Social Contact Networks Research Articles

간호학과 신입생의 대인관계역량이 대학생활적응에 미치는 영향 : 사회적 관계망 접촉빈도의 매개효과를 중심으로

간호학과 신입생의 대인관계역량이 대학생활적응에 미치는 영향 : 사회적 관계망 접촉빈도의 매개효과를 중심으로

Product vatapá type (plant-based) with cashew fiber: Market research, chemical characterization and sensorial profile

This work aimed to develop a product with cashew fiber based on market research about plant-based products in Fortaleza/CE city and metropolitan area. An electronic questionnaire was formulated and distributed through social network contacts using the snowball method, where participants were asked about their eating habits and preferences related to plant-based products with cashew fiber. After obtaining the data, vatapá formulations with 10%, 15%, and 20% of cashew fiber were prepared. Physicochemical (pH, acidity, centesimal composition) and sensory (acceptance and descriptive) analyses were performed. Most respondents (87.4%) follow a normal diet (omnivorous). Of this amount, 62.1% intend to reduce meat consumption in the future, and 84.4% indicated the intention to consume products made with cashew fiber. Among the desired sensory characteristics, the most mentioned were: “Being healthy”, “Good availability of nutrients”, and “Practicality in preparation”. The results obtained for the product vegan vatapá with cashew fiber, for composition on a wet basis, was approximately 5% protein, 7% lipids, and 16% carbohydrates. In the sensory evaluation, the scores were within the range of acceptance, with a mean higher than 6.0 for appearance, taste, texture, and global acceptance (scale from 1 to 9) and; a mean of 3.0 for consistency (scale from 1 to 3), indicating ideal point; and mean above 3.0 for purchase intention (scale from 1 to 5). In the CATA (Check all that apply) descriptive sensory test, the results indicated significant difference (p < 0.05) among the samples for yellow and brown colors. The evaluation of intensity for sensory descriptors, using the RATA test (Rate all that apply), showed that the amount of cashew fiber used in the formulation influences the characteristics of “fibrous texture”, “brown color”, and “yellow color”. It was concluded that plant-based vegan vatapá type product with cashew fiber has potential for commercialization since it was well accepted by the research participants, indicating the formulations with 10% and 15% of cashew fiber for large-scale production.

Adaptive group testing strategy for infectious diseases using social contact graph partitions

Mass testing is essential for identifying infected individuals during an epidemic and allowing healthy individuals to return to normal social activities. However, testing capacity is often insufficient to meet global health needs, especially during newly emerging epidemics. Dorfman’s method, a classic group testing technique, helps reduce the number of tests required by pooling the samples of multiple individuals into a single sample for analysis. Dorfman’s method does not consider the time dynamics or limits on testing capacity involved in infection detection, and it assumes that individuals are infected independently, ignoring community correlations. To address these limitations, we present an adaptive group testing (AGT) strategy based on graph partitioning, which divides a physical contact network into subgraphs (groups of individuals) and assigns testing priorities based on the social contact characteristics of each subgraph. Our AGT aims to maximize the number of infected individuals detected and minimize the number of tests required. After each testing round (perhaps on a daily basis), the testing priority is increased for each neighboring group of known infected individuals. We also present an enhanced infectious disease transmission model that simulates the dynamic spread of a pathogen and evaluate our AGT strategy using the simulation results. When applied to 13 social contact networks, AGT demonstrates significant performance improvements compared to Dorfman’s method and its variations. Our AGT strategy requires fewer tests overall, reduces disease spread, and retains robustness under changes in group size, testing capacity, and other parameters. Testing plays a crucial role in containing and mitigating pandemics by identifying infected individuals and helping to prevent further transmission in families and communities. By identifying infected individuals and helping to prevent further transmission in families and communities, our AGT strategy can have significant implications for public health, providing guidance for policymakers trying to balance economic activity with the need to manage the spread of infection.

Does gamification mediate the relationship between digital social capital and student Performance? A survey-based study in Spain

This article aims to investigate the potential mediating role of gamification in the relationship between students' digital social capital and their academic performance. Social networks are informal platforms where students can develop their own skills in order to adapt to the digital environment and where there is visibility in public rankings. Consequently, we argue that digital social capital developed through the use of social networks can promote student motivation and engagement in online gamification practices, which in turn might help to enhance their course performance. Our empirical study applies a survey-based approach on a sample of 133 undergraduate students enrolled in a hybrid course in corporate finance at a Spanish public university during the COVID-19 pandemic. Empirical evidence suggests that stronger digital social capital (i.e. a greater number of following contacts in social networks) increases a student's propensity to participate in Kahoot! gamification. Additionally, digital social capital has a positive indirect effect on a student's academic performance, with this relationship being mediated by Kahoot! participation. This educational research encourages links between different digital technologies to be exploited to a greater extent in order to strengthen student engagement and maximize their academic performance.

Reconstructing an Epidemic Outbreak Using Steiner Connectivity

Only a subset of infections is actually observed in an outbreak, due to multiple reasons such as asymptomatic cases and under-reporting. Therefore, reconstructing an epidemic cascade given some observed cases is an important step in responding to such an outbreak. A maximum likelihood solution to this problem ( referred to as CascadeMLE ) can be shown to be a variation of the classical Steiner subgraph problem, which connects a subset of observed infections. In contrast to prior works on epidemic reconstruction, which consider the standard Steiner tree objective, we show that a solution to CascadeMLE, based on the actual MLE objective, has a very different structure. We design a logarithmic approximation algorithm for CascadeMLE, and evaluate it on multiple synthetic and social contact networks, including a contact network constructed for a hospital. Our algorithm has significantly better performance compared to a prior baseline.

Retraction Note: Hybrid harmony search algorithm for social network contact tracing of COVID-19.

[This retracts the article DOI: 10.1007/s00500-021-05948-2.].

Network canvas: an open-source tool for capturing social and contact network data.

Social influence and contact networks are extremely important for understanding health behaviour and the spread of disease. Yet, most traditional software tools are not optimized to capture these data, making measurement of personal networks challenging. Our team developed Network Canvas to provide an end-to-end workflow with intuitive interfaces to enable researchers to design and conduct network interviews. Network Canvas consists of three applications (Architect, Interviewer and Server). All applications are written in JavaScript and run on Windows, macOS and Linux; Interviewer also runs on Android and iOS. Network Canvas substantially reduces the complexity and technical knowledge required to collect network data via three point-and-click applications. The tool has wide applicability for measuring contact and social influence networks in epidemiology. Network Canvas is open source and freely available [networkcanvas.com] under the GNU General Public License 3.

The effect of perceived usefulness of recommender systems and information sources on purchase intention

PurposeThe current study aims to empirically analyze the influence of different information sources, together with the persuasiveness of recommender systems (RSs) on the consumer’s purchase intention (PI). It also expands the research on RSs from the point of view of consumer behavior and psychology, considering perceived usefulness and relevance. In addition, it analyzes how different types of personalized recommendations, along with non-personalized ones, influence PI.Design/methodology/approachThe proposed model has been validated using partial least squares structural equation modeling (PLS-SEM), based on the data collected from 597 online shoppers.FindingsThis study proves that both information search and RSs influence PI, being complementary rather than mutually exclusive. Recommender systems’ findings indicate that the PI is primarily influenced by the perceived relevance of RSs, the information provided by manufacturers and reviews. Moreover, only the influence of the perceived usefulness of personalized recommendations strongly affects PI. Conversely, non-personalized recommendations do not affect PI.Practical implicationsDevelopers should focus on increasing the perceived usefulness and relevance of RSs. Thus, they could adopt the hybridization of RSs with the aggregation of both personal shopping behavior and social network contacts. It should integrate information signals from multiple sources to include sentiment extracted from reviews or links to the manufacturer’s page. Furthermore, the recommendation of discounted products must be only for products preferred by customers, because only these influence the PI.Originality/valueThis research provides a structural model that examines together, for the first time, the influence on the PI of the main RSs and sources of information.

The path between socioeconomic inequality and cognitive function: A mediation analysis based on the HAALSI cohort in rural South Africa.

