Connections (Toronto, Ont.)最新文献

{"title":"Methods for Collection of Participant-aided Sociograms for the Study of Social, Sexual and Substance-using Networks Among Young Men Who Have Sex with Men.","authors":"L M Kuhns,&nbsp;M Birkett,&nbsp;S Q Muth,&nbsp;C Latkin,&nbsp;I Ortiz-Estes,&nbsp;R Garofalo,&nbsp;B Mustanski","doi":"10.17266/35.1.1","DOIUrl":"https://doi.org/10.17266/35.1.1","url":null,"abstract":"<p><p>In this study, we adapted and tested a participant-aided sociogram approach for the study of the social, sexual, and substance use networks of young men who have sex with men (YMSM); a population of increasing and disproportionate risk of HIV infection. We used a combination of two interviewer-administered procedures: completion of a pre-numbered list form to enumerate alters and to capture alter attributes; and a participant-aided sociogram to capture respondent report of interactions between alters on an erasable whiteboard. We followed the collection of alter interactions via the sociogram with a traditional matrix-based tie elicitation approach for a sub-sample of respondents for comparison purposes. Digital photographs of each network drawn on the whiteboard serve as the raw data for entry into a database in which group interactions are stored. Visual feedback of the network was created at the point of data entry, using NetDraw network visualization software for comparison to the network structure elicited via the sociogram. In a sample of 175 YMSM, we found this approach to be feasible and reliable, with high rates of participation among those eligible for the study and substantial agreement between the participant-aided sociogram in comparison to a traditional matrix-based approach. We believe that key strengths of this approach are the engagement and maintenance of participant attention and reduction of participant burden for alter tie elicitation. A key weakness is the challenge of entry of interview-based list form and sociogram data into the database. Our experience suggests that this approach to data collection is feasible and particularly appropriate for an adolescent and young adult population. This builds on and advances visualization-based approaches to social network data collection.</p>","PeriodicalId":88856,"journal":{"name":"Connections (Toronto, Ont.)","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4521636/pdf/nihms-689353.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33889250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network Influences on Behavior: A Summary of Tom Valente's Keynote Address at Sunbelt XXXV: The Annual Meeting of the International Network for Social Network Analysis.","authors":"Stephanie R Dyal","doi":"10.17266/35.2.4","DOIUrl":"https://doi.org/10.17266/35.2.4","url":null,"abstract":"Tom Valente’s 2015 keynote address overviewed his career focused on network models of the diffusion of innovations and behavior change, where he made his mark as a skilled theoretician. He is well known in the academic community as a willing collaborator and networker. He has made singular contributions to network models of the diffusion of innovations, including the role of opinion leaders, and network interventions to promote behavior change. Tom’s keynote featured empirical findings from applying his theoretical models to classic diffusion datasets and current work focused on the diffusion of global tobacco policy. He concluded his talk with a summary of network interventions, which may be used to guide intervention development, evaluation, and dissemination (Valente, 2012; Valente, Palinkas, Czaja, Chu, & Brown, 2015). His keynote address emphasized not only his scientific contributions but also how his career was guided and influenced by colleagues, friends, and mentors. Tom’s work highlights the need to examine personal network exposure and thresholds in addition to exposure from the whole network when assessing behavior, behavior change, and intervention effects. Diffusion of innovation theory explains how ideas, behaviors, and products spread throughout a network (Valente & Rogers, 1995). Tom expanded upon diffusion theory for his dissertation by providing theory and techniques for integrating threshold and critical mass models with the diffusion process (Valente, 1995). Tom’s network threshold model differed from Granovetter’s (1983) threshold model in that Granovetter’s model was predicated on people’s innovativeness relative to the whole system, whereas Tom calculated thresholds relative to an individual’s personal network. The novelty of Tom’s dissertation was that some people are innovative relative to the whole community, but late adopters relative to their personal network and vice versa. A person’s position in the network determines their exposure and people can be late adopters because their network position is such that they learn about the innovation late. In order to complete a dissertation on network diffusion, Tom needed data. He realized that he needed to acquire secondary data to analyze as diffusion data can take years to collect since diffusion takes a long time. At this point in time (1989), few network diffusion studies had been conducted and of these some were lost. Of the studies he identified, data from three of them could be obtained and these became the three classic diffusion network datasets: Medical Innovation (Coleman, Katz, & Menzel, 1966), Brazilian Farmers (Rogers, Ascroft, & Röling, 1970), and Korean Family Planning (Rogers & Kincaid, 1981). These three datasets have been","PeriodicalId":88856,"journal":{"name":"Connections (Toronto, Ont.)","volume":"35 2","pages":"52-57"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5683080/pdf/nihms845848.