To realise the full potential of mobile health (mHealth) interventions like Holly Health to support behaviour change and meet and maintain clinically meaningful outcomes, it is necessary to incorporate adaptive technology that provides individualised support and vary the intervention based on an individual's evolving needs and circumstances, as opposed to fixed interventions based on population means which will not be relevant/effective for everyone.
A JITAI is an intervention design that adapts the provision of support (e.g., the type, timing, intensity) over time to an individual’s changing status and context, with the goal to deliver support at the moment (and in the context) that the person needs it most and is most likely to be receptive. JITAIs use a high intensity of adaptation; in other words, there are frequent opportunities for the intervention to be adapted (weekly, daily or many times a day). This high intensity of adaptation is facilitated by the ability of Holly Health to continuously collect information about an individual’s current context and make intervention decisions adapted to this information.
Conceptual model of JITAI components
JITAIs have been shown to be effective in reducing sedentary time, limiting caloric intake, supporting people with depression and aiding with addiction (e.g. smoking), which highlights the potential of developing the first JITAI that combines these findings and applies them for multimorbidity support in a healthcare context.
This project will lead to significant advances in the design and application of JITAIs in a real-world healthcare context. To date, only a few real-world solutions have incorporated JITAIs into their product and their application has been for siloed use cases (e.g. addiction), which highlights the opportunity to be pioneers in driving this cutting-edge approach into the healthcare sector for multimorbidity.
We will develop a JITAI for long-term condition prevention and management, optimised through a micro randomised trial (mRT)
<aside> 💡 Findings from a micro-randomised trial (mRT) can help determine decision rules for when and in what circumstances a JITAI intervention option should be delivered to optimise its efficacy and the efficacy of the intervention as a whole
</aside>
Pseudo-randomised decision points for notification frequency
To develop the JITAI model, we will use contextual inputs such as: