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Results for “social network analysis”

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PubMed2005

Identification of networks of sexually transmitted infection: a molecular, geographic, and social network analysis.

BACKGROUND: Despite widespread efforts to control it, Chlamydia trachomatis remains the most frequently diagnosed bacterial sexually transmitted infection (STI). Analysis of sexual networks has been proposed as a novel tool for control of and research into STI. In the present study, we combine molecular genotype data, analysis of geographic clusters, and sociodemographic descriptors to facilitate analysis of large sexual networks. METHODS: Individual chlamydia genotypes found in Manitoba, Canada, were analyzed to identify geographic clusters, and the identified clusters were further characterized by statistical analysis of sociodemographic variables. RESULTS: A total of 10 geographic clusters of chlamydia-genotype infection were identified. Clusters in Winnipeg showed no or little geographic overlap and could be further differentiated on the basis of the sociodemographic characteristics of the individuals within a cluster. Several clusters in northern Manitoba overlapped geographically but, nonetheless, could be differentiated on the basis of the sociodemographic characteristics of the infected individuals. CONCLUSIONS: On the basis of results of the combined analyses, each geographic cluster appeared to represent a relatively distinct transmission network within the larger sexual network. The geographic analysis of the molecular data provided a basis for establishment of potential epidemiological connections between small groups of unlinked individuals. Analytic approaches of the type described here would help to decipher the patterns that exist within large social network data sets and would be applicable to many types of infectious agents.

Adolescent↗
PubMed1997

Beyond single indicators of social networks: a LISREL analysis of social ties among the elderly.

While the health promoting influences of social networks have been shown in a number of studies, little attention has been paid to measurement issues within the field of epidemiology. The purpose of this paper is to propose a new set of measures of social networks for use in epidemiological research on the elderly. We use confirmatory factor analysis to test a multidimensional model of social networks using data from a large epidemiologic study of community-dwelling adults age 65 and over (U.S.A.). Confirmatory factor analysis conducted using LISREL showed that our model provides a good fit to the data after several adjustments for correlated measurement error were introduced. Based on this analysis, we developed new measures of four dimensions and a summary index of social networks. Bivariate relationships between our new measures and several sociodemographic variables of interest are also presented.

Aged↗
PubMedDate not supplied

Visual analysis of large heterogeneous social networks by semantic and structural abstraction.

Social network analysis is an active area of study beyond sociology. It uncovers the invisible relationships between actors in a network and provides understanding of social processes and behaviors. It has become an important technique in a variety of application areas such as the Web, organizational studies, and homeland security. This paper presents a visual analytics tool, OntoVis, for understanding large, heterogeneous social networks, in which nodes and links could represent different concepts and relations, respectively. These concepts and relations are related through an ontology (also known as a schema). OntoVis is named such because it uses information in the ontology associated with a social network to semantically prune a large, heterogeneous network. In addition to semantic abstraction, OntoVis also allows users to do structural abstraction and importance filtering to make large networks manageable and to facilitate analytic reasoning. All these unique capabilities of OntoVis are illustrated with several case studies.

Algorithms↗
PubMed1984

The social networks of opioid abusers.

Using social network analysis, the pretreatment social networks of 106 street drug abusers are examined. While no significant sociodemographic differences are found between opioid and nonopioid abusers, eight significant univariate differences in the characteristics of their social networks are reported. Four of these differences account for 32% of the variation between the two groups of abusers. The social networks of opioid abusers appear significantly less conventional than those of nonopioid abusers; however, opioid abusers appear less committed to the values and behaviors displayed by their network members. Network reconstruction is discussed as an explicit, empirically supportable rehabilitation strategy.

Adult↗
PubMed2003

Stability and flexibility in preschoolers' social networks: a dynamic analysis of socially directed behavior allocation.

The author studied preschoolers' social networks by investigating the allocation of children's social investment within and across time in a classroom of a French nursery school during an academic year. Observations of children's social exchanges during free play revealed that social behaviors were directed toward particular group members. After an important turnover in the peer group at the beginning of the school year, the social network became more structured. Children's strong associations were mostly same sex and small sized. Even if the stability of children's connections remained low, it increased over time. High-frequency partners as well as same-sex partners were more likely to be maintained over time. These findings as well as conceptual and methodological issues are discussed from a developmental perspective.

Child Behavior↗
PubMed1980

Task force report: social networks as mediators of social support: an analysis of the effects and determinants of social networks.

The intent of this paper is to present a representative, though not exhaustive, overview of the current literature on social networks, with an emphasis on research linking social networks to psychological adaptation. This overview includes a review of social network concepts; and analysis of the multiple determinants of social networks; an analysis of the varied effects of social networks; and the implications for policies and practices of community mental health centers. This paper adopts the view that the concept of social network is a useful tool in examining both the functional and the dysfunctional influences of one's primary group on individual adaption.

Adaptation, Psychological↗
PubMed2006

'Mind control' experiences on the internet: implications for the psychiatric diagnosis of delusions.

BACKGROUND: The DSM criteria for a delusion indicate that it should not include any beliefs held by a person's 'culture or subculture'. The internet has many examples of people reporting 'mind control experiences' (MCEs) on self-published web pages, many of which suggest a community based around such beliefs and experiences. It was hypothesized that some of these reports are likely to reflect delusional beliefs and the hyperlinks between web reports were likely to show evidence of social structure, demonstrating the 'culture or subculture' exemption to be increasingly redundant in light of new technology. SAMPLING AND METHODS: Texts from web sites reporting MCEs (n = 10), experience of cancer (n = 10), depression (n = 10) and being stalked (n = 10) were identified, and were blind-rated by three independent psychiatrists for the presence of delusions. Hyperlinks from web sites reporting MCEs were used to create a network structure; this was compared with a size-matched, randomly generated network and known social networks from the literature using social network analysis. CONCLUSIONS: The sampled web-published accounts of MCEs are highly likely to be influenced by delusional beliefs. Social network analysis suggests there is significant evidence of an online community based around these beliefs. The fact that individuals can form a community based on the content of a potentially delusional belief presents a paradox for the DSM diagnostic criteria for a delusion, and suggests the need to revise and revisit the original operational definition in the light of these new technological developments.

