Facilitators of Multisector Collaboration for Delivering Cancer Control Interventions in Rural Communities: A Descriptive Qualitative Study.

PURPOSE AND OBJECTIVES: Multisector collaboration is a widely promoted strategy to increase equitable availability, access, and use of healthy foods, safe places for physical activity, social supports, and preventive health care services. Yet fewer studies and resources exist for collaboration among governmental and nongovernmental agencies to address public problems in rural areas, despite an excess burden of risk factors for cancer morbidity and mortality. We aimed to learn about cancer prevention activities and collaboration facilitators among rural informal interagency networks. EVALUATION METHODS: In 2020, researchers conducted semistructured interviews with staff from rural public health and social services agencies, community health centers, and extension offices. Agency staff were from 5 service areas across 27 rural counties in Missouri and Illinois with high poverty rates and excess cancer risks and mortality. We conducted a thematic analysis to code interview transcripts and identify key themes. RESULTS: Exchanging information, cohosting annual or one-time events, and promoting other agencies' services and programs were the most commonly described collaborative activities among the 32 participants interviewed. Participants indicated a desire to improve collaborations by writing more grants together to codevelop ongoing prevention programs and further share resources. Participants expressed needs to increase community outreach, improve referral systems, and expand screenings. We identified 5 facilitator themes: commitment to address community needs, mutual willingness to collaborate, long-standing relationships, smaller community structures, and necessity of leveraging limited resources. Challenges included lack of funding and time, long travel distances, competing priorities, difficulty replacing staff in remote communities, and jurisdictional boundaries. Although the COVID-19 pandemic further limited staff availability for collaboration, participants noted benefits of remote collaborative meetings. IMPLICATIONS FOR PUBLIC HEALTH: Rural areas need consistent funding and other resources to support health-improving multisector initiatives. Existing strengths found in the rural underresourced areas can facilitate multisector collaborations for cancer prevention, including long-standing relationships, small community structures, and the need to leverage limited resources.

Evaluation of the Implementation Research Institute: Trainees' Publications and Grant Productivity.

With growth in the field of dissemination and implementation (D&I) research, there has been growth in capacity building, with many training opportunities. As such, it is important to continue to evaluate D&I research training programs. This paper reports the results of an evaluation of the Implementation Research Institute (IRI), a R25 funded by the National Institute of Mental Health with additional funding by the Department of Veterans Affairs (VA). The fourth cohort also had a supplement from the National Institute on Drug Abuse. Using bibliometrics data, we report on a quasi-experimental retrospective cohort study assessing whether the rates of scholarly productivity in D&I science of IRI fellows (those who applied and were accepted to the training) were greater than those who applied but were not accepted to IRI. Our findings show that Selected Applicants' odds of publishing in implementation science were higher for earlier alumni, starting at 12% 1 year out and increasing to 94% for those who were 4 years out from starting training. Chances for Non-Selected Applicants remained relatively stable, starting at 47% at 1 year and going to 33% at 4 years since their application, a pattern that was stable even after controlling for demographic characteristics. These results support the hypothesis that IRI is increasing the D&I research productivity of those selected to the program, and that our fellows are advancing the field of D&I compared to those investigators not selected to our institute. Our finding also indicates the importance of a 2-year training.

Multisector Health Policy Networks in 15 Large US Cities.

