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The Relationship Between Individual Characteristics With Public Stroke Knowledge
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The Relationship Between Individual Characteristics With Public Stroke Knowledge
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The Relationship Between Individual Characteristics With Public Stroke Knowledge
The Relationship Between Individual Characteristics With Public Stroke Knowledge
Journal Article

The Relationship Between Individual Characteristics With Public Stroke Knowledge

2022
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Overview
According to the World Health Organization (WHO), degenerative diseases have caused nearly 17 million deaths worldwide. This increasing number makes degenerative diseases the most significant human killer disease that continues to occur today. Degenerative diseases with high morbidity and mortality rates are vascular diseases. Stroke is considered one of the vascular diseases that often causes high morbidity and mortality rates because stroke is the number 1 cause of disability and the number 3 cause of death after coronary heart disease and cancer. The success of stroke treatment starts from people's knowledge that stroke is an emergency. The philosophy must be adhered to is that time is the brain and the golden hour. To achieve that, education and counselling need to be sought primarily by the community because they are the most likely to meet stroke patients directly. The purpose of this study was to determine the relationship between individual characteristics based on age, gender, education level, address, marital status, employment status, income level, number of family members in one house, information media used, sources of information obtained and family history of stroke owned with public knowledge about stroke which is divided into 4 indicators, namely knowledge about stroke symptoms, stroke risk factors, stroke treatment and stroke prevention. This research is an observational-cross-sectional study conducted on 801 respondents using an accidental sampling technique through the distribution of a validated questionnaire. The distribution of the questionnaire was carried out online with the line and WhatsApp applications through personal chat and existing group chats. The data results were then analyzed and processed using a logistic binary and multivariate logistic regression tests. All tests were conducted using the Statistical Package for Social Sciences (SPSS) version 25 program.