tense' and 'Lonely' for Modulation, with 12 bridge edges between the two clusters. In the combined network, the MIDc-PR nodes showed 12 bridge edges with situational impact, particularly in the health domain. 'Concerned', 'Sleep', and 'Lonely' showed negative linkages with resilience; 'Unmotivated' and 'Trapped' showed negative linkages with well-being. The network models showed good levels of stability and did not differ significantly in network structure and global strength across gender and age groups. LIMITATIONS: The cross-sectional study design only allowed undirected associations in the network and could not model the within-subject effects. CONCLUSIONS: The study findings contributed to the literature by elucidating the network structure of psychological responses to the pandemic. The central and bridge symptoms have clinical implications as potential targets for future interventions.

US black women's pregnancy communication networks: A qualitative network analysis.

The ongoing Black maternal health crisis necessitates a closer examination of how Black women in the United States utilize communication to mitigate the dangers racism poses for pregnancy, delivery and the postpartum period. Previous studies have highlighted the importance of supportive networks to Black women's wellbeing during pregnancy. However, few studies utilize a qualitative network approach to explore communication about pregnancy and related risks within a social network. Twenty-eight Black women from 12 US states who self-identified as previously, currently or recently pregnant, were recruited to participate in this study. Following data collection, participants' networks and related commentary from the interview were qualitatively analyzed for composition and context of networks (who is in the network and why?) and the content of communication (what is discussed and how?). This study found that Black women's perceptions of pregnancy risk and enactment of agency in response to risk was influenced by communication with individuals within their communication networks. The findings of this study also demonstrate that emotional support and guidance for navigating the dangers of the healthcare system constituted an important component of communication with strong ties, including partners, family members and close friends. Additionally, Black women enacted agency in response to pregnancy risk by leaning on trusted experts (healthcare providers) within their networks. However, this study also found limitations to the role of pregnancy communication networks. First, negative ties (relations) with alters (individuals with whom Black women have communication ties) and unwanted advice or guidance was found to be a source of stress. Furthermore, although mothers were an essential source of support for many women, differences related to generation, culture and the circumstances of pregnancy limited the relevance of the advice Black women receive from their mothers. Finally, immigrant women faced an additional challenge, as their support networks were sometimes geographically distant from them.

As vacinas contra a covid-19 em plataformas de vídeos curtos no Brasil: o caso do Kwai / Covid-19 vaccines on short video platforms in Brazil: the case of Kwai / Las vacunas contra la covid-19 en plataformas de videos cortos en Brasil: el caso del Kwai

Neste artigo, analisamos as temáticas, os posicionamentos, as formas expressivas, os atores legitimados e os recursos visuais e sonoros empregados na produção de 482 vídeos sobre vacinas, publicados de 2020 a 2022 na plataforma de vídeos curtos Kwai. A partir de análise temática e de análise de conteúdo, identificamos que os vídeos apresentaram, em sua maioria, posicionamento favorável ou neutro em relação às vacinas e que ressaltaram as experiências pessoais com a vacinação. Não obstante, utilizaram sobretudo um tom hu-morístico no tratamento do assunto, com potencial desinformativo quanto aos efeitos colaterais das vacinas. Concluímos assim que, por um lado, o Kwai tem sido utilizado para expressão de experiências positivas com a vacinação, que podem estimular a adesão aos imunizantes, mas, por outro, tem sido também espaço para a circulação de percepções negativas e temores que podem suscitar dúvidas quanto à segurança das vacinas.

In this article, we analyze the themes, positions, expressive forms, legitimized actors, and both visual and sound resources used in the production of 482 videos about vaccines, published from 2020 to 2022 on the short video platform Kwai. Based on thematic analysis and content analysis, we identified that the videos predominantly presented a favorable or neutral stance toward vaccines and that they highlighted personal experiences with immunization. However, they mainly used a humorous tone when dealing with the subject, thereby potentially disseminating misinformation regarding the adverse effects of vaccines. We thus conclude that, on the one hand, Kwai has been used to express positive experiences with vaccination, which can stimulate adherence to vaccinations, but, on the other hand, it has also been a space for the circulation of negative perceptions and fears that can raise doubts regarding the safety of vaccines.

