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The structure of social networks fundamentally influences spreading dynamics. In general, the more contact between individuals, the more opportunity there is for the transmission of information or disease to take place. Yet, contact between individuals, and any resulting transmission events, are determined by a combination of spatial (where individuals choose to move) and social rules (who they choose to interact with or learn from). Here, we examine the effect of the social-spatial interface on spreading dynamics using a simulation model. We quantify the relative effects of different movement rules (localized, semi-localized, nomadic and resource-based movement) and social transmission rules (simple transmission, anti-conformity, proportional, conformity and threshold rules) to both the structure of social networks and spread of a novel behaviour. Localized movement created weakly connected sparse networks, nomadic movement created weakly connected dense networks, and resource-based movement generated strongly connected modular networks. The resulting rate of spreading varied with different combinations of movement and transmission rules, but-importantly-the relative rankings of transmission rules changed when running simulations on static versus dynamic representations of networks. Our results emphasize that individual-level social and spatial behaviours influence emergent network structure, and are of particular consequence for the spread of information under complex transmission rules.This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

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Drawing on the authors' own ethnographic research, this article discusses the importance of developing polymedia literacy as a key step toward ethical online research on social networking sites (SNS). Polymedia literacy entails the ability to critically analyze the vast landscape of SNS, their affordances, and users' social motivations for choosing specific SNS for their interactions. Internet researchers face several ethical challenges, including issues of informed consent, "public" and "private" online spaces, and data protection. Even when research ethics committees waive the need for a formal ethics approval process, researchers of online spaces need to ensure that their studies are conducted and presented in an ethical and responsible manner. This is particularly important in research contexts that pertain to vulnerable populations in online communities.

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BACKGROUND: There has been an alarming surge in the usage of social networking sites (SNSs) by healthcare professionals (HCPs) without adherence to the principles of professionalism. The widespread use of SNSs in medical practices has been coupled with reports of breaches of professional behaviors. Despite the benefits of SNSs, skepticism prevails about a clearly defined role for SNSs within medicine based upon the core principles of professionalism. Thus, there is a need to understand the manifestations of professionalism in the digital context, classically known as e-professionalism. This study systematically examines HCPs' perceptions of e-professionalism to advance a thorough understanding of e-professionalism. METHODS: This concept analysis was performed using the principle-based approach of Penrod and Hupcey. In January 2023, we searched the databases of PubMed and ISI Web of Science for English-language articles specific to 'e-professionalism' in the medical field. The final selected research corpus of 63 articles was analyzed in this study. RESULTS: A comprehensive analysis of the selected articles highlighted that e-professionalism is an epistemologically mature and distinct concept by a standard definition. However, inconsistencies in conceptual meanings were reported due to varied interpretations despite digital literacy. The pragmatic utility showed a lack of sound methodological and philosophical paradigms. Perhaps the rapid technological advancements and manifestations have hampered linguistic maturity. However, logically, e-professionalism is perceived as an extension of conventional professionalism but with a focus on a distinct framework with a set of attributes to be digitally relevant. CONCLUSION: This study identifies a scarcity of research about the collective perspective of essential stakeholders, underpinning the need to further explore e-professionalism due to its emerging complex nature within the digital context. There is also a recognition that a framework is essential to guide future HCPs to yield a profound understanding and to provide remediation strategies in the rapidly advancing medical field in digital realm.

This principle-based concept analysis provides a nuanced understanding of e-professionalism, addressing its theoretical integration, practical utility, linguistic challenges, and logical boundaries.E-professionalism is acknowledged as a distinct concept across medical disciplines but variations in its interpretation demands a standard, unified, and multi-construct framework.A wealth of generational perceptions surround the concept of e-professionalism, including digital literacy and competency gap, signifying the importance of tailored educational strategies to ensure healthcare professionals uphold high standards while practicing in the digital realm.

