Multi-stage optimization strategy based on contextual analysis to create M-health components for case management model in breast cancer transitional care: the CMBM study as an example.

BACKGROUND: None of the early M-Health applications are designed for case management care services. This study aims to describe the process of developing a M-health component for the case management model in breast cancer transitional care and to highlight methods for solving the common obstacles faced during the application of M-health nursing service. METHODS: We followed a four-step process: (a) Forming a cross-functional interdisciplinary development team containing two sub-teams, one for content development and the other for software development. (b) Applying self-management theory as the theoretical framework to develop the M-health application, using contextual analysis to gain a comprehensive understanding of the case management needs of oncology nursing specialists and the supportive care needs of out-of-hospital breast cancer patients. We validated the preliminary concepts of the framework and functionality of the M-health application through multiple interdisciplinary team discussions. (c) Adopting a multi-stage optimization strategy consisting of three progressive stages: screening, refining, and confirmation to develop and continually improve the WeChat mini-programs. (d) Following the user-centered principle throughout the development process and involving oncology nursing specialists and breast cancer patients at every stage. RESULTS: Through a continuous, iterative development process and rigorous testing, we have developed patient-end and nurse-end program for breast cancer case management. The patient-end program contains four functional modules: "Information", "Interaction", "Management", and "My", while the nurse-end program includes three functional modules: "Consultation", "Management", and "My". The patient-end program scored 78.75 on the System Usability Scale and showed a 100% task passing rate, indicating that the programs were easy to use. CONCLUSIONS: Based on the contextual analysis, multi-stage optimization strategy, and interdisciplinary team work, a WeChat mini-program has been developed tailored to the requirements of the nurses and patients. This approach leverages the expertise of professionals from multiple disciplines to create effective and evidence-based solutions that can improve patient outcomes and quality of care.

Successful bio-electrochemical treatment of nitrogenous mariculture wastewater by enhancing nitrogen removal via synergy of algae and cathodic photo-electro-catalysis.

Systems with catalytic cathode in microbial fuel cell can achieve high treatment efficiency enhanced by the cathode. Such bio-electrochemical systems have potential applications in treating high-salinity nitrogenous mariculture wastewater. For sustainable development of the mariculture industry, enhancing inorganic nitrogen removal is of vital importance due to the low carbon to nitrogen (C/N) ratio of wastewater and strict discharge standard. Herein, simulated mariculture wastewater (high salinity, low COD/N ratio of 0.5-1.0) was successfully treated in an integrated self-biased bio-electrochemical system, with catalyst (TiO2/Co-WO3/SiC) on the cathode and natural-grown algae in the cathode chamber. Satisfactory nitrogen removal (94.05% NH4+-N and 77.35% inorganic nitrogen) and favorable 76.66% removal of organics (UV254) were both achieved, with visible light illumination. The NH4+-N in the effluent was below 2 mg L-1. The synergy of bacteria, algae and cathode, promoted pollutant removal, and made the system sustainable and efficient in treating mariculture wastewater.