Welcome to this episode of The Effective Statistician! Today, I explore an exciting and rapidly growing field: digital health interventions.
Have you ever wondered how to define engagement with these tools?
Why does measuring engagement matter so much for their success?
And how can statisticians solve the unique challenges that come with this digital space?
I speak with Jack Elkes, a PhD researcher focused on digital health, to answer these questions. Together, we tackle the complexities of these interventions, their use in areas like mental health, and how tools like cluster analysis help make sense of multidimensional data. With over 10,000 mental health apps already on the App Store, this field expands rapidly, creating opportunities and challenges.
If you want to know how engagement in digital health connects to marketing strategies or how these tools reshape decentralized trials, you’ll find plenty of insights here. Let’s dive in!
Key points:
- Digital health interventions: Definition, scope, examples.
- Engagement: Definition, importance, complexity.
- Measurement challenges: Multidimensional data, variability, arbitrary definitions.
- Mental health focus: Apps, virtual reality, stigma reduction, barriers to care.
- Cluster analysis: Grouping users, multidimensional engagement measures, case studies.
- Comparison to marketing: Engagement metrics, optimization, dynamic updates.
- Risks and opportunities: Growing field, need for early research, potential harm.
- Role of statisticians: Methodology, decentralized trials, PROs, future research.
- Call to action: Explore the field, learn, engage with associations.
Digital health interventions are transforming healthcare, offering exciting opportunities and posing new challenges for statisticians and researchers alike. From defining engagement to tackling complex data with innovative methods, this field has much to explore.
I hope this episode inspires you to dive deeper into this growing area and consider how you can contribute to its evolution. If you found this discussion valuable, I encourage you to listen to the full episode and share it with your friends and colleagues who might benefit from these insights.
Together, we can shape the future of digital health and make a meaningful impact. Let’s keep the conversation going!
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Jack Elkes
Statistician at Imperial College London
Jack Elkes is a confident, passionate, and driven individual with a strong interest in statistics, particularly in researching digital health interventions for patient care. The knowledge and skills he has gained through various job positions, volunteering, and university degrees have enabled him to pursue his passion as a biostatistician in clinical trials. He actively seeks opportunities outside his current role to further develop his personal skills. Jack consistently demonstrates adaptability in any position, thrives under pressure, and becomes an integral part of any team.
Follow his work at http://jackelkes.com.
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Transcript
Why Is It Important To Measure Exposure To Digital Health Interventions And How To Tackle The Challenge
Alexander: [00:00:00] Welcome to another episode of The Effective Statistician. Today I’m super excited to talk with, Jack about digital health innovations or interventions. Both start with I and, but both of these are also innovations which are a really interesting field to work on. Jack, before we dive into the questions itself, maybe you can talk a little bit. Towards yourself and how you got into working on a PhD in this area.
Jack: Yeah, of course. So hi, I’m Jack Elks. I’m currently doing a PhD looking at digital health interventions and how we engage with them and looking at trying to define engagement groups within a clinical trial setting. Going back a few years, I started in clinical trials in 2017 starting just after a Masters in Medical Statistics.
Really enjoyed clinical trials as an area. I [00:01:00] think it’s a really fascinating problem for statisticians to try and work out how we best design these trials and utilize patients in the best way to, to get answers. But having worked for, so I worked for a contract research organization called IQVIA.
So I’ve got a really good experience there of different types of trials that were available, different therapeutic areas, different types of interventions. And through that discovered my interest for digital health interventions and was attracted to the technology side of things and how they worked.
I wanted to delve deeper into this. I moved in 2019 to a job at Imperial Clinical Trials Unit, which is Where I am now to work with a company called Mayim Health to look at designing some of their trials for new interventions that they had, so apps for asthma, for COPD, for heart disease and diabetes as well.
And throughout those two years, discovered the challenge that we had about how we define engagement [00:02:00] groups for our analysis and trials, and that’s what led me to pick up this question as a PhD. And yeah, start it off. So that’s my journey.
Alexander: Yeah. And what’s that actually means engagement here?
We will dive a little bit deeper into it, into a moment. But let’s start with first some kind of questions to, to set the scenes. What are actually digital health interventions?
