Browse
Submit Data
Databases
API
Help

Dataset Information

21 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

What does team science look like across the CTSA consortium? A qualitative analysis of the Great CTSA Team Science Contest submissions.

ABSTRACT:

Introduction

The Great CTSA Team Science Contest (GTSC) was developed to discover how Clinical and Translational Science Award (CTSA) hubs promote and support team science [1]. The purpose of this study was a secondary qualitative analysis of the GTSC submissions to better understand the diversity of team science initiatives across the CTSA consortium.

Methods

Secondary qualitative analysis of the GTSC data addressed the following research questions, which defined the top-level coding: (1) What CTSA component sponsored it? (2) Who was the team doing the work? (3) Who were the intended beneficiaries? (4) What was the intended outcome? (5) What strategies did they use? (6) What translational science (TS) stage was addressed? (7) How do they align with the NCATS team science strategic goals? (8) How do the CTSA's team science efforts align with the National Academies Research Council (NRC) recommendations for enhancing the effectiveness of team science?

Results

The GTSC received 170 submissions from 45 unique CTSA hubs. Qualitative analysis revealed a great variety of team science strategies for virtually all team science stakeholders. In addition to strategies to promote team science, results show successful examples that focus on outcomes and illustrate ways of measuring success.

Conclusions

The GTSC shows that the CTSA consortium is involved in an extremely diverse array of team science activities, which align well with both the NRC recommendations for enhancing the effectiveness of team science and the NCATS strategic goals for team science. Future research should evaluate the efficacy of team science strategies.

SUBMITTER: Pelfrey CM

PROVIDER: S-EPMC8411266 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Dissemination and implementation science activities across the Clinical Translational Science Award (CTSA) Consortium: Report from a survey of CTSA leaders.

Project description:IntroductionDissemination and implementation (D&I) science is not a formal element of the Clinical Translational Science Award (CTSA) Program, and D&I science activities across the CTSA Consortium are largely unknown.MethodsThe CTSA Dissemination, Implementation, and Knowledge Translation Working Group surveyed CTSA leaders to explore D&I science-related activities, barriers, and needed supports, then conducted univariate and qualitative analyses of the data.ResultsOut of 67 CTSA leaders, 55.2% responded. CTSAs reported directly funding D&I programs (54.1%), training (51.4%), and projects (59.5%). Indirect support (e.g., promoted by CTSA without direct funding) for D&I activities was higher - programs (70.3%), training (64.9%), and projects (54.1%). Top barriers included funding (39.4%), limited D&I science faculty (30.3%), and lack of D&I science understanding (27.3%). Respondents (63.4%) noted the importance of D&I training and recommended coordination of D&I activities across CTSAs hubs (33.3%).ConclusionThese findings should guide CTSA leadership in efforts to raise awareness and advance the role of D&I science in improving population health.

| S-EPMC7348014 | biostudies-literature

Implementing Common Metrics across the NIH Clinical and Translational Science Awards (CTSA) consortium.

Project description:The Clinical and Translational Science Award (CTSA) Consortium and the National Center for Advancing Translational Science (NCATS) undertook a Common Metrics Initiative to improve research processes across the national CTSA Consortium. This was implemented by Tufts Clinical and Translational Science Institute at the 64 CTSA academic medical centers. Three metrics were collaboratively developed by NCATS staff, CTSA Consortium teams, and outside consultants for Institutional Review Board Review Duration, Careers in Clinical and Translational Research, and Pilot Award Publications and Subsequent Funding. The implementation program included training on the metric operational guidelines, data collection, data reporting system, and performance improvement framework. The implementation team provided small-group coaching and technical assistance. Collaborative learning sessions, driver diagrams, and change packages were used to disseminate best and promising practices. After 14 weeks, 84% of hubs had produced a value for one metric and about half had produced an initial improvement plan. Overall, hubs reported that the implementation activities facilitated their Common Metrics performance improvement process. Experiences implementing the first three metrics can inform future directions of the Common Metrics Initiative and other research groups implementing standardized metrics and performance improvement processes, potentially including other National Institutes of Health institutes and centers.

| S-EPMC7103469 | biostudies-literature

Evaluation of initial progress to implement Common Metrics across the NIH Clinical and Translational Science Awards (CTSA) Consortium.

Project description:IntroductionThe Clinical and Translational Science Awards (CTSA) Consortium, about 60 National Institutes of Health (NIH)-supported CTSA hubs at academic health care institutions nationwide, is charged with improving the clinical and translational research enterprise. Together with the NIH National Center for Advancing Translational Sciences (NCATS), the Consortium implemented Common Metrics and a shared performance improvement framework.MethodsInitial implementation across hubs was assessed using quantitative and qualitative methods over a 19-month period. The primary outcome was implementation of three Common Metrics and the performance improvement framework. Challenges and facilitators were elicited.ResultsAmong 59 hubs with data, all began implementing Common Metrics, but about one-third had completed all activities for three metrics within the study period. The vast majority of hubs computed metric results and undertook activities to understand performance. Differences in completion appeared in developing and carrying out performance improvement plans. Seven key factors affected progress: hub size and resources, hub prior experience with performance management, alignment of local context with needs of the Common Metrics implementation, hub authority in the local institutional structure, hub engagement (including CTSA Principal Investigator involvement), stakeholder engagement, and attending training and coaching.ConclusionsImplementing Common Metrics and performance improvement in a large network of research-focused organizations proved feasible but required substantial time and resources. Considerable heterogeneity across hubs in data systems, existing processes and personnel, organizational structures, and local priorities of home institutions created disparate experiences across hubs. Future metric-based performance management initiatives across heterogeneous local contexts should anticipate and account for these types of differences.

| S-EPMC8057371 | biostudies-literature

Reward and punishment in a team contest.