CONTEXT: Local health departments (LHDs) have historically not prioritized policy development, although it is one of the 3 core areas they address. One strategy that may influence policy in LHD jurisdictions is the formation of partnerships across sectors to work together on local public health policy. DESIGN: We used a network approach to examine LHD local health policy partnerships across 15 large cities from the Big Cities Health Coalition. SETTING/PARTICIPANTS: We surveyed the health departments and their partners about their working relationships in 5 policy areas: core local funding, tobacco control, obesity and chronic disease, violence and injury prevention, and infant mortality. OUTCOME MEASURES: Drawing on prior literature linking network structures with performance, we examined network density, transitivity, centralization and centrality, member diversity, and assortativity of ties. RESULTS: Networks included an average of 21.8 organizations. Nonprofits and government agencies made up the largest proportions of the networks, with 28.8% and 21.7% of network members, whereas for-profits and foundations made up the smallest proportions in all of the networks, with just 1.2% and 2.4% on average. Mean values of density, transitivity, diversity, assortativity, centralization, and centrality showed similarity across policy areas and most LHDs. The tobacco control and obesity/chronic disease networks were densest and most diverse, whereas the infant mortality policy networks were the most centralized and had the highest assortativity. Core local funding policy networks had lower scores than other policy area networks by most network measures. CONCLUSION: Urban LHDs partner with organizations from diverse sectors to conduct local public health policy work. Network structures are similar across policy areas jurisdictions. Obesity and chronic disease, tobacco control, and infant mortality networks had structures consistent with higher performing networks, whereas core local funding networks had structures consistent with lower performing networks.

Using organizational network analysis to plan cancer screening programs for vulnerable populations.

OBJECTIVES: We examined relationships among organizations in a cancer screening network to inform the development of interventions to improve cancer screening for South Asians living in the Peel region of Ontario. METHODS: From April to July 2012, we surveyed decision-makers, program managers, and program staff in 22 organizations in the South Asian cancer screening network in the Peel region. We used a network analytic approach to evaluate density (range = 0%-100%, number of ties among organizations in the network expressed as a percentage of all possible ties), centralization (range = 0-1, the extent of variability in centrality), and node characteristics for the communication, collaboration, and referral networks. RESULTS: Density was similar across communication (15%), collaboration (17%), and referral (19%) networks. Centralization was greater in the collaboration network (0.30) than the communication network (0.24), and degree centralization was greater in the inbound (0.42) than the outbound (0.37) referral network. Diverse organizations were central to the networks. CONCLUSIONS: Certain organizations were unexpectedly important to the South Asian cancer screening network. Program planning was informed by identifying opportunities to strengthen linkages between key organizations and to leverage existing ties.

Changes in Harm Perception for E-Cigarettes Among Youth in the United States, 2014-2019.

PURPOSE: To evaluate the trend of harm perception for e-cigarettes and the trend of the association between harm perception for e-cigarettes and for cigarettes among US youth from 2014 to 2019. DESIGN, SETTING AND SUBJECTS: The National Youth Tobacco Survey is an annual, cross-sectional, school-based survey done among youth selected using three-stage probability sampling. ANALYSIS: Data were drawn from the 2014 to 2019 Surveys. A Multinomial logistic regression model was used to assess the association between harm perception for e-cigarettes and harm perception for cigarettes for each year. RESULTS: The percentage of youth who perceived e-cigarettes as harmless decreased from 2014 to 2019 (17.2% to 5.8%). From 2015 to 2018, the percentage of smokers who perceived e-cigarettes as a little harmful increased (33.6% to 41.2%). The positive association between harm perception for e-cigarettes and harm perception for cigarettes became stronger with time. In 2014, the odds of perceiving e-cigarettes as harmless relative to very harmful were 19.55 times greater for youth who perceived cigarettes as harmless, compared to those who perceived cigarettes as very harmful (OR = 19.55; 95% CI: 14.19-26.94). These odds increased to 77.65 times in 2019 (OR = 77.65; 95% CI: 41.48-107.85). CONCLUSION: This study suggests a stronger relationship between perceived harm of cigarettes and e-cigarettes with time. Interventions to prevent smoking have the potential to change e-cigarette use.

Introducing SoNHR-Reporting guidelines for Social Networks In Health Research.