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BACKGROUND: Five-guaranteed elderly individuals are a special group of the elderly Chinese population faced with unique challenges; these individuals lack any financial resources (including support by relatives), and are solely reliant on the government to provide food, clothing, medical care, and housing as well as burials. In this article, we aim to investigate mood problems (depression, anxiety) and cognitive functioning in Five-guaranteed elderly individuals, and to validate the effectiveness of two promising interventions, graphene far-infrared intervention (GFII; an exploratory and noninvasive technique) and social network intervention (SNI), for elderly people to lay the foundation for future social service work. METHODS: To address the emotional and cognitive difficulties experienced by this special group, we designed this study, which is the first to apply GFII in this population. We also administered SNI given the social isolation of these individuals, in addition to a corresponding control group. 108 elderly individuals in 3 elder care facilities were screened to evaluate eligibility to participate in the current study, including 44 from Facility A (allocated to the GFII group), 43 from Facility B (allocated to the SNI group), and 21 from Facility C (allocated to the control group). GFII lasts for four weeks, with professionally trained carers putting on and removing intervention caps for half an hour each day. SNI lasts for three weeks, three times a week, and consists of a total of nine themed activities. The length of an activity is 90 min. We also did pre- and post-test comparisons of depression, anxiety and cognition in each group of older adults. RESULTS: The results showed that GFII led to immediate improvements in anxiety and cognitive impairment in the five-guaranteed elderly individuals, and the improvement in cognitive function was sustained over time. Moreover, SNI group showed significant improvements in cognitive function after the intervention period. CONCLUSIONS: The GFII is a promising intervention that can be applied to intervene in cognitive and mood disorders in older adults. The GFII has short-term interventions for anxiety in older adults, but long-term effects for cognitive impairment. SNI also had an interventional effect on cognition.

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Objective: This research aimed to investigate whether subjective general health mediated the relationship between social networks and subjective well-being and whether the perception of fair payment moderated the mediating effect of subjective general health on subjective well-being. Methods: Data were drawn from round 9 of the European Social Survey (ESS), involving 3,843 respondents from 19 countries, with ages ranging from 65 to 90 years (Meanage = 73.88 ± 6.61 years). The participants completed self-reported measures assessing subjective well-being, social networks, subjective general health, and perception of fair payment. Results: Subjective general health played a mediating role in the relationship between social networks and subjective well-being. The perception of fair payment emerged as a moderator in the mediating effect of subjective general health on the association between social networks and subjective well-being. Conclusion: This study suggests that the impact of social networks on both subjective general health and subjective well-being is contingent upon individuals' perceptions of fair payment. These results highlight the significance of social networks in fostering social connections and promoting overall subjective well-being.

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INTRODUCTION: Social network-based testing approaches (SNAs) encourage individuals ("test promoters") to motivate sexual partners and/or those in their social networks to test for HIV. We conducted a systematic review to examine the effectiveness, acceptability and cost-effectiveness of SNA. METHODS: We searched five databases from January 2010 to May 2023, and included studies that compared SNA with non-SNA. We used random-effects meta-analysis to combine effect estimates. Certainty was assessed using the GRADE approach. RESULTS: We identified 47 studies. SNA may increase uptake of HIV testing compared to non-SNA (RR 2.04, 95% CI: 1.06-3.95, Low certainty). The proportion of first-time testers was probably higher among partners or social contacts of test promoters using SNA compared to non-SNA (RR 1.49, 95% CI: 1.22-1.81, Moderate certainty). The proportion of people who tested positive for HIV may be higher among partners or social contacts of test promoters using SNA compared to non-SNA (RR 1.84, 95% CI: 1.01-3.35, Low certainty). There were no reports of any adverse events or harms associated with SNA. Based on six cost-effectiveness studies, SNA was generally cheaper per person tested and per person diagnosed compared to non-SNA. Based on 23 qualitative studies, SNA is likely to be acceptable to a variety of populations. DISCUSSION: Our review collated evidence for SNA to HIV testing covering the key populations and the general population who may benefit from HIV testing. We summarized evidence for the effectiveness, acceptability and cost-effectiveness of different models of SNA. While we did not identify an ideal model of SNA that could be immediately scaled up, for each setting and population targeted, we recommend various implementation considerations as our meta-analysis showed the effectiveness might differ due to factors which include the testing modality (i.e. use of HIV self-testing), type of test promoters, long or short duration of recruitment and use of financial incentives. CONCLUSIONS: Social network-based approaches may enhance HIV testing uptake, increase the proportion of first-time testers and those testing positive for HIV. Heterogeneity among studies highlights the need for context-specific adaptations, but the overall positive impact of SNA on HIV testing outcomes could support its integration into existing HIV testing services.

