Abstract
PURPOSE: People living with COPD who struggle to take their medicines often experience poorer health outcomes such as exacerbations of symptoms, more frequent and lengthy hospital admissions, and worsening mortality rates. This study aimed to evaluate the psychometric properties of the previously validated SPUR-27 model, a multi-factorial model of medication adherence. PATIENTS AND METHODS: This cross-sectional study was conducted with 100 adult patients living with COPD in a hospital setting in Southwest London. Medication adherence was assessed using a shortened SPUR model (SPUR-27) against the validated Inhaler Adherence Scale (IAS) as a comparator. In addition, objective medication adherence data, presented as the Medication Possession Ratio (MPR), were derived from patient medical and pharmacy records. The COPD Assessment Tool (CAT) score was used to examine the relationship between medication adherence and COPD symptom severity. Reliability of SPUR-27 was assessed using internal consistency estimates. Exploratory factor analysis, partial confirmatory factor analysis, and maximum likelihood analysis were conducted in conjunction with construct, concurrent, and known-group validity testing to explore the psychometric properties of the SPUR model in this population. RESULTS: A 7-factor model for SPUR-27 was derived with adequate factor loadings. SPUR (α=0.893) observed strong internal consistency (>0.8). The model was significantly positively correlated with IAS score (p<0.001) as well as MPR (p<0.01). A significant (p<0.01) relationship between poor medication adherence and worsening symptom severity, as defined by the CAT score, was identified for SPUR (χ (2) = 8.570) using Chi-Square analysis. Furthermore, SPUR-27 demonstrated early evidence of validity with good incremental fit indices: NFI (0.96), TFI (0.97), and CFI (0.93) were all reported as >0.9 in addition to the RMSEA, which was <0.08 (0.059). CONCLUSION: SPUR demonstrated strong psychometric properties in patients living with COPD. Further work should look to examine the test-retest reliability of the model and its application in broader sample populations.