An Item Response Theory-Based Pain Item Bank Can Enhance Measurement Precision

Abstract

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.

Framework and guidance for implementing patient-reported outcomes in clinical practice: evidence, challenges and opportunities

“…These include item response theories [72] and the Rasch model [73], are being increasingly adopted in health services research and have recently been used to develop PROs which measure wide-ranging phenomena including pain, depression, fatigue, and the impact of multimorbidity [74][75][76][77]. However, in other fields where questionnaires are used to capture 'high stakes' information, such as educational testing and psychometric assessment for employers, they have been considered the industry standard for decades [78].…”

The future of outcomes measurement: item banking, tailored short-forms, and computerized adaptive assessment

“…Given our experiences in developing item banks (e.g., physical function [15,16], fatigue [17,18], pain [19]) we have developed a framework to guide our practice and track status (see Table 1), which can be described in 13 steps. Literature review and input from clinicians and patients are used to select domains (step 1).…”

Development of symptom assessments utilising item response theory and computer-adaptive testing—A practical method based on a systematic review

“…1) [9][10][11][12]. The selected studies cover a wide range of PRO instruments assessing physical functioning in different populations, cancer-related fatigue, depression, or anxiety (Table 1).…”

“…The selected studies cover a wide range of PRO instruments assessing physical functioning in different populations, cancer-related fatigue, depression, or anxiety (Table 1). In the papers selected, the candidate items that formed the initial item pool were often chosen from pre-existing questionnaires; only some studies [9,10,18,[21][22][23]35] used newly generated items. The sample data for the calibration studies in the papers selected were often retrospective data from pre-existing questionnaires in which the mode of administration (e.g., paper-pencil) was not computer based (Table 1).…”

“…Now IRT is used in conjunction with powerful computer capabilities and offers an exciting new research area in patient-reported outcome (PRO) measurement. Important groundwork has been the development of item banks containing questions that have been calibrated with a set of psychometric properties covering the whole range of a latent trait, such as pain or fatigue [9,10]. Based on these item banks, a simple reduction of the items at the risk of losing important information is no longer necessary.…”