Measuring the ICF components of impairment, activity limitation and participation restriction: an item analysis using...

The International Classification of Functioning, Disability and Health (ICF) proposes three main health outcomes, Impairment (I), Activity Limitation (A) and Participation Restriction (P), but good measures of these constructs are needed The aim of this study was to use both Classical Test Theory (CTT) and Item Response Theory (IRT) methods to carry out an item analysis to improve measurement of these three components in patients having joint replacement surgery mainly for osteoarthritis (OA).

A geographical cohort of patients about to undergo lower limb joint replacement was invited to participate. Five hundred and twenty four patients completed ICF items that had been previously identified as measuring only a single ICF construct in patients with osteoarthritis. There were 13 I, 26 A and 20 P items. The SF-36 was used to explore the construct validity of the resultant I, A and P measures. The CTT and IRT analyses were run separately to identify items for inclusion or exclusion in the measurement of each construct. The results from both analyses were compared and contrasted.

Overall, the item analysis resulted in the removal of 4 I items, 9 A items and 11 P items. CTT and IRT identified the same 14 items for removal, with CTT additionally excluding 3 items, and IRT a further 7 items. In a preliminary exploration of reliability and validity, the new measures appeared acceptable.

New measures were developed that reflect the ICF components of Impairment, Activity Limitation and Participation Restriction for patients with advanced arthritis. The resulting Aberdeen IAP measures (Ab-IAP) comprising I (Ab-I, 9 items), A (Ab-A, 17 items), and P (Ab-P, 9 items) met the criteria of conventional psychometric (CTT) analyses and the additional criteria (information and discrimination) of IRT. The use of both methods was more informative than the use of only one of these methods. Thus combining CTT and IRT appears to be a valuable tool in the development of measures.