Interpretative biases

OVERVIEW

Facts do not accumulate on the blank slates of researchers’ minds and data simply do not speak for themselves

Ted J Kaptchuk. 2003

• Evidence must be interpreted for quality and likelihood of error
• Interpretation is never completely independent of a scientist’s beliefs, preconceptions, or theoretical commitments
• Scientific interpretation can lead to sound judgment or interpretative biases; the distinction can often be made only in retrospect
• The interpretative process is a necessary aspect of science and represents an ignored subjective and human component of rigorous medical inquiry

TYPES OF INTERPRETATIVE BIAS

• Confirmation bias — evaluating evidence that supports one’s preconceptions differently from evidence that challenges these convictions
• Rescue bias — discounting data by finding selective faults in the experiment
• Auxiliary hypothesis bias — introducing ad hoc modifications to imply that an unanticipated finding would have been otherwise had the experimental conditions been different
• Mechanism bias — being less skeptical when underlying science furnishes credibility for the data
• “Time will tell” bias — the phenomenon that different scientists need different amounts of confirmatory evidence
• Orientation bias — the possibility that the hypothesis itself introduces prejudices and errors and becomes a determinate of experimental outcomes

References and Links

Journal articles

• Kaptchuk TJ. Effect of interpretive bias on research evidence. BMJ. 2003 Jun 28;326(7404):1453-5. PubMed PMID: 12829562; PubMed Central PMCID: PMC1126323. (This page summarizing interpretation biases is extracted from the Kaptchuk paper)
• Elstein AS. Human factors in clinical judgment: discussion of Scriven’s clinical judgment. In: Engelhardt HT, Spicker SF, Towers B. Clinical judgment: a critical appraisal. Dordrecht: Reidel, 1979.