Anxiety subtypes in rural ischaemic stroke survivors: A latent profile analysis

AIM: To determine the potential profile classes of anxiety reported by ischaemic stroke survivors in rural China, and to explore the characteristics of patients having different types of post-stroke anxiety. DESIGN: A cross-sectional survey. METHODS: A cross-sectional survey was conducted by using convenience sampling to collect data from 661 ischaemic stroke survivors in rural Anyang city, Henan Province, China, from July 2021 to September 2021. The parameters included in the study were the socio-demographic characteristics, self-rating anxiety scale (SAS), self-rating depression scale (SDS) and the Barthel index of daily activity ability. Potential profile analysis was done to recognize subgroups of post-stroke anxiety. The Chi-square test was performed to explore the characteristics of individuals with different types of post-stroke anxiety. RESULTS: The model fitting indices of stroke survivors supported three classes of anxiety models which were as follows: (a) Class 1, low-level, stable group (65.3%, N = 431); (b) Class 2, moderate-level, unstable group (17.9%, N = 118) and (c) Class 3, high-level, stable group (16.9%, N = 112). The risk factors associated with post-stroke anxiety were female patients, lower levels of education, living alone, lower monthly household income, other chronic diseases, impaired daily activity ability and depression. CONCLUSIONS: This study identified three different subgroups of post-ischaemic stroke anxiety and their characteristics in patients in rural China. IMPACT: This study has significance in providing evidence for the development of targeted intervention measures to reduce negative emotions in different subgroups of post-stroke anxiety patients. PATIENT OR PUBLIC CONTRIBUTION: In this study, the researchers arranged the time of questionnaire collection with the village committee in advance, gathered the patients to the village committee for face-to-face questionnaire survey and collected the household data of the patients with mobility difficulties.