En este artículo, analizamos los temas, posiciones, formas expresivas, actores legitimados y recursos visuales y sonoros utilizados en la producción de 482 videos sobre vacunas publicados de 2020 a 2022 en la plataforma de videos cortos Kwai. A partir del análisis temático y de contenido, identificamos que los videos presentaban, en su mayoría, una posición favorable o neutral con relación a las vacunas y que destacaban experiencias per-sonales con la vacunación. Sin embargo, al abordar el tema, utilizaron, principalmente, un tono humorístico, con potencial desinformativo sobre los efectos secundarios de las vacunas. De ese modo, concluimos que, por un lado, el Kwai tiene sido utilizado para expresar experiencias positivas con la vacunación que pueden estimular la adhesión a las vacunas, pero, por otro lado, también tiene sido un espacio para la circulación de percepciones negativas y miedos que pueden plantear dudas sobre la seguridad de las vacunas.

Navigating agricultural nonpoint source pollution governance: A social network analysis of best management practices in central Pennsylvania.

The Chesapeake Bay watershed is representative of governance challenges relating to agricultural nonpoint source pollution and, more generally, of sustainable resources governance in complex multi-actor settings. We assess information flows around Best Management Practices (BMPs) undertaken by dairy farmers in central Pennsylvania, a subregion of the watershed. We apply a mixed-method approach, combining Social Network Analysis, the analysis of BMP-messaging (i.e. information source, flow, and their influences), and qualitative content analysis of stakeholders' interviews. Key strategic actors were identified through network centrality measures such as degree of node, betweenness centrality, and clustering coefficient. The perceived influence/credibility (by farmers) of BMP-messages and their source, allowed for the identification of strategic entry points for BMP-messages diffusion. Finally, the inductive coding process of stakeholders' interviews revealed major hindrances and opportunities for BMPs adoption. We demonstrate how improved targeting of policy interventions for BMPs uptake may be achieved, by better distributing entry-points across stakeholders. Our results reveal governance gaps and opportunities, on which we draw to provide insights for better tailored policy interventions. We propose strategies to optimize the coverage of policy mixes and the dissemination of BMP-messages by building on network diversity and actors' complementarities, and by targeting intervention towards specific BMPs and actors. We suggest that (i) conservation incentives could target supply chain actors as conservation intermediaries; (ii) compliance-control of manure management planning could be conducted by accredited private certifiers; (iii) policy should focus on incentivizing inter-farmers interaction (e.g. farmers' mobility, training, knowledge-exchange, and engagement in multi-stakeholders collaboration) via financial or non-pecuniary compensation; (iv) collective incentives could help better coordinate conservation efforts at the landscape or (sub-)watershed scale; (v) all relevant stakeholders (including farmers) should be concerted and included in the discussion, proposition, co-design and decision process of policy, in order to take their respective interests and responsibilities into account.

Use of social network analysis in health research: a scoping review protocol.

INTRODUCTION: Social networks can affect health beliefs, behaviours and outcomes through various mechanisms, including social support, social influence and information diffusion. Social network analysis (SNA), an approach which emerged from the relational perspective in social theory, has been increasingly used in health research. This paper outlines the protocol for a scoping review of literature that uses social network analytical tools to examine the effects of social connections on individual non-communicable disease and health outcomes. METHODS AND ANALYSIS: This scoping review will be guided by Arksey and O'Malley's framework for conducting scoping reviews. A search of the electronic databases, Ovid Medline, PsycINFO, EMBASE and CINAHL, will be conducted in April 2024 using terms related to SNA. Two reviewers will independently assess the titles and abstracts, then the full text, of identified studies to determine whether they meet inclusion criteria. Studies that use SNA as a tool to examine the effects of social networks on individual physical health, mental health, well-being, health behaviours, healthcare utilisation, or health-related engagement, knowledge, or trust will be included. Studies examining communicable disease prevention, transmission or outcomes will be excluded. Two reviewers will extract data from the included studies. Data will be presented in tables and figures, along with a narrative synthesis. ETHICS AND DISSEMINATION: This scoping review will synthesise data from articles published in peer-reviewed journals. The results of this review will map the ways in which SNA has been used in non-communicable disease health research. It will identify areas of health research where SNA has been heavily used and where future systematic reviews may be needed, as well as areas of opportunity where SNA remains a lesser-used method in exploring the relationship between social connections and health outcomes.

An empirical study on social network analysis for small residential communities in Gangwon State, South Korea.

Social Network Analysis (SNA) provides a dynamic framework for examining interactions and connections within networks, elucidating how these relationships impact behaviors and outcomes. This study targeted small residential communities in Gangwon State, South Korea, to explore network formation theories and derive strategies for enhancing health promotion services in rural communities. Conducted in 12 small residential areas, the survey led to a network categorization model distinguishing networks as formal, informal, or non-existent. Key findings demonstrated that demographic and socio-economic factors, specifically age, income, living environment, leisure activities, and education level, significantly influence network formation. Importantly, age, environmental conditions, satisfaction with public transportation, and walking frequency were closely associated with the evolution of formal networks. These results highlight the importance of early community network assessments, which must consider distinct network traits to develop effective health promotion models. Utilizing SNA early in the assessment process can improve understanding of network dynamics and optimize the effectiveness of health interventions.

