Alexandra Marin

Simplifying the Personal Network Name Generator: Alternatives to Traditional Multiple and Single Name Generators

Researchers studying personal networks often collect network data using name generators and name interpreters. We argue that when studying social support, multiple name generators ensure that researchers sample from a multidimensional definition of support. However, because administering multiple name generators is time consuming and strains respondent motivation, researchers often use single name generators. We compared network measures obtained from single generators to measures obtained from a six-item multiple-name generator. Although some single generators provided passable estimates of some measures, no single generator provided reliable estimates across a broad spectrum of network measures. We then evaluated two alternative methods of reducing respondent burden: (1) the MMG, a multiple generator using the two most robust name generators and (2) the MGRI, a six-item name generator with name interpreters administered for a random subset of alters. Both the MMG and the MGRI were more reliable than single generators when measuring size, density, and mean measures of network composition or activity, though some single name generators were more reliable for measures consisting of sums or counts.

Don't Mention It: Why People Don't Share Job Information, When They Do, and Why it Matters

Abstract Network-based job search is especially likely to foster workplace segregation and limit status attainment when information flows through homophilous ties. This paper takes the perspective of information holders and examines how the use of strong versus weak ties – which tend to be homophilous and heterophilous, respectively – differs with characteristics of labour markets in which jobs are located. Using in-depth interviews with entry-level white collar workers I show that information holders with opportunities to mention specific jobs to specific people do so only 27% of the time. Because they hesitate to share information if they are uncertain the information is specifically sought, information flows more commonly to strong ties, whose career goals are more likely to be known. Information is more likely to be shared with weak ties if it concerns occupations for which one may be specifically credentialed, since receiving relevant training serves as signal of interest in such jobs. These finding suggest that the homophily of referrals and their inequality-generating effects may vary across occupations.

Social and organizational factors affecting implementation of evidence-informed practice in a public health department in Ontario: a network modelling approach

ObjectiveThe objective of this study is to develop a statistical model to assess factors associated with information seeking in a Canadian public health department.MethodsManagers and professional consultants of a public health department serving a large urban population named whom they turned to for help, whom they considered experts in evidence-informed practice, and whom they considered friends. Multilevel regression analysis and exponential random graph modeling were used to predict the formation of information seeking and expertise-recognition connections by personal characteristics of the seeker and source, and the structural attributes of the social networks.ResultsThe respondents were more likely to recognize the members of the supervisory/administrative division as experts. The extent to which an individual implemented evidence-based practice (EBP) principles in daily practice was a significant predictor of both being an information source and being recognized as expert by peers. Friendship was a significant predictor of both information seeking and expertise-recognition connections.ConclusionThe analysis showed a communication network segregated by organizational divisions. Managers were identified frequently as information sources, even though this is not a part of their formal role. Self-perceived implementation of EBP in practice was a significant predictor of being an information source or an expert, implying a positive atmosphere towards implementation of evidence-informed decision making in this public health organization. Results also implied that the perception of accessibility and trust were significant predictors of expertise recognition.

The evolution of social networks through the implementation of evidence-informed decision-making interventions: a longitudinal analysis of three public health units in Canada

BackgroundWe studied the evolution of information-seeking networks over a 2-year period during which an organization-wide intervention was implemented to promote evidence-informed decision-making (EIDM) in three public health units in Ontario, Canada. We tested whether engagement of staff in the intervention and their EIDM behavior were associated with being chosen as information source and how the trend of inter-divisional communications and the dominance of experts evolved over time.MethodsLocal managers at each health unit selected a group of staff to get engage in Knowledge Broker-led workshops and development of evidence summaries to address local public health problems. The staff were invited to answer three online surveys (at baseline and two annual follow-ups) including name generator questions eliciting the list of the staff they would turn to for help integrating research evidence into practice. We used stochastic actor-oriented modeling to study the evolution of networks. We tested the effect of engagement in the intervention, EIDM behavior scores, organizational divisions, and structural dynamics of social networks on the tendency of staff to select information sources, and the change in its trend between year 1 and year 2 of follow-up.ResultsIn all the three health units, and especially in the two units with higher levels of engagement in the intervention, the network evolved towards a more centralized structure, with an increasing significance of already central staff. The staff showed greater tendencies to seek information from peers with higher EIDM behavior scores. In the public health unit that had highest engagement and stronger leadership support, the engaged staff became more central. In all public health units, the engaged staff showed an increasing tendency towards forming clusters. The staff in the three public health units showed a tendency towards limiting their connections within their divisions.ConclusionsThe longitudinal analysis provided us with a means to study the microstructural changes in public health units, clues to the sustainability of the implementation. The hierarchical transformation of networks towards experts and formation of clusters among staff who were engaged in the intervention show how implementing organizational interventions to promote EIDM may affect the knowledge flow and distribution in health care communities, which may lead to unanticipated consequences.

