#373: Creative Clinical Recruitment

Kelly Palmer: Welcome to the global medical Device podcast, where today's brightest minds in the medical device industry go to get their most useful and actionable insider knowledge direct from some of the world's leading medical device experts and companies.

Etienne Nichols: Hey everyone, are you struggling to streamline your clinical evidence generation processes? Look no further than Greenlight guru clinical. Greenlight Guru Clinical is the all in one platform that simplifies your clinical development journey. With guided workflows, expert insights and powerful electronic data capture capabilities, you can accelerate your timelines, ensure data integrity, and bring your life changing devices to patients faster. Our intuitive EDC tools make it effortless to collect, analyze and report clinical data while maintaining audit readiness. Say goodbye to the hassles of paper based data management and hello to a more efficient, compliant and secure clinical trial experience. Hundreds of innovative med tech companies trust Greenlight guru to power their clinical success. Join industry leaders who have reduced their time to market, save countless hours, and gained unparalleled peace of mind. Are you ready to experience the Greenlight guru difference? Visit Greenlight guru to learn more and request your personalized demo. Greenlight guru Clinical your partner in simplifying clinical evidence generation with me today is a part time co host for me, Stephanie Hinton. Thanks for being with us today, Stephanie, and I'm going to let you introduce the main guest for today, if that's all right.

Stephanie Hinton: Absolutely. So I have the pleasure of introducing Kelly Palmer. Doctor Palmer is one of my friends. We work together at IU School of Medicine. She now is a principal investigator and has her PhD and she's teaching at University of Arizona. But I can't say enough kind words about her. She has a ton of clinical research experience and a lot of fascinating interests outside of that as well. But I'll let her take it and introduce herself in addition to that.

Kelly Palmer: Hi. Yeah, so I'm Kelly Palmer. My pronouns are she, herself, hers, El, and Eya. And I'm an assistant professor here at the University of Arizona in the College of Public Health, Department of Health Promotion Sciences. And my research is centered on health equity and how to develop and implement interventions that are culturally relevant, culturally tailored to communities that need them the most.

Etienne Nichols: Really excited to have you with us today. One of the things that we were talking about just before and just in the conversations leading up to this was your extensive experience with all things clinical. But one of the things that Stephanie really highlighted was your ability to recruit in a world where it feels like it's hard to get enough subjects for a study, you don't seem to have that problem. What is your secret. And do you want to. Do you have any stories to share here?

Kelly Palmer: You know, I hate to be cliche, but I like to think outside of the box. Right. And so in my role at IU School of Medicine, working with Stephanie, being responsible for recruitment and retention of our study participants, you know, our PIs, our principal investigators, they would have their protocol that they wrote for recruitment. And oftentimes, that, to me, kind of felt a little bit like an afterthought. You know, these scientists are amazing in terms of developing their research interventions and their approaches and methods. But recruitment and how we actually get the people to participate in the studies kind of gets overlooked. Right? It's kind of this if we build it, they will come mentality. And, you know, I just think about it from my own perspective, like, as a regular person, you know, what would it take for me to know about research? What would it take for me to want to participate? And so, you know, we would be handed these kind of recruitment protocols and, you know, feel like, okay, that's one way to do it, right? You know, we can make phone calls and send out postcards, but. And I would do those things because obviously that was my job, was to do what I was told, but always trying to think about how to optimize and how to do things differently. And I like to think that maybe in a past life, I was an engineer and always thinking about how do we improve things, right? So in this case, it was how do we improve processes? So we would start out kind of doing whatever the protocol was, but it was always important to track. So it was kind of like me, a scientist in training, understanding the value of data and tracking our efforts, right? So we would do the phone calls, we would do the postcard mailings or the letters, but we will also track how people heard about the study and kind of what our return on investment was, right? So all of these efforts have a cost associated with them, whether it's mailings or personnel. And then we started kind of brainstorming and thinking about other ways to reach people. When I looked at the people who would most benefit from our research studies, I'm like, well, how are these people going to hear about our study if we're just sending them, you know, a postcard or calling people? And the phone numbers have changed and, you know, we can't get in touch with people because they're at work from eight to five, so what else do we really need to be doing? And so we just started kind of boots on the ground. I had a what we call a guerrilla marketing background. I worked for years as a brand ambassador for different companies and understood the value of that type of promotion. Being on the ground, you know, handing off people flyers and being in spaces where people are already at. Right. So this idea of meeting people where they were, this whole equity mindset. And so we started doing some of those things, and as we were tracking them, we started to see that we were getting better return on our investment, just doing those things than we were the things that we thought, you know, that were costing us a lot of money, like the mailings and the phone calls. And so it kind of just felt intuitive. Worked.

