Application of Health Education Program based on Intelligent Recommendation Algorithm in the Development of School-age Children's Hand Hygiene Behavior

Abstract

The cultivation of hand hygiene behavior among school-age children is an important way to prevent the spread of diseases and ensure children’s health. However, traditional health education methods lack personalized programs tailored to each child, which cannot effectively improve their hand hygiene awareness and behavior. In response to this issue, the study combines multi-objective particle swarm optimization algorithm to provide personalized hand hygiene behavior development recommendations for school-age children, improving their hand hygiene awareness and behavioral level. The study adopted multi-objective particle swarm optimization algorithm and convolutional neural network, combined with the personalized needs of school-age children and the goal of cultivating hand hygiene behavior, and proposed a health education plan based on intelligent recommendation algorithm. Through deep learning, match the hand hygiene needs of school-age children with corresponding health education plans to achieve personalized recommendations. The average accuracy of the health education recommendation plan for hand hygiene behavior cultivation of school-age children based on multi-objective particle swarm optimization algorithm reaches 99.07%. Meanwhile, after introducing convolutional neural networks, the feature matching error between the recommended scheme and school-age children ranges from 10-1 to 10-2. After testing, the designed algorithm performs more stably and has less fluctuations under different sparsity conditions. Health education solutions based on intelligent recommendation algorithms can provide personalized solutions for school-age children, effectively cultivate their hand hygiene behavior, and meet various health needs.