OBJECTIVE: The overall goal of this work is to produce a set of recommendations (SoNHR-Social Networks in Health Research) that will improve the reporting and dissemination of social network concepts, methods, data, and analytic results within health sciences research. METHODS: This study used a modified-Delphi approach for recommendation development consistent with best practices suggested by the EQUATOR health sciences reporting guidelines network. An initial set of 28 reporting recommendations was developed by the author team. A group of 67 (of 147 surveyed) experienced network and health scientists participated in an online feedback survey. They rated the clarity and importance of the individual recommendations, and provided qualitative feedback on the coverage, usability, and dissemination opportunities of the full set of recommendations. After examining the feedback, a final set of 18 recommendations was produced. RESULTS: The final SoNHR reporting guidelines are comprised of 18 recommendations organized within five domains: conceptualization (how study research questions are linked to network conceptions or theories), operationalization (how network science portions of the study are defined and operationalized), data collection & management (how network data are collected and managed), analyses & results (how network results are analyzed, visualized, and reported), and ethics & equity (how network-specific human subjects, equity, and social justice concerns are reported). We also present a set of exemplar published network studies which can be helpful for seeing how to apply the SoNHR recommendations in research papers. Finally, we discuss how different audiences can use these reporting guidelines. CONCLUSIONS: These are the first set of formal reporting recommendations of network methods in the health sciences. Consistent with EQUATOR goals, these network reporting recommendations may in time improve the quality, consistency, and replicability of network science across a wide variety of important health research areas.

Sustainability determinants of an intervention to identify clinical deterioration and improve childhood cancer survival in Latin American hospitals: the INSPIRE study protocol.

BACKGROUND: More than 90% of children with cancer live in low-resourced settings, where survival is only 20%. Sustainable evidence-based (EB) interventions yielding ongoing beneficial patient outcomes are critical to improve childhood cancer survival. A better understanding of factors promoting intervention sustainability in these settings is urgently needed. The aim of this study is to provide an empirical understanding of how clinical capacity for sustainability, or the resources needed to sustain an intervention, impacts the sustainment of Pediatric Early Warning System (PEWS), an EB intervention that improves pediatric oncology outcomes in low-resource hospitals by detecting clinical deterioration and preventing the need for more intense treatment. METHODS: We will conduct a prospective, longitudinal study of approximately 100 resource-variable hospitals implementing and sustaining PEWS participating in Proyecto EVAT, a quality improvement collaborative of Latin American pediatric oncology centers. Aim 1: We will evaluate how clinical capacity for sustainability changes over time through 5 to 9 prospective measurements of capacity via survey of clinical staff using PEWS (approximately n = 13 per center) during the phases of PEWS adoption, implementation, and sustainability using the Clinical Sustainability Assessment Tool (CSAT). Aim 2: We will determine the relationship between capacity and a) PEWS sustainment and b) clinical deterioration mortality among pediatric oncology patients at centers sustaining PEWS for 2 to 10 years using chart review and an existing patient outcomes registry. Aim 3: We will develop novel strategies to promote sustainability by gaining a deeper understanding of perceived challenges to building capacity and PEWS sustainment. In combination with quantitative outcomes, we will conduct 24 focus groups with staff (doctors, nurses, and administrators) from hospitals with both high (n = 4) and low capacity (n = 4). We will then use implementation mapping to generate theoretically driven, empirically-supported sustainability strategies. DISCUSSION: This study will advance implementation science by providing a theoretically driven, foundational understanding of factors that predict sustainability among a large, diverse cohort of hospitals. We will then use this knowledge to develop sustainability evidence-informed strategies that optimize capacity and promote long-term sustainment of PEWS and improvements in patient outcomes, thus promoting equity in childhood cancer care globally.

Exempting casinos from the Smoke-free Illinois Act will not bring patrons back: they never left.