Jack: Digital health really is quite a broad term when we think about interventions. It’s quite encompassing. It can mean really the technology that a patient can engage with. That could be a health service that they’re accessing. It could be that the digital health intervention is delivering treatment.
And it can take the form of many different things that we’ll be familiar with. A website. It could be a mobile app that you download to your phone and you use these days as well. We’ve got AI to think about. So it could be something AI based that’s being used to either help a clinician monitor the health of that patient or the patient themselves to track and [00:03:00] monitor their own their own health.
But really it’s it’s something which can be described as a, an intervention that is accessed away from a hospital, away from a site and something where the patient. Typically is in control and able to decide when they’re accessing that intervention for how long as well and how often.
Alexander: And I think it can be both diagnostic and therapeutic. I think this is also a very interesting part. I think many of us first think when we think about these kind of things. Yeah, it’s imaging or monitoring or these kind of things. But that’s also opportunities, especially in the.
Intervention area. You’ve done especially also lots of research in the mental health space. Can you talk a little bit about the opportunities for interventions there?
Jack: Yeah, definitely. Digital health has been seen as a real potential solution to mental health sort of solving or helping mental [00:04:00] health treatment.
So the challenge at the moment with mental health is that they, the service available to patients is currently outpaced by the demand. It’s one in four women and perhaps the same again for men suffer with mental health conditions in their lifetime. And this number is growing. So the number of people who need treatment is increasing.
So that’s a big challenge. And at the moment, there’s not enough psychologists or clinical experts who are able to treat these patients. So digital health is something which can be seen as a solution to this, being able to provide. Support supplied there. Sorry, let me start that again. That was a waffle.
Go back. Okay, so I’m going to start that one again.
So in the area of mental health digital interventions can be, are seen as a potential solution here because at the moment the demand for these services is being outpaced by the supply or availability of these services. So [00:05:00] that’s not just in the number of clinical expert experts there are, but also in the number of people who have mental health conditions, it’s going up as well.
Digital health interventions have are seen as potential solutions because they can overcome traditional barriers. So that might include being able to physically access the treatment. So that might be not just the access to clinical experts, but also it could be the location of these as well.
So if you’re in a city, perhaps that’s a lot easier. But if you’re somewhere more urban, then there’s obviously the considerations around the travel, which. Wouldn’t be the case for digital interventions also in some cultures as well. There’s a stigma about getting access to treatments and digital health interventions are seen as a solution there because they can Someone more discreetly and get access to treatment as well
Alexander: Yeah, and I think they can very often go hand in hand with other interventions.
Yeah if you have worked a little bit in [00:06:00] that space, then you will often see that as these so called multimodal interventions so you have biological interventions like pharmaceutical treatments. You have also interventions that are more on the yeah, basically through discussions and interviewing techniques interventions but also other interventions like sports and, Other kind of, more, more structural things.
And in that kind of overall spectrum, there’s a lot of opportunity for this. By the way, there’s one interesting thing is that there’s also an emergent. Number of societies, like the Digital Medicine Society, other associations that are starting in that field, and also a number of new companies that evolve in that field, that are starting in that field.
Create [00:07:00] these applications, you can find probably lots of them in the app store or on Google play. And in Germany, there’s one specific thing that is quite interesting. In Germany, you can even get these. Apps on prescription and so basically paid through the national health insurance system.
Now that is only possible if these apps get through an approval system and that usually includes a clinical trial. So it’s a similar assessment. As if it would be a pharmacological intervention so that is a super interesting area as well. I’ve recorded a podcast about this with Stefan Walser quite some time ago.
And if you search for DIGA, which stands for digital health intervention in Germany, Then he will find that podcast episode quite easily. So [00:08:00] that’s a little bit just about background. So have you looked a little bit into how frequent these kind of applications are, how many of them are there?
Jack: Yeah, definitely. So this was a big motivating factor when starting my PhD. So if we take apps alone, for example, for mental health apps just on the Apple app store there’s over 10, 000 available. And that was a stat from a few years ago. So I’m sure this number is even more now.
