Social Model Research Articles

An extended social force model for the dynamics of electric bicycles in isolated non-motorized lanes

An extended social force model for the dynamics of electric bicycles in isolated non-motorized lanes

Quality of Video Content Related to Deep Inferior Epigastric Perforator Flap Breast Reconstruction: Social Media Platforms Versus Large Language Models.

The deep inferior epigastric perforator (DIEP) flap is currently one of the main options in breast reconstruction. The information about this surgery is critical for the patient, in order to choose the breast reconstruction method. Our study aims to analyze and compare the quality and accuracy of the information related to the DIEP flap reconstruction method provided by social media platforms (SMPs) and the new large language models (LLMs). A total of 50 videos in English and Spanish were selected from the main SMPs (YouTube, Instagram, and Facebook) using the keywords "DIEP flap" and "colgajo DIEP." The duration, number of likes, dislikes, number of visits, upload date, author, and the video category (institutional video, media, patient experience, academic, and surgery) were analyzed. 3 specific questions were asked to 2 new LLMs (ChatGPT and Google Bard). The quality of information in SMPs and LLMs was analyzed and compared by 2 independent board-certified plastic surgeons using the Journal of American Medical Association and DISCERN scales. LLMs showed a statistically significant higher quality of information when compared with SMPs based on the DISCERN scores. The average DISCERN scores for answers given by ChatGPT and Google Bard were 54 ± 6.841 and 61.17 ± 6.306, respectively (good quality). In SMPs, the average scores were 2.31 ± 0.67 (insufficient quality) and 32.87 ± 9.62 (low quality) for the Journal of American Medical Association and DISCERN scales respectively. Thirty-eight percent of the videos in SMPs were performed by nonmedical authors. The quality of information for breast reconstruction using DIEP flaps from LLMs was considered good and significantly better than in SMPs. The information found in SMPs was insufficient and of low quality. Academic plastic surgeons have an opportunity to provide quality content on this type of reconstruction in LLM and SMPs.

The influence maximization algorithm for integrating attribute graph clustering and heterogeneous graph transformer

In social networks, maximizing influence is an important research direction. However, traditional influence maximization algorithms often overlook the attribute information of nodes and the heterogeneity of networks, leading to inefficiency and inaccuracy in the propagation process. To address this issue, this study first constructs a social network influence maximization propagation model, and then combines auto-encoder and graph convolutional autoencoder to extract social network user attributes. Finally, Transformer is used to learn the feature representation of social network nodes. Moreover, a heterogeneous graph neural network is introduced to combine with Transformer to further learn the feature representation of nodes, so as to design an influence maximization algorithm combining attributed graph clustering and heterogeneous graph Transformer. The results showed that the loss values of the fusion algorithm on different datasets were 0.619 and 0.17, respectively, proving its good fitting performance. The recall rate and F1 of this fusion algorithm were 92.5 % and 0.90, respectively, proving its high clustering accuracy. The influence maximization model based on fusion algorithm achieved active node coverage of 67 % and 48 % on two datasets, respectively, proving its good influence propagation effect. The above results demonstrate that the designed model can effectively spread influence. This helps to better understand and utilize the influence dissemination mechanisms in social networks, thereby promoting the development of social network research.

Urban Natural Gas Pipeline Operational Vulnerability Under the Influence of a Social Spatial Distribution Structure: A Case Study of the Safety Risk Patterns in Kunming, China.

Frequent urban natural gas pipeline accidents pose a serious threat to the safety of people and property in surrounding areas. However, current research on natural gas pipeline risks primarily focuses on evaluating the pipelines themselves, with no established method for assessing the impact of pipeline disasters on surrounding areas. This paper proposes an urban natural gas pipeline risk assessment method that integrates the physical attributes of the pipelines with an analysis of social vulnerability based on urban social spatial distribution. Using urban Point of Interest (POI) data, a social spatial distribution model for potential natural gas pipeline accidents is constructed. The risk of pipeline failure is assessed based on physical vulnerability, while the consequences of failure are evaluated through social vulnerability. This method combines the analysis of physical and social vulnerabilities to achieve a comprehensive urban natural gas pipeline risk assessment. The results identified 68 out of 6148 pipelines in the study area as "double high" pipelines, characterized by high physical vulnerability (relatively high risk pipelines) and high social vulnerability (involving level IV areas). The high risk communities identified in the study area are the Cuihu West Road Community and the Daguan Commercial City Community, highlighting the characteristics of risk distribution. The findings suggest that this study contributes to improving urban resilience to natural gas pipeline incidents, reducing potential economic losses and public impacts, and enhancing urban public safety. It also provides new insights into natural gas pipeline risk assessment and urban public safety research.