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BACKGROUND: Peer support for chronic pain is increasingly taking place on social media via social networking communities. Several theories on the development and maintenance of chronic pain highlight how rumination, catastrophizing, and negative social interactions can contribute to poor health outcomes. However, little is known regarding the role web-based health discussions play in the development of negative versus positive health attitudes relevant to chronic pain. OBJECTIVE: This study aims to investigate how participation in online peer-to-peer support communities influenced pain expressions by examining how the sentiment of user language evolved in response to peer interactions. METHODS: We collected the comment histories of 199 randomly sampled Reddit (Reddit, Inc) users who were active in a popular peer-to-peer chronic pain support community over 10 years. A total of 2 separate natural language processing methods were compared to calculate the sentiment of user comments on the forum (N=73,876). We then modeled the trajectories of users' language sentiment using mixed-effects growth curve modeling and measured the degree to which users affectively synchronized with their peers using bivariate wavelet analysis. RESULTS: In comparison to a shuffled baseline, we found evidence that users entrained their language sentiment to match the language of community members they interacted with (t198=4.02; P<.001; Cohen d=0.40). This synchrony was most apparent in low-frequency sentiment changes unfolding over hundreds of interactions as opposed to reactionary changes occurring from comment to comment (F2,198=17.70; P<.001). We also observed a significant trend in sentiment across all users (ß=-.02; P=.003), with users increasingly using more negative language as they continued to interact with the community. Notably, there was a significant interaction between affective synchrony and community tenure (ß=.02; P=.02), such that greater affective synchrony was associated with negative sentiment trajectories among short-term users and positive sentiment trajectories among long-term users. CONCLUSIONS: Our results are consistent with the social communication model of pain, which describes how social interactions can influence the expression of pain symptoms. The difference in long-term versus short-term affective synchrony observed between community members suggests a process of emotional coregulation and social learning. Participating in health discussions on Reddit appears to be associated with both negative and positive changes in sentiment depending on how individual users interacted with their peers. Thus, in addition to characterizing the sentiment dynamics existing within online chronic pain communities, our work provides insight into the potential benefits and drawbacks of relying on support communities organized on social media platforms.

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Purpose: The purpose of this paper is to review the existing research on the antecedents of entrepreneurial networking behavior namely motivational factors and personality factors and its impact on business performance. Design/methodology/approach: This study employs a systematic review methodology, adhering to PRISMA guidelines.. Using the SCOPUS database, the search involved Boolean operators to narrow down relevant articles published in English between 2000 and 2024. Following a meticulous screening process, 32 articles were selected for review after removing duplicates and excluding non-English articles. Methodological quality assessment ensuring focused research questions, precise subject selection methods, representative samples, and reliable measurement instruments was carried out. Findings: The results demonstrate that entrepreneurs who are self-reliant and extroverted have fewer partners, however, these traits positively impact networking activities. The Big Five personality traits predict business creation and success of ventures. Desire for financial gain, risk-taking propensity, self-confidence, and the need for achievement influences networking behavior. Implications: The insights given in this paper can be used for establishing valuable connections, investing in resources, and preparing effective strategies for businesses. Policymakers who aim to promote entrepreneurial behavior among experienced individuals must emphasize the motivations for starting a business and the role of personalities in harnessing and leveraging individual entrepreneurial expertise. Originality: The existing literature on antecedents of entrepreneurial networking Behavior and the relationship of these antecedents together with business performance is limited. Further, this review article also offers avenues for future researchers.

