BACKGROUND: Validated psychometric tools measuring quality of life, asthma control, and asthma severity have been developed, but their relationships with each other and with other important patient-centered outcomes have not been rigorously assessed. OBJECTIVE: To use factor analysis to evaluate the relationships of these validated tools with each other and with other patient-centered outcomes. METHODS: Surveys were completed by a random sample of 2854 Health Maintenance Organization members age 18 to 56 years with persistent asthma. Surveys included demographic information; validated tools measuring generic (Short Form-12; SF-12) and asthma-specific (Juniper Mini Asthma Quality of Life Questionnaire; AQLQ) quality of life, asthma control (Asthma Therapy Assessment Questionnaire), and asthma symptom severity (Asthma Outcomes Monitoring System); self-described severity, control, and course over time; and history of acute exacerbations. RESULTS: Principal component analysis suggested a 5-factor model that accounted for approximately 59% of the variability. The most prominent rotated factor reflected asthma symptom frequency (19.4% of variability), was measured by the symptom subscale of the AQLQ, and was the only factor significantly related to the Asthma Therapy Assessment Questionnaire, Asthma Outcomes Monitoring System, or the self-reported assessments of severity, control, or course. Other factors included symptom bother (12.1% of variability), reflected by the environment and emotion AQLQ subscales; activity limitation (13.9% of variability), reflected by the activity AQLQ subscale and the SF-12 physical component scale; mental health (8.3% of variability), reflected by the SF-12 mental component scale; and acute exacerbations (5.0% of variability), not measured by any of the validated scales. CONCLUSION: Distinct components of patient-reported asthma health status can be identified by factor analysis. Distinct constructs of severity versus control cannot be identified by the use of these tools alone.
BACKGROUND: Validated psychometric tools measuring quality of life, asthma control, and asthma severity have been developed, but their relationships with each other and with other important patient-centered outcomes have not been rigorously assessed. OBJECTIVE: To use factor analysis to evaluate the relationships of these validated tools with each other and with other patient-centered outcomes. METHODS: Surveys were completed by a random sample of 2854 Health Maintenance Organization members age 18 to 56 years with persistent asthma. Surveys included demographic information; validated tools measuring generic (Short Form-12; SF-12) and asthma-specific (Juniper Mini Asthma Quality of Life Questionnaire; AQLQ) quality of life, asthma control (Asthma Therapy Assessment Questionnaire), and asthma symptom severity (Asthma Outcomes Monitoring System); self-described severity, control, and course over time; and history of acute exacerbations. RESULTS: Principal component analysis suggested a 5-factor model that accounted for approximately 59% of the variability. The most prominent rotated factor reflected asthma symptom frequency (19.4% of variability), was measured by the symptom subscale of the AQLQ, and was the only factor significantly related to the Asthma Therapy Assessment Questionnaire, Asthma Outcomes Monitoring System, or the self-reported assessments of severity, control, or course. Other factors included symptom bother (12.1% of variability), reflected by the environment and emotion AQLQ subscales; activity limitation (13.9% of variability), reflected by the activity AQLQ subscale and the SF-12 physical component scale; mental health (8.3% of variability), reflected by the SF-12 mental component scale; and acute exacerbations (5.0% of variability), not measured by any of the validated scales. CONCLUSION: Distinct components of patient-reported asthma health status can be identified by factor analysis. Distinct constructs of severity versus control cannot be identified by the use of these tools alone.
Authors: C Archea; I H Yen; H Chen; M D Eisner; P P Katz; U Masharani; E H Yelin; G Earnest; P D Blanc Journal: Thorax Date: 2006-08-23 Impact factor: 9.139
Authors: Sandra R Wilson; Cynthia S Rand; Michael D Cabana; Michael B Foggs; Jill S Halterman; Lynn Olson; William M Vollmer; Rosalind J Wright; Virginia Taggart Journal: J Allergy Clin Immunol Date: 2012-03 Impact factor: 10.793
Authors: Cathy D Sherbourne; Brian D Stucky; Maria Orlando Edelen; Nicole K Eberhart; Eric Kleerup; Marielena Lara Journal: J Allergy Clin Immunol Date: 2014-04-18 Impact factor: 10.793