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Open Access 01-12-2024 | Expert Opinion | Research

Building capacity in dissemination and implementation research: the presence and impact of advice networks

Authors: Allison J. L’Hotta, Rebekah R. Jacob, Stephanie Mazzucca-Ragan, Russell E. Glasgow, Sharon E. Straus, Wynne E. Norton, Ross C. Brownson

Published in: Implementation Science | Issue 1/2024

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Abstract

Background

As dissemination and implementation (D&I) research increases, we must continue to expand training capacity and research networks. Documenting, understanding, and enhancing advice networks identifies key connectors and areas where networks are less established. In 2012 Norton et al. mapped D&I science advice and collaboration networks. The current study builds on this work and aims to map current D&I research advice networks.

Methods

D&I researchers in the United States (US) and Canada were identified through a combination of publication metrics, and key persons identified networks and were invited to participate (n = 1,576). In this social network analysis study, participants completed an online survey identifying up to 10 people from whom they sought and/or gave advice on D&I research. Participants identified four types of advice received: research methods, grant, career, or another type (e.g., work/life balance). We used descriptive statistics to characterize the sample and network metrics and visualizations to describe the composition of advice networks.

Results

A total of 482 individuals completed the survey. Eighty-six (18%) worked in Canada and 396 (82%) in the US. Respondents had varying D&I research expertise levels; 14% beginner expertise, 45% intermediate, 29% advanced, and 12% expert. The advice network included 978 connected nodes/individuals. For all research types, out-degree, or advice giving, was higher for those with advanced or expert-level expertise (6.9 and 11.9, respectively) than those with beginner or intermediate expertise (0.8 and 2.2, respectively). Respondents reporting White race reported giving (out-degree = 5.2) and receiving (in-degree = 6.1) more advice compared to individuals reporting Asian (out-degree = 2.9, in-degree = 5.3), Black (out-degree = 2.3, in-degree = 5.2), or other races (out-degree = 2.5, in-degree = 5.4). Assortativity analyses revealed 98% of network ties came from individuals within the same country. The top two reasons for advice seeking were trusting the individual to give good advice (78%) and the individual’s knowledge/experience in specific D&I content (69%).

Conclusions

The D&I research network is becoming more dispersed as the field expands. Findings highlight opportunities to further connect D&I researchers in the US and Canada, individuals with emerging skills in D&I research, and minoritized racial groups. Expanding peer mentoring opportunities, especially for minoritized groups, can enhance the field’s capacity for growth.
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Literature
4.
go back to reference Chambers DA, et al. Mapping training needs for dissemination and implementation research: lessons from a synthesis of existing D&I research training programs. Transl Behav Med. 2017;7(3):593–601.CrossRefPubMed Chambers DA, et al. Mapping training needs for dissemination and implementation research: lessons from a synthesis of existing D&I research training programs. Transl Behav Med. 2017;7(3):593–601.CrossRefPubMed
10.
go back to reference Dickson KS, et al. Value of peer mentoring for early career professional, research, and personal development: a case study of implementation scientists. J Clin Transl Sci. 2021;5(1):e112.CrossRefPubMedPubMedCentral Dickson KS, et al. Value of peer mentoring for early career professional, research, and personal development: a case study of implementation scientists. J Clin Transl Sci. 2021;5(1):e112.CrossRefPubMedPubMedCentral
12.
go back to reference Boulware LE, et al. Diversity, equity and inclusion actions from the NCATS Clinical and Translational Science awarded programs. Nat Med. 2022;28(9):1730–1.CrossRefPubMedPubMedCentral Boulware LE, et al. Diversity, equity and inclusion actions from the NCATS Clinical and Translational Science awarded programs. Nat Med. 2022;28(9):1730–1.CrossRefPubMedPubMedCentral
18.
go back to reference Kantek F, et al. Social network analysis: Understanding nurses’ advice-seeking interactions. Int Nurs Rev. 2023;70(3):322–8.CrossRefPubMed Kantek F, et al. Social network analysis: Understanding nurses’ advice-seeking interactions. Int Nurs Rev. 2023;70(3):322–8.CrossRefPubMed
20.
go back to reference Isba R, Woolf K, Hanneman R. Social network analysis in medical education. Med Educ. 2017;51(1):81–8.CrossRefPubMed Isba R, Woolf K, Hanneman R. Social network analysis in medical education. Med Educ. 2017;51(1):81–8.CrossRefPubMed
25.
go back to reference Marin A, Wellman B. Social network analysis: An introduction. The SAGE handbook of social network analysis. 2011:11–25. Marin A, Wellman B. Social network analysis: An introduction. The SAGE handbook of social network analysis. 2011:11–25.
26.
go back to reference R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2016 [cited 2023 October 1]; Available from: http://www.R-project.org/. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2016 [cited 2023 October 1]; Available from: http://​www.​R-project.​org/​.
29.
go back to reference Wickham H, et al. Welcome to the Tidyverse. J Open Source Softw. 2019;4(43):1686.CrossRef Wickham H, et al. Welcome to the Tidyverse. J Open Source Softw. 2019;4(43):1686.CrossRef
31.
go back to reference Csardi, G. and T. Nepusz. The igraph software package for complext network research. 2006 [cited 2023 October 1]; Available from: https://igraph.org. Csardi, G. and T. Nepusz. The igraph software package for complext network research. 2006 [cited 2023 October 1]; Available from: https://​igraph.​org.
37.
go back to reference Rogers EM, Singhal A, Quinlan MM. Diffusion of innovations. In: An integrated approach to communication theory and research. Routledge; 2014. p. 432–48. Rogers EM, Singhal A, Quinlan MM. Diffusion of innovations. In: An integrated approach to communication theory and research. Routledge; 2014. p. 432–48.
38.
go back to reference Proctor EK, et al. The implementation research institute: training mental health implementation researchers in the United States. Implement Sci. 2013;8:1–12.CrossRef Proctor EK, et al. The implementation research institute: training mental health implementation researchers in the United States. Implement Sci. 2013;8:1–12.CrossRef
44.
go back to reference Wasserman S, Faust K, Social network analysis: Methods and applications. New York. NY: Cambridge University Press; 1999. Wasserman S, Faust K, Social network analysis: Methods and applications. New York. NY: Cambridge University Press; 1999.
Metadata
Title
Building capacity in dissemination and implementation research: the presence and impact of advice networks
Authors
Allison J. L’Hotta
Rebekah R. Jacob
Stephanie Mazzucca-Ragan
Russell E. Glasgow
Sharon E. Straus
Wynne E. Norton
Ross C. Brownson
Publication date
01-12-2024
Publisher
BioMed Central
Published in
Implementation Science / Issue 1/2024
Electronic ISSN: 1748-5908
DOI
https://doi.org/10.1186/s13012-024-01408-1