The Value in Your Research is NOT in the Technology
The value in your research is not in the technology – it’s in the research design and what you do with the data.
You’ve spent years, perhaps decades, becoming an expert in your field. That field of research is relying on you to keep probing the important questions and making new breakthroughs in theory and implementation. You can’t do that effectively if simultaneously you are attempting to figure out how to guide a development team to build an app. There are too many unknown and frequently changing variables for you to be able to effectively manage both projects.
Stop spending your time on technology development and focus on what you do best – research design and data analysis.
The research project you are planning has very specific requirements, there are certain variables you need to measure in specific ways at particular points in time. But you don’t need a custom built app to do that – you simply need a system that allows you to define what you want to measure, how you want to measure it and at what point in time for each of your study participants. Assuming that system allows you to do all that without any coding expertise then you are good to go!
We recently started working with a hospital system research center. They came to us after wasting $50K with third party developer who built for them, from scratch, an app to deliver an Ecological Momentary Intervention that still wasn’t able to collect data reliably after 8 months. We got them up and running in 1 month. Now they are collecting data and delivering intervention content via our app to patients that come through their eating disorders clinic. How did we manage that?
Because our platform has been in production since 2009 and has been designed to be agnostic to content we don’t need to build any software from scratch. You just type in your content – your survey items, intervention content, notification schedules, and decision logic – and off you go.
So if you are thinking of custom building an app, please consider, is this really what you want to spend your limited time on?
Fast, Easy Iteration is Key
Easy, fast iteration is key to designing a study and especially an intervention.
Being able to test your hypotheses quickly, collect data from participants then refine and test again is a critical part of any design process. When you are paying by the hour for each change to your custom built app your budget is going to quickly limit how much you can iterate.
If you are moving from traditional data collection or intervention delivery methods to Smartphone or wearable data collection and delivery then you will need to go through the build-test-refine cycle a few times – even if it’s just with your own team – before you launch your official study. You need the freedom to test and refine your protocols.
We supported a study out of USC that was focused on smoking cessation with Korean youth in California. They knew they wanted to deliver a smoking cessation intervention for this specific demographic group but didn’t yet have all the data they needed to do that. So they designed a two phase study with mEMA. In Phase 1 they simply collected data from participants about where they were, what they were doing and who they were with each time they smoked. Once they had collected these data from each individual in the study they moved into Phase 2 where they changed the content each participant saw every day on the app to deliver tailored intervention messages when the app knew they were at those trigger locations, doing those activities or with those people.
They were able to go through that entire process with the same app because the app is agnostic to content – they were able to change the content as they needed it, and to see the data coming back from participants in real-time so they knew when to change the content. Any changes they made made to content were automatically delivered to that participants’ app they next time they connected to the server – which was happening multiple times a day.
No lag time, no waiting for developers to make changes, no astronomical coding bill.
It’s easy to get caught in short-term thinking and looking for a solution to solve the problem of delivering your upcoming project. But take a moment to think forward and imagine the evolution of this work: if technology wasn’t a constraint – you could make it do whatever you want – how would you design the next study?
Mobile Operating Systems are Dynamic
Expect Mobile Operating Systems to Change
You might think that if you invest the time and resources into building an EMA app then it will save you time and money long term. Once it’s built then it’s built and there’s nothing more to do right?
No! Both the Android and Apple operating systems are updated frequently – by which I mean multiple times a year – on each platform. Each update can bring unknown changes that may affect your app. Complex apps, like mMEA, that tap into many of the instruments on the phone – for instance, the location services, the notification service, the camera, microphone and so on – are especially likely to be impacted by operating system updates. When you add in integrations with other devices and wearables then there’s a lot of maintenance to take care of.
It’s a full time job – literally! If you are thinking about building your own EMA or EMI app then you’ll need to factor in hiring both Android and Apple developers to continue to maintain the apps once in production. That is a significant expense.
Again, think about the long-term evolution of your work. Do you want to be managing a team of developers or spending your time focused purely on research?
The DIY Method is Always Available
Instead of hiring a developer you could attempt to patch together a system from various pieces of software out there. You could find an online survey provider to do the baseline and follow up questionnaires, maybe try a free, made by researchers EMA app or a text messaging survey system and try to find a provider that will give you data from a wearable sensor.
But then you are left with the headache of finding all these different parts – that is going to suck up a lot of your time
Then you have to make all the parts talk to each other or at least be in enough alignment that you can recognize one individual’s data in all the systems. Something as seemingly simple as having a shared subject ID# likely will not work across different systems. Leaving you with a mass of datasets you have to somehow match manually.
Similarly different systems use different naming and timestamping protocols – it’s hard to make sense of datasets that are timestamped in different ways, maybe one uses Unix time while another uses data/time format in UTC and another translates UTC into local time to the phone.
With a system like this who do you turn to when you have questions or something is not working? There’s no one, it’s up to you to figure it out.
mEMA Can Do It For You
So to run a successful EMA or EMI study on time and on budget without hiring a developer you just need to use a system that allows you to:
- Decide which variables you want to capture, how you want to measure them and when
- Iterate frequently on your design and add new data streams as you need them
- Plan ahead to keep up with changing technology without having to budget for custom software develop
All things that mEMA is already built to do!