Etienne Nichols: So, specifically, what would you say is, is. Is one of the activities that you would give advice? I know, thinking outside the box, that's really true, and it's hard to just deconstruct that into a formula. But what do you think one of those activities was that had the greatest return that you would, could be universal? Potentially, yeah.

Kelly Palmer: So I think one of the biggest things is developing relationships. Right. So it's kind of one of these things where it takes a village. We can't do this work on our own. And so particularly when you're trying to recruit people from marginalized communities and backgrounds that maybe don't have the trust of research and academic medicine, you really have to rely on those relationships in the community to really support for it, amplify the work. And so as we were starting to not just recruit individual participants, but working with community groups, so we were going in Indianapolis to Cathay, which is a community organization on the far east side of Indianapolis that serves a lot of black residents of Indianapolis and working with different organizations like that. And as they're starting to put the word out about our recruitment efforts, the people in the community trust those organizations, and they're like, wow, if they're putting their stamp of approval on this, then this is something that might be worthwhile for me to get involved with. And so we were just making those connections. We partnered with a medical facility in Indianapolis that served a high hispanic and spanish speaking population. And again, this is an organization, a facility that those people trust. And so hearing about our research from those entities really helped bolster recruitment. So I would say it was really kind of the mechanism of partnering with community organizations, getting those organizations to kind of stand in the gap for us. The local churches were really instrumental in helping us with recruitment, not just of their congregation. Right. But by hosting recruitment events at the church. People within that community who maybe didn't even attend the church could hear about the research and come and find out more for themselves.

Stephanie Hinton: Yeah, that was one of my biggest takeaways from working with Kelly. At the time, I was a research assistant, so I was undergrad at IUPY, you know, just learning, working part time and then working full time. But I learned from her the value of going into the community to reach these people. So, you know, number one with research, the biggest takeaway that I have is gratitude for these people. It is completely voluntary, and, you know, we always took that very seriously, but we need subjects for the study. It's voluntary, but we need you. So how do we add value? What is our study? This was lifestyle interventions to hopefully prevent type two diabetes. So who's at risk for diabetes? What are the risk factors? But also thinking of trials. There is obviously a benefit to having a diverse sample set or population. So you're not just talking, you know, race education, but you're talking urban rural areas. So there's so many facets here. And that's one of the biggest things. You know, Kelly being my boss, but also a mentor, you need to go to the community. And that's where her guerrilla marketing background of having this promotional knowledge that she had, and that's why I wanted to have her on the podcast, because this is so overlooked in research. And a lot of times, research is a very dry topic of, you know, it's black and white, but there's a lot of gray areas, especially when you're talking about recruitment. You know, it's up to your IRB or your notified body what is ethical, what's safe for people. But, I mean, one of our co workers, she attended a church, and Kelly talked to her and said, would the pastor be open to us having an event there? But it wasn't doing it haphazardly or, okay, we're just going to show up and we have all these asks for the church. It was very intentional of Kelly meeting with the pastor, our principal investigator, taking the time to go to the site, explain what the study was, you know, in layman's terms, and then two, also providing benefit. So even if people were not interested, as it was a voluntary trial, were there other resources we could provide or other connections we could make for that church? You know, and we started developing a newsletter with healthy recipes. And, you know, there were some people that, you know, benefited or followed us on our Facebook Twitter accounts that could get those resources even if they decided, oh, I really don't want to get a finger ***** or test my a one c today. That's fine. But thank you so much for stopping by. So not always just asking this site or place, hey, we want all of this from you. But it being a true partnership, which is what Kelly's speaking to, getting those stakeholders involved, but making sure it's mutually beneficial.

