An item response theory-based pain item bank can enhance measurement precision.
Cancer-related pain is often under-recognized and undertreated. This is partly due to the lack of appropriate assessments, which need to be comprehensive and precise yet easily integrated into clinics. Computerized adaptive testing (CAT) can enable precise-yet-brief assessments by only selecting the most informative items from a calibrated item bank. The purpose of this study was to create such a bank. The sample included 400 cancer patients who were asked to complete 61 pain-related items. Data were analyzed using factor analysis and the Rasch model. The final bank consisted of 43 items which satisfied the measurement requirement of factor analysis and the Rasch model, demonstrated high internal consistency and reasonable item-total correlations, and discriminated patients with differing degrees of pain. We conclude that this bank demonstrates good psychometric properties, is sensitive to pain reported by patients, and can be used as the foundation for a CAT pain-testing platform for use in clinical practice.
Lai
Jin-Shei
JS
Center on Outcomes Research and Education, Evanston Northwestern Healthcare and Northwestern University, Evanston, Illinois 60201, USA.
Dineen
Kelly
K
Reeve
Bryce B
BB
Von Roenn
Jamie
J
Shervin
Daniel
D
McGuire
Michael
M
Bode
Rita K
RK
Paice
Judith
J
Cella
David
D
D000328:Adult; D000368:Aged; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000150:complications; D010147:Pain Measurement / Q000379:methods*; D010148:Intractable Pain / Q000209:etiology / Q000628:therapy*; D011471:Prostatic Neoplasms / Q000150:complications; D011594:Psychometrics; D012959:Socioeconomic Factors