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Statistical competencies for medical research learners: What is fundamental?
- Source :
- Journal of Clinical and Translational Science, Journal of clinical and translational science, vol 1, iss 3
- Publication Year :
- 2016
-
Abstract
- IntroductionIt 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.MethodsWe 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.’ResultsThere 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%).ConclusionWe 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.
- Subjects :
- medicine.medical_specialty
media_common.quotation_subject
Statistical competency
Translational research
Clinical and Translational Science
01 natural sciences
Literacy
Likert scale
Education
010104 statistics & probability
03 medical and health sciences
0302 clinical medicine
team science
Medicine
030212 general & internal medicine
0101 mathematics
Curriculum
media_common
Medical education
Evidence-Based Medicine
biology
business.industry
4. Education
Public health
General Medicine
Evidence-based medicine
biology.organism_classification
Pollock
3. Good health
Special Communications
Professional association
Public Health
business
Subjects
Details
- ISSN :
- 20598661
- Volume :
- 1
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Journal of clinical and translational science
- Accession number :
- edsair.doi.dedup.....5d04a9616fa9a274d67314f410e3cc40