Computerized adaptive testing in back pain: validation of the CAT-5D-QOL.
METHODS
We have conducted an outcome instrument validation study.


OBJECTIVE
Our objective was to develop a computerized adaptive test (CAT) to measure 5 domains of health-related quality of life (HRQL) and assess its feasibility, reliability, validity, and efficiency.


BACKGROUND
Kopec and colleagues have recently developed item response theory based item banks for 5 domains of HRQL relevant to back pain and suitable for CAT applications. The domains are Daily Activities (DAILY), Walking (WALK), Handling Objects (HAND), Pain or Discomfort (PAIN), and Feelings (FEEL).


METHODS
An adaptive algorithm was implemented in a web-based questionnaire administration system. The questionnaire included CAT-5D-QOL (5 scales), Modified Oswestry Disability Index (MODI), Roland-Morris Disability Questionnaire (RMDQ), SF-36 Health Survey, and standard clinical and demographic information. Participants were outpatients treated for mechanical back pain at a referral center in Vancouver, Canada.


RESULTS
A total of 215 patients completed the questionnaire and 84 completed a retest. On average, patients answered 5.2 items per CAT-5D-QOL scale. Reliability ranged from 0.83 (FEEL) to 0.92 (PAIN) and was 0.92 for the MODI, RMDQ, and Physical Component Summary (PCS-36). The ceiling effect was 0.5% for PAIN compared with 2% for MODI and 5% for RMQ. The CAT-5D-QOL scales correlated as anticipated with other measures of HRQL and discriminated well according to the level of satisfaction with current symptoms, duration of the last episode, sciatica, and disability compensation. The average relative discrimination index was 0.87 for PAIN, 0.67 for DAILY and 0.62 for WALK, compared with 0.89 for MODI, 0.80 for RMDQ, and 0.59 for PCS-36.


CONCLUSIONS
The CAT-5D-QOL is feasible, reliable, valid, and efficient in patients with back pain. This methodology can be recommended for use in back pain research and should improve outcome assessment, facilitate comparisons across studies, and reduce patient burden.
Kopec
Jacek A
JA
Department of Health Care and Epidemiology, University of British Columbia, Vancouver, BC, Canada. jkopec@arthritisresearch.ca
Badii
Maziar
M
McKenna
Mario
M
Lima
Viviane D
VD
Sayre
Eric C
EC
Dvorak
Marcel
M
D000328:Adult; D000368:Aged; D000465:Algorithms; D001416:Back Pain / Q000175:diagnosis* / Q000523:psychology; D001955:British Columbia; D003936:Diagnosis, Computer-Assisted / Q000592:standards*; D004185:Disability Evaluation; D005240:Feasibility Studies; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D020407:Internet; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011788:Quality of Life; D015203:Reproducibility of Results; D011795:Surveys and Questionnaires / Q000592:standards*