Hyo-Sook Oh1, Hyeoun-Ae Park. 1. Department of Nursing, Daebul University, 72, Sanho-ri, Samho-up, Korea. ohs0@mail.daebul.ac.kr
Abstract
PURPOSE: This study was performed to develop and test a decision-tree model of treatment-seeking behaviors about when Korean patients visit a doctor after experiencing stroke symptoms. METHODS: The study used methodological triangulation. The model was developed based on qualitative data collected from in-depth interviews with 18 stroke patients. The model was tested using quantitative data collected from interviews and a structured questionnaire involving 150 stroke patients. The predictability of the decision-tree model was quantified as the proportion of participants who followed the pathway predicted by the model. RESULTS: Decision outcomes of the model were categorized into immediate and delayed treatment-seeking behavior. The model was influenced by lowered consciousness, social-group influences, perceived seriousness of symptoms, past history of hypertension or stroke, and barriers to hospital visits. The predictability of the model was found to be 90.7%. CONCLUSIONS: The results from this study can help healthcare personnel understand the education needs of stroke patients regarding treatment-seeking behaviors, and hence aid in the development of educational strategies for stroke patients.
PURPOSE: This study was performed to develop and test a decision-tree model of treatment-seeking behaviors about when Korean patients visit a doctor after experiencing stroke symptoms. METHODS: The study used methodological triangulation. The model was developed based on qualitative data collected from in-depth interviews with 18 strokepatients. The model was tested using quantitative data collected from interviews and a structured questionnaire involving 150 strokepatients. The predictability of the decision-tree model was quantified as the proportion of participants who followed the pathway predicted by the model. RESULTS: Decision outcomes of the model were categorized into immediate and delayed treatment-seeking behavior. The model was influenced by lowered consciousness, social-group influences, perceived seriousness of symptoms, past history of hypertension or stroke, and barriers to hospital visits. The predictability of the model was found to be 90.7%. CONCLUSIONS: The results from this study can help healthcare personnel understand the education needs of strokepatients regarding treatment-seeking behaviors, and hence aid in the development of educational strategies for strokepatients.