Predictive Model of Self-management in Patients With Stroke Based on the Information-Motivation-Behavioral Skills Model

Background Patients who had a stroke are required to manage risk factors, and self-management for risk factor control in stroke is essential. Recent studies using the information-motivation-behavioral skills model reported that the model is effective for predicting and explaining self-management behavior in chronically ill patients. Objectives This study aimed to develop and verify the predictive model of self-management based on the information-motivation-behavioral skills model in patients with stroke. Methods This was a descriptive, cross-sectional study; path analysis was conducted to develop and verify the hypothesized predictive model. We recruited 242 patients who had a stroke using convenience sampling from the neurological outpatient clinic. Results The model's fit indices were adequate. Stroke self-management knowledge, social support, and self-efficacy had a direct effect on stroke self-management, and stroke self-management knowledge and attitude and social support had an indirect effect on stroke self-management, mediated by self-efficacy. Stroke self-management knowledge and attitude, social support, and self-efficacy explained 27.5% of the total variance in stroke self-management. Conclusions The information-motivation-behavioral skills model is potentially a predictive model for self-management for patients who had a stroke. Considering the level of stroke knowledge and attitude, social support, and self-efficacy together may help to understand the required level of self-management. In addition, using this model for the development of self-management interventions for patients who had a stroke could be a strategy for improving self-management in patients with stroke.