Identification of Planned Stroke Awareness Behavior: A Structural Equation Modeling

Abstract

Introduction: Stroke is one of the most common neurological diseases, often causing death or gross physical impairment or disability. The associated risk factors such as hypertension, high cholesterol, diabetes, heart disease, and smoking should serve as warnings. However, most people are still not aware of these risks. The main aim of this study is to identify stroke awareness behavior using the construct variable from the Theory of Planned Behavior as the predictor (attitude factor, subjective norm factor, perceived behavioral factor, and intention to perform behavior). Methods: A cross-sectional study was conducted on 256 people who have a high risk of stroke at the Poncokusumo Health Center, Malang, Indonesia. The sampling technique used was purposive sampling. The authors used all the construct variables in the Theory of Planned Behavior. The stroke awareness behavior was measured using a questionnaire developed from the National Stroke Awareness Guide, while the attitude factor, subjective norm factor, perceived behavioral factor, and intention were measured using the instruments developed from standard instruments from the Theory of Planned Behavior. Structural Equation Modeling (SEM-PLS) was used to analyse the data. Result: This study found that 68.4% of respondent with high or low intention of preventing a stroke can be predicted by attitude factors, subjective norm factors, and perceived behavioral factors. While 96.1% of good or bad stroke awareness behavior can be predicted by the model used in this study, the rest (3.9%) is explained by other variables outside this research model. Conclusion: The hypothesis testing results showed that all construct variables in the Theory of Planned Behavior can be strong predictors of stroke awareness behavior. All variables in the Theory of Planned Behavior can be powerful predictors of stroke awareness behavior.