Socioeconomic position (SEP) strongly predicts late-life cognitive health, yet the pathways between SEP and cognitive function remain unclear. This study assessed whether and to what extent the association between SEP and cognitive function in the adult population in rural South Africa is mediated by some health conditions, behavioral factors, and social capital factors. In this cross-sectional study, we used data from the 2014-15 "Health and Aging Africa: A Longitudinal Study of an INDEPTH Community in South Africa" (HAALSI) cohort, including 5,059 adults aged 40+ years from the Agincourt sub-district in Mpumalanga Province, South Africa. SEP, the independent variable, was measured based on ownership of household goods. Cognitive function, the dependent variable, was assessed using questions related to time orientation and immediate and delayed word recall. We used the multiple-mediation analysis on 4125 individuals with complete values on all variables to assess the mediating roles of health conditions (hypertension, diabetes, obesity, and disability), behavioral factors (leisure physical activity, alcohol consumption, and tobacco smoking), and social capital factors (community's willingness to help, trust, sense of safety, and social network contact) in the association between SEP and cognitive function. Compared to adults in the poorest wealth quintile, those in the richest wealth quintile had better cognition (β = 0.903, p < 0.001). The mediation analysis revealed that health conditions mediated 20.7% of the total effect of SEP on cognitive function. In comparison, 3.3% was mediated by behavioral factors and only 0.7% by social capital factors. In the multiple-mediator model, 17.9% of the effect of SEP on cognitive function was jointly mediated by health conditions, behavioral factors, and social capital factors. Low socioeconomic position is a significant factor associated with poor cognitive function among adults aged 40 years and above in South Africa. Health conditions mainly mediate the effects between SEP and cognitive function. Therefore, actions to prevent and control chronic health conditions can serve as the entry point for intervention to prevent poor cognitive function among people with low socioeconomic status.

The illusion of personal health decisions for infectious disease management: disease spread in social contact networks.

Close contacts between individuals provide opportunities for the transmission of diseases, including COVID-19. While individuals take part in many different types of interactions, including those with classmates, co-workers and household members, it is the conglomeration of all of these interactions that produces the complex social contact network interconnecting individuals across the population. Thus, while an individual might decide their own risk tolerance in response to a threat of infection, the consequences of such decisions are rarely so confined, propagating far beyond any one person. We assess the effect of different population-level risk-tolerance regimes, population structure in the form of age and household-size distributions, and different interaction types on epidemic spread in plausible human contact networks to gain insight into how contact network structure affects pathogen spread through a population. In particular, we find that behavioural changes by vulnerable individuals in isolation are insufficient to reduce those individuals' infection risk and that population structure can have varied and counteracting effects on epidemic outcomes. The relative impact of each interaction type was contingent on assumptions underlying contact network construction, stressing the importance of empirical validation. Taken together, these results promote a nuanced understanding of disease spread on contact networks, with implications for public health strategies.

Contact networks have small metric backbones that maintain community structure and are primary transmission subgraphs.

The structure of social networks strongly affects how different phenomena spread in human society, from the transmission of information to the propagation of contagious diseases. It is well-known that heterogeneous connectivity strongly favors spread, but a precise characterization of the redundancy present in social networks and its effect on the robustness of transmission is still lacking. This gap is addressed by the metric backbone, a weight- and connectivity-preserving subgraph that is sufficient to compute all shortest paths of weighted graphs. This subgraph is obtained via algebraically-principled axioms and does not require statistical sampling based on null-models. We show that the metric backbones of nine contact networks obtained from proximity sensors in a variety of social contexts are generally very small, 49% of the original graph for one and ranging from about 6% to 20% for the others. This reflects a surprising amount of redundancy and reveals that shortest paths on these networks are very robust to random attacks and failures. We also show that the metric backbone preserves the full distribution of shortest paths of the original contact networks-which must include the shortest inter- and intra-community distances that define any community structure-and is a primary subgraph for epidemic transmission based on pure diffusion processes. This suggests that the organization of social contact networks is based on large amounts of shortest-path redundancy which shapes epidemic spread in human populations. Thus, the metric backbone is an important subgraph with regard to epidemic spread, the robustness of social networks, and any communication dynamics that depend on complex network shortest paths.

포스트 코로나 시대에서 간호대학 신입생의 사회적 관계망, 대인관계역량 및 문제해결역량이 대학생활 적응에 미치는 영향

Objectives This study is a descriptive survey study to evaluate the effect of social network, interpersonal competency, and problem-solving competency of nursing college freshmen on college life adaptation after COVID-19.&#x0D; Methods This study was conducted on 149 first-year nursing students from two universities in D from May 15 to May 31, 2022, and data collection was measured using a self-report questionnaire measuring social network, interpersonal competency, and problem-solving competency. Data analysis was analyzed using descriptive statistics, t-test, ANOVA, Pearson's correlation, and Multiple Linear Regression using the SPSS 23.0 program.&#x0D; Results Among the general characteristics of the subjects, there was a significant difference in college life adaptation according to major satisfaction. Major satisfaction, problem-solving competency, social network size and contact frequency, interpersonal competency, and college life adaptation were found to have significant positive correlations.In addition, factors affecting the adaptation of nursing college freshmen to college life were in the order of interpersonal competence, major satisfaction, and social network contact frequency, and the explanatory power of these variables was 36.6%.&#x0D; Conclusions Based on the research results of this study, it is necessary to develop and apply a program that can improve major satisfaction and interpersonal skills in order to increase the adaptability of nursing college freshmen to college life.

