E-health literacy in stroke patients: Latent profile analysis and influencing factors.

Abstract

This study sought to explore latent categories of electronic health (e-health) literacy among stroke patients and analyse its influencing factors. A cross-sectional, descriptive exploratory design with the STROBE reporting checklist was applied. Between July and October 2020, 558 stroke participants from three tertiary care hospitals in Henan Province, China, were recruited using a convenience sampling method. A general information questionnaire and the Electronic Health Literacy Scale were used to collect their socio-demographic information and e-health literacy. Latent profile analysis was used to analyse latent categories of e-health literacy in stroke patients. Multiple logistic regression was used to analyse factors influencing latent categories of e-health literacy in stroke patients. Three latent categories of e-health literacy existed, including the low e-health literacy group, the low application-high decision-making group and the high literacy-low decision-making group. Multiple logistic regression showed that education level, presence of comorbidities, willingness to interact with people with mental illness, health information sources, frequency of Internet access, frequency of health information inquiry and willingness to receive remote care were predictors of the participants' latent categories of e-health literacy. Three latent categories of e-health literacy in stroke patients exist, and each latent category's characteristics should be considered while developing health education programmes. It is imperative that healthcare providers understand the requirement of creating tailored and efficient health education programmes for various categories of stroke patients to enhance their e-health literacy. It is imperative to improve Chinese stroke patients' overall e-health literacy. We categorized stroke patients' e-health literacy using advanced LPA. These findings hold implications for healthcare approaches, contributing to the enhancement of stroke patients' e-health literacy, enabling them to apply the acquired e-health information to manage and solve their own health issues. No patient or public contribution.