Introduction Statistics is an essential training component for a career in clinical and translational science (CTS). Given the increasing complexity of statistics, learners may have difficulty selecting appropriate courses. Our question was: what depth of statistical knowledge do different CTS learners require? Methods For three types of CTS learners (principal investigator, co-investigator, informed reader of the literature), each with different backgrounds in research (no previous research experience, reader of the research literature, previous research experience), 18 experts in biostatistics, epidemiology, and research design proposed levels for 21 statistical competencies. Results Statistical competencies were categorized as fundamental, intermediate, or specialized. CTS learners who intend to become independent principal investigators require more specialized training, while those intending to become informed consumers of the medical literature require more fundamental education. For most competencies, less training was proposed for those with more research background. Discussion When selecting statistical coursework, the learner’s research background and career goal should guide the decision. Some statistical competencies are considered to be more important than others. Baseline knowledge assessments may help learners identify appropriate coursework. Conclusion Rather than one size fits all, tailoring education to baseline knowledge, learner background and future goals increases learning potential while minimizing classroom time.
Introduction Although regression is widely used for reading and publishing in the medical literature, no instruments were previously available to assess students' understanding. The goal of this study was to design and assess such an instrument for graduate students in Clinical and Translational Science and Public Health. Methods A 27-item REsearch on Global Regression Expectations in StatisticS (REGRESS) quiz was developed through an iterative process. Consenting students taking a course on linear regression in a Clinical and Translational Science program completed the quiz pre- and post-course. Student results were compared to practicing statisticians with a master's or doctoral degree in statistics or a closely related field. Results 52 students responded pre-course, 59 post-course, and 22 practicing statisticians completed the quiz. The mean (SD) score was 9.3 (4.3) for students pre-course and 19.0 (3.5) post-course (p<0.001). Post-course students had similar results to practicing statisticians (mean (SD) of 20.1(3.5); p=0.21). Students also showed significant improvement pre/post course in each of six domain areas (p<0.001). The REGRESS quiz was internally reliable (Cronbach's alpha 0.89). Conclusion The initial validation is quite promising with statistically significant and meaningful differences across time and study populations. Further work is needed to validate the quiz across multiple institutions.
Three delivery systems with low versus high content structure were investigated in terms of immediate learning performance. Included were captioned videotape, classroom instruction, and connected prose on paper. A 2 x 3 analysis of covariance indicated that high content structure yielded significantly greater learning performance than low structure. Specific analyses of the interaction revealed that this performance occurred only for the classroom mode. Also, the prose condition was significantly and markedly higher than the other modes, which did not differ. These findings were discussed in terms of the cost and benefit of the prose mode and the indicated criticalness of high content structure in classroom instruction of hearing-impaired students.
Linear regression is typically taught as a second and potentially last required (bio)statistics course for Public Health and Clinical and Translational Science students. There has been much research on the attitudes of students toward basic biostatistics, but there has not been much assessing students' understanding of critical regression topics. The REGRESS (REsearch on Global Regression Expectations in StatisticS) quiz developed at Mayo Clinic utilizes 27 questions to assess understanding for simple and multiple linear regression. We performed an initial external validation of this tool with 117 University of Michigan public health students. We compare the results of pre-and postcourse quiz scores from the Michigan cohort to scores of Mayo medical students and professional statisticians. University of Michigan students performed higher than Mayo students on the precourse quiz due to previous related coursework, but did not perform as high postcourse indicating the need for course modification. In the Michigan cohort, REGRESS scores improved by a mean (standard deviation) of 4.6 (3.4), p < 0.0001. Our results support the use of the REGRESS quiz as a learning tool for students and an evaluation tool to identify topics for curricular improvement for teachers, while we highlight future directions of research. Clin Trans Sci 2014; Volume 7: 447-455
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