Kelly Palmer: That's such a great point, Stephanie. I'm glad you brought that up. Like she said, building those relationships, being a resource instead of just coming in with an ask in a true partnership, because it can't just be, come help us something. But also for the study participants. And so having that, letting them know, like, yes, we have a research study. We're trying to answer a research question, and we have the things that we have to do per the grant or per the funding organization. But also, how is this going to benefit you as a participant? Right. So even if you're not benefiting directly from the study, which in our study, there was a benefit. Right. If you the way to do the things that we're trying to get you do this intervention, we knew that we could help people prevent or at least delay the onset of type two diabetes. So that is a benefit. But what do people need in this moment, right? What is something tangible that people need in their daily lives today that can also help facilitate their ability to participate in the research settings? So, you know, we're making sure that we're compensating people appropriately for the time that they're taking to participate in a study. We're making sure we're providing them with other resources, letting them know what else is in the community that they can tap into. You know, if it's a social need, if it's a financial need, if it's something else medically related. Right. We were always communicating back to their medical providers. They're learning about their health. We're explaining to them, what do these numbers mean, right? So we were doing measurements, blood pressure, cholesterol, diabetes testing through a one c, and there was a lot of education that went into, what are we talking about? What does this mean when you go to your doctor and you take this piece of paper, right? Because we would print out all of their results. When you go back to your doctor, how can you use this paper to have a conversation with your doctor that can help benefit your goals, your health goals? So we made sure that we were providing resources to our partners and to the participants and not, like Stephanie said, just having an ask for our needs and what we needed to accomplish in the research study, which was so important.

Etienne Nichols: I want to draw something on that guerrilla marketing background, because knowing your audience is really important in marketing, obviously, or you're not going to get very far. You're just going to do a spray and pray, which I kind of wonder if maybe that's how a lot of recruitment options go. What are some of the things that you feel like maybe people miss?

Kelly Palmer: Yeah. So in our studies in particular, you know, we were looking at diabetes prevention, and like Stephanie said, we knew who, who is at the highest risk for this disease. Right. So it's going to be, you know, people over 45. It's going to be people of marginalized socioeconomic backgrounds and racial and ethnic minority individuals as well. We know that it's women who have had a baby nine pounds or greater had gestational diabetes. Right. So we have some demographics that we know we want to kind of go after. So, so it's brought, but then it's not. And then we have to do our due diligence and being intentional about making sure that we're including those people who are at greatest risk in the study, because we could just say, okay, if you're at risk for type two diabetes, like, sure, come on. But a lot of people don't know that they're at risk. They don't know that it's me. Right. Or we put out the call, and depending on how we frame the study, you get a certain demographic. And so in one of our studies, we were partnering with the commercial weight loss organization. And once the word got out that we were using this entity to deliver our intervention, we had a high, high numbers of a certain demographic that were signing up because this particular organization was very synonymous. Their branding, their history really resonated with a certain demographic. But we knew that we weren't capturing everybody that was really at higher risk for diabetes. And so we had to be very intentional about how we were going to include those people. We could have just hit the number, right? We could have said, look, we're just trying to recruit 250 people, and the first 250 people we get, great, problem solved. We did it. But are we really doing what's right? Are we really doing what's fair, what's equitable? And so as we started to recruit and we saw, oh, we're not going to have a problem hitting our goal, but how do we want to hit our goal, right? Want to make sure that we're doing the right thing. And so it really took that intentionality to say, we have to make sure that we're, we're going to where the people are to get the people that we need in a society. So, yes, I really did take that kind of guerrilla marketing approach, but with a more intentional and focused effort. Right.

