Latent Profile Analysis of Self-Management Ability and Its Influencing Factors in Patients With Atrial Fibrillation

To explore the latent classes and various characteristics of self-management ability of patients with atrial fibrillation, and to analyse the influencing factors.

A cross-sectional study design.

A convenience sampling was used to select 208 patients with atrial fibrillation from 2 hospitals in Shandong Province, China between August 2022 and June 2023. The survey tools included the general data questionnaire, Brief Illness Perception Questionnaire and Self-Management Ability Scale for patients with atrial fibrillation. Data were analysed using latent profile analysis, univariate analysis and binary logistic regression.

The results of the latent profile analysis showed that the self-management ability of patients with atrial fibrillation was divided into two different latent classes. Binary logistic regression analysis showed that disease duration, primary caregiver and illness perception were significantly associated with self-management ability.

There are 2 potential categories of self-management ability in patients with atrial fibrillation. Appropriate individualised health management interventions for patients with atrial fibrillation, focusing on the patient's disease duration, primary caregiver and illness perception, may improve self-management in these patients.

This study is beneficial in providing information reference for medical staff. Medical staff can implement targeted interventions based on the categorical characteristics of the different profiles of self-management ability in patients with atrial fibrillation to improve their self-management ability.

We thank all participants for taking part in the survey throughout the study.