Tipping the Scales: A Corpus-Based Reconstruction of Adjective Scales in the McGill Pain Questionnaire


Miriam Stern, Princeton University, USA


Modern medical diagnosis relies on precise pain assessment tools in translating clinical information from patient to physician. The McGill Pain Questionnaire (MPQ) is a clinical pain assessment technique that utilizes 78 adjectives of different intensities in 20 categories to quantify a patient’s pain. The questionnaire’s efficacy depends on a predictable pattern of adjective use by patients experiencing pain. In this study, I recreate the MPQ’s adjective intensity orderings using data gathered from patient forums and modern NLP techniques. I extract adjective intensity relationships by searching for key linguistic contexts, and then combine the relationship information to form robust adjective scales. Of 17 adjective relationships predicted by this research, 10 show agreement with the MPQ, which is statistically significant at the .5 alpha level. The results suggest predictable patterns of adjective use by people experiencing pain, but call into question the MPQ’s categories for grouping adjectives.


Corpus Construction, Adjective Scales, Pain Assessment, McGill Pain Questionnaire.

Full Text  Volume 11, Number 14