JMIR Publications

ABSTRACT

Background:

Cancer remains a leading cause of morbidity worldwide. To reduce this burden, scalable, effective approaches are needed to address modifiable risk factors for cancer and support behavioral self-management. With smartphone ownership now nearly ubiquitous, mobile health (mHealth) interventions offer a powerful means to extend the reach, accessibility, and sustainability of evidence-based treatments for a variety of modifiable risk factors (eg, excessive alcohol use, physical inactivity, poor diet, smoking). Moreover, the flexibility of mHealth platforms enables efficient delivery of novel interventions, supports innovative study designs, and facilitates real-time data collection to advance public health research.

Objective:

Despite the great potential of mHealth interventions, developing high-quality mHealth tools is complex, time consuming, and resource intensive. To address these challenges, we are developing a coordinated, accessible, research-grade infrastructure for mHealth app development, testing, and dissemination.

Methods:

The mHealth Florida infrastructure (mFLi) will provide a comprehensive, low-code software platform that enables researchers to build applications compatible with major mobile operating systems, namely Apple iOS and Google Android. Through a modular interface, users will select from a menu of prebuilt features to tailor functionality to specific study needs. The platform will include three integrated environments (development, testing, and production), allowing researchers to prototype, evaluate, and deploy mHealth interventions. This infrastructure will be developed and maintained by a multidisciplinary team, ensuring the platform is technically robust and usable and adheres to institutional and regulatory standards. To demonstrate the platform’s functionality, utility, and adaptability, a multisite study comprised of three initial projects focused on smoking cessation among cancer patients are being conducted: (1) participant screening and enrollment, (2) randomization and treatment delivery, and (3) data processing using machine learning methods with on-device and cloud-based approaches.

Results:

This study was approved by the institutional review boards at the H. Lee Moffitt Cancer Center (Advarra), University of Miami, and the University of Florida. Participant enrollment is ongoing.

Conclusions:

Collectively, these projects will illustrate how mFLi can streamline app development, facilitate rapid translation of research into practice, and reduce barriers for researchers and developers. Ultimately, mFLi is designed to accelerate innovation in mHealth research, enhance access to behavioral interventions, and improve health outcomes among diverse populations. Clinical Trial: This protocol was registered on clinicaltrials.gov (NCT06909357) on April 3, 2025.