This number is huge and it’s growing rapidly. And that’s just for apps. There are many different types of digital mental health interventions that we can talk about. So there’s virtual reality, if you like, for things like exposure therapy. So guiding a patient through perhaps a fear or a stressful situation that perhaps they’ve avoided and guiding them in a more controlled environment that allows them to to, Feel more comfortable and more able to handle that situation.
There’s apps which I’ve mentioned obviously, [00:09:00] so that’s things like Apps to help with mindfulness apps to help with depression apps to help with perhaps more formal treatment like cognitive behavioral therapy or attention bias modification and Could also talk about chatbots as well. So this could be a more automated service, which people can talk to, to be steered in the right direction of where they can get access to treatment and also more, perhaps more passive as well.
There’s digital technologies, which could be used as well to monitor patients more passively. So that could be thinking about the social activity of a person. So I’ve heard of it. Of trials which passively monitor patients via their phones to see how how are they communicating. So that could be, do they text their family members often?
Do they make calls? Are they leaving the house? And all of that is to help to understand when people perhaps get depressed and they withdraw [00:10:00] from society, then it helps put up some early warning signs to help people. either experts to reach out to that person and offer help or If it’s an app to remind that person that help is available to them as well So yes, there’s a lot of different areas where men digital health interventions are being applied in This area I think the for all of these the intention themselves, although it might be seen as just an app or just a website.
Actually, these are quite complex interventions and they often have a lot of different components to them. So we’ve talked briefly. About, is it monitoring does the app monitor or does it help that per person manage? But within that there will be different aspects as well that are available to that person.
So it could be perhaps to monitor a certain biomarker or to report a questionnaire they can fill in to report as well. So yeah, so there’s lots of different aspects as well that need to be considered.
Alexander: [00:11:00] I think these apps can interact with the users through email, through service, through homepage, through watching videos, lots of different ways how you can interact with these and Yeah,
Jack: and just to add to that, I think that’s a really good point that when we talk about digital interventions, the difference here compared to more traditional treatments is that idea about these are quite dynamic in the sense that they are, first of all, they’re always updated.
So there’s this sort of software update that happens perhaps yearly or weekly. More often, but also the actual intervention itself. If you take an app, for example, that can be quite dynamic. So a patient will start reporting how they feel and based on how they’re reporting to the app might actually change the information that’s being provided to that patient.
So over time it’s dynamic, it’s changing and often a different service, depending on how that patient is responding to the app.
Alexander: Yeah. And I think that is a super interesting area. If you [00:12:00] come from a typical pharmaceutical treatment area. Yes, there’s actually not so many things you can do.
Yeah, maybe you can. have different routes of application, or you can dose up or down, or you can maybe add a co medication. Let’s see, the number of ways you can actually change the treatment is quite limited. As compared to this digital space now that brings also quite a challenge and you talked about engagement earlier on.
So what does that mean? Engagement for digital health applications.
Jack: Yeah, so engagement as a concept, I think can be related quite similarly to perhaps it’s the dose or the prescription that someone is getting for a drug treatment, perhaps more the dose actually. So it’s how much of that are you actually taking the same for a complex intervention.
So [00:13:00] working in my area, if I think of an in person equivalent, so let’s take cognitive behavioral therapy, then engagement or Yeah, engagement to that would be how many of those sessions have you attended? So if there’s six available, it’s how many of those are you turning up to receive the therapy being offered?
Whereas for digital health interventions in the area of mental health, engagement is described as how are you interacting with that? digital treatment. So a simple way to look at this could be with, if I go back to the app idea again, so cognitive behavioral therapy, as I mentioned, can be an app. So if we think of engagement to cognitive behavioral therapy, that would be how are you interacting with that therapy via the app?
Are you logging in and looking at each module of treatment in one go? Are you accessing that? Perhaps in a different way where you’re doing smaller stints where you’re trying to review the content that’s being given to you through Half an [00:14:00] hour 15 minutes each day where you’re looking at this and do you come back to that and how often so yeah engagement’s more about I think very similar to the idea of it’s how that patient is accessing that treatment
Alexander: So it’s in a way related to exposure, but also adherence or compliance is also another kind of aspect in it.
Yeah. In the pharmaceutical world, we usually say if you don’t take the pill, it can’t work. Yeah. And here, of course, it’s a little bit the same. Yeah. And of course that has. Is, pill count or looking at number of injections or things like that. That’s pretty, pretty easy.
So to say, yeah. Although that is some people will argue that even that is not easy. Which I would probably agree with, however, see the number of different ways you can interact with an app, yeah, or with all the different features we talked about is.
Jack: [00:15:00] Absolutely. And I think this is the big difference.
So yes, I agree with you that it’s not so straightforward, but if we do take a drug treatment and we look at this idea of dose, then it’s very straightforward. The point is, Patient comes in, they take the treatment and then you know how much they’ve given because you knew the dose that was in that pill or that liquid that you gave them.
With an app, it’s, yes, we can measure it. So it can be something we can assess, but it’s not a single measure. So that’s the difference here. So with an app or with a website. These kind of interventions there’s a lot more measures available. So it’s not as straightforward as just looking at how many times that person has interacted.
But as you say, it’s looking at what are the features that they’re looking at? What are they doing in the app? How long are they spending there? Also, are they repeating content? So that’s perhaps another difference is with a drug treatment or anything like that. It’s quite straightforward. You take that treatment and they’ve taken [00:16:00] it.
There’s That’s it. Whereas with a app, for example, that patient may have read the material for a given feature or part of the therapy, but we don’t know whether or not that person actually has processed and taken on those suggested changes that’s been given to them. And they may come back and revisit that information again and again.
Alexander: Yeah. So I think this kind of engagement is quite an interesting term in itself because it’s exactly the same terms that online marketeers. We use, yeah, when they do a campaign or in terms of, with social media posts, with emails, with homepages, all these kinds of different things. All digital, yeah.
They will also look into engagement rates. Yeah. How many emails get opened? How many, what kind of clicks do you have? How many kind of, how long are the videos that get looked? What kind of material gets [00:17:00] downloaded? All these kinds of different things. Yeah. And I think that’s an area where we basically can learn a lot from in that space.
Jack: Yeah, definitely. That’s a really nice comparison. I think to think of the concept of engagement if you’ve ever posted on social media, then I agree. That’s a real clear, perhaps comparison of how engagement is working and something to learn from for sure. Yeah.
Alexander: So now if we have. These lots of different variables, like different clicks, different, opens videos downloads, all these kinds of different things, setters, these lots of different digital inventions offer, we are not short of data, but how do we then tackle, it’s this multidimensional.
Jack: So that’s a really good question. That’s definitely what my PhD is looking at. And firstly, just to your point there about engagement measures being available. Absolutely. I did a systematic [00:18:00] review recently, which looked at asking that question, first of all. So that was the first part of my PhD.
So we wanted to know whether or not these interventions did have engagement measures available. And the answer was yes. There were 70 over 75 percent that did have at least one measure available, but it was very variable. So that was definitely a big challenges that even when they had engagement measures available, it was quite different.
So even if you had very similar interventions, the measures themselves were different from one intervention to the other. So that really posed a big challenge to how do you determine or how do you, how do really assess what is engagement and something as trialists we all are familiar with is something like compliance or adherence and wanting to know what a treatment effect is for someone who has a certain level of compliance or has adhered to the treatment in terms of the protocol we’ve set out.
Yeah, that’s a big challenge and [00:19:00] something that’s, I think it’s not going to be one size fits all. So there’s one thing that I’m learning through my PhD is that when we think of engagement and how we can assess this in terms of, so for me, that’s looking at what’s the efficacy of these interventions for a given level or group of engagement for these interventions.
And there’s not this idea of one size fits all. It’s something which I’ve been looking at as a sort of a general methodology that can be used to I’ll be applied, sorry, to these interventions and that’s looking at cluster analysis. One thing I’ve come across is how can we use cluster algorithms which
Alexander: Which are basically a dimensional reduction. Yes. Is a proper approach. Yeah. And unsupervised learning. So if you have read the book of T. B. Shahrani, Elements of Statistical Learning, you’ll find that under the chapter of unsupervised learning methods. And there’s actually, by the way, lots [00:20:00] of different clustering methods.
