Note: The I AM GPH podcast is produced by NYU GPH’s Office of Communications and Promotion. It is designed to be heard. If you are able, we encourage you to listen to the audio, which includes emphasis that may not be captured in text on the page. Transcripts are generated using a combination of software and human transcribers, and may contain errors. Please check the corresponding audio before quoting in print. Subscribe now on Apple Podcasts, Spotify, Google Play or Stitcher Radio.
EP13 MapMob Project by the NYU mHealth Lab Research Group
Deborah Onakomaiya: Hey guys, and welcome to another episode of I AM GPH. I'm your host Deborah Onakomaiya. On the show today, we have a faculty member, a research scientist, and an associate research scientist, from the mHealth lab. NYU mHealth is a research group within GPH that works to leverage the power of cell phones to collect data. They're here today to talk about MapMob, which is an NIH funded project about neighborhoods in health. We're joined by Dr. Kirchner, who is the director and principal investigator of the mHealth lab. Dr. Kirchner is a clinical health psychologist and methodologist by trading. His interests are in the graphical representation of longitudinal and geographic data. He uses GIS to understand health related behavior and decision making in real time. Also on the show today, is Avagal Vantu, a research scientist at the lab. She started as a graduate research assistant and was then promoted to research scientist. Avagal is an alumni of the NYU Center for Urban Science, where she received a masters in urban informatics. Currently, she oversees the daily management and development of mapmob.com, as well as data analysis that's related to the project. Finally on the show today, we have Hong Gao, who is a data scientist. Prior to joining the lab in 2015, she had worked with Dr. Kirchner on tobacco research. She holds an MPH degree from the Johns Hopkins School of Public Health and is currently enrolled at the NYU Center for Data Science. Her research interest involves spatial temporal changes and behavior data analysis. Let's go to our conversation with them. Thank you so much for joining us on our show today. It's so wonderful to have everyone here today.
Thomas Kirchner: Thank you. Thanks for having us.
Deborah Onakomaiya: All right, so let's dive right in. So what is mHealth in the context of the NYU environment?
Thomas Kirchner: So why mHealth? What's the role of mHealth, in that regard? Well, humans are connected and more than just to each other in some virtual way, right? Humans are fundamentally, we think in a more fundamental way than virtual connections connected to places. And so for us, mHealth is really about the connection between people and the places they go. Sure, the people that they see there, but it's the daily routine, the places that we move through, through our days that we think form the basis for a lot of these preventable health behaviors, right? The decisions we make about what to eat, whether to smoke cigarettes, whether to go for that jog, they're often very much tied to our daily routines. And that's the mobile piece that intrinsically the link between people, places, each other, their health is mobile and it's bound to the places that they move. So that's in some ways the way we think about this concept at mHealth.
Deborah Onakomaiya: At NYU, what projects have you guys worked on in the mHealth research lab?
Hong Gao: Well, I came in with mHealth as my interest has always been the interaction between people and places, as Tom just mentioned. It's very important in terms of understanding people's behavior to understand the interaction between people, as well as the places they've been to. So if you think about where people are in their daily life, it's different places they've been to and how much time they spend there. We have published a paper studying people's exposure to tobacco retail outlets. What we found out is that in the literature, people take where people's residences as their exposure level. But what we find out is that people spend most of their time outside. So you can't purely consider where they live as what they are exposed to. The idea of our projects comes with this notion that we want to understand where people really move to, what are the real places they've been exposed to. And also we are interested not only on tobacco retailer exposure, as Tom mentioned before, we are also interested in food environment. How do they use their neighborhood? They're exposed to alcohol outlets and also walkability around their neighborhood. So this kind of idea drove us to start this project.