Social Support and Adherence to Treatment Regimens among Patients Undergoing Hemodialysis

Background/Objectives: Following recommended treatment plans is essential to the success of the treatment. In hemodialysis, adherence to the treatment regimen remains a challenge in many healthcare settings. Many factors, including the patient’s level of social support, influence treatment adherence, but few studies have addressed these relationships. Methods: A correlational cross-sectional design was used to assess the relationship between perceived social support and adherence to treatment regimens among patients undergoing hemodialysis. Self-reported surveys were used to collect data. Results: One hundred and twenty-one hemodialysis patients were recruited from two dialysis centers. Overall, 45.5% of participants demonstrated good adherence, 47.9% had moderate adherence, and 6.6% had poor adherence. Specifically, 76% of participants consistently took their prescribed medications, 75% regularly attended hemodialysis sessions, 67.8% adhered to dietary restrictions, and 62% followed fluid-intake guidelines. Perceived social support was reported as highest from family members (89.3%), followed by significant others (62.8%) and friends (49.6%). There were significant correlations between perceived social support and overall adherence to treatments among hemodialysis patients. Conclusions: This study provides evidence for positive relationships between perceived social support and adherence to treatment regimens among hemodialysis patients. It is recommended that professional caregivers intervene with clients and their families, prepare recreational and educational programs for patients undergoing hemodialysis, and inspire other researchers to suggest different social support models and approaches.

Sinkhorn Distance Minimization for Adaptive Semi-Supervised Social Network Alignment.

Social network alignment, aiming at linking identical identities across different social platforms, is a fundamental task in social graph mining. Most existing approaches are supervised models and require a large number of manually labeled data, which are infeasible in practice considering the yawning gap between social platforms. Recently, isomorphism across social networks is incorporated as complementary to link identities from the distribution level, which contributes to alleviating the dependency on sample-level annotations. Adversarial learning is adopted to learn a shared projection function by minimizing the distance between two social distributions. However, the hypothesis of isomorphism might not always hold true as social user behaviors are generally unpredictable, and thus a shared projection function is insufficient to handle the sophisticated cross-platform correlations. In addition, adversarial learning suffers from training instability and uncertainty, which may hinder model performance. In this article, we propose a novel meta-learning-based social network alignment model Meta-SNA to effectively capture the isomorphism and the unique characteristics of each identity. Our motivation lies in learning a shared meta-model to preserve the global cross-platform knowledge and an adaptor to learn a specific projection function for each identity. Sinkhorn distance is further introduced as the distribution closeness measurement to tackle the limitations of adversarial learning, which owns an explicitly optimal solution and can be efficiently computed by the matrix scaling algorithm. Empirically, we evaluate the proposed model over multiple datasets, and the experimental results demonstrate the superiority of Meta-SNA.

Reassessing Cervical Cancer Prevention: Evaluating the NHS Cervical Cancer Screening Programme Through the Health Belief Model and Global Health Promotion Strategies

Cervical cancer remains a significant public health issue in the United Kingdom, with disparities in screening coverage and outcomes persisting despite robust national programs. This critical analysis evaluates the NHS Cervical Screening Programme (CSP) through the lens of the Health Belief Model (HBM) and global health promotion strategies, such as those outlined in the Ottawa Charter. The analysis explores how individual beliefs about susceptibility, severity, benefits, and barriers influence participation in cervical screening, while also critiquing the CSP's reliance on these factors to the potential exclusion of broader social determinants of health. Key findings reveal that while the HBM provides a valuable framework for understanding individual health behaviors, its emphasis on personal responsibility may overlook significant socioeconomic and cultural barriers, leading to inequities in screening uptake. Furthermore, the CSP's approach, though well-intentioned, may inadvertently undermine patient autonomy by promoting a top-down model of health promotion. The analysis is supported by data from the 2022-2023 Cervical Screening Standards Data Report and other contemporary sources, highlighting the need for more culturally sensitive and equitable strategies. Recommendations for policymakers include the enhancement of targeted interventions for high-risk groups, improved communication strategies, and the integration of a social model of health that considers the broader determinants of health. Future studies are encouraged to explore the sociocultural factors influencing screening behaviors and to evaluate the effectiveness of new screening technologies and integrated HPV vaccination programs. This analysis underscores the importance of rethinking cervical cancer prevention strategies to ensure they are inclusive, equitable, and aligned with the principles of health promotion.

