An item response theory-based pain item bank can enhance measurement precision

Jin Shei Lai*, Kelly Dineen, Bryce B. Reeve, Jamie Von Roenn, Daniel Shervin, Michael McGuire, Rita K. Bode, Judith Paice, David Cella

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

37 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)278-288
Number of pages11
JournalJournal of Pain and Symptom Management
Issue number3
StatePublished - Sep 2005


  • Cancer
  • Disease management
  • Item banking
  • Item response theory
  • Pain
  • Rasch

ASJC Scopus subject areas

  • Nursing(all)
  • Clinical Neurology
  • Anesthesiology and Pain Medicine


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