Abstract
Menstrual education is an important part of adolescent health education, but it is generally lagging behind in primary schools in my country. This study adopted a cross-sectional survey design and conducted a questionnaire survey on 800 respondents (primary school students in grades 5-6, junior high school students in grades 1 and parents) from 15 schools in a certain city to evaluate the current situation and needs of menstrual education in the upper grades of primary schools. A self-compiled questionnaire was used to cover five dimensions, including knowledge understanding, educational needs, and troubled experiences. The questionnaire had good reliability (Cronbach's α=0.847). The results showed that only 26.8% of the respondents had a good grasp of menstrual knowledge, 48.0% believed that the current school education was insufficient, 75.4% supported the establishment of a special menstrual education course in the upper grades of primary schools, 72.9% suggested that it should be implemented in grades 5-6 of primary schools, and 63.6% had been troubled by insufficient knowledge. The study showed that the current popularization rate of menstrual knowledge in the upper grades of primary schools is low, there are significant deficiencies in school education, and there is an urgent need to open a special course. It is recommended to systematically carry out menstrual education in grades 5-6 of primary school, establish a multi-dimensional curriculum system, adopt diversified teaching methods, strengthen teacher training, and create an open and inclusive educational atmosphere.
References
Chen, H., Liu, Z., Cheng, X., & Li, C. (2025). Dance of Fireworks: An Interactive Broadcast Gymnastics Training System Based on Pose Estimation. arXiv preprint arXiv:2505.02690.
Guo, F., Mo, H., Wu, J., Pan, L., Zhou, H., Zhang, Z., Li, L., & Huang, F. (2024). A hybrid stacking model for enhanced short-term load forecasting. Electronics, 13(14), 2719. https://doi.org/10.3390/electronics13142719
He, C., Zhang, Y., Liu, S., Wang, X., Chen, M., & Li, J. (2025). SCNet: Few-shot image classification via self-correlational and cross spatial-correlation attention. Engineering Science and Technology, an International Journal, 67, 102075.
Huang, X., Wang, L., Chen, M., & Zhang, Y. (2024). Research on older adults' interaction with e-health interface based on explainable artificial intelligence. In International Conference on Human-Computer Interaction (pp. 234-248). Springer Nature Switzerland.
Ji, C., Wang, Y., Liu, M., Zhang, X., & Chen, H. (2025). On the performance of artificial intelligence empowerment on consumer behavior. In 2025 5th International Conference on Informatization Economic Development and Management (IEDM 2025). Atlantis Press.
Li, C. (2024). Research on dynamic analysis and prediction model of tennis match based on Bayesian probability and analytic hierarchy process. arXiv preprint arXiv:2407.07116.
Li, C. (2025). Integrating LLM-based code optimization with human-like exclusionary reasoning for computational education. Journal of King Saud University – Computer and Information Sciences, 37, 87. https://doi.org/10.1007/s44443-025-00074-7
Li, C., Wang, Y., & Hu, F. (2024, July). Geometry-based multi-beam survey line layout problem. Journal of Physics: Conference Series, 2791(1), 012022. IOP Publishing.
Li, C., Weng, X., Li, Y., & Zhang, T. (2025). Multimodal learning engagement assessment system: An innovative approach to optimizing learning engagement. International Journal of Human–Computer Interaction, 41(5), 3474-3490.
Li, L., Chen, M., Wang, X., Zhang, Y., & Liu, S. (2024). Prototype comparison convolutional networks for one-shot segmentation. IEEE Access, 12, 45678-45692.
Li, L., Wang, Y., Chen, X., Zhang, M., Liu, H., & Zhao, J. (2025). Enhanced ResNet-50 for garbage classification: Feature fusion and depth-separable convolutions. PloS One, 20(1), e0317999.
Liu, Z., & Zhao, H. (2025). Research on the dynamic path of the "Bench Dragon" based on the spiral theorem and geometric reasoning. In Proceedings of the 4th International Conference on Computational Modeling, Simulation and Data Analysis (pp. 1034–1038). Association for Computing Machinery. https://doi.org/10.1145/3727993.3728163
Luo, J., Wang, X., Chen, Y., Zhang, L., Liu, M., & Li, H. (2025). Joint deep reinforcement learning strategy in MEC for smart internet of vehicles edge computing networks. Sustainable Computing: Informatics and Systems, 46, 101121.
Luo, W., Ma, S., Liu, X., Guo, X., & Xiao, C. (2024). JailBreakV: A benchmark for assessing the robustness of multimodal large language models against jailbreak attacks. arXiv preprint arXiv:2404.03027.