The Urgency of Social Media “Diet” for Generation Z

Social media and generation Z (Gen Z) are like two sides of a coin that cannot be separated. Various positive and negative impacts have arisen as a result of internet addiction among Gen Z. Thus, this research was conducted to obtain a suitable formulation for Gen Z, both in consuming information and using social media. Hopefully, this research contributes to decreasing the negative impacts from the consumption of information and use of social media. The research was conducted through a qualitative approach. Data was collected through Focus Group Discussions (FGD) through Zoom meetings and literature studies. The research findings provide a social media diet model that includes three aspects: Self-Awareness, Action, and Evaluation (SAAE). The first chart of Self-Awareness includes action, motivation, and self-knowledge. The Action aspect contains five dimensions: choosing social media that suits your needs, limiting and selecting the type of information consumed, setting a daily schedule, consuming more offline content, and doing productive activities. The Evaluation highlights the concern on obedience and consistency. Researchers believe that this model can create awareness among social media users about the importance of social media diet information and provide real implications in the application of social media diet models. The social media diet prospectively works for Gen Z and other generations. Keywords: Generation Z, information diet, social media, social media diet models, urgency.

Adapting international social responsibility experience to Ukrainian content

In the conditions of martial law, business activities directly impact the reputation of the company, as well as consumer and public attitudes. Corporate social responsibility is crucial for economic stability, job preservation, and ensuring budget revenues. Studying and disseminating the experience of Ukrainian companies' social responsibility during the war is necessary to solidify practical experience and ensure their impact on the economy and society in the future. Purpose, objectives and research methods. The aim of the research is to study and promote the experience of corporate social responsibility of Ukrainian companies during martial law, as well as to formulate recommendations for consolidating best practices in the future. The subject of the research is corporate social responsibility in wartime conditions, specifically of Ukrainian companies, and their impact on society and the state. The research employs critical analysis of existing concepts and definitions of corporate social responsibility, comparative analysis of international social responsibility models (American, European, Japanese), as well as in-depth analysis of practical examples from international companies. The information base of the research includes scientific papers, statistical data, and practical examples of social responsibility implementation by well-known companies. Research results. Corporate social responsibility is becoming a key element not only for enhancing corporate capitalization but also for global socio-economic development. The social responsibility models in the USA, Europe, and Japan demonstrate different approaches: individual, collective, and intra-family. The American model emphasizes personal philanthropy, the European model focuses on state regulation and income redistribution, while the Japanese model highlights corporate collectivism and employee social protection. The practical value of the results lies in the fact that analyzing different models of social responsibility allows for adapting these practices to Ukrainian realities. Practical recommendations for integrating elements of international experience can help Ukrainian companies enhance their social responsibility and positively impact the economic and social development of the country. The conclusions drawn can be used to develop a national model of social responsibility, taking into account international experience and the specifics of the Ukrainian economy. This includes state propaganda, local budget involvement, tax incentives, and mandatory social reporting.

Talking about diseases; developing a model of patient and public-prioritised disease phenotypes.

Deep phenotyping describes the use of standardised terminologies to create comprehensive phenotypic descriptions of biomedical phenomena. These characterisations facilitate secondary analysis, evidence synthesis, and practitioner awareness, thereby guiding patient care. The vast majority of this knowledge is derived from sources that describe an academic understanding of disease, including academic literature and experimental databases. Previous work indicates a gulf between the priorities, perspectives, and perceptions held by different healthcare stakeholders. Using social media data, we develop a phenotype model that represents a public perspective on disease and compare this with a model derived from a combination of existing academic phenotype databases. We identified 52,198 positive disease-phenotype associations from social media across 311 diseases. We further identified 24,618 novel phenotype associations not shared by the biomedical and literature-derived phenotype model across 304 diseases, of which we considered 14,531 significant. Manifestations of disease affecting quality of life, and concerning endocrine, digestive, and reproductive diseases were over-represented in the social media phenotype model. An expert clinical review found that social media-derived associations were considered similarly well-established to those derived from literature, and were seen significantly more in patient clinical encounters. The phenotype model recovered from social media presents a significantly different perspective than existing resources derived from biomedical databases and literature, providing a large number of associations novel to the latter dataset. We propose that the integration and interrogation of these public perspectives on the disease can inform clinical awareness, improve secondary analysis, and bridge understanding and priorities across healthcare stakeholders.

