Exploring illness uncertainty categories in ischemic stroke patients and the relationship with perceived social support: a latent class analysis.

Objectives: This study examined the categories of illness uncertainty and their influencing factors in ischemic stroke patients and analyzed their relationship with perceived social support.

Methods: Patients with ischemic stroke who were admitted to the neurology department of a tertiary general hospital in Yibin City from June to December 2024 were selected for this study. The general information questionnaire, the Mishel Uncertainty in illness scale, and the perceived social support scale were used. Latent class analysis was carried out based on the patients' illness uncertainty and explored the relationship with perceived social support.

Results: Illness uncertainty in ischemic stroke patients could be classified into 3 different latent classes, namely, "low-level-unpredictability group" (16.43%), "medium-level group" (14.52%), and "high-level-complexity group" (69.05%). Logistic regression analysis showed that place of residency, educational level, per capita monthly household income, number of comorbid other chronic diseases, mRS scores, and self-care ability were the factors influencing the latent class of illness uncertainty in stroke patients (p < 0.05). The difference between the three latent classes of illness uncertainty in ischemic stroke patients was statistically significant in the perceived social support score (p < 0.05).

Conclusion: Illness uncertainty in ischemic stroke patients has a distinct categorical class and perceived social support differs for each category. Targeted interventions should be carried out according to the categorization of patients' illness uncertainty class traits in order to reduce the level of patients' illness uncertainty and promote physical and mental health.