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Etienne Nichols: And that was the thing that I wanted to bring out is you're a principal investigator now, so how does that translate from your experience then? Working with a PI, and now you are the PI and working with the team, are there things that you see teams and maybe even principal investigators tripping up on common things that they could do better as a just working back and forth. What are your thoughts?

Kelly Palmer: I feel so fortunate to have gone through all the roles, right, starting out as a research assistant, being responsible for just recruitment and data collection and data entry to my time, kind of running the studies, managing the studies all the way up to being a PI. I think having that perspective gives me such an appreciation for all of the elements that go into a project. Like I said, as a PI, as a scientist getting my doctorate, I was trained to write grants. I was trained to develop interventions and to do these things. And so for PIs who haven't been staff, who haven't been a research assistant or coordinator or a manager, they don't have that lens. And so I feel so blessed to be able to have kind of that 360 lens to be able to understand. Yeah, I can write a great project. I can write a great intervention in theory. Right. I can use my theories and my methods and all the tools that I learned in school, but the practical side of it, the logistical side of, like, what it actually takes to make that science happen. And I talk a lot with PIs because they don't have that background. Right. And they don't understand it. So you write a grant and you say, oh, we're going to spend three months recruiting. Well, I know that that's not true because I've done it right, and I've sympathized. I don't know whose idea it was to say we would recruit in three months. That's not realistic. And so I think a lot of PIs do get tripped up on some of the practical and logistical aspects of science because they don't have that background. But that's why it's really important that if they don't, they rely on their project team and really listen to their coordinators and our research assistants, because they know, like, that's their expertise. Right. Our expertise lies in the science, but their expertise relies in the logistics and the operations. And you have to. You have to take a step back and understand that. Yeah, that's. That's not my bag. I'm not, you know, like Stephanie says, she's not a biostatistician. Guys also have to understand that they're not project managers, and they may not understand some of the things that their staff do.

Etienne Nichols: Yeah, that's a really good point. I. I think that's really shows a lot of wisdom when you recognize the gaps in your knowledge or the potential gaps and bring in people to fill those gaps or at least identify who could be the one to fill those gaps. One of the things you mentioned was all the different places you went to capture this data. How does that work in the data capture? It seems like it could really get out of hand really fast to make sure everything stays accurate, consistent, compiled to the right places. What are some of the things that you did to make sure that that stayed true to what it needed to be?

Kelly Palmer: Yeah, it can be a circus. I feel like sometimes we. A circus on wheels, right, Stephanie?

Stephanie Hinton: Like, I think, oh, yeah, I'll let you start, and then I'll add on. But that is a great question because it. We perfected it eventually or as close to perfection as you can be. But, yeah, Kelly, tell them. Tell them a little bit about that.

Kelly Palmer: I think everything, you know, there's a science to everything, right? I talk about science, and as it relates to. To the research and stuff I do. But really, there's a science to everything. And I think, as Stephanie said, there was a science involved with how we did data collection, and we had almost, like, our own research study embedded within the research studies, right? Like, how can we improve? And we took one way of doing things and said, okay, we got to make this better. We got to level up. And so when Stephanie and I first started as research assistants, we were going out with paper surveys, big packets of paper. We would have these, you know, paper consent forms and paper screeners and the paper surveys, and it was a lot.

Stephanie Hinton: And then we killed a lot of trees, for sure.

