How to limit clinical errors in interpretation of data [PDF]
Patricia Wright, Carel Jansen, Jeremy C. Wyatt
The Lancet: Volume 352, Issue 9139, 7 November 1998, Pages 1539–1543
Text entries in medical records must be succinct, but must also avoid ambiguity. The note, “Pain in left knee—not sitting” may be concise and clear to the writer, but to other readers it could mean that the pain disappears when the patient sits or that, because of pain, the patient is not sitting. If, while entering data, writers anticipate the needs of readers, there can be benefits in speed and accuracy for future users, including the original writer.
Ambiguities can also arise with quantifiers such as “sometimes” or “often”, because these convey different meanings to patients and clinicians, with patients tending to attribute higher frequencies. Ambiguity is lessened if frequency is explicitly specified—for example, as “once a month”. Similarly, use of illdefined words (eg, large, likely) to quantify size or probability, is best avoided. The different >interpretation by doctors of alternative, equivalent measures of drug efficacy, such as absolute and relative difference, is a further warning that words matter.
There's plenty of experimental work about how humans make poor judgments and decisions, but I haven't yet found much about how humans make poor judgments and decisions because of confusions about words. And yet, I expect such errors are common — I, at least, encounter them frequently.
It would be nice to have some scientific studies which illustrate the ways in which confusions about words affect everyday decision making, but instead all I can do is make philosophical arguments and point people to things like Yudkowsky's 37 Ways That Words Can Be Wrong or Chalmers' Verbal Disputes and Philosophical Progress.
Which keywords do I need to find experimental work on this topic? I tried Google scholar searches like "fuzzy concepts" "decision making" and effect of connotations on choices but I didn't find much in my first hour of looking into this.