Social networks and implementation of evidence-based practices in public youth-serving systems: a mixed-methods study

<p>Abstract</p> <p>Background</p> <p>The present study examines the structure and operation of social networks of information and advice and their role in making decisions as to whether to adopt new evidence-based practices (EBPs) among agency directors and other program professionals in 12 California counties participating in a large randomized controlled trial.</p> <p>Methods</p> <p>Interviews were conducted with 38 directors, assistant directors, and program managers of county probation, mental health, and child welfare departments. Grounded-theory analytic methods were used to identify themes related to EBP adoption and network influences. A web-based survey collected additional quantitative information on members of information and advice networks of study participants. A mixed-methods approach to data analysis was used to create a sociometric data set (n = 176) for examination of associations between advice seeking and network structure.</p> <p>Results</p> <p>Systems leaders develop and maintain networks of information and advice based on roles, responsibility, geography, and friendship ties. Networks expose leaders to information about EBPs and opportunities to adopt EBPs; they also influence decisions to adopt EBPs. Individuals in counties at the same stage of implementation accounted for 83% of all network ties. Networks in counties that decided not to implement a specific EBP had no extra-county ties. Implementation of EBPs at the two-year follow-up was associated with the size of county, urban versus rural counties, and in-degree centrality. Collaboration was viewed as critical to implementing EBPs, especially in small, rural counties where agencies have limited resources on their own.</p> <p>Conclusions</p> <p>Successful implementation of EBPs requires consideration and utilization of existing social networks of high-status systems leaders that often cut across service organizations and their geographic jurisdictions.</p> <p>Trial Registration</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT00880126">NCT00880126</a></p

Detecting Community Structure in Dynamic Social Networks Using the Concept of Leadership

Detecting community structure in social networks is a fundamental problem empowering us to identify groups of actors with similar interests. There have been extensive works focusing on finding communities in static networks, however, in reality, due to dynamic nature of social networks, they are evolving continuously. Ignoring the dynamic aspect of social networks, neither allows us to capture evolutionary behavior of the network nor to predict the future status of individuals. Aside from being dynamic, another significant characteristic of real-world social networks is the presence of leaders, i.e. nodes with high degree centrality having a high attraction to absorb other members and hence to form a local community. In this paper, we devised an efficient method to incrementally detect communities in highly dynamic social networks using the intuitive idea of importance and persistence of community leaders over time. Our proposed method is able to find new communities based on the previous structure of the network without recomputing them from scratch. This unique feature, enables us to efficiently detect and track communities over time rapidly. Experimental results on the synthetic and real-world social networks demonstrate that our method is both effective and efficient in discovering communities in dynamic social networks

Gathering opinion leader data for a tailored implementation intervention in secondary healthcare: a randomised trial

Background: Health professionals’ behaviour is a key component in compliance with evidence-based recommendations. Opinion leaders are an oft-used method of influencing such behaviours in implementation studies, but reliably and cost effectively identifying them is not straightforward. Survey and questionnaire based data collection methods have potential and carefully chosen items can – in theory – both aid identification of opinion leaders and help in the design of an implementation strategy itself. This study compares two methods of identifying opinion leaders for behaviour-change interventions. Methods: Healthcare professionals working in a single UK mental health NHS Foundation Trust were randomly allocated to one of two questionnaires. The first, slightly longer questionnaire, asked for multiple nominations of opinion leaders, with specific information about the nature of the relationship with each nominee. The second, shorter version, asked simply for a list of named “champions” but no more additional information. We compared, using Chi Square statistics, both the questionnaire response rates and the number of health professionals likely to be influenced by the opinion leaders (i.e. the “coverage” rates) for both questionnaire conditions. Results: Both questionnaire versions had low response rates: only 15% of health professionals named colleagues in the longer questionnaire and 13% in the shorter version. The opinion leaders identified by both methods had a low number of contacts (range of coverage, 2–6 each). There were no significant differences in response rates or coverage between the two identification methods. Conclusions: The low response and population coverage rates for both questionnaire versions suggest that alternative methods of identifying opinion leaders for implementation studies may be more effective. Future research should seek to identify and evaluate alternative, non-questionnaire based, methods of identifying opinion leaders in order to maximise their potential in organisational behaviour change interventions

Addressing Cancer Disparities via Community Network Mobilization and Intersectoral Partnerships: A Social Network Analysis

Community mobilization and collaboration among diverse partners are vital components of the effort to reduce and eliminate cancer disparities in the United States. We studied the development and impact of intersectoral connections among the members of the Massachusetts Community Network for Cancer Education, Research, and Training (MassCONECT). As one of the Community Network Program sites funded by the National Cancer Institute, this infrastructure-building initiative utilized principles of Community-based Participatory Research (CBPR) to unite community coalitions, researchers, policymakers, and other important stakeholders to address cancer disparities in three Massachusetts communities: Boston, Lawrence, and Worcester. We conducted a cross-sectional, sociometric network analysis four years after the network was formed. A total of 38 of 55 members participated in the study (69% response rate). Over four years of collaboration, the number of intersectoral connections reported by members (intersectoral out-degree) increased, as did the extent to which such connections were reported reciprocally (intersectoral reciprocity). We assessed relationships between these markers of intersectoral collaboration and three intermediate outcomes in the effort to reduce and eliminate cancer disparities: delivery of community activities, policy engagement, and grants/publications. We found a positive and statistically significant relationship between intersectoral out-degree and community activities and policy engagement (the relationship was borderline significant for grants/publications). We found a positive and statistically significant relationship between intersectoral reciprocity and community activities and grants/publications (the relationship was borderline significant for policy engagement). The study suggests that intersectoral connections may be important drivers of diverse intermediate outcomes in the effort to reduce and eliminate cancer disparities. The findings support investment in infrastructure-building and intersectoral mobilization in addressing disparities and highlight the benefits of using CBPR approaches for such work

