Main Article Content
Abstract
Pneumonia remains a leading cause of mortality among children under five worldwide, with recurring cases significantly contributing to this burden. In Indonesia, pneumonia ranks as the second leading cause of infant death, with high rates of recurrence that impair child health. This study aims to develop and evaluate a Peer Education Model, HBA (Hygiene Behaviour Awareness), integrated with Artificial Intelligence (AI) to prevent recurrent pneumonia and reduce transmission risks in preschool children. The research adopts a quasi-experimental design with pre- and post-tests without a control group, involving 20 participants who were divided into two intervention groups. Data collection included a literature review, instrument development, prototype design, and implementation of the AI-based peer education intervention, conducted over two months with six sessions, followed by a four-month follow-up to assess pneumonia recurrence. Statistical analysis was conducted to evaluate the effectiveness of the intervention. The results are expected to demonstrate improved parental knowledge, behaviors, and adherence to pneumonia prevention steps, ultimately reducing recurrence rates. This innovative approach integrates digital technology and peer groups to enhance health literacy and early detection of at-risk children. The findings are expected to contribute to sustainable health efforts aligned with SDGs 3 and 4, emphasizing health promotion and quality education. The developed HBA-10M AI prototype will be published and protected by copyright, offering a scalable strategy for pneumonia prevention in similar contexts. This study highlights the potential of AI-supported peer education in improving child health outcomes and provides a model for community-based health interventions. Overall, this research offers a novel solution to mitigate recurrent pneumonia among vulnerable populations by combining technological innovation with peer-led health education.
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JKEP (Jurnal Keperawatan)
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