Evidence map›Paper›PMID 35321218›Full record

ArticleJournal of clinical and translational science2022

A network analysis of dissemination and implementation research expertise across a university: Central actors and expertise clusters.

Reza Yousefi Nooraie, Gretchen Roman, Kevin Fiscella, James M McMahon, Elissa Orlando, Nancy M Bennett

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

6 authors.

Reza Yousefi NooraieDepartment of Public Health Sciences, University of Rochester, Rochester, New York, USA.ORCID https://orcid.org/0000-0002-9002-7121
Gretchen RomanDepartment of Public Health Sciences, University of Rochester, Rochester, New York, USA.
Kevin FiscellaDepartment of Family Medicine, University of Rochester, Rochester, New York, USA.ORCID https://orcid.org/0000-0003-3613-8012
James M McMahonSchool of Nursing, University of Rochester, Rochester, New York, USA.
Elissa OrlandoClinical & Translational Science Institute, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA.
Nancy M BennettDepartment of Medicine, University of Rochester, Rochester, New York, USA.

Funding

The University of Rochester's Clinical and Translational Science InstituteUL1TR002001 · NCATS · UNIVERSITY OF ROCHESTER · PI WILSON, KAREN M., ZAND, MARTIN S · 2016 to 2024
$34.6M
NRSA Training CoreTL1TR002000 · NCATS · UNIVERSITY OF ROCHESTER · PI THAKAR, JUILEE, VAN WIJNGAARDEN, EDWIN · 2016 to 2024
$4.1M
NCATS NIH HHS TL1 TR002000NCATS NIH HHS UL1 TR002001
6 · The paper itself

Abstract

Background: Although dissemination and implementation (D&I) science is a growing field, many health researchers with relevant D&I expertise do not self-identify as D&I researchers. The goal of this work was to analyze the distribution, clustering, and recognition of D&I expertise in an academic institution. Methods: A snowball survey was administered to investigators at University of Rochester with experience and/or interest in D&I research. The respondents were asked to identify their level of D&I expertise and to nominate others who were experienced and/or active in D&I research. We used social network analysis to examine nomination networks. Results: Sixty-eight participants provided information about their D&I expertise. Thirty-eight percent of the survey respondents self-identified as D&I researchers, 24% as conducting D&I under different labels, and 38% were familiar with D&I concepts. D&I researchers were, on average, the most central actors in the network (nominated most by other survey participants) and had the highest within-group density, indicating wide recognition by colleagues and among themselves. Researchers who applied D&I under different labels had the highest within-group reciprocity (25%), and the highest between-group reciprocity (29%) with researchers familiar with D&I. Participants significantly tended to nominate peers within their departments and within their expertise categories. Conclusions: Identifying and engaging unrecognized clusters of expertise related to D&I research may provide opportunities for mutual learning and dialog and will be critical to bridging across departmental and topic area silos and building capacity for D&I in academic settings.

Indexed as

Capacity BuildingClinical & Translational Science Award (CTSA)Dissemination & Implementation ScienceProgram AssessmentSocial Network Analysis

Identifiers

PMID35321218
PMCPMC8922289

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.