Journal:Adapting data management education to support clinical research projects in an academic medical center

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Full article title Adapting data management education to support clinical research projects in an academic medical center
Journal Journal of the Medical Library Association
Author(s) Read, Kevin B.
Author affiliation(s) New York University School of Medicine
Primary contact Email: kevin dot read at nyumc dot org
Year published 2019
Volume and issue 107(1)
Page(s) 89–97
DOI 10.5195/jmla.2019.580
ISSN 1558-9439
Distribution license Creative Commons Attribution 4.0 International
Website http://jmla.pitt.edu/ojs/jmla/article/view/580/792
Download http://jmla.pitt.edu/ojs/jmla/article/download/580/773 (PDF)
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Abstract

Background

Librarians and researchers alike have long identified research data management (RDM) training as a need in biomedical research. Despite the wealth of libraries offering RDM education to their communities, clinical research is an area that has not been targeted. Clinical RDM (CRDM) is seen by its community as an essential part of the research process where established guidelines exist, yet educational initiatives in this area are unknown.

Case presentation

Leveraging my academic library’s experience supporting CRDM through informationist grants and REDCap training in our medical center, I developed a 1.5 hour CRDM workshop. This workshop was designed to use established CRDM guidelines in clinical research and address common questions asked by our community through the library’s existing data support program. The workshop was offered to the entire medical center four times between November 2017 and July 2018. This case study describes the development, implementation, and evaluation of this workshop.

Conclusions

The four workshops were well attended and well received by the medical center community, with 99% stating that they would recommend the class to others and 98% stating that they would use what they learned in their work. Attendees also articulated how they would implement the main competencies they learned from the workshop into their work. For the library, the effort to support CRDM has led to the coordination of a larger institutional collaborative training series to educate researchers on best practices with data, as well as the formation of institution-wide policy groups to address researcher challenges with CRDM, data transfer, and data sharing.

Background

For over 10 years, data management training has been identified as a need by the biomedical research community and librarians alike. From the perspective of biomedical researchers, the lack of good quality information management for research data[1][2] and an absence of training for researchers to improve their data management skills are recurring issues cited in the literature and a cause for concern for research overall.[1][3][4] Similarly, librarians practicing data management have identified that researchers generally receive no formal training in data management[5] yet have a desire to learn[6] because they lack confidence in their skills.

To address this need, librarians from academic institutions have been working to provide data management education and support to their communities. By developing specific approaches to creating data management education, libraries have found successful avenues in implementing stand-alone courses and one-shot workshops[7], integrating research data management into an existing curriculum[8], and offering domain-specific training.[9] Libraries have offered these training programs by providing general data management training to undergraduate and graduate students[10][11][12], doctoral scholars[13], and the general research community[14][15][16][17][18][19][20], whereas domain-specific data management can be seen most prominently in the life sciences [21], earth and environmental sciences [22, 23], social sciences [24], and the digital humanities [25].