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Suicidal thought and behavior (STB) is highly stigmatized and taboo. Prone to censorship, yet pervasive online, STB risk detection may be improved through development of uniquely insightful digital markers. Focusing on Sanctioned Suicide, an online pro-choice suicide forum, this work derived 17 egocentric network features to capture dynamics of social interaction and engagement within this uniquely uncensored community. Using network data generated from over 3.2 million unique interactions of N = 192 individuals, n = 48 of which were determined to be highest risk users (HRUs), a machine learning classification model was trained, validated, and tested to predict HRU status. Model prediction dynamics were analyzed using introspection techniques to uncover patterns in feature influence and highlight social phenomena. The model achieved a test AUC = 0.73 ([0.61, 0.85], 95% CI), suggesting that network-based socio-behavioral patterns of online interaction can signal for heightened suicide risk. Transitivity, density, and in-degree centrality were among the most important features driving this performance. Moreover, predicted HRUs tended to be targets of social exchanges with lesser frequency and possessed egocentric networks with "small world" network properties. Through the implementation of an underutilized method on an unlikely data source, findings support future incorporation of network-based social interaction features in descriptive, predictive, and preventative STB research.

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Camoni, the largest digital health community in Israel, involves thousands of patients in the decision-making process concerning their illness and treatment. This approach reflects the recent global shift towards digital tools that combine professional information with social networking capabilities to enable problem-solving, emotional support, and knowledge sharing. Digital health communities serve as an invaluable resource for individuals seeking to learn more about their health, connect with others with shared experiences, and receive encouragement. Our research investigates user trends in digital health communities using the Camoni platform as a case study. To this end, we compile a comprehensive database of 12 years of site activity and conduct a large-scale analysis to identify and assess significant trends in user behavior. We observe several significant trends concerning different genders engagement and note a narrowing of gaps between men and women users' participation and publication volume. Furthermore, we find that younger users have become increasingly active on the platform over time. We also uncover unique gender-specific behavior patterns that we attempt to characterize and explain. Our findings suggest that the rise of digital health communities has accelerated in recent years, reflecting the public's growing preference to take a more active role in their medical care.

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Representing social systems as networks, starting from the interactions between individuals, sheds light on the mechanisms governing their dynamics. However, networks encode only pairwise interactions, while most social interactions occur among groups of individuals, requiring higher-order network representations. Despite the recent interest in higher-order networks, little is known about the mechanisms that govern the formation and evolution of groups, and how people move between groups. Here, we leverage empirical data on social interactions among children and university students to study their temporal dynamics at both individual and group levels, characterising how individuals navigate groups and how groups form and disaggregate. We find robust patterns across contexts and propose a dynamical model that closely reproduces empirical observations. These results represent a further step in understanding social systems, and open up research directions to study the impact of group dynamics on dynamical processes that evolve on top of them.

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This paper studies higher-order interactions in social-ecological networks, which formally represent interactions within the social and ecological units of an ecosystem. Many real-world social ecosystems exhibit not only pairwise interactions but also higher-order interactions among their units. Therefore, the conventional graph-theoretic description of networks falls short of capturing these higher-order interactions due to the inherent limitations of the graph definition. In this work, a mathematical framework for capturing the higher-order interactions of a social-ecological system has been given by incorporating notions from combinatorial algebraic topology. In order to achieve this, two different simplicial complexes, the clique and the neighbourhood complex, have been constructed from a pairwise social-ecological network. As a case study, the Q-analysis and a structural study of the interactions in the rural agricultural system of southern Madagascar have been done at various structural levels denoted by q. The results obtained by calculating all the structural vectors for both simplicial complexes, along with exciting results about the participation of facets of the clique complex at different q-levels, have been discussed. This work also establishes significant theorems concerning the dimension of the neighbourhood complex and clique complex obtained from the parent pairwise network.

