Abstract
Background: Breast cancer surgery requires comprehensive postoperative care to optimize recovery and patient outcomes. Mobile health applications have gained attention as tools to enhance patient engagement, provide education, and support recovery through features like symptom tracking and communication with healthcare providers. This systematic review aims to evaluate the impact of these applications on care outcomes in patients undergoing breast cancer surgery.
Methods: This systematic literature study was conducted from January 2012 to December 2022 across PubMed, ProQuest and Google Scholar databases to identify randomized controlled trials assessing the effect of mobile applications on care outcomes in patients who underwent breast cancer surgery. Studies were included based on specific criteria: they had to evaluate mobile health interventions post-surgery and report on at least one outcome related to symptom management, quality of life, anxiety, depression, or distress. The content, methods and quantitative findings of all publications were analyzed.
Results: The review included, four randomized controlled trial, covering a total of 318 participants. Across the studies, mobile health applications demonstrated a significant improvement in care outcomes. Symptom management effectiveness improved by 15-25%, anxiety and distress levels decreased by 10-20%, and patient-reported quality of life increased by an average of 15-25%. Additionally, mobile applications were associated with enhanced communication with healthcare providers, facilitating early intervention and support.
Conclusion: Mobile health applications were found to significantly improve care outcomes for breast cancer patients undergoing surgery. These applications are also effective and safe in improving the quality of life, managing symptoms, and reducing psychological distress. The integration of mobile health tools can enhance patient care pathways and postoperative recovery. Future research should explore long-term impacts, optimal app features, and scalability in diverse patient populations.
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