Thomas Kirchner: One way to understand what we do is to think about the study of the behavioral foundations of public policy. Let me put it that way. All right. Why are we a public health lab and not a psychology lab? Why do we want to do that? Well, ultimately, we want to understand and try to help guide public policy and help guide how we as a society deal with these things, these things like the dilemma that we all need to eat food and yet we're inundated by unhealthy options, right? And the problem that we have, which is that what tobacco even means is rapidly changing. It's not just cigarettes anymore, it's everything under the sun, electronic versions of vaporizers and etc. Half the things that most people haven't even heard of yet. You've got what's happening with cannabis, marijuana legalization, medicalization, decriminalization. Everything's moving really fast, and what we do in general is a broad range of projects that are built into that same general framework, which is to say that we're interested in the way these human health behaviors, whether it's drinking alcohol, smoking cigarettes, gambling, going for a jog, while those are playing out in really an elaborate dance with the way our municipal departments of health, and the government more in general, tries to shape public policies that are a good balance with what our society believes is important in terms of controlling the impact that these behaviors can have on us collectively as individuals. Understand that using the information that we would collect as part of a project focused on individual decision making to help guide and help form as a basis for a conversation we might have with, say policymakers, or the folks who are trying to understand how to intervene in neighborhoods, how they might do so more effectively. An example is how is a city Department of Health to understand something, a concept like a food dessert, right? I'm not crazy about the term because it seems to imply a complete lack of food, right? Yes, some people are hungry and that's a major problem in New York City. But here in the Western world, it's less an issue of a true dessert, a true lack of food and true emergency, which would be starvation. And to us it's much more about access, right? If you're a city and you think in terms of census blocks, and yes or no, is there any food in one census block versus another? You might identify a food desert and you might, I don't know, you might build a supermarket there. But that's been tried. And the literature, there's some, unfortunately, the prevailing wisdom that data seems to be telling us is that doesn't always work. And so the question we're left with is why? Well, the theory that we have in our lab is that again, it's not an issue of a complete absence of food. It's an issue of not understanding how do people access food in the first place. Maybe to a neighborhood in East Brooklyn, it isn't so much about a complete absence or desert of food, but about the equity and fairness issues around how long does it take to access the ingredients that a family might want to use because of their preferences, maybe from their cultural heritage or maybe it's just how they like to eat. Can we, using data, like the data that Hong and Avagal were talking about, city systems data, really anything, a lot of people refer to this as big data. How can we use the data that we have out there about the way a city operates to help us understand something like how do people access food and make decisions about food, balanced against how to get their kids to school and how to get to and from work. How can we help think about those problems in a smarter way, instead of such a sort of traditionally black and white way in terms of opposite of a desert?
Deborah Onakomaiya: Wow, that sounds very, very innovative. And you know, it's a different way to, especially highlighting what you said about food desserts, it's a very different way to actually intervene in terms of that, not necessarily that there is no food, but how are people actually accessing it? I've heard about a particular project that you guys have been working on, the MapMob project. First off, what is this project about?
Avigal Vantu: Yeah, so the MapMob project is I guess our main project we're working on right now. It's funded by an NIH grant. We basically developed, we are developing for a few months now, a web interface that is accessible at mapmob.com for participants to get more information about the project and get engaged by having bill on account and follow all the steps of joining this project. With this project, we're looking to investigate, as Tom mentioned, questions about how do residents use their own livelihood? Where do they travel? For that, we were going to collect a few different types of data. The first one is a survey concerning neighborhood norms, asking about nutrition and exercise, tobacco product use and demographics. We collect the survey through NYU Qualtrics. We're also going to collect neighborhood boundaries from the participants, asking them where do they live in. And the third type of dataset we're going to collect is 40 days of mobility data connected to the participants' smartphones.
Deborah Onakomaiya: Interesting. How did this idea come about? What sparked this project coming to life?