The impact of partially missing communities~on the reliability of centrality measures

Network data is usually not error-free, and the absence of some nodes is a very common type of measurement error. Studies have shown that the reliability of centrality measures is severely affected by missing nodes. This paper investigates the reliability of centrality measures when missing nodes are likely to belong to the same community. We study the behavior of five commonly used centrality measures in uniform and scale-free networks in various error scenarios. We find that centrality measures are generally more reliable when missing nodes are likely to belong to the same community than in cases in which nodes are missing uniformly at random. In scale-free networks, the betweenness centrality becomes, however, less reliable when missing nodes are more likely to belong to the same community. Moreover, centrality measures in scale-free networks are more reliable in networks with stronger community structure. In contrast, we do not observe this effect for uniform networks. Our observations suggest that the impact of missing nodes on the reliability of centrality measures might not be as severe as the literature suggests

Message-Passing Methods for Complex Contagions

Message-passing methods provide a powerful approach for calculating the expected size of cascades either on random networks (e.g., drawn from a configuration-model ensemble or its generalizations) asymptotically as the number $N$ of nodes becomes infinite or on specific finite-size networks. We review the message-passing approach and show how to derive it for configuration-model networks using the methods of (Dhar et al., 1997) and (Gleeson, 2008). Using this approach, we explain for such networks how to determine an analytical expression for a "cascade condition", which determines whether a global cascade will occur. We extend this approach to the message-passing methods for specific finite-size networks (Shrestha and Moore, 2014; Lokhov et al., 2015), and we derive a generalized cascade condition. Throughout this chapter, we illustrate these ideas using the Watts threshold model.Comment: 14 pages, 3 figure

The impact of social networks on knowledge transfer in long-term care facilities: Protocol for a study

<p>Abstract</p> <p>Background</p> <p>Social networks are theorized as significant influences in the innovation adoption and behavior change processes. Our understanding of how social networks operate within healthcare settings is limited. As a result, our ability to design optimal interventions that employ social networks as a method of fostering planned behavior change is also limited. Through this proposed project, we expect to contribute new knowledge about factors influencing uptake of knowledge translation interventions.</p> <p>Objectives</p> <p>Our specific aims include: To collect social network data among staff in two long-term care (LTC) facilities; to characterize social networks in these units; and to describe how social networks influence uptake and use of feedback reports.</p> <p>Methods and design</p> <p>In this prospective study, we will collect data on social networks in nursing units in two LTC facilities, and use social network analysis techniques to characterize and describe the networks. These data will be combined with data from a funded project to explore the impact of social networks on uptake and use of feedback reports. In this parent study, feedback reports using standardized resident assessment data are distributed on a monthly basis. Surveys are administered to assess report uptake. In the proposed project, we will collect data on social networks, analyzing the data using graphical and quantitative techniques. We will combine the social network data with survey data to assess the influence of social networks on uptake of feedback reports.</p> <p>Discussion</p> <p>This study will contribute to understanding mechanisms for knowledge sharing among staff on units to permit more efficient and effective intervention design. A growing number of studies in the social network literature suggest that social networks can be studied not only as influences on knowledge translation, but also as possible mechanisms for fostering knowledge translation. This study will contribute to building theory to design such interventions.</p

Exposure and impact of a mass media campaign targeting sexual health amongst Scottish men who have sex with men: an outcome evaluation

Background: This paper explores the exposure and impact of a Scottish mass media campaign: Make Your Position Clear. It ran from October 2009 to July 2010, targeted gay men and other men who have sex with men (MSM), and had two key aims: to promote regular sexual health and HIV testing every 6 months, and to promote the use of appropriate condoms and water-based lubricant with each episode of anal intercourse. Methods: A cross-sectional survey (anonymous and self-report) was conducted 10 months after the campaign was launched (July 2010). Men were recruited from commercial venues. Outcome measures included use of lubricant, testing for sexually transmitted infections and HIV, and intentions to seek HIV testing within the following six months. Linear-by-linear chi-square analysis and binary logistic regressions were conducted to explore the associations between the outcome measures and campaign exposure. Results: The total sample was 822 men (62.6% response rate). Men self-identifying as HIV positive were excluded from the analysis (n = 38). Binary logistic analysis indicated that those with mid or high campaign exposure were more likely to have been tested for HIV in the previous six months when adjusted for age, area of residence and use of the “gay scene” (AOR = 1.96, 95% CI = 1.26 to 3.06, p = .003), but were not more likely to be tested for STIs (AOR = 1.37, 95% CI = 0.88 to 2.16, p = .167). When adjusted for previous HIV testing, those with mid or high campaign exposure were not more likely to indicate intention to be tested for HIV in the following six months (AOR = 1.30, 95% CI = 0.73 to 2.32, p = .367). Those with no campaign exposure were less likely than those with low exposure to have used appropriate lubricant with anal sex partners in the previous year (AOR = 0.42, 95% CI = 0.23 to 0.77, p = .005). Conclusions: The campaign had demonstrable reach. The analysis showed partial support for the role of mass media campaigns in improving sexual health outcomes. This suggests that a role for mass media campaigns remains within combination HIV prevention