Jargon is frequently a barrier to effective communication, especially when discussing a complicated topic like the risks associated with screening. The two purposes of this paper were to describe residents’ use of jargon during counseling about prostate and breast cancer screening and to introduce a new method for quantifying jargon usage that can be used in population-based samples. In the analysis we found that jargon words were common, explanations were rare, and many explanations lagged well behind usage of the words that they were supposed to explain. The analysis was limited by use of a small sample of residents from a single program, which limits generalizability to other residency programs or clinicians in practice. Additional research should be conducted in more broadly representative samples of physicians before wider implementation of the method.
From the patient perspective, our approach may overestimate jargon burden because of the low explanation ratio of the word “prostate” and words beginning with “mammogra-” (Table ). The high prevalence of these words is understandable since they were central to the topic of conversation, but the words’ low explanation ratio could have been affected by the standardized patient’s necessary use of the words to begin conversation. When these words were removed for the sensitivity analysis described in the results section, however, the jargon count was still high, and the explanation ratio was still quite small. In addition, the finding that 60% and 17% of residents choose to explain the word mammogram and prostate, respectively, (Table ) suggests that some residents still thought it was necessary to explain these words even though they had already been used by the patient.
Regardless of the size of the problem, we are concerned about the challenge that jargon presents for patients with limited health literacy or English skills, and for patients who are ethnically or culturally different from their clinicians.5
Patients with high health literacy may have sufficient understanding of words like “prostate” and therefore might not need an explanation, but clinicians should be cognizant that patients may use words that they do not entirely understand and consider taking a conservative approach of providing an explanation when there is doubt about likely understanding.3–6
Several research questions remain. The finding that most residents explained at least one jargon word suggests that they may already be aware that misunderstanding of certain words is possible; thus, studies should investigate whether clinicians tend to overestimate their patients’ vocabularies or if there is some other reason why jargon is often unexplained. A statewide study of counseling after newborn screening currently in progress will allow us to quantify the association between jargon usage and comprehension in that population.33
In the time since this manuscript was first submitted, two other research groups have developed methods to quantify jargon usage. In one study of primary care visits,34
Castro et al. operationalized jargon as either “clinical or technical terms with only one meaning listed in a medical dictionary (e.g., hemoglobin A1c)” or “clinical terms used in health care contexts with distinct meanings in lay contexts (e.g., your weight is stable)” (p. s86). In another study, Keselman et al. developed a “predictive familiarity model” based on input to a multiple regression formula from text frequencies found in Reuter’s news reports, queries to an Internet health search engine, queries to a general Internet search engine, and further input from 41 laypersons.35
The model was used to categorize 45 words as either “likely,” “somewhat likely,” or “unlikely” to be familiar to laypersons. This line of research is a positive development. Future research comparing the models, their generalizability, costs, and their relationship to care outcomes will advance the field further.
In our view, the most important area for future jargon research is the development of metrics that can be applied on a population-wide scale with the ultimate goal of reducing jargon usage and improving clinicians’ explanations. To be successful on these large scales, methods will need to be quantitatively reliable, concrete enough for use by quality improvement professionals with typical training, and able to function on a lean budget. We have adapted a methodological approach from Quality Improvement because of that field’s track record for improving other complex clinician behaviors over large populations.36
The main goal of this project was to extend our previous work17–22
into a method that will reliably and affordably quantify jargon usage and explanations for use in population-based quality improvement projects.
In summary, the high prevalence of jargon words and low prevalence of jargon explanations suggests that there may be problems with communication and patient comprehension during discussions about cancer screening. Our explicit-criteria method is concrete enough for use by quality improvement professionals and customizable for different clinical topics. Since it is not possible to draw conclusions about individuals based on population-based data, we advise clinicians to approach each patient as an individual, regardless of the patients’ apparent health literacy, and to be conservative about word choice, explanation, and assessment of understanding. Reduced use of jargon and improved explanations by individual clinicians or over entire populations are likely to result in increased communication effectiveness and patient participation in care.