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A Balance Beam Aid for Instruction in Clinical Diagnostic Reasoning

Author

Listed:
  • Robert M. Hamm
  • William Howard Beasley
  • William Jay Johnson

Abstract

We describe a balance beam aid for instruction in diagnosis (BBAID) and demonstrate its potential use in supplementing the training of medical students to diagnose acute chest pain. We suggest the BBAID helps students understand the process of diagnosis because the impact of tokens (weights and helium balloons) attached to a beam at different distances from the fulcrum is analogous to the impact of evidence to the relative support for 2 diseases. The BBAID presents a list of potential findings and allows students to specify whether each is present, absent, or unknown. It displays the likelihood ratios corresponding to a positive (LR+) or negative (LR–) observation for each symptom, for any pair of diseases. For each specified finding, a token is placed on the beam at a location whose distance from the fulcrum is proportional to the finding’s log(LR): a downward force (a weight) if the finding is present and a lifting force (a balloon) if it is absent. Combining the physical torques of multiple tokens is mathematically identical to applying Bayes’ theorem to multiple independent findings, so the balance beam is a high-fidelity metaphor. Seven first-year medical students and 3 faculty members consulted the BBAID while diagnosing brief patient case vignettes. Student comments indicated the program is usable, helpful for understanding pertinent positive and negative findings’ usefulness in particular situations, and welcome as a reference or self-test. All students attended the effect of the tokens on the beam, although some stated they did not use the numerical statistics. Faculty noted the BBAID might be particularly helpful in reminding students of diseases that should not be missed and identifying pertinent findings to ask for.

Suggested Citation

  • Robert M. Hamm & William Howard Beasley & William Jay Johnson, 2014. "A Balance Beam Aid for Instruction in Clinical Diagnostic Reasoning," Medical Decision Making, , vol. 34(7), pages 854-862, October.
  • Handle: RePEc:sae:medema:v:34:y:2014:i:7:p:854-862
    DOI: 10.1177/0272989X14529623
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