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Social isolation and fragmentation represent global challenges, with the former stemming from a lack of interaction and the latter from exclusive mobs-both rooted in communication issues. Addressing these challenges, the philosophical realm introduces the concept of the "mixbiotic society." In this framework, individuals with diverse freedoms and values mix together in physical proximity with diverse mingling, recognizing their respective "fundamental incapacities" and uniting in solidarity. This study aims to provide novel measures to balance freedom and solidarity, specifically the intermediate between isolation and mobbing, within a mixbiotic society. To achieve this, we introduce simplified measures to evaluate dynamic communication patterns. These measures complement traditional social network analysis of static structures and conventional entropy-based assessments of dynamic patterns. Our specific hypothesis posits that the measures corresponding to four distinct phases are established by representing communication patterns as multidimensional vectors. These measures include the mean of Euclidean distance to quantify "mobism" for fragmentation, the relative distance change for "atomism" indicating isolation, and a composite measure derived from multiplying the mean and variance of cosine similarity for "mixism," reflecting the well-going state of a mixbiotic society. Additionally, nearly negligible measures correspond to "nihilism." Through the evaluation of seven real-society datasets (high school, primary school, workplace, village, conference, online community, and email), we demonstrate the utility of the "mixism" measure in assessing freedom and solidarity in society. These measures can be employed to typify communities on a radar chart and a communication trajectory graph. The superiority of the measures lies in their ability to evaluate dynamic patterns, ease of calculation, and easily interpretable meanings compared to conventional analyses. As a future development, alongside additional validation using diverse datasets, the mixbiotic society measures will be employed to analyze social issues and applied in the fields of digital democracy and platform cooperativism.

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Advancing sexual and reproductive health is essential for promoting human rights and women's empowerment, and combating the HIV/AIDS epidemic. A large body of literature across the social sciences emphasizes the importance of social capital, generated through the strength of social networks, for shaping health behaviours. However, large-scale measurement of social capital and social networks remains elusive, especially in the context of low-income countries. Here we delve into the role of social capital dynamics, and in particular social connectedness across communities as measured through Facebook friendship links, in shaping knowledge diffusion and behaviour related to sexual and reproductive health in 495 regions across 33 countries in Africa. Our findings demonstrate that regions with higher levels of social connectedness are more similar in their knowledge about contraception and HIV testing, as well as their adoption of these behaviours. We further observe that the influence of social connectedness becomes stronger when the knowledge gaps between regions are larger. In other words, regions are more similar in behaviours, despite knowledge gaps, when they are socially connected. These insights carry significant policy implications, especially for the design and targeting of public health campaigns. We highlight that social connectedness can serve both as a driver and an obstacle in behaviour formation, underscoring the importance of understanding its influence on health-related outcomes.

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Since the 2011 Fukushima nuclear power plant accident, multiple social network disruptions have been reported among the community in Fukushima, while posttraumatic stress symptoms among the residents have persisted. In this study, we aimed to explore the influence of time and social networks on the recovery of posttraumatic stress symptoms based on longitudinal data from community residents in Fukushima, following up five to ten years after the nuclear power plant accident. We conducted five questionnaire surveys quasi-annually, the targets of which were randomly sampled 4900 non-evacuee community residents. In this study, the data of 1809 respondents who participated in at least one survey were used (36.9% of the initial target). Setting posttraumatic stress symptoms as the outcome, we examined the interaction between time and social network size using a mixed model, adjusting for sociodemographic characteristics and disaster-related events. Their interaction was statistically significant, and the posttraumatic stress symptoms of those with small social networks persisted, while those with larger social networks recovered. Maintaining and promoting social networks may contribute to mental health recovery after a nuclear disaster.