OBJECTIVE: The Smoke-free Illinois Act was implemented in January 2008, one month after the beginning of a national recession. In December 2010, the Illinois legislature proposed new legislation that would provide an exemption for casinos from the act until neighbouring states also implement smoke-free casino policies. Lobbyists and gaming commission representatives argued that Illinois casinos were losing patrons to casinos in neighbouring states that allow smoking. This study examined the influence of the act on casino admissions in Illinois and neighbouring states in light of the economy. METHODS: A multilevel model was developed to examine monthly casino admissions from January 2007 to December 2008. RESULTS: There was no difference in changes in admissions across the four states over time after accounting for the economic downturn. CONCLUSIONS: The Smoke-Free Illinois Act did not have a detectable effect on Illinois casino admissions.

Mapping the Lay of the Land: Using Interactive Network Analytic Tools for Collaboration in Rural Cancer Prevention and Control.

BACKGROUND: Cancer mortality rates in the United States are higher in rural than urban areas, especially for colorectal cancer. Modifiable cancer risks (e.g., tobacco use, obesity) are more prevalent among U.S. rural than urban residents. Social network analyses are common, yet rural informal collaborative networks for cancer prevention and control and practitioner uses of network findings are less well understood. METHODS: In five service areas in rural Missouri and Illinois, we conducted a network survey of informal multisector networks among agencies that address cancer risk (N = 152 individuals). The survey asked about contact, collaborative activities, and referrals. We calculated descriptive network statistics and disseminated network visualizations with rural agencies through infographics and interactive Network Navigator platforms. We also collected feedback on uses of network findings from agency staff (N = 14). RESULTS: Service areas had more connections (average degree) for exchanging information than for more time-intensive collaborative activities of co-developing and sustaining ongoing services and programs, and co-developing and sharing resources. On average, collaborative activities were not dependent on just a few agencies to bridge gaps to hold networks together. Users found the network images and information useful for identifying gaps, planning which relationships to establish or enhance to strengthen certain collaborative activities and cross-referrals, and showing network strengths to current and potential funders. CONCLUSIONS: Rural informal cancer prevention and control networks in this study are highly connected and largely decentralized. IMPACT: Disseminating network findings help ensure usefulness to rural health and social service practitioners who address cancer risks.

Referrals among cancer services organizations serving underserved cancer patients in an urban area.

Significant racial, socioeconomic, and geographic disparities exist nationwide in cancer screenings, treatments, and outcomes. Differences in health and social service provision and utilization may contribute to or exacerbate these disparities. We evaluated the composition and structure of a referral network of organizations providing services to underserved cancer patients in an urban area in 2007. We observed a need for increased awareness building among provider organizations, broader geographic coverage among organizations, and increased utilization of tobacco cessation and financial assistance services.

Demographic and geographic differences in exposure to secondhand smoke in Missouri workplaces, 2007-2008.

INTRODUCTION: African Americans, Hispanics, service and blue-collar workers, and residents of rural areas are among those facing higher rates of workplace secondhand smoke exposure in states without smokefree workplace laws. Consequently, these groups also experience more negative health effects resulting from secondhand smoke exposure. The objective of this study was to examine disparities in workplace secondhand smoke exposure in a state without a comprehensive statewide smokefree workplace law and to use this information in considering a statewide law. METHODS: We developed a logistic multilevel model by using data from a 2007-2008 county-level study to account for individual and county-level differences in workplace secondhand smoke exposure. We included sex, age, race, annual income, education level, smoking status, and rural or urban residence as predictors of workplace secondhand smoke exposure. RESULTS: Factors significantly associated with increased exposure to workplace secondhand smoke were male sex, lower education levels, lower income, living in a small rural or isolated area, and current smoking. For example, although the overall rate of workplace exposure in Missouri is 11.5%, our model predicts that among young white men with low incomes and limited education living in small rural areas, 40% of nonsmokers and 56% of smokers may be exposed to secondhand smoke at work. CONCLUSION: Significant disparities exist in workplace secondhand smoke exposure across Missouri. A statewide smokefree workplace law would protect all citizens from workplace secondhand smoke exposure.

Building the Next Generation of Researchers: Mentored Training in Dissemination and Implementation Science.

