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A4827 - Performance of the Asthma Impact on Quality of Life Scale in Diverse Asthma Research Samples and Demographic Sub-Groups
Author Block: S. R. Wilson1, R. A. Wise2, M. Castro3, M. J. Mulligan4, E. Ayala5, A. Chausow5, S. Gummidipundi1, Q. Huang1; 1Research Institute, Palo Alto Medical Foundation, Palo Alto, CA, United States, 2Bloomberg School of Public Health, Johns Hopkins Univ, Baltimore, MD, United States, 3Medicine and Pediatrics, Washington Univ Sch of Med, Saint Louis, MO, United States, 4Allergy and Immunology, Palo Alto Medical Foundation, Mountain View, CA, United States, 5Pulmonary and Critical Care, Palo Alto Medical Foundation, Mountain View, CA, United States.
Rationale: The Asthma Impact on Quality of Life Scale (A-IQOLS) assesses patient-perceived negative effect of asthma on 16 dimensions of quality of life (QoL). A-IQOLS has been shown to have strong construct, convergent, and divergent validity, and it provides information that is unique among asthma outcome measures. Its standard error of measurement (SEM), as estimated in the AQOLIS test-retest study, is 0.27. Objective: To further characterize A-IQOLS’ psychometric properties and suitability for use in diverse adult asthma populations. Methods: Pooled baseline data on standardized measures of lung function, symptoms, asthma control, asthma-related functional status, as well as QoL dimension importance and A-IQOLS scores, were obtained from participants (n = 599) in five diverse, independent asthma research studies -- LASST, AQOLIS, DASH, CPAP, and BTR and analyzed to determine the psychometric performance of A-IQOLS scores, overall and in multiple demographic and clinical subgroups. Results: Pooled sample age averaged 45 years; 66% were female, 65% were White, 22% African American, 11% Hispanic, and 11% had ≤ high school education. Both the rated importance of the 16 underlying life dimensions and the correlations between A-IQOLS scores and lung function, symptoms, asthma control, Juniper Mini-AQLQ, and Marks AQLQ scores were found to have very similar patterns regardless of patient demographic characteristics. A-IQOLS scores discriminated among the individual study samples as well as did other patient-reported symptom and health status measures. Distribution and anchor-based considerations suggest an A-IQOLS minimum clinically important difference (MID) in the vicinity of 0.50, and not lower than 0.33 scale score units. Conclusions: A-IQOLS is valid for use in clinically and demographically diverse asthma patients. The psychometric data available from the present analyses can inform power and sample size calculations for future research use of this measure and potential clinical use. Further study of its sensitivity to within person changes in asthma status and to experimental group differences are in process. Additional research is needed to evaluate and inform its use in clinical practice.