We provide expertise using a deliberate process that integrates behavioral theory, design thinking, user-centered design, and rigorous evaluation.
We utilize the IDEAS framework to develop, implement, and disseminate effective, sustainable, and scalable mHealth solutions.
We conduct formative research to gather qualitative and quantitative data from target users (e.g., in-depth interviews, focus groups, surveys). Focus inquiry assesses population use of mHealth modalities and needs and identifies theory-based behavioral strategies most aligned with the intervention area of focus and target users.
To ensure our apps are culturally and contextually relevant, appropriate and respectful, we keep our users at the heart of our process. We start with an understanding of our user, what their problem or challenge is, what their capabilities are, and keep a focus on them throughout the design and implementation phase.
We encourage and assist all our partners to hire consultants from the community itself. We ourselves often leverage our Diversity, Equity, and Inclusion Research Consultants (DEI RCs) to help us develop creative solutions that feel designed for users’ unique needs. Our DEI RCs and other community advising groups provide consultation on app user interface (UI) and UX (user experience), as well as language, images, and overall content.
It is pertinent to us that the product is evaluated first by individuals from the target population prior to real world usage. Each project undergoes rigorous beta testing with a subset of their user population. This allows the study team to iterate and enhance the app, incorporating user feedback and customizations, allowing for an even further tailored experience.
When working with our partners to design and adapt the HMP platform, we keep the end-user and project objectives in mind, ensuring that the app is built appropriately for and responsive to our focus populations’ unique needs. We continually ask ourselves:
Can we push personalized and relevant material?
Can we respond at the right time with the right intervention?
Will this maximize engagement at the individual level?
Could this allow for more efficient and expedient scale-up?
We use passive data collected by the app to follow users’ journeys and respond according to their needs and interests. We can track in real-time how folks are engaging with the app, including whether they are tracking medication, what types of articles they read, how frequently they log in, which videos interest them, and so on. From this information we can respond by pushing tailored content in the right format at the right time.
Having access to passive data such as this also provides us a measurement to evaluate if increased engagement with the app, which we hope improves a user’s knowledge on health and wellness, self-efficacy implementing healthy, protective behaviors and resilience to social stigmas, will improve one’s health outcomes.
Pilot testing of interventions assesses the feasibility, acceptability, and potential efficacy of each intervention.
We rigorously utilize paradata to evaluate intervention engagement and iterate to improve for a larger trial.
After iterating from lessons learned in our pilot-testing, we then conduct larger efficacy trials to better evaluate behavioral change outcomes and implementation-focused outcomes. Measures we consider during these larger trials include:
Study Analysis and Dissemination
We assist with study analysis including paradata metrics, for dissemination and publication as well as ensure the sustainability of mHealth platforms for future scale-up.
Check out our publications in peer-reviewed, academic journals!
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