Jack: Yeah, definitely. So this was how I’ve looked at the problem. So looking at some case studies and looking at how we can define engagement groups by using cluster analysis. The reason why I chose to do this, first of all, was because in my systematic review, I looked at the data. It was very apparent that yes, there was engagement measures and some studies, although not many did.
Think about what that compliance definition should be for these interventions. The definition itself was typically quite arbitrary and only used a single measure. What that means is you’d have perhaps one intervention in, let’s take CPT, so stick on a consistent theme here. So CPT, if we had one intervention, it might have defined engagement to an effective level as they’ve logged in twice.
Versus another intervention, which is CBT where it would have defined this sort of effective engagement [00:21:00] level as they’ve logged in twice and they’ve looked at four of the six modules that were given to the person. And then there’s lots of other definitions as well, such as based on time, how long are they spending logged in and so on.
All of which though, are you see this idea of variability, but also they are quite simple in their approach. It’s. Quite hard to say that if you just look at whether someone has logged in twice or not, can you really say if that’s effective engagement? And also, how would you know that person who’s logged in twice has done the same thing as someone else who’s logged in twice?
One person could be logging in and updating their profile versus the other person, which could be doing some of the therapeutic aspects that have been given to them. So that was the incentive of why we, I felt that. Cluster analysis wasn’t a way forward because it was trying to build up that picture in a way that took into account all of the engagement measures available.
Thinking [00:22:00] that the patterns aren’t just on a single measure, but actually it’s important we look at all the other. Aspects as well and build up. Why is that person different to another person? So even if they’ve logged in twice We’d be able to tell that one of them perhaps has got and more Activity and the therapeutic aspects and that’s why they’re in this group versus the other person and having that understanding is then Enabling us to understand, to assess what is the efficacy difference efficacy differences for one group versus the other.
Alexander: Yeah. Yeah. I think that’s a it’s a very nice approach because you get distinct groups and you can basically in the future even look into, okay. Given some data, what’s the likelihood that someone would fall into one of the different clusters? Yeah. And you can also use it for prediction as a future and things like that.
I think it’s definitely a nice way to [00:23:00] make sense of this big number of variables. Pretty complex to tackle otherwise. Have you looked into other approaches beyond clustering?
Jack: No, I haven’t looked at other approaches. I settled on cluster analysis because it’s really because of conversations I had with patient partners that are helping me throughout my PhD. And I went into those discussions with the idea that we have lots of different engaged measures. Available and actually what we care about is just a select few of them.
And really, we just need to know what are those select few. And then from there. We can determine what people’s engagement is going to be just on those measures ignoring the rest I took that to my public partners, who are people with lived experiences in depression anxiety and so on and I spoke to them about this and put that idea forward and discussed it And very quickly realized that [00:24:00] wasn’t the case.
And actually, every measure we went through, there was some aspect to it, which was going to be important. So just as an example one of the interventions that I brought to them had the ability to post to discussion forums. And we talked about what are the important measures In a discussion forum, and there are pros and cons to all of them.
So it makes it very difficult. You’ve got, for example, post length could be a good measure because, if someone really has a lot to say, then perhaps there’s something there that is important. We don’t want to miss. But the flip side to that is they have a style of writing that perhaps is different to another person who is very brief doesn’t mean that the actual people.
Content of that question or query is any different. Yeah, that, that kind of made me very clear to me that there, the cluster analysis was very attractive because it enabled someone who’s designing interventions to incorporate all of that useful information. And really, I would say it is [00:25:00] useful information.
That’s the one thing I found. Yeah, there’s not an engagement measure where It could be dropped easily, I think, without careful consideration. So that’s what led me there, but not saying it’s the right way. I think this is just one approach that I’ve suggested, which helps us to come to a conclusion.
And then from that learn, these are the say four or five different groups we can find working backwards. Now, once we’ve got those groups, we can look at why they’re different. And then that gives us some information to go forward.
Alexander: Yeah, I found working with cluster analysis always super easy because then you can look into the different characteristics of these clusters and you can better understand what these kind of types of patients are and very often that has some kind of clinical meaningfulness which makes it really nice.
