Evidence map›Paper›PMID 39790472›Full record

ArticleJournal of clinical and translational science2024

Facilitating multidisciplinary working groups in translational research: Strategies to promote cross-center collaboration and sustain the Cancer Center Cessation Initiative Consortium.

Mara Minion, Betsy Rolland

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Mara MinionCenter for Tobacco Research & Intervention, University of Wisconsin-Madison, Madison, WI, USA.
Betsy RollandCarbone Cancer Center, University of Wisconsin-Madison, Madison, WI, USA.ORCID https://orcid.org/0000-0002-4947-988X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As funding for large translational research consortia increases across the National Institutes of Health (NIH), focused working groups provide an opportunity to leverage the power of unique networks to conduct high-impact science and offer a strategy for building collaborative infrastructure to sustain networks long-term. This sustainment leverages the existing NIH investments, amplifying the impact and creating conditions for future innovative translational research. However, few resources exist that detail practical strategies for establishing and sustaining working groups in consortia. Here, we describe how the Coordinating Center for the National Cancer Institute-funded Cancer Center Cessation Initiative (C3I) utilized principles derived from the Science of Team Science to develop replicable strategies for building and sustaining an effective working group-led consortium. These strategies include continually engaging community members in strategic planning, prioritizing diversity in leadership and membership, creating multi-level opportunities for leadership and participation, providing intensive community management and facilitation, and incentivizing projects that support the consortium sustainment. When assessing the impact of these interventions through qualitative exit interviews, four key themes emerged: through the C3I working group consortium, members co-created new dissemination products, gained new insights and innovations, enhanced local program implementation, and invested in cross-network collaboration to support sustained engagement in the initiative.

Indexed as

best practicescollaborationteam scienceWorking groups

Identifiers

PMID39790472
PMCPMC11713431

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.