Investigating and Prioritizing Factors Affecting Health Literacy in University Students of Yazd Using Artificial Neural Network Technique - Hamideh Shekari (Shahid Sadoughi University of Medical Sciences, 2019)
Background: Current university students are potential and actual parents of future generations. The level of their health literacy affects health and health literacy level of future generations. Therefore, the purpose of the present study was investigating and prioritizing the factors affecting the health literacy of students in Yazd (a city in central Iran) using an artificial neural network technique. Methods: This study was cross-sectional and descriptive and it was conducted on 400 university students in Yazd during autumn 2018. Data were collected using a questionnaire on health literacy and 14 independent variables. Data were analyzed with SPSS software via descriptive statistics, one sample T-test, and artificial neural network. Results: The mean of students' health literacy was 80.65±12.21. The most important factors affecting the level of students' health literacy were the grade, college, father's education level, age, and residence. Conclusion: Since grade had the greatest impact on health literacy of students, it is suggested that university officials consider the campus to hold classes, lectures, workshops and distribute appropriate resources such as brochures, booklets among students and also provide health information stations at locations such as dining room, university entrance, and dormitory to promote students' health literacy in lower grades.