Informing the implementation of evidence-informed decision making interventions using a social network analysis perspective; a mixed-methods study

BackgroundWorkforce development is an important aspect of evidence-informed decision making (EIDM) interventions. The structure of formal and informal social networks can influence, and be influenced, by the implementation of EIDM interventions.MethodsIn a mixed methods study we assessed the outcomes of a targeted training intervention to promote EIDM among the staff in three public health units in Ontario, Canada. This report focuses on the qualitative phase of the study in which key staff were interviewed about the process of engagement in the intervention, communications during the intervention, and social consequences.ResultsSenior managers identified staff to take part in the intervention. Engagement was a top-down process determined by the way organizational leaders promoted EIDM and the relevance of staff’s jobs to EIDM. Communication among staff participating in the workshops and ongoing progress meetings was influential in overcoming personal and normative barriers to implementing EIDM, and promoted the formation of long-lasting social connections among staff. Organization-wide presentations and meetings facilitated the recognition of expertise that the trained staff gained, including their reputation as experts according to their peers in different divisions.ConclusionSelective training and capacity development interventions can result in forming an elite versus ordinary pattern that facilitates the recognition of in-house qualified experts while also strengthening social status inequality. The role of leadership in public health units is pivotal in championing and overseeing the implementation process. Network analysis can guide and inform the design, process, and evaluation of the EIDM training interventions.

Diffusion of Innovations model helps interpret the comparative uptake of two methodological innovations: co-authorship network analysis and recommendations for the integration of novel methods in practice

OBJECTIVE The objective of this study was to characterize the diffusion of methodological innovation. STUDY DESIGN AND SETTING Comparative case study analysis of the diffusion of two methods that summarize confounder information into a single score: disease risk score (DRS) and high-dimensional propensity score (hdPS). We completed systematic searches to identify DRS and hdPS papers in the field of pharmacoepidemiology through to the end of 2013, plotted the number of papers and unique authors over time, and created sociograms and animations to visualize co-authorship networks. First and last author affiliations were used to ascribe institutional contributions to each paper and network. RESULTS We identified 43 DRS papers by 153 authors since 1981, reflecting slow uptake during initial periods of uncertainty and broader diffusion since 2001 linked to early adopters from Vanderbilt. We identified 44 hdPS papers by 147 authors since 2009, reflecting rapid and integrated diffusion, likely facilitated by opinion leaders, early presentation at conferences, easily accessible statistical code, and improvement in funding. Most contributions (87% DRS, 96% hdPS) were from North America. CONCLUSION When proposing new methods, authors are encouraged to consider innovation attributes and early evaluation to improve knowledge translation of their innovations for integration into practice, and we provide recommendations for consideration.

The Relationship Between the Position of Name Generator Questions and Responsiveness in Multiple Name Generator Surveys

Using randomly ordered name generators, we tested the effect of name generators’ relative position on the likelihood of respondents’ declining to respond or satisficing in their response. An online survey of public health staff elicited names of information sources, information seekers, perceived experts, and friends. Results show that when name generators are asked later, they are more likely to go unanswered and respondents are more likely to respond that they do not know anyone or list fewer names. The effect of sequence was not consistent in different question types, which could be the result of the moderating effect of willingness to answer and question sensitivity.

Implementation of evidence-informed practice through central network actors; a case study of three public health units in Canada

BackgroundWorkforce development is an important aspect of evidence-informed decision making (EIDM) interventions. The social position of individuals in formal and informal social networks, and the relevance of formal roles in relation to EIDM are important factors identifying key EIDM players in public health organizations. We assessed the role of central actors in information sharing networks in promoting the adoption of EIDM by the staff of three public health units in Canada, over a two-year period during which an organization-wide intervention was implemented.MethodsA multi-faceted and tailored intervention to train select staff applying research evidence in practice was implemented in three public health units in Canada from 2011 to 2013. Staff (n = 572) were asked to identify those in the health unit whom they turned to get help using research in practice, whom they considered as experts in EIDM, and friends. We developed multi-level linear regression models to predict the change in EIDM behavior scores predicted by being connected to peers who were central in networks and were engaged in the intervention.ResultsOnly the group of highly engaged central actors who were connected to each other, and the staff who were not engaged in the intervention but were connected to highly engaged central actors significantly improved their EIDM behavior scores. Among the latter group, the staff who were also friends with their information sources showed a larger improvement in EIDM behavior.ConclusionsIf engaged, central network actors use their formal and informal connections to promote EIDM. Central actors themselves are more likely to adopt EIDM if they communicate with each other. These social communications should be reinforced and supported through the implementation of training interventions as a means to promoting EIDM.

Social Network Analysis: An Example of Fusion Between Quantitative and Qualitative Methods

A quantitative approach to social network analysis involves the application of mathematical and statistical techniques and graphical presentation of results. Nonetheless—as with all sciences—subjectivity is an integral aspect of network analysis, manifested in the selection of measures to describe connection patterns and actors’ positions (e.g., choosing a centrality indicator), in the visualization of social structure in graphs, and in translating numbers into words (telling the story). Here, we use network research as an example to illustrate how quantitative and qualitative approaches, techniques, and data are mixed along a continuum of fusion between quantitative and qualitative realms.