Project description:A team contest entails both public good characteristics within the teams as well as a contest across teams. In an experimental study, we analyse behaviour in such a team contest when allowing to punish or to reward other team members. Moreover, we compare two types of contest environment: One in which two teams compete for a prize and another one in which we switch off the between-group element of the contest. We find that reward giving, as opposed to punishing, induces higher contributions to the team contest. Furthermore, expenditures on rewarding other co-players are significantly higher than those for punishing.

| S-EPMC7498014 | biostudies-literature

Team science for science communication.

Project description:Natural scientists from Climate Central and social scientists from Carnegie Mellon University collaborated to develop science communications aimed at presenting personalized coastal flood risk information to the public. We encountered four main challenges: agreeing on goals; balancing complexity and simplicity; relying on data, not intuition; and negotiating external pressures. Each challenge demanded its own approach. We navigated agreement on goals through intensive internal communication early on in the project. We balanced complexity and simplicity through evaluation of communication materials for user understanding and scientific content. Early user test results that overturned some of our intuitions strengthened our commitment to testing communication elements whenever possible. Finally, we did our best to negotiate external pressures through regular internal communication and willingness to compromise.

| S-EPMC4183174 | biostudies-other

Great cities look small.

Project description:Great cities connect people; failed cities isolate people. Despite the fundamental importance of physical, face-to-face social ties in the functioning of cities, these connectivity networks are not explicitly observed in their entirety. Attempts at estimating them often rely on unrealistic over-simplifications such as the assumption of spatial homogeneity. Here we propose a mathematical model of human interactions in terms of a local strategy of maximizing the number of beneficial connections attainable under the constraint of limited individual travelling-time budgets. By incorporating census and openly available online multi-modal transport data, we are able to characterize the connectivity of geometrically and topologically complex cities. Beyond providing a candidate measure of greatness, this model allows one to quantify and assess the impact of transport developments, population growth, and other infrastructure and demographic changes on a city. Supported by validations of gross domestic product and human immunodeficiency virus infection rates across US metropolitan areas, we illustrate the effect of changes in local and city-wide connectivities by considering the economic impact of two contemporary inter- and intra-city transport developments in the UK: High Speed 2 and London Crossrail. This derivation of the model suggests that the scaling of different urban indicators with population size has an explicitly mechanistic origin.

| S-EPMC4535402 | biostudies-literature

Fluctuating Team Science: Perceiving Science as Collaborative Improves Science Motivation.

Project description: Not available

| S-EPMC6284825 | biostudies-literature

Toward a translational team science hierarchy of needs: Exploring the information management challenges of team science.

Project description:BackgroundClinical and Translational Research (CTR) requires a team-based approach, with successful teams engaging in skilled management and use of information. Yet we know little about the ways that Translational Teams (TTs) engage with information across the lifecycle of CTR projects. This qualitative study explored the challenges that information management imposes on the conduct of team-based CTR.MethodsWe conducted interviews with ten members of TTs at University of Wisconsin. Interviews were transcribed and thematic analysis was conducted.ResultsTTs' piecemeal and reactive approaches to information management created conflict within the team and slowed scientific progress. The lack of cohesive information management strategies made it more difficult for teams to develop strong team processes like communication, scientific coordination, and project management. While TTs' research was hindered by the institutional challenges of interdisciplinary team information sharing, TTs who had developed shared approaches to information management that foregrounded transparency, accountability, and trust, described substantial benefits to their teamwork.ConclusionWe propose a new model for the Science of Team Science field - a Translational Team Science Hierarchy of Needs - that suggests interventions should be targeted at the appropriate stage of team development in order to maximize a team's scientific potential.

| S-EPMC10603362 | biostudies-literature

Research coordinator networks and support models among academic health centers in the CTSA consortium.

Project description:IntroductionResearch coordinators (RCs) are vital to the clinical research enterprise, ensuring research is conducted ethically, results are scientifically sound and human research subjects are protected. Given the absence of a prior systematic inquiry, we sought to understand the ways in which Clinical & Translational Science Award-funded academic health centers support RCs.MethodsOur survey asked questions about existing coordinator networks and where none existed, collected data on the characterization of resources and services provided to support RCs (outside of salary).ResultsFindings show 4 mechanisms support RCs: identification of the workforce, professionalization of the position, dissemination of information, and offering of services.ConclusionAn academic health center that wishes to deliver research training and services to their RC workforce will need identification and communication structures in place before supportive activities can be effectively implemented.

| S-EPMC5915804 | biostudies-literature

Gender Differences in Grant Submissions across Science and Engineering Fields at the NSF.

Project description:There has been great growth in women's participation in the US academic doctoral workforce, but underrepresentation remains in all science and engineering fields, especially at high academic ranks. We obtained estimates of the numbers of professorial women and men in fields likely to seek funding from the National Science Foundation and aligned those numbers with each of six research directorates to investigate temporal trends in submission patterns. We found that women are as likely to be funded as men, but the percentage of women submitting proposals was less than expected in every field but engineering. Women are as likely as men to be employed at the most research active institutions, but women are less likely than men to self-report research as their primary work activity in almost all fields but engineering. This work imbalance ultimately limits the diversity of basic science research ideas in science and engineering.

| S-EPMC7498325 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data