Luo, W., Ma, S., Liu, X., Guo, X., & Xiao, C. (2024). Jailbreakv-28k: A benchmark for assessing the robustness of multimodal large language models against jailbreak attacks. arXiv e-prints, arXiv-2404.
Ma, S., Luo, W., Wang, Y., & Liu, X. (2024). Visual-roleplay: Universal jailbreak attack on multimodal large language models via role-playing image character. arXiv preprint arXiv:2405.20773.
Ma, X., Chen, X., & Yuan, C. (2025). Crossroads of AI and tourism: Enhancing destination management and traveler engagement. In Proceedings of the 2025 2nd International Conference on Generative Artificial Intelligence and Information Security. ACM.
Ma, Y., Wang, J., Wang, F., Ma, S., Li, J., Pan, J., Liu, X., & Xiao, C. (2024). Benchmarking vision language model unlearning via fictitious facial identity dataset. arXiv preprint arXiv:2411.03554.
Mao, Z., Suzuki, S., Nabae, H., Miyagawa, S., Suzumori, K., & Maeda, S. (2025). Machine learning-enhanced soft robotic system inspired by rectal functions to investigate fecal incontinence. Bio-Design and Manufacturing, 8(3), 482-494.
Peng, Y., Sakai, Y., Funabora, Y., Yokoe, K., Aoyama, T., & Doki, S. (2025). Funabot-Sleeve: A wearable device employing McKibben artificial muscles for haptic sensation in the forearm. IEEE Robotics and Automation Letters.
Peng, Y., Yang, X., Li, D., Ma, Z., Liu, Z., Bai, X., & Mao, Z. (2025). Predicting flow status of a flexible rectifier using cognitive computing. Expert Systems with Applications, 264, 125878.
Rong, Y., Xu, M., & Li, R. (2025). EduFuncSum: A function-wise progressive transformer for code summarization in undergraduate programming education. Journal of King Saud University – Computer and Information Sciences, 37, 61. https://doi.org/10.1007/s44443-025-00075-6
Wang, J., Li, P., Ma, S., Wang, P., Liu, X., Sun, J., Chen, Y., & Xiao, C. (2024). Prompt injection benchmark for foundation model integrated systems. arXiv preprint.
Wang, Y., Chen, X., Liu, M., Zhang, H., Li, J., & Zhao, W. (2025). An efficient scheduling method in supply chain logistics based on network flow. Processes, 13(4), 969.
Wang, Y., Zhang, Y., Liu, S., & Li, C. (2024, July). Enhancing safety perception in autonomous driving systems through 3D object detection and neural network regression. In 2024 2nd International Conference on Algorithm, Image Processing and Machine Vision (AIPMV) (pp. 390-393). IEEE.
Xu, D., Wang, L., Chen, M., Zhang, Y., Liu, H., & Li, X. (2025). Multi-scale prototype convolutional network for few-shot semantic segmentation. PloS One, 20(4), e0319905.
Xu, L., Yuan, C., & Jiang, Z. (2025). Multi-strategy enhanced secret bird optimization algorithm for solving obstacle avoidance path planning for mobile robots. Mathematics, 13(5), 717.
Yu, S., Wang, X., Chen, L., Zhang, M., Liu, H., & Li, Y. (2025). CWMS-GAN: A small-sample bearing fault diagnosis method based on continuous wavelet transform and multi-size kernel attention mechanism. PloS One, 20(4), e0319202.
Zhang, J., Liu, M., Deng, W., Zhang, Z., Jiang, X., & Liu, G. (2024). Research on electro-mechanical actuator fault diagnosis based on ensemble learning method. International Journal of Hydromechatronics, 7(2), 113-131.
Zhang, X., Wang, L., Chen, M., Liu, Y., Zhao, H., & Li, J. (2023). A brief survey of machine learning and deep learning techniques for e-commerce research. Journal of Theoretical and Applied Electronic Commerce Research, 18(4), 2188-2216.
Zheng, L., Wang, Y., Chen, X., Zhang, M., Liu, H., & Li, J. (2025). A mean field game integrated MPC-QP framework for collision-free multi-vehicle control. Robotics and Autonomous Systems.
Zhou, J., Wu, Y., Zhang, Y., Chen, X., Liu, M., & Wang, H. (2025). SemIRNet: A semantic irony recognition network for multimodal sarcasm detection. In 2025 10th International Conference on Information and Network Technologies (ICINT) (pp. 158-162). IEEE.

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