Background Traditional in-clinic methods of collecting self-reported information are costly, time-consuming, subjective, and often limited in the quality and quantity of observation. However, smartphone-based ecological momentary assessments (EMAs) provide complementary information to in-clinic visits by collecting real-time, frequent, and longitudinal data that are ecologically valid. While these methods are promising, they are often prone to various technical obstacles. However, despite the potential of smartphone-based EMAs, they face technical obstacles that impact adaptability, availability, and interoperability across devices and operating systems. Deficiencies in these areas can contribute to selection bias by excluding participants with unsupported devices or limited digital literacy, increase development and maintenance costs, and extend deployment timelines. Moreover, these limitations not only impede the configurability of existing solutions but also hinder their adoption for addressing diverse clinical challenges. Objective The primary aim of this research was to develop a cross-platform EMA app that ensures a uniform user experience and core features across various operating systems. Emphasis was placed on maximizing the integration and adaptability to various study designs, all while maintaining strict adherence to security and privacy protocols. JTrack-EMA+ was designed and implemented per the FAIR (findable, accessible, interpretable, and reusable) principles in both its architecture and data management layers, thereby reducing the burden of integration for clinicians and researchers. Methods JTrack-EMA+ was built using the Flutter framework, enabling it to run seamlessly across different platforms. This platform comprises two main components. JDash (Research Centre Jülich, Institute of Neuroscience and Medicine, Brain and Behaviour [INM-7]) is an online management tool created using Python (Python Software Foundation) with the Django (Django Software Foundation) framework. This online dashboard offers comprehensive study management tools, including assessment design, user administration, data quality control, and a reminder casting center. The JTrack-EMA+ app supports a wide range of question types, allowing flexibility in assessment design. It also has configurable assessment logic and the ability to include supplementary materials for a richer user experience. It strongly commits to security and privacy and complies with the General Data Protection Regulations to safeguard user data and ensure confidentiality. Results We investigated our platform in a pilot study with 480 days of follow-up to assess participants’ compliance. The 6-month average compliance was 49.3%, significantly declining (P=.004) from 66.7% in the first month to 42% in the sixth month. Conclusions The JTrack-EMA+ platform prioritizes platform-independent architecture, providing an easy entry point for clinical researchers to deploy EMA in their respective clinical studies. Remote and home-based assessments of EMA using this platform can provide valuable insights into patients’ daily lives, particularly in a population with limited mobility or inconsistent access to health care services.