Skip to main content Accessibility help
×
Home

Statistical competencies for medical research learners: What is fundamental?

  • Felicity T. Enders (a1), Christopher J. Lindsell (a2), Leah J. Welty (a3), Emma K. T. Benn (a4), Susan M. Perkins (a5), Matthew S. Mayo (a6), Mohammad H. Rahbar (a7), Kelley M. Kidwell (a8), Sally W. Thurston (a9), Heidi Spratt (a10), Steven C. Grambow (a11), Joseph Larson (a1), Rickey E. Carter (a1), Brad H. Pollock (a12) and Robert A. Oster (a13)...

Abstract

Introduction

It is increasingly essential for medical researchers to be literate in statistics, but the requisite degree of literacy is not the same for every statistical competency in translational research. Statistical competency can range from ‘fundamental’ (necessary for all) to ‘specialized’ (necessary for only some). In this study, we determine the degree to which each competency is fundamental or specialized.

Methods

We surveyed members of 4 professional organizations, targeting doctorally trained biostatisticians and epidemiologists who taught statistics to medical research learners in the past 5 years. Respondents rated 24 educational competencies on a 5-point Likert scale anchored by ‘fundamental’ and ‘specialized.’

Results

There were 112 responses. Nineteen of 24 competencies were fundamental. The competencies considered most fundamental were assessing sources of bias and variation (95%), recognizing one’s own limits with regard to statistics (93%), identifying the strengths, and limitations of study designs (93%). The least endorsed items were meta-analysis (34%) and stopping rules (18%).

Conclusion

We have identified the statistical competencies needed by all medical researchers. These competencies should be considered when designing statistical curricula for medical researchers and should inform which topics are taught in graduate programs and evidence-based medicine courses where learners need to read and understand the medical research literature.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Statistical competencies for medical research learners: What is fundamental?
      Available formats
      ×

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Statistical competencies for medical research learners: What is fundamental?
      Available formats
      ×

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Statistical competencies for medical research learners: What is fundamental?
      Available formats
      ×

Copyright

This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.

Corresponding author

*Address for correspondence: F. T. Enders, Ph.D., M.P.H., Division of Biomedical Statistics & Informatics, Department of Health Sciences Research, Mayo Clinic, 200 First Street, SW, Rochester, MN 55905, USA. (Email: Enders.Felicity@mayo.edu)

References

Hide All
1. Oster, RA, et al. Assessing statistical competencies in clinical and translational science education: one size does not fit all. Clinical and Translational Science 2015; 8: 3242.
2. Oxford Dictionary [Internet]. http://www.oxforddictionaries.com/us/definition/american_english/competence. Last accessed April 12, 2017.
3. CTSA Education Core Competency Workgroup. Core Competencies in Clinical and Translational Science for Master’s Candidates, Revised 2011 [Internet]. [cited May 25, 2016]. (https://ctsacentral.org/wp-content/documents/CTSA%20Core%20Competencies_%20final%202011.pdf)
4. Calhoun, JG, et al. Development of a core competency model for the Master of Public Health degree. American Journal of Public Health 2008; 98: 15981607.
5. Enders, F. Evaluating mastery of biostatistics for medical researchers: need for a new assessment tool. Clinical and Translational Science 2011; 4: 448454.
6. Rao, G. Physician numeracy: essential skills for practicing evidence-based medicine. Family Medicine 2008; 40: 354358.
7. Novack, L, et al. Evidence-based medicine: assessment of knowledge of fundamental epidemiological and research methods among medical doctors. Postgraduate Medical Journal 2006; 82: 817822.
8. Chatterji, M, Graham, MJ, Wyer, PC. Mapping cognitive overlaps between practice-based learning and improvement and evidence-based medicine: an operational definition for assessing resident physician competence. Journal of Graduate Medical Education 2009; 1: 287298.
9. Bloom, BS, Krathwohl, DR. Taxonomy of Educational Objectives: The Classification of Educational Goals, by a Committee of College and University Examiners. Handbook 1: Cognitive Domain . New York, NY: Longman Publishing, 1956.
10. Anderson, LW, Krathwohl, DR. A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives, complete edition. New York, NY: Longman Publishing, 2001.
11. Forehand, M. Bloom’s taxonomy: original and revised. In: Orey M, ed. Emerging Perspectives on Learning, Teaching, and Technology [Internet]. 2005 [cited May 25, 2016]. (http://projects.coe.uga.edu/epltt/index.php?title=Bloom%27s_Taxonomy)
12. Albanese, MA, et al. Defining characteristics of educational competencies. Medical Education 2008; 42: 248255.
13. Harris, PA, et al. Research electronic data capture (REDCap) – a metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics 2009; 42: 377381.
14. Perkins, S.M, et al. Best practices for biostatistical consultation and collaboration in academic health centers. American Statistican 2016; 70: 187194.
15. Welty, LJ, et al. Strategies for developing biostatistics resources in an academic health center. Academic Medicine 2013; 88: 454460.
16. Silva, SA, Wyer, PC. The roadmap: a blueprint for evidence literacy within a scientifically informed medical practice and learning model. European Journal for Person Centered Healthcare 2013; 1: 5368.
17. Miettinen, OS, Bachmann, LM, Steurer, J. Clinical research: up from ‘clinical epidemiology’. Journal of Evaluation in Clinical Practice 2009; 15: 12081213.

Keywords

Type Description Title
WORD
Supplementary materials

Enders supplementary material S1
Appendix

 Word (1.9 MB)
1.9 MB
WORD
Supplementary materials

Enders supplementary material S2
Appendix

 Word (21 KB)
21 KB

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed