Measurement properties of the Inventory of Cognitive Bias in Medicine (ICBM).
BACKGROUND
Understanding how doctors think may inform both undergraduate and postgraduate medical education. Developing such an understanding requires valid and reliable measurement tools. We examined the measurement properties of the Inventory of Cognitive Bias in Medicine (ICBM), designed to tap this domain with specific reference to medicine, but with previously questionable measurement properties.


METHODS
First year postgraduate entry medical students at Flinders University, and trainees (postgraduate doctors in any specialty) and consultants (N = 348) based at two teaching hospitals in Adelaide, Australia, completed the ICBM and a questionnaire measuring thinking styles (Rational Experiential Inventory).


RESULTS
Questions with the lowest item-total correlation were deleted from the original 22 item ICBM, although the resultant 17 item scale only marginally improved internal consistency (Cronbach's alpha = 0.61 compared with 0.57). A factor analysis identified two scales, both achieving only alpha = 0.58. Construct validity was assessed by correlating Rational Experiential Inventory scores with the ICBM, with some positive correlations noted for students only, suggesting that those who are naïve to the knowledge base required to "successfully" respond to the ICBM may profit by a thinking style in tune with logical reasoning.


CONCLUSIONS
The ICBM failed to demonstrate adequate content validity, internal consistency and construct validity. It is unlikely that improvements can be achieved without considered attention to both the audience for which it is designed and its item content. The latter may need to involve both removal of some items deemed to measure multiple biases and the addition of new items in the attempt to survey the range of biases that may compromise medical decision making.
Sladek
Ruth M
RM
School of Medicine, Flinders University, Adelaide, Australia. Ruth.Sladek@flinders.edu.au
Phillips
Paddy A
PA
Bond
Malcolm J
MJ
D000328:Adult; D001315:Australia; D003071:Cognition; D003657:Decision Making; D005163:Factor Analysis, Statistical; D005260:Female; D006784:Hospitals, Teaching; D006801:Humans; D007396:Internship and Residency; D008297:Male; D008875:Middle Aged; D011287:Prejudice; D011594:Psychometrics / Q000295:instrumentation*; D011908:Rationalization; D015203:Reproducibility of Results; D013337:Students, Medical / Q000523:psychology* / Q000706:statistics & numerical data; D011795:Surveys and Questionnaires