Reliability and Validity of the Patient Activation Measure in Kidney Disease: Results of Rasch Analysis

Background and objectives: Despite the increasing prioritization of the promotion of patient activation in nephrology, its applicability to people with CKD is not well established. Before the Patient Activation Measure is universally adopted for use in CKD, it is important to critically evaluate this measure. The aim of this study was to describe the psychometric properties of the Patient Activation Measure in CKD.

Design, setting, participants, & measurements: A survey containing the 13-item Patient Activation Measure was completed by 942 patients with CKD, not treated with dialysis. Data quality was assessed by mean, item response, missing values, floor and ceiling effects, internal consistency (Cronbach's alpha and average interitem correlation), and item-rest correlations. Rasch modeling was used to assess item performance and scaling (item statistics, person and item reliability, rating scale diagnostics, factorial test of residuals, and differential item functioning).

Results: The item response was high, with a small number of missing values (<1%). Floor effect was small (range 1%-5%), but the ceiling effect was above 15% for nine items (range 15%-38%). The Patient Activation Measure demonstrated good internal consistency overall (Cronbach α=0.925, and average interitem correlation 0.502). The difficulty of the Patient Activation Measure items ranged from -0.90 to 0.86. Differential item functioning was found for disease type (item 3) and age (item 12). The person separation index was 9.48 and item separation index was 3.21.

Conclusions: The 13-item Patient Activation Measure appears to be a suitably reliable and valid instrument for assessing patient activation in CKD. In the absence of a kidney-specific instrument, our results support the 13-item Patient Activation Measure as a promising measure to assess activation in those with CKD, although consideration for several items is warranted. The high ceiling effect may be a problem when using the 13-item Patient Activation Measure to measure changes over time.