Thomas Kirchner: There's some pressing policy questions around some of the things I mentioned earlier. So the drug use norms are changing rapidly in this country, right? And a project that's funded the MapMob platform is focused on some of those issues. In particular, what's happening with marijuana and tobacco and the way those things are affecting each other over time. The whole vaping phenomenon as well. You can even think about certain devices that would allow you to use one, the other, or both of these substances, tobacco and cannabis. The question, though, is what's changing about our neighborhoods and our cities as a result of these products becoming available? And how does that matter? Why does it matter, and can we do anything about it to understand and try to guide policy moving forward? Our working hypothesis is that what's not happening necessarily is a change in access. So thinking about marijuana, everybody in New York City has access to marijuana. They might not realize it, but at their local park they probably do and they always have and it's going to be at a lower price point than they could get it out in Denver right now. So we don't view what's happening with legalization and decriminalization and SOPA medicalization of marijuana is necessarily just a carp watch, an access issue or access was there where it wasn't before, so much as it's a change in drug use norms, how our society thinks about these substances and what it means that they're becoming more accepted and more common in different cities. With this project, we're based in New York City. We also have sites in Washington DC, New Orleans, Louisiana and Denver. And that's intentional, because we're interested in understanding how these things are playing out in different areas with very different regulatory environments. Think about the DC area. We have fairly progressive Washington DC and Maryland smack right next to Virginia, which is much more conservative in terms of regulation of something like cannabis. You have people working in the same buildings there, in the District of Columbia, traveling back and forth home to very different residentially based policy environments. And they're fascinated by how that dynamic is going to play out over time. And so really, what we're trying to do is start a conversation with people about where they live, where they would define that. I think I mentioned just asking them, "Forget about census blocks, where do you think your neighborhood is? If somebody was going to ask you, where would you draw the lines?" And then helping us understand, within those boundaries, and outside of them, what's their experience? What's their experience of how things are evolving over time with these substances and how that interrelates to their own behavior. How for instance, if you're the sort of person who uses the city parks a lot and moves through them, you might notice differences in the amount of marijuana smoke in the air as you're walking through certain parks. There's real world ways that the changing environment of our cities affects people, and we want to give people a chance to chime in on those things. But giving people a voice touches on a topic that's close to all of our hearts here, I think it's safe to say, which is what technically people in the field might refer to as voluntary or volunteer geographic information. It touches more generally this issue of privacy, and just questions around what does it mean? Who has access to this kind of information, and what should we be concerned about, and where should we see opportunities rather than fear? It starts to touch on this. You mentioned giving people a voice. Absolutely. It's also about giving them access. I'll tell you right now that the phone companies, the internet companies, many marketing companies, don't even need to mention the CIA and the NSA, although I just did, they all have access to this data and data about where we move from day to day, data about the purchases that we're making from moment to moment. It's right for us to be concerned about privacy. Of course it's right. We're all concerned. None of us, including myself, want somebody watching my every movement and my every decision to make a purchase. But we also think it's important to start a conversation, because when the powers that be are taking this data to the bank, literally making a lot of money based on this data, you have to ask yourself, "At what point are communities going to be empowered to use this kind of data and how can we use this data for good?" If our lab does a good job, well, that's one of our longer term hopes, that we can start that conversation, and maybe in concrete ways, we can help give some demonstrable examples of how we can take data, we can collect data in a voluntary, shared, consent based way with residents, citizens of communities who understand why we're collecting that information and can work with us to use it for good, to leverage that data to help improve access to foods and ingredients. Maybe it's helping mobility options for people with mobility issues, getting to doctor's appointments, access to medical care, access to green spaces. All of these issues that are of interest, a lot of these have an inherent link to ... some of this can be pretty sensitive data. But again, are we going to stick our heads in the sand? Are we going to pretend the data isn't there? Or are we going to try to rabble with what can be certainly a challenging topic, but in a way that could really benefit the folks who traditionally, or at least so far haven't really been doing much with this data?
Hong Gao: The initial idea of MapMob comes with legalization of marijuana. But I think our idea is that if this policy makes changes to people's thoughts, behaviors, it's probably not only changes people's perception on marijuana, also changes people's perception on other things. That's why if you go to MapMob and look at our surveys, we asked all aspects of people's life around their neighborhood. So we got the whole picture of what was this policy changes like potentially affect other aspects of lives? And I also just want to comment on the privacy issues. Why not contribute all the data to the companies where they can make decisions on where to put a store where you can spend money, instead of you have a choice to contribute your data and let people know where to put a grocery store or where to put public facilities, where it can help build their neighborhood.
