Development and Preliminary Testing of a Computerized Adaptive Assessment of Chronic Pain
Received 7 October 2008; received in revised form 10 January 2009; accepted 6 March 2009. published online 13 July 2009.
Abstract
The aim of this article is to report the development and preliminary testing of a prototype computerized adaptive test of chronic pain (CHRONIC PAIN-CAT) conducted in 2 stages: (1) evaluation of various item selection and stopping rules through real data–simulated administrations of CHRONIC PAIN-CAT; (2) a feasibility study of the actual prototype CHRONIC PAIN-CAT assessment system conducted in a pilot sample. Item calibrations developed from a US general population sample (N = 782) were used to program a pain severity and impact item bank (κ = 45), and real data simulations were conducted to determine a CAT stopping rule. The CHRONIC PAIN-CAT was programmed on a tablet PC using QualityMetric's Dynamic Health Assessment (DYHNA) software and administered to a clinical sample of pain sufferers (n = 100). The CAT was completed in significantly less time than the static (full item bank) assessment (P < .001). On average, 5.6 items were dynamically administered by CAT to achieve a precise score. Scores estimated from the 2 assessments were highly correlated (r = .89), and both assessments discriminated across pain severity levels (P < .001, RV = .95). Patients' evaluations of the CHRONIC PAIN-CAT were favorable.
Perspective
This report demonstrates that the CHRONIC PAIN-CAT is feasible for administration in a clinic. The application has the potential to improve pain assessment and help clinicians manage chronic pain.
∗QualityMetric Incorporated, Lincoln, Rhode Island
†National Research Centre for the Working Environment, Copenhagen, Denmark
Address reprint requests to Dr Milena Anatchkova, QualityMetric Incorporated, 24 Albion Road, Bldg 400, Lincoln, RI 02865.
Supported by Small Business Innovation Research Grant #1R43AR052251-01A1 from the National Institute of Arthritis and Musculoskeletal and Skin Diseases.