PROBLEM: Dissemination and implementation (D&I) science provides the tools needed to close the gap between known intervention strategies and their effective application. The authors report on the Mentored Training for Dissemination and Implementation Research in Cancer (MT-DIRC) program-a D&I training program for postdoctoral or early-career cancer prevention and control scholars. APPROACH: MT-DIRC was a 2-year training institute in which fellows attended 2 annual Summer Institutes and other conferences and received didactic, group, and individual instruction; individualized mentoring; and other supports (e.g., pilot funding). A quasi-experimental design compared changes in 3 areas: mentoring, skills, and network composition. To evaluate mentoring and D&I skills, data from fellows on their mentors' mentoring competencies, their perspectives on the importance of and satisfaction with mentoring priority areas, and their self-rated skills in D&I competency domains were collected. Network composition data were collected from faculty and fellows for 3 core social network domains: contact, mentoring, and collaboration. Paired t tests (mentoring), linear mixed models (skills), and descriptive analyses (network composition) were performed. OUTCOMES: Mentors were rated as highly competent across all mentoring competencies, and each mentoring priority area showed reductions in gaps between satisfaction and importance between the 6 and 18 months post-first Summer Institute. Fellows' self-rated skills in D&I competencies improved significantly in all domains over time (range: 42.5%-52.9% increase from baseline to 18 months post-first Summer Institute). Mentorship and collaboration networks grew over time, with the highest number of collaboration network ties for scholarly manuscripts (n = 199) in 2018 and for research projects (n = 160) in 2019. NEXT STEPS: Building on study findings and existing literature, mentored training of scholars is an important approach for building D&I skills and networks, and thus to better applying the vast amount of available intervention evidence to benefit cancer control.

Systems analysis of collaboration in 5 national tobacco control networks.

OBJECTIVES: We studied 5 members of the National Network Consortium on Tobacco Control in Priority Populations. These networks, which consist of governmental and nongovernmental organizations, targeted lesbian, gay, bisexual, and transgender persons; Asian Americans, Native Hawaiians, and Pacific Islanders; American Indians and Alaska Natives; African Americans; and persons with low socioeconomic status, respectively. METHODS: We used statistical network analysis modeling to examine collaboration among these national networks in 2007. RESULTS: Network size and composition varied, but all 5 networks had extensive interorganizational collaboration. Location and work area were significant predictors of collaboration among network members in all 5 networks. Organizations were more likely to collaborate with their network's lead agency; collaborations with other agencies were more likely if they were geographically close. Collaboration was perceived to be important for achieving the goals of the national network. CONCLUSIONS: The similarity of collaboration patterns across the 5 networks suggests common underlying partnership formation processes. Statistical network modeling promises to be a useful tool for understanding how public health systems such as networks and coalitions can be used to improve the nation's health.

Use of reproducible research practices in public health: A survey of public health analysts.

OBJECTIVE: Use of reproducible research practices improves the quality of science and the speed of scientific development. We sought to understand use of reproducible research practices in public health and associated barriers and facilitators. METHODS: In late 2017, we surveyed members of the American Public Health Association Applied Public Health Statistics section and others; 247 of 278 who screened eligible answered the survey, and 209 answered every applicable question. The survey included questions about file management, code annotation and documentation, reproducibility of analyses, and facilitators and barriers of using reproducible practices. RESULTS: Just 14.4% of participants had shared code, data, or both. Many participants reported their data (33%) and code (43.2%) would be difficult for colleagues to find if they left their institution. Top reported barriers to using reproducible practices were data privacy (49.8%) and lack of time (41.7%). Participants suggested training (50.9%) and requirements by journals (44.4%) and funders (40.2%) to increase use of reproducible research practices. CONCLUSIONS: Increasing use of reproducible research practices is important for public health and requires action from researchers, training programs, funders, and journals.

The Translational Science Benefits Model: A New Framework for Assessing the Health and Societal Benefits of Clinical and Translational Sciences.

