## 4 Discussion
### Strengths and Limitations  
The PERSIST project effectively engaged cancer survivors and provided a positive experience. Participants demonstrated patient activation and self-efficacy, and the project enhanced self-management among cancer patients. The majority of participants were satisfied with the mobile app and its usage. However, despite high attrition rates forquestionnaires, particularly for the SUS, the overall retention rate for the trial remained moderate. The PERSIST system shows potential applications in various medical fields, particularly in primary care settings, where it could significantly improve patient outcomes and clinical decision-making. Patient engagement with the mHealth app was robust, as evidenced by consistent follow-up and active data monitoring. Additionally, the integration of mHealth apps and smart bracelets significantly reduced depression and anxiety symptoms, suggesting a positive impact on patients' mental health. Clinicians also provided positive feedback, indicating that both the PERSIST system and the mClinician app (version 1.0) have the potential to be useful tools in clinical practice. They highlighted their value in monitoring patient parameters, receiving timely alerts, and providing personalized care plans. Several limitations inherent to this study should be acknowledged. Firstly, the substantially smaller sample size than initially projected by the power analysis is the primary limitation of this study, which directly impacts our ability to detect statistically significant effects. The observed effects in our study may not reach statistical significance due to the limited sample size, even if the intervention had a positive impact on healthy habits. This limitation is particularly relevant for the SUS questionnaire, which had the highest attrition rate and the smallest final sample size. While we report observed effect sizes, the lack of statistical power weakens the strength of our conclusions regarding the intervention's effectiveness. This highlights the need for cautious interpretation of the findings and underscores the importance of future research with larger, more stable samples to confirm these preliminary observations. Factors contributing to the attrition included participant burden, fluctuating health conditions, technical difficulties, and a lack of perceived benefit or decreasing motivation. To mitigate these challenges in future studies, researchers should focus on minimizing participant burden, recruiting more participants than initially estimated, providing enhanced technical support, maximizing perceived benefit, and incentivizing participation. The second limitation was the challenge of ensuring continuous data integration into the medical workflow, particularly regarding the timely transfer of lifestyle data, laboratory results, and other EHR data. Future research should prioritize the development of automated data entry systems to ensure that the warning system and prediction models remain up-to-date, fast, and accurate, ultimately optimizing clinical decision-making. Thirdly, technical considerations limited participant recruitment. To avoid burdening participants with complex devices, simple and cost-effective options were chosen. However, this decision potentially impacted the richness of the collected data. In the future, careful device selection and testing will be essential to balance participant comfort with comprehensive data collection. Fourthly, the absence of a traditional control or comparison group is a key limitation resulting from the SCED methodology employed in this study. While SCED offers strong internal validity by controlling for individual variability, it lacks the between-participant comparison provided by traditional randomized controlled trials or cohort studies. This means we cannot directly compare the outcomes of participants using the PERSIST platform with a separate group receiving standard care or no intervention.