If you look just into. Dimension reduction in terms of the correlation between all these [00:26:00] kind of different endpoints and you want to do some principal components analysis, these kind of things. You don’t end up actually with. things that are very easy to interpret in the end. So that’s why I think this cluster analysis is also a very nice approach.
Now, if there’s one thing that someone should take away from this episode what would that be?
Jack: I
think what someone should take away from this is that the area of digital health interventions and how we look at engagement for patients is complex. I think it’s still quite new. Like I said, in this systematic review I did we can see people are using quite arbitrary definitions. And that I think is not because people, I think it’s really because people don’t know how to define it yet.
So we’re not clear on what [00:27:00] effective engagement is. So I think that’s a big challenge. I think that idea I’m hoping that ideas like my PhD to suggest a more methodical approach and how we can find groups of patients and then look at their efficacy will help us to understand the pathway much better.
I think that means that It will help us to understand the perhaps the mechanistic side of how these apps work and what are the kind of important features or the features in each intervention that are driving changes and allowing people to engage and feel the benefit. I think the other aspect I’d like to People to take away from this as well is the idea that I think it’s really important we act sooner rather than later and it’s important we investigate this now.
The reason why I say that is because like I mentioned earlier, there’s over 10, 000 apps already available on the app store and lots more if we [00:28:00] think elsewhere. So that’s a lot of interventions that are currently being used, at the moment there’s not a lot of research into what The relationship is between engagement and efficacy.
So what that means is there’s a real risk here that we could have interventions which perhaps are more harmful than we anticipated, or they have adverse effects that we didn’t even realize. I remember speaking to some public partners at the start of my PhD about the idea that I think engagement is just the more the better.
It’s linear, the idea that you just need someone to use the app or use the website more and more. When I spoke to the patients about this, I quickly realized that wasn’t the case. They told me that there is an aspect of harm there. So I think they were talking about the idea of an optimum window rather than higher is better because someone who’s using it perhaps daily.
Yes, that’s great for our metrics. Yes, that’s great because it [00:29:00] seems like they’re using the app well, but in reality, that person could be not understanding or not really getting benefit from the content. And, especially with mental health, they could be stressed. They could be worried about it could be making their symptoms worse.
And that’s why they’re re engaging more and more because they are trying to get better and they just aren’t with this app. Yeah, I think if we act now and look at this. Now, then that can be solved quicker and there’s less concern there rather than letting this, delay it basically.
Alexander: I would add one important thing.
It’s an area that is growing and I think everybody working in healthcare and in research should have some high level understanding of these kind of different things. So I would encourage you to look into that aspect. It’s only going to get More and lots of, when we think [00:30:00] about doing clinical trials, we have more and more decentralized trials and these kind of things where, you know the, that is also we can measure engagements there.
Yeah. And so I think this is not just for health interventions. It’s also for how we run our studies. We can learn a lot from how people use PROs, how people use diaries, how people use all kinds of different other features, because that will tell us something about how people actually engage with all the different trial material.
Jack: Definitely. I definitely agree with that. And I think. The one, not the one, one of the many benefits of digital health interventions is that they are digital. It’s a technology that can be updated and I think the attractiveness here is that Engagement, we know has an effect. If you don’t use it, you won’t get better.
And it’s trying to understand what’s [00:31:00] the right way to use it. And once you understand that, you can make an update to that technology to that intervention to the the app itself to, to make it easier or better for people. It’s to make it easier for people to get to that optimal level.
Spotting why is it that people aren’t engaging with it, or they’re not in the optimum group and once we understand that, you can push people to the optimum group much more easily.
Alexander: Yeah, it’s basically the same thing, what digital marketeers use it for. They look into engagement and then when, certain emails are not opened or clicked, yeah, they learn from it and improve it for the next time.
Yeah. And you can even do tests there. Yeah. You have, two different versions and look. So where’s the better engagement? Yeah. So there’s lots of opportunities for us as statisticians to help in that space. And if you have an interest there, yeah. Please have a look into we, for example, [00:32:00] mentioned digital medicine societies as other associations as well.
Engage with people, learn more about it. Thank you. And I think there’s a lot of opportunity for us. Thanks so much, Jack, for this awesome discussion.
Jack: Thank you so much.
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