Culture↗
PubMed2005

[Analysis of transfer from one hospital to another in patients with myocardial infarction in the Provence-Alpes-Côte-d'Azur].

OBJECTIVE: The aim of the study is to assess the transfer from one hospital to another in patients with myocardial infarction in the Provence Alpes CBte d'Azur (PACA). METHODS: To apply a methodology initially used in sociology "social network analysis" which allow us to describe and model the relational structure of a whole of actors, represented in this work by the establishments of care. Flows between the actors are represented by the transfers of patients. This approach is innovating in the analysis of the medical system. RESULTS: - A total of 2049 patients were admitted in 74 hospitals. The average age is 68.9 years. The density of the hospital network is 0.12. The number of click is 51. Multivariate analysis showed that the following factors were associated with decreased mortality: prestige, age < 65 years, angioplasty alone or thrombolysis associated to angioplasty. CONCLUSION: Social Network Analysis offers a synthetic sight of the relational systems in the health system. It constitutes an open field of search in Public health, and can also be applied to the evaluation of the networks.

Age Factors↗
PubMed1994

The contribution of influence and selection to adolescent peer group homogeneity: the case of adolescent cigarette smoking.

Understanding the homogeneity of peer groups requires identification of peer groups and consideration of influence and selection processes. Few studies have identified adolescent peer groups, however, or examined how they become homogeneous. This study used social network analysis to identify peer groups (cliques), clique liaisons, and isolates among adolescents in 5 schools at 2 data collection rounds (N = 926). Cigarette smoking was the behavior of interest. Influence and selection contributed about equally to peer group smoking homogeneity. Most smokers were not peer group members, however, and selection provided more of an explanation than influence for why isolates smoke. The results suggest the importance of using social network analysis in studies of peer group influence and selection.

Adolescent↗
PubMed2006

Individuals with diabetes mellitus with and without depressive symptoms: could social network explain the comorbidity?

OBJECTIVES: The main objective of the present study was to obtain an approximate prevalence of depressive symptoms in a community sample of persons with diabetes mellitus and to discover whether social networks could explain comorbidity of diabetes mellitus and depressive symptoms. METHOD: Subjects were persons with diabetes mellitus, members of the Diabetes Association of Ljubljana (N = 396, average age: 62.9 +/- 13.4, average duration of diabetes: 17.2 +/- 10.6). Firstly, subjects were screened with CESD (Centre for Epidemiological Studies Depression Scale) and demographic data were also gathered. Secondly, two samples (individuals with and without depressive symptoms) were compared on the basis of social network analysis. RESULTS: The prevalence of depressive symptoms was higher among persons with diabetes in comparison with general population. Individuals with depressive symptoms compared with individuals without depressive symptoms were less dissatisfied with diabetes (p = 0.011), and had better informational (p = 0.039) and instrumental support (p = 0.046), relations between them and support givers were closer (p = 0.050), more important and less conflicting (p = 0.042). Compared groups did not differ in quantitative characteristics of social networks (eg. size of the network or the network gender structure). CONCLUSIONS: The community sample results in Slovenia support the already reported association between diabetes mellitus and depression. Furthermore, social network analysis offered some potentially relevant explanation for comorbidity of diabetes mellitus and depressive symptoms.

Adult↗
PubMed2006

Diffusion of innovations and network segmentation: the part played by people in promoting health.

OBJECTIVE: The objective of this study was to describe how diffusion of innovations theory can integrate mass media, interpersonal communication, and social network analysis. These principles can be used to implement and tailor data-based health promotion activities. GOAL: The goal of this study was to develop a model for using and incorporating interpersonal communication into health promotion programs designed to encourage behaviors that reduce the spread of sexually transmitted diseases (STDs)/HIV. STUDY DESIGN: The authors conducted a review of selected studies that exemplify how diffusion of innovations theory has applied interpersonal communication to promote STD/HIV preventive health behaviors. RESULTS: Few studies have incorporated interpersonal communication as an intervention strategy to encourage STD/HIV preventive behavior. Interventions that have used interpersonal communication have observed successes in health promotion and increases in safer sex behaviors. CONCLUSIONS: This study shows that social network analysis can be used to design more appropriate and perhaps more effective health promotion programs.

Communication↗
PubMed2005

Infection in social networks: using network analysis to identify high-risk individuals.

Simulation studies using susceptible-infectious-recovered models were conducted to estimate individuals' risk of infection and time to infection in small-world and randomly mixing networks. Infection transmitted more rapidly but ultimately resulted in fewer infected individuals in the small-world, compared with the random, network. The ability of measures of network centrality to identify high-risk individuals was also assessed. "Centrality" describes an individual's position in a population; numerous parameters are available to assess this attribute. Here, the authors use the centrality measures degree (number of contacts), random-walk betweenness (a measure of the proportion of times an individual lies on the path between other individuals), shortest-path betweenness (the proportion of times an individual lies on the shortest path between other individuals), and farness (the sum of the number of steps between an individual and all other individuals). Each was associated with time to infection and risk of infection in the simulated outbreaks. In the networks examined, degree (which is the most readily measured) was at least as good as other network parameters in predicting risk of infection. Identification of more central individuals in populations may be used to inform surveillance and infection control strategies.

Community-Acquired Infections↗