Evaluating existing measures of health numeracy using item response theory

Abstract

Objective To evaluate existing measures of health numeracy using item response theory (IRT). Methods A cross-sectional study was conducted. Participants completed assessments of health numeracy measures including the Lipkus expanded health numeracy scale (Lipkus), and the Medical Data Interpretation Test (MDIT). The Lipkus and MDIT were scaled with IRT utilizing the two-parameter logistic model. Results Three-hundred and fifty-nine (359) participants were surveyed. Classical test theory parameters and IRT scaling parameters of the numeracy measures found most items to be at least moderately discriminating. Modified versions of the Lipkus and MDIT were scaled after eliminating items with low discrimination, high difficulty parameters, and poor model fit. The modified versions demonstrated a good range of discrimination and difficulty as indicated by the test information functions. Conclusion An IRT analysis of the Lipkus and MDIT indicate that both health numeracy scales discriminate well across a range of ability. Practice implications Health numeracy skills are needed in order for patients to successfully participate in their medical care. The accurate assessment of health numeracy may help health care providers to tailor patient education interventions to the patient's level of understanding and ability. Item response theory scaling methods can be used to evaluate the discrimination and difficulty of individual items as well as the overall assessment.