Scientific/Quantitative Methods Needed to be Covered in Undergraduate Medical Education

History, Methods, and Strategy of Science

The scientific method is an enduring concept to which all medical students should be exposed (and about which pre-med education should be enhanced). One hour each on the history of science and on the scientific method should be considered for inclusion in the curriculum. Just as important for medical students is an exposure to scientific strategies. This includes how pathways and mechanisms are discovered, how to optimally sequence experiments, and global strategy such as when and how to run a mechanism facilitation experiment and when to run a mechanism blocking experiment.

Biostatistics/Experimental Design

Students do not have the luxury of time to learn how to analyze data, but they should learn how to interpret data and how to interpret statistical summaries used to report experimental and observational results. Some suggested areas to cover in 2-3 hours of instruction and examples can include:

• Experimental and clinical trial design
  1. Properties of suitable scientific measurements
  2. Masking
  3. Randomization
  4. Parallel group, factorial, and crossover designs
• Statistical summaries for raw data
  1. Measures for comparing proportions: risk difference and odds ratios
  2. Summaries for continuous measurements: percentiles, mean, standard deviation
  3. Statistical graphics
• Statistical summaries of results
  1. Interpretation of confidence intervals
  2. Definition and hazards of P-values

Epidemiology

• Basic principles of epidemiology for etiology, diagnosis, and prognosis
• Confounding
• Observational study designs

Critical Appraisal of the Scientific Literature

At least a two hour exposure is needed for this all-important topic that continually affects clinical practice. One hour could be spent on the basic tools of critically reading the literature, and one hour could be spent on case studies.

How to Detect Bad Science

This one-hour session will cover how sloppiness, manipulation of data, and other questionable research practices contribute to scientific "discoveries" that do not replicate, exaggeration of diagnostic accuracy of devices, biomarkers, and molecular signatures, and exaggeration of treatment benefits.