Background: Postpartum depression is a significant mental health problem, affecting up to 20% of women in the postpartum period. Mobile health applications offer the potential to improve early detection of Detection postpartum depression, yet a comprehensive understanding of these technologies' effectiveness, challenges, and implications is limited. Objectives: This literature review aims to analyze the development and implementation of mobile health applications for the early detection of postpartum depression. Methods: A systematic search was conducted on PubMed, Scopus, Web of Science, IEEE Xplore, and PsycINFO databases for studies published between 2019 and 2024; the method follows the PRISMA guidelines. Of the 486 articles identified, nine studies met the inclusion criteria and were analyzed using a narrative synthesis approach. Results: Of the nine studies, the analysis revealed mobile apps' significant potential in improving the detection of Detection postpartum depression. However, it emphasized the importance of approaches that consider technical and social aspects in design and implementation. Key challenges include long-term compliance, data privacy, cross-cultural validation, and integration with existing healthcare systems. Conclusion: Mobile health apps offer a promising tool for the early detection of postpartum depression. Full realization of this potential requires a multidisciplinary approach involving collaboration between researchers, technology developers, healthcare providers, and users
                        
                        
                        
                        
                            
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