We report the development of the Translational Science Benefits Model (TSBM), a framework designed to support institutional assessment of clinical and translational research outcomes to measure clinical and community health impacts beyond bibliometric measures. The TSBM includes 30 specific and potentially measurable indicators that reflect benefits that accrue from clinical and translational science research such as products, system characteristics, or activities. Development of the TSBM was based on literature review, a modified Delphi method, and in-house expert panel feedback. Three case studies illustrate the feasibility and face validity of the TSBM for identification of clinical and community health impacts that result from translational science activities. Future plans for the TSBM include further pilot testing and a resource library that will be freely available for evaluators, translational scientists, and academic institutions who wish to implement the TSBM framework in their own evaluation efforts.

The Structure of Policy Networks for Injury and Violence Prevention in 15 US Cities.

OBJECTIVES: Changes in policy can reduce violence and injury; however, little is known about how partnerships among organizations influence policy development, adoption, and implementation. To understand partnerships among organizations working on injury and violence prevention (IVP) policy, we examined IVP policy networks in 15 large US cities. METHODS: In summer 2014, we recruited 15 local health departments (LHDs) to participate in the study. They identified an average of 28.9 local partners (SD = 10.2) working on IVP policy. In late 2014, we sent survey questionnaires to 434 organizations, including the 15 LHDs and their local partners, about their partnerships and the importance of each organization to local IVP policy efforts; 319 participated. We used network methods to examine the composition and structure of the policy networks. RESULTS: Each IVP policy network included the LHD and an average of 21.3 (SD = 6.9) local partners. On average, nonprofit organizations constituted 50.7% of networks, followed by government agencies (26.3%), schools and universities (11.8%), coalitions (11.2%), voluntary organizations (9.6%), hospitals (8.5%), foundations (2.2%), and for-profit organizations (0.7%). Government agencies were perceived as important by the highest proportion of partners. Perceived importance was significantly associated with forming partnerships in most networks; odds ratios ranged from 1.07 (95% CI, 1.02-1.13) to 2.35 (95% CI, 1.68-3.28). Organization type was significantly associated with partnership formation in most networks after controlling for an organization's importance to the network. CONCLUSIONS: Several strategies could strengthen local IVP policy networks, including (1) developing connections with partners from sectors that are not well integrated into the networks and (2) encouraging indirect or less formal connections with important but missing partners and partner types.

Academic Cross-Pollination: The Role of Disciplinary Affiliation in Research Collaboration.

Academic collaboration is critical to knowledge production, especially as teams dominate scientific endeavors. Typical predictors of collaboration include individual characteristics such as academic rank or institution, and network characteristics such as a central position in a publication network. The role of disciplinary affiliation in the initiation of an academic collaboration between two investigators deserves more attention. Here, we examine the influence of disciplinary patterns on collaboration formation with control of known predictors using an inferential network model. The study group included all researchers in the Institute of Clinical and Translational Sciences (ICTS) at Washington University in St. Louis. Longitudinal data were collected on co-authorships in grants and publications before and after ICTS establishment. Exponential-family random graph models were used to build the network models. The results show that disciplinary affiliation independently predicted collaboration in grant and publication networks, particularly in the later years. Overall collaboration increased in the post-ICTS networks, with cross-discipline ties occurring more often than within-discipline ties in grants, but not publications. This research may inform better evaluation models of university-based collaboration, and offer a roadmap to improve cross-disciplinary collaboration with discipline-informed network interventions.

Forging a link between mentoring and collaboration: a new training model for implementation science.

