The cross-cultural validation of the English version of RhinAsthma patient's perspective (RAPP).
Margaret C LimIlaria BaiardiniGiorgia MolinengoCecilia G Navarro-LocsinGiorgio W CanonicaFulvio BraidoPublished in: The Journal of asthma : official journal of the Association for the Care of Asthma (2019)
Objective: No validated instrument is currently available in English for use in daily practice to assess Health Related Quality of Life (HRQoL) in asthma and comorbid allergic rhinitis (AR). The aim of this study was to validate and assess the psychometric characteristics of an English language version of RhinAsthma Patient Perspective (RAPP).Methods: The study was performed in the Philippines. The RAPP was translated into English. Adult patients, diagnosed with asthma and AR, were recruited. Clinical and functional data were collected on two occasion with a 4-week interval between visits. At both visits patients completed the following questionnaires: RAPP, Short Form Heath Survey-12 (SF-12), asthma control test (ACT), and rhinitis symptom Visual Analog Scale (VAS). Scale dimensions, internal consistency and convergent validity, reliability, discriminant ability, responsiveness, and minimal important difference (MID) were evaluated.Results: About 150 patients (mean age 39.3 years) completed the study. Exploratory and confirmatory factor analysis identified a uni-dimensional structure of the questionnaire. Internal consistency was satisfactory (0.87 at visit 1; 0.89 at visit 2). The tool showed good discriminant and convergent validity at both visits (p < 0.01). High reliability was confirmed by an ICC of 0.97 and a CCC of 0.95. Responsiveness was shown by a significant association with VAS (r = 0.34, p < 0.01) and ACT (r = -0.35, p < 0.01). The MID value was 2.Conclusions: The English version of RAPP was shown to have good psychometric properties and is a valid tool for assessing asthma and AR HRQoL in clinical practice.
Keyphrases
- psychometric properties
- allergic rhinitis
- chronic obstructive pulmonary disease
- end stage renal disease
- lung function
- ejection fraction
- newly diagnosed
- clinical practice
- healthcare
- chronic kidney disease
- clinical trial
- primary care
- cross sectional
- machine learning
- patient reported
- physical activity
- big data
- patient reported outcomes
- deep learning
- cystic fibrosis
- artificial intelligence
- study protocol
- electronic health record
- data analysis