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35556584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The \"Madre Sana\" Data Set.","authors":"S. Gesell, Eric A. Tesdahl","doi":"10.17266/35.2.6","DOIUrl":"https://doi.org/10.17266/35.2.6","url":null,"abstract":"The Madre Sana data set was compiled as a part of a community-engaged health promotion research study. The data set includes 150 actor variables plus multiplex edges between study participants (N=116 pregnant women) at two time points.","PeriodicalId":88856,"journal":{"name":"Connections (Toronto, Ont.)","volume":"35 2 1","pages":"62-65"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67582851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mobile Phone Assessment in Egocentric Networks: A Pilot Study on Gay Men and Their Peers.","authors":"W Scott Comulada","doi":"10.17266/34.1.4","DOIUrl":"https://doi.org/10.17266/34.1.4","url":null,"abstract":"<p><p>Mobile phone-based data collection encompasses the richness of social network research. Both individual-level and network-level measures can be recorded. For example, health-related behaviors can be reported via mobile assessment. Social interactions can be assessed by phone-log data. Yet the potential of mobile phone data collection has largely been untapped. This is especially true of egocentric studies in public health settings where mobile phones can enhance both data collection and intervention delivery, e.g. mobile users can video chat with counselors. This is due in part to privacy issues and other barriers that are more difficult to address outside of academic settings where most mobile research to date has taken place. In this article, we aim to inform a broader discussion on mobile research. In particular, benefits and challenges to mobile phone-based data collection are highlighted through our mobile phone-based pilot study that was conducted on egocentric networks of 12 gay men (n = 44 total participants). HIV-transmission and general health behaviors were reported through a mobile phone-based daily assessment that was administered through study participants' own mobile phones. Phone log information was collected from gay men with Android phones. Benefits and challenges to mobile implementation are discussed, along with the application of multi-level models to the type of longitudinal egocentric data that we collected.</p>","PeriodicalId":88856,"journal":{"name":"Connections (Toronto, Ont.)","volume":"34 1-2","pages":"43-51"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4380161/pdf/nihms-671928.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33190257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Injection Drug Users' Involvement In Drug Economy: Dynamics of Sociometric and Egocentric Social Networks.","authors":"Cui Yang, Carl Latkin, Stephen Q Muth, Abby Rudolph","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>The purpose of this analysis was to examine the effect of social network cohesiveness on drug economy involvement, and to test whether this relationship is mediated by drug support network size in a sample of active injection drug users. Involvement in the drug economy was defined by self-report of participation in at least one of the following activities: selling drugs, holding drugs or money for drugs, providing street security for drug sellers, cutting/packaging/cooking drugs, selling or renting drug paraphernalia (e.g., pipes, tools, rigs), and injecting drugs in others' veins. The sample consists of 273 active injection drug users in Baltimore, Maryland who reported having injected drugs in the last 6 months and were recruited through either street outreach or by their network members. Egocentric drug support networks were assessed through a social network inventory at baseline. Sociometric networks were built upon the linkages by selected matching characteristics, and k-plex rank was used to characterize the level of cohesiveness of the individual to others in the social network. Although no direct effect was observed, structural equation modeling indicated k-plex rank was indirectly associated with drug economy involvement through drug support network size. These findings suggest the effects of large-scale sociometric networks on injectors' drug economy involvement may occur through their immediate egocentric networks. Future harm reduction programs for injection drug users (IDUs) should consider providing programs coupled with economic opportunities to those drug users within a cohesive network subgroup. Moreover, individuals with a high connectivity to others in their network may be optimal individuals to train for diffusing HIV prevention messages.</p>","PeriodicalId":88856,"journal":{"name":"Connections (Toronto, Ont.)","volume":"33 1","pages":"24-34"},"PeriodicalIF":0.0,"publicationDate":"2013-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4193503/pdf/nihms524879.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32740836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What You Believe Travels Differently: Information and Infection Dynamics across Sub-networks.","authors":"Patrick Grim,&nbsp;Christopher Reade,&nbsp;Daniel J Singer,&nbsp;Steven Fisher,&nbsp;Stephen Majewicz","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>In order to understand the transmission of a disease across a population we will have to understand not only the dynamics of contact infection but the transfer of health-care beliefs and resulting health-care behaviors across that population. This paper is a first step in that direction, focusing on the contrasting role of linkage or isolation between sub-networks in (a) contact infection and (b) belief transfer. Using both analytical tools and agent-based simulations we show that it is the structure of a network that is primary for predicting contact infection-whether the networks or sub-networks at issue are distributed ring networks or total networks (hubs, wheels, small world, random, or scale-free for example). Measured in terms of time to total infection, degree of linkage between sub-networks plays a minor role. The case of belief is importantly different. Using a simplified model of belief reinforcement, and measuring belief transfer in terms of time to community consensus, we show that degree of linkage between sub-networks plays a major role in social communication of beliefs. Here, in contrast to the case of contract infection, network type turns out to be of relatively minor importance. What you believe travels differently. In a final section we show that the pattern of belief transfer exhibits a classic power law regardless of the type of network involved.