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BACKGROUND: Social networks have emerged as powerful tools in education, offering new opportunities for interactive learning. TikTok has gained popularity among young people and has potential for use as a teaching tool in health disciplines. OBJECTIVE: To evaluate the effectiveness of an educational program based on a multimodal intervention using the TikTok platform to improve theoretical-practical knowledge about diabetic debut and vaccination schedules and satisfaction in nursing students. DESIGN: A quasi-experimental study design. SETTINGS: Faculty of Nursing, University of Cadiz, Spain. PARTICIPANTS: 74 third-year undergraduate university nursing students. METHODS: According to Kolb's experiential learning model, a multimodal educational intervention was carried out during the academic year 2022/2023, with 12 h of training. In these sessions, theoretical content on the vaccination calendar and diabetic debut was developed with written case studies. In the last session, 19 working groups were formed and each group was given a practical case study to solve through role-playing and creating a video in TikTok. A questionnaire to measure individual knowledge and a rubric questionnaire were used to evaluate the simulations in TikTok platform. RESULTS: A significant improvement (z = 6.843, p < 0.001) was observed in the mean scores (9.93 ± 1.65) of the posttest of the knowledge questionnaire, used to evaluate abstract conceptualisation abilities. Additionally, a mean score of 10.42 (SD = 1.42) of the items on the rubric questionnaire, designed to assess active experimentation and reflective observation abilities, were correctly performed. It stands out that 97.1 % of the students positively valued the elements of teaching innovation implemented, while 82.9 % showed a high level of satisfaction with their activity. CONCLUSION: A multimodal educational intervention using TikTok platform proved to be effective in improving the acquisition of theoretical-practical knowledge in the university students included in the study. Therefore, this type of experiential training is recommended for the training of future health professionals.

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Online digital networks, including social networks, have significantly impacted individuals' personal and professional lives. Aside from exchanging news and topics of interest, digital networks play an essential role in the diffusion of information, which frequently significantly impacts worldwide societies. In this paper, we present a new mathematical epidemic model for digital networks that considers the sentiment of solitary misinformation in the networks and characteristics of human intelligence that play an important role in judging and spreading misinformation inside the networks. Our mathematical analysis has proved the existence and validity of the system in a real-time environment. Considering the real-world data, our simulation predicts how the misinformation could spread among different global communities and when an intervention mechanism should have to be carried out by the policyholders. Our simulation using the model proves that effective intervention mechanisms by isolating the fake news can effectively control the spread of misinformation among larger populations. The model can analyze the emotional and social intelligence of groups frequently subjected to disinformation and disseminating fake news.

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Despite the availability of pre-exposure prophylaxis (PrEP), Latino sexual minority men (LSMM) continue to experience disparities in PrEP uptake and subsequently, HIV vulnerability. Social network norms are an underutilized solution to increase PrEP uptake. We used a peer influence model (network autocorrelation model) to examine the role of social network descriptive norms (i.e., actual behaviors) surrounding PrEP use. A total of 11 sociocentric networks of 13 friends (n = 143 LSMM) were recruited into our study from 2018 to 2019 in South Florida. Most participants were in PrEP pre-contemplation (n = 44), and almost one-third of our sample were using PrEP (n = 38). Three network autocorrelation models were estimated using an empirically informed Bayesian analysis. We found a positive association between participants' Motivational PrEP Cascade (MPC) position and their network members' (friends') cascade position based on three different measures of connection even when accounting for PrEP knowledge: friendship (ρ = 0.22; 95% CIa = 0.01-0.42), emotional closeness (ρ = 0.24; 95% CI = 0.03-0.44), and frequency of interaction (ρ = 0.22; CI = 0.03-0.42). Our findings highlight that an individual's progress in the MPC may be influenced by their network members' progress in the MPC, suggesting that LSMM using PrEP may serve as role models to their peers for PrEP use due to descriptive norms. Our findings further suggest that PrEP interventions for LSMM along the MPC can be implemented at the social network level.

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