Usefulness of pain drawings in identifying real or imagined pain: accuracy of pain professionals, nonprofessionals, and a decision model.
The aim of this study was to determine the accuracy of pain specialists, nonprofessionals, and a decision model in judging whether a pain diagram was marked by a patient with chronic pain or by a healthy volunteer. Two hundred twenty-eight pain drawings were shown in random order to 10 pain medicine physicians, 10 pain medicine fellows, 10 nonphysician specialists, and 10 nonprofessionals. One half of the drawings (n = 114) had been produced by patients treated at a pain center and the other half (n = 114) by healthy individuals who were instructed to mark the diagrams as if they had a pain problem. The nonprofessionals were found to be 51.5% accurate, pain medicine fellows 52.7%, nonphysician specialists 54.3%, and pain medicine physicians 55.2 % accurate at distinguishing drawings by actual pain patients from drawings from volunteers without pain. A decision model was able to achieve 68.9% accuracy in determining which drawings were made by pain patients and which drawings were made by healthy individuals. The results suggest that subjective assessment of pain drawings alone is not useful in determining whether someone has real or imagined pain. A decision model that makes decisions on the basis of the number of highlighted squares on the pain diagram can identify real pain drawings with greater accuracy than humans.


CONCLUSIONS
Pain drawings are clinically useful but have limitations. This study illustrates some of the benefits of computerized pain assessment and highlights the importance of not judging patients on the basis of one source of information.
Jamison
Robert N
RN
Department of Anesthesia and Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA. Jamison@zeus.bwh.harvard.edu
Fanciullo
Gilbert J
GJ
Baird
John C
JC
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002908:Chronic Disease; D003661:Decision Support Techniques; D005260:Female; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D008297:Male; D008511:Medicine / Q000379:methods*; D008875:Middle Aged; D010146:Pain / Q000175:diagnosis*; D018710:Pain Clinics; D010147:Pain Measurement / Q000379:methods* / Q000592:standards; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D013038:Specialization