Technology Training & Dissemination

Training & Dissemination Lead: Vivek Shetty

Co-Investigator: Minjeong Jeon

The mDOT Center is working to develop and disseminate the methods, tools, and infrastructure necessary for researchers to pursue the discovery, optimization and translation of temporally-precise mHealth interventions. Given that the inherently transdisciplinary, team-based nature of mHealth research requires scientists to cross disciplinary and institutional boundaries, training and dissemination in mHealth technologies requires a team-science approach. mDOT leverages our established and mature infrastructure, widely visible mHealthHUB platform, and an experienced team to develop training and dissemination activities to involve new research groups with little or no technological expertise. By reducing access barriers, we seek to reduce the growing disparity among various research groups in using latest mHealth sensing, biomarker, and analytics technology in their research.

The main goals of the mDOT’s Technology Training and Dissemination (TT&D) Core are two-fold: (a) improve the general understanding and uptake of the mDOT technologies and methods by the mHealth research communities; (b) develop a perpetuating cadre of transdisciplinary researchers conversant with the mDOT technologies and able to effectively apply them in their own research programs. Envisioned as national resource, the dissemination activities of mDOT focus on informing the scientific community about the tools and processes developed by mDOT and facilitate broad distribution and optimized use of the mDOT technologies. Training efforts reach beyond mDOT affiliates to include mentorships, a scholar exchange program, and a visiting scholar residency program. Our annual mHealth Training Institute (mHTI) and other group courses and workshops are common forums that blend mDOT’s dissemination with direct training activities. We offer a combined approach of “light-touch” outreach using web-portals (such as mHealthHUB) with “heavy-touch” outreach activities including training sessions, workshops, and conferences to inform the scientific community about the technical capabilities and accomplishments of mDOT, and to both promote and enable a broader use of the mDOT methods and technologies.

A key feature of mDOT’s training and dissemination activities is an evaluative component that will use a combination of Google Analytics and Robotic Process Automation (RPA) to automate repetitive assessments of the uptake and effectiveness of the mDOT’s infrastructure and tools by a diverse population of mHealth researchers. The ongoing evaluations will refine the infrastructure based on user feedback and gauge ongoing community support for the mDOT’s activities. The effectiveness evaluation and iterative refinement of infrastructure operations will be anchored to a “Theory of Action” logic model that will provide an analytic framework linking the mDOT’s activities (e.g., tools, training/dissemination) to the outcomes (reduce the barriers to entry for mHealth researchers engaging in sensor-derived biomarkers and sensor-guided mHealth interventions, to increase utilization of the mDOT tools, reduce fragmentation of research efforts across studies, and facilitate increased engagement of the mHealth community in mDOT’s activities).