BACKGROUND
Cardiovascular disease (CVD) is a leading global health issue with rising morbidity and mortality rates. Despite medical progress, effective self-management remains a challenge due to limited health knowledge among patients. The emergence of information technology offers new solutions for online self-management, but its success hinges on eHealth literacy. The m-eHEALS aim to assess this literacy, yet they have limitations, particularly in comprehensiveness and application to diverse populations.
OBJECTIVE
To assess the m-eHEALS psychometric properties for CVD patients with Rasch analysis.
METHODS
atients from neurology and cardiology departments in two Beijing hospitals were selected through continuous inclusion from February 20 to May 4, 2023. The study involved m-eHEALS and demographic information to examine CVD patients, focusing on unidimensionality, item fit, reliability, difficulty, item characteristic curve, and differential item functioning (DIF) using Rasch analysis.
RESULTS
The scale divided into three dimensions showed items in the self-perception dimension aligning well, but items N4, N5, N6, N10, and N11 had poor fit. The person separation index was 4.02 (reliability = 0.94), and the item separation index was 8.96 (reliability = 0.99), with no ceiling or floor effect. DIF analysis revealed a 0.71 logit difference between genders for item N12.
CONCLUSIONS
The m-eHEALS has good psychometric properties in CVD patients, despite some items poorly matching subjects, suggesting future refinements and focus on subgroup characteristics to enhance scale accuracy and applicability.