Social Mediators of the Association Between Depression and Falls Among Older Adults.

To investigate the role of social factors in the association between depression and falls among older adults. The sample included data from 3443 older adults from three waves of the Health and Retirement Study (2010-2014). A Lifestyle Questionnaire was used to measure social engagement, social network contact, and neighborhood social context. Mediating effects of social factors were estimated through causal mediation analysis. Results: Poorer social engagement and network contact were associated with greater likelihood of falls, while poorer neighborhood context was associated with greater likelihood of fall injuries. Social engagement mediated a significant portion of the effect of depression on falls (OR: 1.03, 95% CI: 1.00, 1.06), and neighborhood context mediated a portion of the effect of depression on fall injuries (OR: 1.03, 95% CI: 1.00, 1.07). Discussion: The direct and indirect impacts of social factors suggest that considering them may help improve existing fall prevention approaches.

Epidemic dynamics in census-calibrated modular contact network.

Network-based models are apt for understanding epidemic dynamics due to their inherent ability to model the heterogeneity of interactions in the contemporary world of intense human connectivity. We propose a framework to create a wire-frame that mimics the social contact network of the population in a geography by lacing it with demographic information. The framework results in a modular network with small-world topology that accommodates density variations and emulates human interactions in family, social, and work spaces. When loaded with suitable economic, social, and urban data shaping patterns of human connectance, the network emerges as a potent decision-making instrument for urban planners, demographers, and social scientists. We employ synthetic networks to experiment in a controlled environment and study the impact of zoning, density variations, and population mobility on the epidemic variables using a variant of the SEIR model. Our results reveal that these demographic factors have a characteristic influence on social contact patterns, manifesting as distinct epidemic dynamics. Subsequently, we present a real-world COVID-19 case study for three Indian states by creating corresponding surrogate social contact networks using available census data. The case study validates that the demography-laced modular contact network reduces errors in the estimates of epidemic variables.

Sparse Resource Allocation for Spreading Processes on Temporal-Switching Networks

Spreading processes, e.g. epidemics and rumors, are often modeled on static networks. However, their underlying network structures, such as changing contacts in social networks, are, due to ever-changing circumstances, inherently time-varying in nature. In this paper, we propose an optimization framework for sparse resource allocation for control of spreading processes over temporal networks with known connectivity patterns. We use convex optimization, in particular exponential cone programming, and dynamic programming techniques to bound and minimize the risk of an undetected outbreak by allocating budgeted resources each time step. We demonstrate with dynamic misinformation and epidemic examples how the method can provide targeted allocation of resources.

The Effects of Control Measures and Social Networks on Depression Among Older People During the SARS-CoV-2 Pandemic

This study examined the correlates of change in the depressed state among people aged 65 and older during the SARS-CoV-2 pandemic, particularly the effects of crucial pandemic-related variables. Data were drawn from the longitudinal Survey of Health, Ageing and Retirement in Europe (SHARE), including information obtained from two special pandemic-related telephone interviews (N = 18, 266). The analysis regressed depressed state soon after the outbreak (T1) and again a year later (T2), on four pandemic-related variables (infection status, the stringency of control measures, and two forms of social network contact during the pandemic: face-to-face contact and communication through electronic means), controlling for baseline depression and health, sociodemographic variables, personality traits, and social network characteristics. The main findings were threefold. First, the epidemic-control measures were found to increase the likelihood of a depressed state soon after the pandemic outbreak, but not in the longer run. This data suggests that respondents became more resilient about the pandemic and its effects over time. Second, interpersonal contact utilizing electronic media did not reduce depression rates in the long run and increased depressed state in the short run. Thus, as mandated by epidemic-control policy, the promotion of electronic contact instead of face-to-face contact constituted a mental health risk factor. Third, face-to-face contact reduced the likelihood of change for the worse in the rate of depression among the respondents. This last finding underscores the need for older people to have close interpersonal contact, even in times of pandemic.

Accelerometer-Assessed Physical Activity and Cognitive Performance among European Adults Aged 50+: The Mediating Effects of Social Contacts and Depressive Symptoms.

