Literature DB >> 33191865

Assessing Connections in an Agricultural Community Using Social Network Analysis.

Cheryl L Beseler1, Annie J Keeney2,3, Robyn Garratt4, Alix Wertheimer4, Lorann Stallones1.   

Abstract

Agricultural workers experience higher rates of injury and illness than other occupational groups. NIOSH-supported agricultural centers in the U.S. are funded to reduce injury and illness but require effective partnerships with other agricultural organizations to achieve this goal. Our purpose was to understand the structure of agricultural organization connections within six states in the western U.S., including how different types of organizations connect to one another, and specifically where the High Plains Intermountain Center for Agricultural Health and Safety (HICAHS) is positioned in the agricultural organization network. An electronic survey was distributed to contacts within organizations that had a previous history with HICAHS leadership and advisory board members. The survey asked respondents about their position in the organization, years with the organization and frequency of contact in the past year. A social network analysis was undertaken to assess the connections between agricultural organizations using measures of centrality (density, closeness, betweenness), cliques, clusters, and brokers. A two-tier structure was identified with a core group of 21 organizations and a peripheral group of 30 organizations. Influence was centered in the core group as evidenced by high centrality scores with minimal bridging between organizations. HICAHS was on the periphery, but on the cusp of being in the core. Agricultural producers, agricultural extension and insurance companies were central in the network. Centers are in a unique position to promote collaboration with stakeholders. The social network analysis identified missing connections that need further development in order to address agricultural safety and health.

Entities:  

Keywords:  Social networks; agriculture; cluster analysis

Year:  2020        PMID: 33191865      PMCID: PMC8329729          DOI: 10.1080/1059924X.2020.1837317

Source DB:  PubMed          Journal:  J Agromedicine        ISSN: 1059-924X            Impact factor:   1.675


  7 in total

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Journal:  Annu Rev Public Health       Date:  2007       Impact factor: 21.981

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Journal:  Nature       Date:  1998-06-04       Impact factor: 49.962

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Journal:  Nature       Date:  1998-06-04       Impact factor: 49.962

4.  Social Networking in an Agricultural Research Center: Using Data to Enhance Outcomes.

Authors:  Mary E Cramer; Ozgur M Araz; Mary J Wendl
Journal:  J Agromedicine       Date:  2017       Impact factor: 1.675

5.  Innovation diffusion in an agricultural health center: moving information to practice.

Authors:  Fabio Almeida; Mary Cramer; Mary Wendl; Matthew Anderson; Risto Rautianinen
Journal:  J Agromedicine       Date:  2019-03-27       Impact factor: 1.675

6.  Social network analysis for program implementation.

Authors:  Thomas W Valente; Lawrence A Palinkas; Sara Czaja; Kar-Hai Chu; C Hendricks Brown
Journal:  PLoS One       Date:  2015-06-25       Impact factor: 3.240

7.  Agricultural science in the wild: a social network analysis of farmer knowledge exchange.

Authors:  Brennon A Wood; Hugh T Blair; David I Gray; Peter D Kemp; Paul R Kenyon; Steve T Morris; Alison M Sewell
Journal:  PLoS One       Date:  2014-08-14       Impact factor: 3.240

  7 in total
  1 in total

1.  Evaluating the Evolution of Social Networks: A Ten-Year Longitudinal Analysis of an Agricultural, Fishing and Forestry Occupational Health Research Center.

Authors:  Melissa B Scribani; Pamela J Tinc; Erika E Scott; Julie A Sorensen; Nancy H Tallman; Anne M Gadomski
Journal:  Int J Environ Res Public Health       Date:  2021-12-07       Impact factor: 3.390

  1 in total

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