Health Belief Clusters Among Stroke Patients: Insights for Tailored Interventions Using Latent Profile Analysis

Area of Science:

• Health Psychology
• Clinical Neurology
• Biostatistics

Background:

• Health beliefs significantly influence patient outcomes and adherence to treatment post-stroke.
• Understanding the heterogeneity in health beliefs among stroke survivors is essential for developing effective interventions.
• Previous research has not fully elucidated the distinct profiles of health beliefs in stroke patient populations.

Purpose of the Study:

• To identify latent profiles of health beliefs among stroke patients.
• To analyze differences in health beliefs across various clusters of stroke patients.
• To inform the development of targeted health education strategies for stroke survivors.

Main Methods:

• A stratified cluster random sampling approach recruited 1358 stroke patients in Henan Province, China.
• Data collected using validated questionnaires including the Short Form Health Belief Model Scale.
• Latent profile analysis (Mplus 8.3) identified health belief clusters; group differences analyzed using SPSS 26.0.

Main Results:

• A three-class model of health beliefs was supported, identifying distinct clusters: absent beliefs, self-deficiency, and higher perception behavior disorder.
• Significant differences in Short Form Health Belief Model Scale scores were observed across the three clusters.
• Key demographic and clinical factors, including modified Rankin Scale, health behavior, health knowledge, education, and hypertension, showed significant associations with health belief profiles.

Conclusions:

• Individual heterogeneity in health beliefs among stroke patients is significant and can be classified into three distinct profiles.
• These findings provide a basis for developing tailored health belief interventions and guidance for stroke patients.
• The study offers methodological insights for future clinical research on health beliefs in chronic disease populations.