Cognitive decline is a major public health concern worldwide and it is vital to identify and better understand effective population-based means to improve cognitive performance in old age. The current study set out to examine the links between accelerometer-based physical activity with cognitive performance in later life, as well the indirect pathways through one's social network contacts and depression. We used data from 855 participants aged 50 and above who took part in a cross-sectional accelerometer study as part of the Survey of Ageing, Retirement and Health (SHARE). Cognitive function was measured as an average score of fluency, immediate and delayed recall tests, social contacts were the average contact frequency with members of the social support network, and depression was the Euro-D summary score of depressive symptoms. A multiple mediation analysis was conducted to test the direct and indirect associations between total physical activity (intensity gradient) and cognitive function, as well as the mediation of this association by social contacts and depressive symptoms. Intensity of physical activity was directly related to better cognitive performance (B = 0.170, p = 0.007). The association was partially mediated by social contacts (B = 0.022, 95% CI 0.005, 0.046) and depressive symptoms (B = 0.009, 95% CI 0.009, 0.025), such that total physical activity was linked to cognitive health via more frequent contacts with network members and low depressive symptoms. Practitioners might consider encouraging a physically active lifestyle that involves social interactions to support better cognitive aging and mental health.

Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support.

This paper describes an integrated, data-driven operational pipeline based on national agent-based models to support federal and state-level pandemic planning and response. The pipeline consists of (i) an automatic semantic-aware scheduling method that coordinates jobs across two separate high performance computing systems; (ii) a data pipeline to collect, integrate and organize national and county-level disaggregated data for initialization and post-simulation analysis; (iii) a digital twin of national social contact networks made up of 288 Million individuals and 12.6 Billion time-varying interactions covering the US states and DC; (iv) an extension of a parallel agent-based simulation model to study epidemic dynamics and associated interventions. This pipeline can run 400 replicates of national runs in less than 33 h, and reduces the need for human intervention, resulting in faster turnaround times and higher reliability and accuracy of the results. Scientifically, the work has led to significant advances in real-time epidemic sciences.

Competing control scenarios in probabilistic SIR epidemics on social-contact networks.

A probabilistic approach to the epidemic evolution on realistic social-contact networks allows for characteristic differences among subjects, including the individual number and structure of social contacts, and the heterogeneity of the infection and recovery rates according to age or medical preconditions. Within our probabilistic Susceptible-Infectious-Removed (SIR) model on social-contact networks, we evaluate the infection load or activation margin of various control scenarios; by confinement, by vaccination, and by their combination. We compare the epidemic burden for subpopulations that apply competing or cooperative control strategies. The simulation experiments are conducted on randomized social-contact graphs that are designed to exhibit realistic person–person contact characteristics and which follow near homogeneous or block-localized subpopulation spreading. The scalarization method is used for the multi-objective optimization problem in which both the infection load is minimized and the extent to which each subpopulation’s control strategy preference ranking is adhered to is maximized. We obtain the compounded payoff matrices for two subpopulations that impose contrasting control strategies, each according to their proper ranked control strategy preferences. The Nash equilibria, according to each subpopulation’s compounded objective, and according to their proper ranking intensity, are discussed. Finally, the interaction effects of the control strategies are discussed and related to the type of spreading of the two subpopulations.

Testing Together Behaviors in Secondary Distribution of HIV/Syphilis Self-testing Program Among Men Who have Sex with Men in China.

HIV self-testing (HIVST) is recommended as a promising way to increase HIV testing uptake among MSM. MSM sometimes used HIVST kits together with their sexual partners or friends. However, limited data was reported on MSM's testing together behaviors with sexual partners and non-sexual contacts. Data were collected among MSM in China from June 2018 to June 2019. Eligible participants (referred to as "index participants") finished a baseline survey and applied for HIVST kits. They were encouraged to distribute the kits to other people (referred to as "alters"). Index participants finished a 3-month follow-up survey on the distribution and usage of the kits. Alters finished an online survey on the usage of HIVST kits after they returned the photographed testing results. Results were reported based on index participants and alters, respectively. Based on follow-up data, 138 index participants successfully motivated others for HIVST, most of them (77.5%) tested together with at least one alter. Around half of alters (52.3%) reported testing together with index participants. Index participants distributed more HIVST kits to friends than sexual partners. MSM who had ever tested for HIV were more likely to test together. Our study demonstrated that the testing together behaviors during HIVST distribution among sexual partners and social network contacts were common. The social network-based approach is essential in promoting testing together and HIV status disclosure among MSM.