Kelly Palmer: Oh, my gosh. All the trees, right. And then we had all this equipment, because we were doing certain biometric testing, and we had equipment, and it was a clunky operation. You know, we would have, like, bags and boxes, and it was just a lot. Paper clips and just. It was a lot. And so we did that at first, right. Because that's what we knew. That's what our project managers had us do. That's what the PIs were accustomed to. And then as we started kind of thinking through, how can we make this more efficient? How can we tighten it up? Right? That's where the science comes in, where you start questioning things, and we start looking into new technologies and what's out there, what's being used to kind of make things better, how do we make it so that our data collection, because the way we were doing it on paper, the participants would fill out the survey you know, we would look over and make sure that there weren't any missing answers, make sure that things were tight. We would pass it off to our project manager, project coordinator. She would take it to the biostatistician. They would do another quality check, send it back to us to say, like, oh, this answer is missing, or, there's duplicates on this answer, or whatever. Yeah. You know, and then we would have to call the participant to try to, you know, get the answers back or to say, like, did you really mean this? Or did you mean that? Right. Lengthy process, multiple steps, multiple hands in the pot. So you can see a lot of areas where there could be error in the study is only as good as the data that's collected. Right. The PI can only report on what's, what we have in terms of the data, and that data informs the outcomes. Was it successful? Did it work? Who did it work for? And then that sets itself for the next project. As Stephanie was saying, the pilot then turns into the larger study. So in thinking through, how can we take out some of those layers, some of those steps, some of those areas that error can be introduced? So we started working with our biostats team and looking at electronic data capture. So we started using a program that allowed us to collect data in real time on iPads. And luckily for us, our PI was a tech guy. He loved technology and gadgets. So when I was able to go to him and say, hey, we could buy some iPads and use this application to enter data directly into this electronic data capture system and remove these multiple steps and multiple layers and save money, because the process of the paper and the scanning personnel that it took back and forth was expensive, and to be able to say, we can save money, we can reduce the margin of error and be more efficient. Sold.

Etienne Nichols: Yeah.

Kelly Palmer: So we did so. And then we kept trying to refine processes over and over again. And that was a good thing about the team we had. Everybody on the team was very innovative and always looking for ways to make things better and to improve our processes.

Stephanie Hinton: Kelly covered most of it there. I think the only thing that I wanted to add was, again, what you mentioned earlier, Etienne, knowing your. Whether it's your population that you're targeting or knowing your audience, same thing here. But that's where, yes, we used electronic data capture that was crucial for our study, and that made it so much cleaner. And that's where, of course, PI, biostatisticians, all these people at the top, they want clean data. So you make an argument for that, you show this versus this. It's a no brainer that there is an adjustment there, but you also have to think of plan a, plan b, and sometimes plan C. And that's what Kelly was great about. Most teams, you'll have SoP for this and Sop for that. Standard operating procedures. So before we would go into a new site, it was doing a lot of research, development, going to the site, doing a dry run. And this is where my job now, when I'm working with our customers and med device, making sure they're thinking of these things, because if you haven't done clinical research, you have this idea in your head. It's black and white. We'll do XYZ. Research is messy. The real world is messy. There's so much of that gray area. So we'd go to the site, take our iPads there. How's the service? Okay. Do we have an issue here? If so, you need to have that plan be implemented. You need to have your site personnel, your data entry staff trained on it. So research assistants know, if we had an outage with that EDC platform, which would happen, what do we do? Okay. It's not ideal, but we have paper just in case. So while, you know, I definitely believe in electronic data, there are instances where you need to do paper in addition to that, too. Some teams I'm working with, if they're med devices to older populations, less tech savvy participants, making sure you're accounting for that. So, yes, I love technology. Most people are on board with it. What do we do if you're using econsent these days? We worked on this a while ago. We didn't have that option, but now, what if they don't have a cell phone? You don't want to exclude participants based on this small barrier. So how can you do that? Okay, we can do a paper consent form, upload the PDF, and we'll train staff on that procedure. Or, you know, handing a tablet to a patient, and that might work for 90% of your subjects or 80%, but the subjects who really struggle with that interface, even if they're able to touch it and not type and use a mouse, maybe it is appropriate for you to hand them a paper survey. You want to make it convenient for that person, because, again, it's a lot of times what. What I don't like about research, and I don't currently work in research, is you. It's all about these aims. You know your hypothesis, and you need to reach that. You need to learn this, but it has to be centered around the people. And that's really where you need to remember. These people are giving their time. Yes, sometimes they're financially compensated or the study has benefits, but making sure that it's realistic for them. You're not asking the subjects too much. Or if the subject is 85 years old and she doesn't have a smartphone, do you really want to hand her a tablet? And if she's struggling, you can offer it. Would you like to do this on paper? Oh, thank goodness. You really want to be mindful of who you're dealing with and have plan a, plan b, plan c. And that's where Kelly eventually. And it wouldn't be, you know, this didn't all happen within one month, but within one year of having all of these different sites, we had it down to a science. We had this a one c machine, this machine that we would use for LDL, HDL. We would have the blood pressure cuff. We'd have everything set. We'd have a checklist. And she even, you know, we're auditing all of these readouts. Everything is structured, everything is written down. That's what I did like about research, is it's not this guessing game. There is an SoP for everything, but we just perfected it down to supplies. Okay, we have a clipboard here. We have this layout of all the different steps of what we're doing. So it was high level process logistics that eventually we again got as close to perfecting as you could. And it was really exciting because Kelly was great at listening to the research assistants, because she had been in that role. She knew the value of, okay, these research assistants are engaging with the patients more than I'm able to. I'm working with the IRB. I'm in these meetings with the PI. She also engaged plenty with our participants, but she listened to us, and then we had somewhat of a flattened hierarchy. But there were things where our team, we could go to Kelly, give her an idea, and she'd say, well, we need this data, or we need to do this research on what this would cost. We'd work collaboratively, or she'd take it on and then go to RPI and go from there.