The Role of social care in health organizations for managing chronic Medical Conditions: A Comprehensive Review

This review examines the role of social care in managing chronic medical conditions within health organizations. Chronic diseases such as diabetes, hypertension, and cardiovascular conditions require comprehensive management strategies that extend beyond medical treatment to address the broader social determinants of health, including socioeconomic factors, social support systems, and community resources. The integration of social care into healthcare settings has emerged as a critical approach to improving patient outcomes and reducing healthcare costs. This review highlights the impact of social care models, such as Accountable Care Organizations (ACOs) and Health Homes, on chronic disease management. By analyzing current literature and case studies, the review explores how health organizations have successfully integrated social services to support patients with chronic conditions. Challenges such as funding, workforce development, and institutional barriers are also discussed. The findings suggest that a multidisciplinary approach combining medical care with social support can enhance care continuity, patient engagement, and long-term disease management. This review emphasizes the need for policy changes and innovative models to facilitate the effective integration of social care into chronic disease management frameworks.

Access, Choice, and Pleasure: Towards a New Model of Disability Sexual Rights

The paper offers a comprehensive exploration of the concept of disability sexual rights by integrating insights from both legal and sociological frameworks. Sexuality is an integral and inseparable part of human existence, encompassing a wide range of biological, physiological, psychological, and social aspects. Our understanding of sexuality developed over time, and contemporary social models view sexuality as shaped by social, cultural, and political factors. The rise of disability studies and social and critical models marked a significant shift in the way disabled sexuality is perceived. These studies underpin social aspects and constructions that contribute to the disabling process. Current Literature situates disability and sexuality within broader sociological frameworks of sexual citizenship, disability legal studies, and human rights, emphasizing the importance of recognizing disability sexual rights in forming an inclusive society. We examine the evolution of human rights discourse, mainly focusing on disability sexual rights as a marginalized subject within the human rights and disability rights agendas. We conclude by weaving together theories from disability studies, sexual citizenship, and law, proposing a new theoretical model of sexual rights that situates them in the intersection of disability, sexuality, law, and society. The model suggests three essential elements that cover the full scope of disability sexual rights: Access, choice, and pleasure. These elements can be applied to all aspects of disabled sexuality, encompassing sexual needs, participation, and autonomy.

Mathematical analysis and optimal control of age‐structured social interaction model with law enforcement

Optimal use of available resources is one of the major issues in many situations. Apart from this, age is also an important factor in modeling social interaction in a society. In this article, we consider an age‐dependent social interaction model and study the stability and optimal control. Law enforcement is an important factor in controlling crime, and the deployment of police to enforce it is important. Now cost is a major issue, so optimal deployment is very important to study. Stability results are derived in terms of threshold parameters. Basic reproduction number is calculated for stability analysis. Using the adjoint system, the form of the law enforcement factor is obtained in terms of state space variables. We see that the cost functional increases with the increase in the population density of criminal population. Numerical results are also added to visually illustrate our theoretical results.

A Novel Service: The Role of the Community Connector for Older Persons within ICPOP

Abstract Background The Community Connector (CC) uses a social prescribing model to work with Older Persons who have recently engaged with ICPOP, complementing the multidisciplinary interventions they receive. A holistic approach is used to support the patient to access a range of community supports to benefit their health and wellbeing and address the social determinants of their health. Reviews show the impact that social prescribing has on the cost implications and healthcare demands. Studies have shown a reduction in GP services, ED attendances and referrals to hospital among those linked with a social prescribing project. Methods Results Conclusion

CSR and Sustainable Environmental Performance: An Exploration of Mediating and Moderating Factors

Taking into consideration the moderating role of perceived organizational support within the framework of the natural resource-based view (RBV) theory, the purpose of this study is to investigate the connection between corporate social responsibility (CSR) and sustainable environmental performance. Specifically, this study focuses on the roles that green capability and green transformational leadership play as mediators in this relationship. Through the use of a survey questionnaire, information was collected from 420 employees working for small- and medium-sized enterprises (SMEs) in Bangladesh. The data were analyzed with the help of AMOS and SPSS. The findings indicate that the level of CSR has a significant impact on the performance of sustainable environmental practices. To a large extent, green capability and green transformational leadership serve as mediators in the relationship between CSR and sustainable environmental performance. Furthermore, perceived organizational support plays a significant role in moderating the relationship between CSR and sustainable environmental performance. The relationship between green transformational leadership and sustainable environmental performance is also significantly moderated by perceived organizational support. This is a significant contributor to the connection. This multidimensional corporate social responsibility model can be used to assess sustainable environmental performance in both industrialized and developing countries, and it can also be extended to other service sectors, according to the theoretical conclusion that can be drawn from the research. This research demonstrates that there is a direct connection between corporate social responsibility and sustainable environmental performance. As a result, practitioners are able to develop strategies that are effective in terms of corporate social responsibility. These findings should be taken into consideration by policymakers and managers who are dedicated to promoting equitable development of the country.