BACKGROUND: Training investigators for the rapidly developing field of implementation science requires both mentoring and scientific collaboration. Using social network descriptive analyses, visualization, and modeling, this paper presents results of an evaluation of the mentoring and collaborations fostered over time through the National Institute of Mental Health (NIMH) supported by Implementation Research Institute (IRI). METHODS: Data were comprised of IRI participant self-reported collaborations and mentoring relationships, measured in three annual surveys from 2012 to 2014. Network descriptive statistics, visualizations, and network statistical modeling were conducted to examine patterns of mentoring and collaboration among IRI participants and to model the relationship between mentoring and subsequent collaboration. RESULTS: Findings suggest that IRI is successful in forming mentoring relationships among its participants, and that these mentoring relationships are related to future scientific collaborations. Exponential random graph network models demonstrated that mentoring received in 2012 was positively and significantly related to the likelihood of having a scientific collaboration 2 years later in 2014 (p = 0.001). More specifically, mentoring was significantly related to future collaborations focusing on new research (p = 0.009), grant submissions (p = 0.003), and publications (p = 0.017). Predictions based on the network model suggest that for every additional mentoring relationships established in 2012, the likelihood of a scientific collaboration 2 years later is increased by almost 7 %. CONCLUSIONS: These results support the importance of mentoring in implementation science specifically and team science more generally. Mentoring relationships were established quickly and early by the IRI core faculty. IRI fellows reported increasing scientific collaboration of all types over time, including starting new research, submitting new grants, presenting research results, and publishing peer-reviewed papers. Statistical network models demonstrated that mentoring was strongly and significantly related to subsequent scientific collaboration, which supported a core design principle of the IRI. Future work should establish the link between mentoring and scientific productivity. These results may be of interest to team science, as they suggest the importance of mentoring for future team collaborations, as well as illustrate the utility of network analysis for studying team characteristics and activities.

An Examination of Two Policy Networks Involved in Advancing Smokefree Policy Initiatives.

This study examines smokefree policy networks in two cities­Kansas City and St. Louis, Missouri­one that was successful in achieving widespread policy success, and one that was not. Descriptive social network analyses and visual network mapping were used to compare importance and contact relationships among actors involved in the smokefree policy initiatives. In Kansas City, where policy adoption was achieved, there was a higher level of connectivity among members, with network members being in contact with an average of more than five people, compared to just over two people for the St. Louis network. For both cities, despite being recognized as important, politicians were in contact with the fewest number of people. Results highlight the critical need to actively engage a variety of stakeholders when attempting city wide public health policy change. As evident by the success in smokefree policy adoption throughout Kansas City compared to St. Louis, closer linkages and continued communication among stakeholders including the media, coalitions, public health agencies, policymakers, and other partners are essential if we are to advance and broaden the impact of public health policy. Results indicate that the presence of champions, or those that play leadership roles in actively promoting policy by linking individuals and organizations, play an important role in advancing public health policy. Those working in public health should examine their level of engagement with the policy process and implement strategies for improving that engagement through relationship building and ongoing interactions with a variety of stakeholders, including policymakers.

Breaking down silos: mapping growth of cross-disciplinary collaboration in a translational science initiative.

The importance of transdisciplinary collaboration is growing, though not much is known about how to measure collaboration patterns. The purpose of this paper is to present multiple ways of mapping and evaluating the growth of cross-disciplinary partnerships over time. Social network analysis was used to examine the impact of a Clinical and Translational Science Award (CTSA) on collaboration patterns. Grant submissions from 2007 through 2010 and publications from 2007 through 2011 of Institute of Clinical and Translational Sciences (ICTS) members were examined. A Cohort Model examining the first-year ICTS members demonstrated an overall increase in collaborations on grants and publications, as well as an increase in cross-discipline collaboration as compared to within-discipline. A Growth Model that included additional members over time demonstrated the same pattern for grant submissions, but a decrease in cross-discipline collaboration as compared to within-discipline collaboration for publications. ICTS members generally became more cross-disciplinary in their collaborations during the CTSA. The exception of publications for the Growth Model may be due to the time lag between funding and publication, as well as pressure for younger scientists to publish in their own fields. Network analysis serves as a valuable tool for evaluating changes in scientific collaboration.