Etienne Nichols: Yeah. One of the things that I kind of took away from that was, you have to be able, with your tools, whatever you're using, however you're doing your processes, you have to be able to separate the signal from the noise. And sometimes we introduce some signal with different things. So that was a really good point. I thought, for me personally, the other thing that you mentioned was research is messy, and I'm sure you have some stories about that, and I wonder if you could share any, and if we could take. Have some takeaways from that.

Kelly Palmer: Oh, yeah. I mean, like I said, it. It was a circus on. On wheels. I mean, every site we went to was different, right? So, like Stephanie said, we had to be flexible. We had to be adaptable. Like she said, we try to plan as much in advance as possible for as many different scenarios that could. That could pop up. Right? And that was everything from what she said, going to the site and doing a walkthrough and literally drawing up a schematic of the space and being like, okay, this site, this is how the room is set up. This is where this is going to be. This is where this table is going to go. This is where you're going to stand, you know? And the next week, it's going to change, because now we're in a different location. This week we're in a church. Next week we're in a senior community center. Right? And so we had to be down to the schematics of the physical space, having checklists, like she said, all the supplies, you know, need everything. We need backups to. Backups. Some of our machines would, you know, break down. Okay, we're going to take two machines because you never know if the first one's going to break down. And so, you know, but again, being flexible and adapting to the needs of the participants and to the needs of the people that we're trying to engage. So, like Stephanie said, we had a study that there was a lot of data collection involved. Like, there. There was a lot of data collection involved. It was with moms and their children. We were doing lots of surveys, lots of, you know, we were doing finger sticks, and it was time consuming, and so really being able to provide things for the participants, to allow them to participate. Right. So, one, just increasing the amount of incentive that we were giving them. I went back to the PIs, and I said, look, we're asking for quite a bit of time to collect this data, and I just don't think $25 is going to cut it. It just doesn't seem fair. Right. You're asking a mother to bring her children to wherever we are and give us 2 hours sometimes of their time. You know, I sat in on a data collection visit that Stephanie was actually conducting, and, you know, the kids didn't want to get their fingerprint. And Stephanie was doing everything she could to calm this child down. She almost got kicked in the face because the child was like, you know, really upset by the fact that we were doing this. And I told the P's, we really have to be accommodating, and we have to know when to fold, too. Right. So there are some instances where it's like, this isn't going to work as much as we have our own agenda. This is just not working. It's not working. So, you know, so we increased incentive. That was one thing for some of our participants to engage in the intervention required child care. So in one arm of that particular study, moms were going to the YMCA for an hour once a week to participate in the intervention. But the study was about moms who have kids. So we're expecting a mother to come to a location 1 hour a week without her children, but what's she going to do with her children?