Rumor detection using BERT-based social circle and interaction network model

Rumor detection using BERT-based social circle and interaction network model

An Evaluation of the Maternal Patient Experience through Natural Language Processing Techniques: The Case of Twitter Data in the United States during COVID-19

The healthcare sector constantly investigates ways to improve patient outcomes and provide more patient-centered care. Delivering quality medical care involves ensuring that patients have a positive experience. Most healthcare organizations use patient survey feedback to measure patients’ experiences. However, the power of social media can be harnessed using artificial intelligence and machine learning techniques to provide researchers with valuable insights into understanding patient experience and care. Our primary research objective is to develop a social media analytics model to evaluate the maternal patient experience during the COVID-19 pandemic. We used the “COVID-19 Tweets” Dataset, which has over 28 million tweets, and extracted tweets from the US with words relevant to maternal patients. The maternal patient cohort was selected because the United States has the highest percentage of maternal mortality and morbidity rate among the developed countries in the world. We evaluated patient experience using natural language processing (NLP) techniques such as word clouds, word clustering, frequency analysis, and network analysis of words that relate to “pains” and “gains” regarding the maternal patient experience, which are expressed through social media. The pandemic showcased the worries of mothers and providers on the risks of COVID-19. However, many people also shared how they survived the pandemic. Both providers and maternal patients had concerns regarding the pregnancy risks due to COVID-19. This model will help process improvement experts without domain expertise to understand the various domain challenges efficiently. Such insights can help decision-makers improve the patient care system.

Unraveling relationship dynamics in sports teams: A primer on the social relations model

Interpersonal behavior in sports teams are inherently intricate. The Social Relations Model (SRM) presents a compelling framework to conceptualize and dissect these complexities, enabling the empirical testing of theories concerning relationships within group settings. The SRM decomposes dyadic measurements obtained from a round-robin design into components at the individual (actor and partner) level, relationship level, and team level. Leveraging data on need satisfaction, as experienced by the coach, team captain and two other athletes in relation to each other across 96 sports teams, we showcase the application of the SRM. A step-by-step introduction to the implementation of the model in R is provided. We elucidate how the SRM facilitates the investigation of research questions that deepen our understanding of team dynamics. Our illustration reveals that while the team effect exhibits minimal explanatory power over variability, substantial variability in need satisfaction is accounted for by both individual factors (actor and partner) and relationship effects. Notably, considerable differences are observed between sports teams in the extent to which coaches elicited need satisfaction in their team members. On average, coaches elicit lower levels of need satisfaction compared to other team members. Reciprocal relationships are evident in the team captain-athlete dyad and the athlete-athlete dyad, but not in dyadic relationships with the coach. In sum, this tutorial illustrates how analyzing dyadic data from a round-robin design using the SRM can enhance our understanding of dyadic relationship data within sports teams.

The role of altruistic behavior in emergency evacuation: A simulation study

Given the rising threat of terror attacks and the increasing frequency of natural disasters attributed to climate change, enhancing evacuation capacities in various spaces has become crucial for saving lives and accelerating recovery processes. This study investigates the influence of altruistic behavior on evacuation efficiency by developing a social force model that categorizes individuals into three demographic groups: youth, middle-aged, and seniors. Simulation experiments based on the model were conducted to evaluate the impact of altruistic behavior on evacuation efficiency under different conditions, such as evacuation capacity, reliability, and recovery time. The simulation results show that a higher probability of falling leads to longer evacuation times. While an increase in the probability of altruistic behavior improves evacuation efficiency, excessive altruistic behavior causes evacuation times to vary in a zigzag pattern. When the help range exceeds 0.7m, evacuation efficiency fluctuates without a clear trend of improvement.

Influence of Internet Use on Happiness in China: Mediating Effects of Environmental Quality Perception and Moderating Role of Sense of Environmental Security.

This study aims to comprehensively examine the effects of different types of Internet use and happiness while considering the mediating role of environmental quality perception and the moderating role of a sense of environmental security. Drawing on the uses and gratifications theory, negativity bias, and social cognitive theory, the study investigates the mediating role of environmental quality perception and the moderating role of environmental security in the above relationship. Using data from 3162 respondents in the 2021 Chinese Social Survey (CSS) and Structural Equation Modeling (SEM), the study finds that Internet use for information and educational purposes significantly enhances happiness, with environmental quality perception acting as a mediator. Moreover, a moderating effect of environmental security was observed in the relationship between Internet use for educational purposes and national environmental quality perception. Specifically, the interaction between study-related Internet use and the sense of environmental security significantly and positively predicted national environmental quality perception. These findings highlight the complex interaction between Internet use, environmental factors, and happiness, offering insights into policy interventions aimed at improving Internet access and environmental awareness to enhance public mental health outcomes in China.