References

  1. ↑ 1.0 1.1 Anderson, N.R.; Lee, E.S.; Brockenbrough, J.S. et al. (2007). "Issues in biomedical research data management and analysis: Needs and barriers". JAMIA 14 (4): 478–88. doi:10.1197/jamia.M2114. PMC PMC2244904. PMID 17460139. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2244904. 
  2. ↑ Wang, X.; Williams, C.; Liu, Z.H.; Croghan, J. (2019). "Big data management challenges in health research—A literature review". Briefings in Bioinformatics 20 (1): 156–67. doi:10.1093/bib/bbx086. PMID 28968677. 
  3. ↑ Barone, L.; Williams, J.; Micklos, D. (2017). "Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators". PLoS Computer Biology 13 (10): e1005755. doi:10.1371/journal.pcbi.1005755. PMC PMC5654259. PMID 29049281. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5654259. 
  4. ↑ Johansson, B.; Fogelberg-Dahm, M.; Wadensten, B. (2010). "Evidence-based practice: The importance of education and leadership". Journal of Nursing Management 18 (1): 70-7. doi:10.1111/j.1365-2834.2009.01060.x. PMID 20465731. 
  5. ↑ Federer, L.M.; Lu, Y.L.; Joubert, D.J. (2016). "Data literacy training needs of biomedical researchers". Journal of the Medical Library Association 104 (1): 52–7. doi:10.3163/1536-5050.104.1.008. PMC PMC4722643. PMID 26807053. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4722643. 
  6. ↑ Scaramozzino, J.M.; Ramírez, M.L.; McGaughey, K.J. (2012). "A Study of Faculty Data Curation Behaviors and Attitudes at a Teaching-Centered University". College & Research Libraries 73 (4): 349–65. doi:10.5860/crl-255. 
  7. ↑ Carlson, J.; Johnston, L.; Westra, B.; Nichols, M. (2013). "Developing an Approach for Data Management Education: A Report from the Data Information Literacy Project". International Journal of Digital Curation 8 (1): 204–17. doi:10.2218/ijdc.v8i1.254. 
  8. ↑ MacMillan, D. (2015). "Developing data literacy competencies to enhance faculty collaborations". LIBER Quarterly 24 (3): 140–60. doi:10.18352/lq.9868. 
  9. ↑ Wittenberg, J.; Elings, M. (2017). "Building a Research Data Management Service at the University of California, Berkeley: A tale of collaboration". IFLA Journal 43 (1): 89–97. doi:10.1177/0340035216686982. 
  10. ↑ Piorun, M.E.; Kafel, D.; Leger-Hornby, T. et al. (2012). "Teaching Research Data Management: An Undergraduate/Graduate Curriculum". Journal of eScience Librarianship 1 (1): 8. doi:10.7191/jeslib.2012.1003. 
  11. ↑ Reisner, B.A.; Vaughan, K.T.L.; Shorish, Y.L. (2014). "Making Data Management Accessible in the Undergraduate Chemistry Curriculum". Journal of Chemical Education 91 (11): 1943–6. doi:10.1021/ed500099h. 
  12. ↑ Adamick, J.; Reznik-Zellen, R.C.; Sheridan, M. (2013). "Data Management Training for Graduate Students at a Large Research University". Journal of eScience Librarianship 1 (3): e1022. doi:10.7191/jeslib.2012.1022. 
  13. ↑ Fransson, J.; Lagunas, P.T.; Kjellberg, S.; Toit, M.D. (2016). "Developing integrated research data management support in close relation to doctoral students' research practices". Proceedings of the Association for Information Science and Technology 53 (1): 1–4. doi:10.1002/pra2.2016.14505301094. 
  14. ↑ Clement, R.; Blau, A.; Abbaspour, P. et al. (2017). "Team-based data management instruction at small liberal arts colleges". IFLA Journal 43 (1): 105–18. doi:10.1177/0340035216678239. 
  15. ↑ Johnston, L.; Jeffryes, J. (2014). "Steal this idea: A library instructors’ guide to educating students in data management skills". College & Research Libraries News 75 (8): 431–4. doi:10.5860/crln.75.8.9175. 
  16. ↑ Johnston, L.; Lafferty, M.; Petsan, B. (2012). "Training Researchers on Data Management: A Scalable, Cross-Disciplinary Approach". Journal of eScience Librarianship 1 (2): 2. doi:10.7191/jeslib.2012.1012. 
  17. ↑ Muilenburg, J.; Lebow, M.; Rich, J. (2014). "Lessons Learned From a Research Data Management Pilot Course at an Academic Library". Journal of eScience Librarianship 3 (1): 8. doi:10.7191/jeslib.2014.1058. 
  18. ↑ Southall, J. Scutt, C. (2017). "Training for Research Data Management at the Bodleian Libraries: National Contexts and Local Implementation for Researchers and Librarians". New Review of Academic Librarianship 23 (2–3): 303–22. doi:10.1080/13614533.2017.1318766. 
  19. ↑ Tammaro, A.M.; Casarosa, V. (2014). "Research Data Management in the Curriculum: An Interdisciplinary Approach". Procedia Computer Science 38: 138–42. doi:10.1016/j.procs.2014.10.023. 
  20. ↑ Verbakel, E.; Grootveld, M. (2016). "‘Essentials 4 Data Support’: Five years’ experience with data management training". IFLA Journal 42 (4): 278–83. doi:10.1177/0340035216674027. 

Notes

This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added.

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