Quality in care homes: How wearable devices and social network analysis might help.

Social network analysis can support quality improvement in care homes but traditional approaches to social network analysis are not always feasible in care homes. Recalling contacts and movements in a home is difficult for residents and staff and documentary and other sources of individual contacts can be unreliable. Bluetooth enabled wearable devices are a potential means of generating reliable, trustworthy, social network data in care home communities. In this paper, we explore the empirical, theoretical and real-world potential and difficulties in using Bluetooth enabled wearables with residents and staff in care homes for quality improvement. We demonstrate, for the first time, that a relatively simple system built around the Internet of Things, Bluetooth enabled wearables for residents and staff and passive location devices (the CONTACT intervention) can capture social networks and data in homes, enabling social network analysis, measures, statistics and visualisations. Unexpected variations in social network measures and patterns are surfaced, alongside "uncomfortable" information concerning staff time spent with residents. We show how technology might also help identify those most in need of social contact in a home. The possibilities of technology-enabled social network analysis must be balanced against the implementation-related challenges associated with introducing innovations in complex social systems such as care homes. Behavioural challenges notwithstanding, we argue that armed with social network information, care home staff could better tailor, plan and evaluate the effects of quality improvement with the sub-communities that make up a care home community.

Exploration and future trends on spatial correlation of green innovation efficiency in strategic emerging industries under the digital economy: A social network analysis.

With digital technological change and the increasing frequency of interregional innovation links, the spatial correlation and diversity of strategic emerging industries' green innovation efficiency (SEI-GIE) need to be explored in depth. This paper innovatively constructs the SEI-GIE input-output index system under digital economy. The proposed grey model FINGBM(1,1) with ω-order accumulation and weighted initial value optimization realizes effective prediction of 7 input-output indicators of 30 provinces in China from 2021 to 2025. Super-SBM-DEA, gravity model, and social network analysis are applied to explore spatial network structure's dynamic process of SEI-GIE from 12th to 14th Five-Year-Plan period (2011-2025). Empirical results show that (1) Under the effect of digital economy, the SEI-GIE in China generally shows a U-shaped fluctuation trend, in which the growth trend in the central region is obvious, and the western region shows significant fluctuations. (2) The spatial correlation network of SEI-GIE presents a complex and stable center-periphery circle. Particularly, the overall increase in network efficiency highlights the strong small-world characteristics. (3) Beijing, Shanghai, Zhejiang and Jiangsu have always been in the leading core position, with strong influence and control; And Tianjin's core position in the network will decline. Additionally, Guangxi and Chongqing have great potential, but Guangdong needs to strengthen its radiation effect. (4) Block model shows that plate-I (Beijing, Tianjin) receive spatial spillovers from others, while plates-III,IV have significant spillover effects. This study provides theoretical reference for policymakers from a network perspective to promote development of China's SEI-GIE.

Social network analysis of a decade-long collaborative innovation network between hospitals and the biomedical industry in China.

Collaborative innovation between hospitals and biomedical enterprises is crucial for ensuring breakthroughs in their development. This study explores the structural characteristics and examines the main roles of associated key actors of collaborative innovation between hospitals and biomedical enterprises in China. Using the jointly owned patent data within the country's healthcare industry, a decade-long collaborative innovation network between hospitals and biomedical enterprises in China was established and analyzed through social network analysis. The results revealed that the overall levels of collaborative innovation network density, collaborative frequency, and network connectivity were significantly low, especially in less-developed regions. In terms of actors with higher degree centrality, hospitals accounted for the majority, whereas a biomedical enterprise in Shenzhen had the highest degree centrality. Organizations in underdeveloped and northwest regions and small players were more likely to implement collaborative innovation. In conclusion, a collaborative innovation network between hospitals and biomedical enterprises in China demonstrated high dispersion and poor development levels. Stimulating organizations' initiatives for collaborative innovation may enhance quality and quantity of such innovation. Policy support and economic investments, strategic collaborative help, and resource and partnership optimization, especially for small players and in less-developed and northwest regions, should be encouraged to enhance collaborative innovation between hospitals and the biomedical industry in China and other similar countries or regions.

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.