</p>","PeriodicalId":88856,"journal":{"name":"Connections (Toronto, Ont.)","volume":"30 2","pages":"50-63"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3883135/pdf/nihms528235.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32015862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leadership Insularity: A New Measure of Connectivity Between Central Nodes in Networks.","authors":"Samuel Arbesman,&nbsp;Nicholas A Christakis","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>We combine two foci of interest with respect to community identification and node centrality and create a novel metric termed \"leadership insularity.\" By determining the most highly connected nodes within each community of a network, we designate the 'community leaders' within the graph. In doing this, we have the basis for a novel metric that examines how connected, or disconnected, the leaders are to each other. This measure has a number of appealing measurement properties and provides a new way of understanding how network structure can affect its dynamics, especially information flow. We explore leadership insularity in a variety of networks.</p>","PeriodicalId":88856,"journal":{"name":"Connections (Toronto, Ont.)","volume":"30 1","pages":"4-10"},"PeriodicalIF":0.0,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3955896/pdf/nihms-251051.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32192906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Correlated Are Network Centrality Measures?","authors":"Thomas W Valente,&nbsp;Kathryn Coronges,&nbsp;Cynthia Lakon,&nbsp;Elizabeth Costenbader","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":88856,"journal":{"name":"Connections (Toronto, Ont.)","volume":"28 1","pages":"16-26"},"PeriodicalIF":0.0,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2875682/pdf/nihms80042.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"29019600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of Personal Network Exposure on Injecting Equipment Sharing among IDUs in Budapest, Hungary.","authors":"V Anna Gyarmathy,&nbsp;Alan Neaigus","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Until the mid-1990s, the prevalence and incidence of HIV infection was uniformly low in countries across the Central and Eastern European region. In the past decade, however, this has changed dramatically, with a rapid increase in HIV infections in the region, especially in Eastern Europe where 41% of new HIV infection cases were among injecting drug users (IDUs) and as much as 66% of IDUs are infected with HIV in certain regions. While Russia, the largest country in Eastern Europe, has the fastest growing HIV rates in the world, the situation is different in Central Europe. For example, Hungary has low levels of HIV infection - estimated less than 1% of IDUs. Understanding the role of network factors in the spread and prevention of HIV could not only enable us to keep the HIV rates low among IDUs in countries like Hungary, but also provide a means for the effective prevention of other blood-borne and sexually transmitted infections (STIs) that share similar routes of transmission as HIV. Rogers' diffusion of innovations theory may help explain why HIV rates among IDUs are low in Hungary. Valente's related exposure or contagion model postulates that the more individuals within a social network adopt an innovation or a practice, the greater the probability of an individual is to adopt this innovation or practice. Personal network exposure (PNE), measured both within egocentric and sociocentric networks quantifies the extent to which a person is exposed to risk through their social network. The aim of this analysis was to assess the association of PNE and other correlates with injecting equipment sharing among IDUs in Budapest, Hungary.</p>","PeriodicalId":88856,"journal":{"name":"Connections (Toronto, Ont.)","volume":"27 1","pages":"25-38"},"PeriodicalIF":0.0,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496454/pdf/nihms-1605467.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39504409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"\"Big Events\" and Networks.","authors":"Samuel Friedman,&nbsp;Diana Rossi,&nbsp;Peter L Flom","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Some, but not all, \"big events\" such as wars, revolutions, socioeconomic transitions, economic collapses, and ecological disasters in recent years seem to lead to large-scale HIV outbreaks (Friedman et al, in press; Hankins et al 2002). This was true of transitions in the USSR, South Africa and Indonesia, for example, but not those in the Philippines or (so far) in Argentina. It has been hypothesized that whether or not HIV outbreaks occur is shaped in part by the nature and extent of changes in the numbers of voluntary or involuntary risk-takers, which itself may be related to the growth of roles such as sex-sellers or drug sellers; the riskiness of the behaviors engaged in by risk-takers; and changes in sexual and injection networks and other \"mixing patterns\" variables. Each of these potential causal processes, in turn, is shaped by the nature of pre-existing social networks and the patterns and content of normative regulation and communication that happen within these social networks-and on how these social networks and their characteristics are changed by the \"big event\" in question. We will present ideas about what research is needed to help understand these events and to help guide both indigenous community-based efforts to prevent HIV outbreaks and also to guide those who organize external intervention efforts and aid.</p>","PeriodicalId":88856,"journal":{"name":"Connections (Toronto, Ont.)","volume":"27 1","pages":"9-14"},"PeriodicalIF":0.0,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3143004/pdf/nihms309648.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30038333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}