Deborah Onakomaiya: Just to get down to more personal stuff, why are you guys motivated to do this? What motivates you guys to continue this work? Because sometimes it can be, like you guys touched on, there can be some issues here and there that could come about. What motivates you guys to do this?
Avigal Vantu: I can speak about myself personally that what motivates me to work with cities is the democratic point of view, the almost non-political democratic point of view. Make systems more efficient, influence a big scale and quantify. So in a sense, of course no answer is definite, and even using data and using analysis can be approached from different ways and can be interpreted in different ways. But I think working in the urban setting and working on real people, datasets, real time, doing such innovative stuff has the potential to really bring a change, gets cities more efficient and better and have different populations access. So for me, it's just social impact.
Deborah Onakomaiya: How about for you?
Hong Gao: I think for me personally, I was always interested in people, how people's behavior is and how they make decisions. So I was really interested in learning where people move and how they decide where they move. Then I get to understand, it can tell more stories when you combine the places around them. I participated in a study where smokers, they're trying to quit. They also recorded where they spend time. So we were able to see for the people who try to quit, what doors, what kind of behavior could stop them from that? So from the study, I really learned the interaction between the places in your neighborhood really affect your neighborhood. So this project really affects your behavior. So this project, I'm very interested in recruiting residents, see their data and see what their experiences are.
Deborah Onakomaiya: Then you mentioned something about a website where people can sign up?
Hong Gao: Yes, sure. To access the website, you should go to MapMob.com. That's a website that we developed within our team and has a few components of both collecting data for the neighborhood polygons we mentioned earlier, as well as giving a personal page, so a login system for participants to login the first time and come back to it later and monitor how they're going with the participants, as well as a little bit of information about our research and about our team.
Thomas Kirchner: MapMob. Why MapMob? We wanted to emphasize we're playing off the idea of a flash mob, right? This is a group of people gathering in a place and time. Well, they're just having fun with the flash mob usually. But the idea is really about focusing on the way crowds can come together on the map to make a difference. It's really not about watching people. It's not about following people around. It's how we can bring people together with this common idea that maps matter and places matter, for health in particular. The MapMob platform is really geared around being an infrastructural hub, in a way, for people in New York City to begin, to be able to come together, join this conversation, add their own experience, but also learn from others about what's happening across the city. I think that mHealth, in terms of our human connections to places, has always been here and always will be. I think that what makes us human is our connections to the places that we go. We happen to carry cell phones now, though, and so there's a physical connection which opens a lot of gates in terms of what we can do with data. I think, though, in the future, we're going to be able to use science and mHealth tools, science more generally, to understand the connection between people and places in a way that's going to be much more applied and pragmatic and useful, perhaps, than it has been in the past.
Deborah Onakomaiya: How can students get involved with your amazing work?
Thomas Kirchner: We're collaborative by nature. The mHealth lab, it has opened doors literally every week. We have at least one open meeting. I think all the time we're meeting with people, hallways, meetups, elsewhere, and we're constantly telling people, "Come by our meetings." So students can reach out to us and learn about our open meetings. Faculty, too. Anyone, we're very open. In terms of training and just collaboration around the mHealth lab, we're excited to continue collaborating with any and all takers. In terms of the MapMob project, the gates are open there, too. Really the inception of it was that if you're a resident of a neighborhood, which includes a lot of people, then they could be relevant to you if you're interested in joining that conversation. We're excited to invite people to check that out as well.
Deborah Onakomaiya: Wow, thank you so much for coming on. Your project is so innovative. I'm sure after this, a lot of students are going to be signing up, looking for you guys. And the implications alone of what you guys are doing is huge, so thank you so much for coming on our show today.
Avigal Vantu: Thank you.
Hong Gao: Thank you for having us.
Thomas Kirchner: Thank you.