Etienne Nichols: Yeah.

Kelly Palmer: Right. And so this was a problem. And so it's like we can't even answer our research question because if we can't get the moms to come to the intervention, we'll never know if it works. So these are things that we have to think about and be cognizant of. So it's messy. So we got childcare.

Stephanie Hinton: Yep.

Kelly Palmer: Back to the funder and we said, hey, we need more money because we have to be able to provide child care or we're not even going to know if this thing works. And so we got to come to our data collection visits. You know, we worked with a lot of people who were of low socio economic status, and we're like, they don't have a ride. They don't have transportation. They don't. They can't park. Sometimes we were on the campus of the university or of Indian IpuI, and we need parking. Let's pay for transportation. Let's pay for parking. Right. And so this is the part that, like, it's messy, but if you're just intentional and if you just think through and try to troubleshoot, it's possible. My current research, I have a project that I work with people who are older, and so that technology barrier. Right. This study is all about introducing technology. And so we want to be out there with our iPads. But I also have the research assistants trained to sit with the participants. Right. Some of them are fine. They'll take the iPad and totally fill it out themselves. Give them a stylist. They know what to do and some don't. So the research assistants have to know when it's appropriate to say, okay, I will administer the survey. I will ask them the questions and I will answer the data. Or I could hand it all and let them have added. Right. So it's having the protocols in place by knowing where to adjust, when to adjust, when to take it up the ladder, and when to empower your team to be able to make decisions on the fly. That's appropriate.

Stephanie Hinton: If you've worked in research, you know exactly what Kelly's talking about. For anyone listening who has not worked in research, I. For me, what was difficult, and again, I don't work in research anymore for several reasons. But one of the reasons is when you're collecting data, you have to be really careful about biasing the data collection. And that was very challenging. I'm very emotional. I want to either affirm or confirm what someone's saying that is so critical, and I don't think it's talked about enough. But Kelly was good on training about that. Our PI talked about it, but we would, in our regular meetings, talk about, were there any unique scenarios that came up? Do we need more training here or there? And that's where, again, pivoting quickly on something that you can improve on. So maybe it's something we can't control, but we can control the training that we're doing or writing more sops. So just for example, in the few studies we had, we'd ask about physical activity, and, you know, I would get sometimes participants talking about their sex lives and, you know, going into detail and, you know, you would have to be creative with rerouting that conversation without biasing their answer, but also acknowledging what they're saying, being professional, number one, which you would just want to laugh, or it was just, people are funny, people would say wild things. And I loved our participants. They kept me laughing. But there was also tough moments where, you know, we'd have. We'd be sitting with someone who didn't. Maybe they were at a normal weight for their frame and they. They knew maybe they had some risk factors or family history of diabetes. And they're sitting there looking at these numbers and people having a very real emotional response. So it's. I don't call it messy, but it's real. It's the real world. You're collecting data on humans, people, you know? So if someone's having that emotional response, how can you be compassionate without know, you know, in your head, you need to do the consent form, you need to collect data, so you can't always say what you want to say. This is so difficult. You know, you're going to be fine, or, you know, you have to be mostly neutral, and you have to be really careful with your speech if you are the person collecting data. And that's especially, too, if you're the principal investigator and you're wearing a white coat or you're a medical doctor or you're a professor at the university and you have these other roles and you're speaking with a potential subject, you have to be aware of that come down to a level of not biasing, that they feel pressure to consent. And, you know, there's so many different examples I could give, but I would say the overall theme that I took away is, and that was really hard for me, is people having an emotional response, or you want to say something, but you can't bias that data collection. And now I work in the for profit industry, and I help customers, and I can be totally, you know, myself, and I don't have to worry about biasing any. I'm not collecting data. But that is so key when you're a data personnel, if you're collecting data or your role is to ask those questions, finding that line of being compassionate, being there for the person, and showing sympathy without crossing that line. And that was really challenging, and I struggled with that, definitely.

Etienne Nichols: Yeah, that's important, not to lose the human touch. I think that's important for the medical device industry in general. When we're developing medical devices, it's sometimes, surprisingly, a lot of medical device professionals forget about the patient. Not. Not so much that they forget about it, but it's so far away. It's a little bit out of touch, doesn't almost feel real. But when you hear those patient stories, you can relate that back. So I can almost see that introducing those. Those experiences that you went through. Stephanie, maybe back to the team helping with that short feedback loop like you were talking about with the training. Okay, well, this is how we're going to do this, but it also reinforces what we're doing. We're trying to help these situations so that they don't occur later. Prevention and so forth.

Stephanie Hinton: And the other one thing I wanted to quickly add was another shout out to a different Kelly. Kelly Norton, who also worked with us. She was so savvy and so smart, and one of the biggest takeaways I took from her was, you know, everyone has these ideas of what the site will be like, what the population will be like, but then you get there and you learn as you go, and again, quickly make decisions, plan to do things differently. So we had a few different sites where sometimes, and we actually ended up having to go to the IRB and talk about how we were consenting people because there was illiteracy popping up where we would discover. And that was a very delicate situation where most people don't want to share that openly off the bat, and you don't want to outrightly ask everyone that. So. But you want to build in a process that works for everyone and is inclusive. But that was. That was incredibly eye opening, and that's what I did take the most. I took it very seriously. Consenting is a big topic, and we could have a whole other podcast episode. But she. She worked with this nonprofit called indie reads that's working to get rid of illiteracy in Indianapolis. So that's where. Okay, we come into this scenario. We want to enroll this participant. They're really interested in the trial. We have discovered that maybe they don't reach the requirements for capacity to consent, but we also know that this is a delicate topic, and maybe they feel embarrassed or they're bummed they can't be in the study, and we feel bad about it, too. How can we make this exchange less awkward? And how can we give this person something that may help? We would give them resources for this organization, saying, hey, we really appreciate your time. Unfortunately, I can't enroll you into this study. I'm really sorry about that. But if you're interested, again, they might not be. But if you're interested, these are additional resources, and we would have that ready and not, we'll follow up with you, or we'll get back in touch with you, or you can google this, you can do this on your own, having that ready to hand to them. And that's where sometimes paper material, something tangible is appropriate. And that I took that away, and I implemented that later on in other studies that I did. Even if we're enrolling a very highly educated population, okay, are we? That doesn't mean that you won't run into this ever. So if it does happen, being prepared for that.

Etienne Nichols: One thing I want to emphasize that Kelly had said earlier was about the childcare and the parking, and it reminded me of something. She didn't use these words, but you described root cause analysis. Really? Why are they not coming? Well, they don't have childcare. Why are they not coming? Well, they don't have parking. I thought that was a really good point. I just popped into my head. I want to just kind of emphasize that one more time. We're almost out of time, but I have one more question. Kelly, if you. If there's one thing our audience could take away from this conversation. What one thing would you want the audience to. To walk away with if you were.

Stephanie Hinton: Anyone involved with human trials? Again, these are people. I strongly encourage you to participate in research yourself by participating in studies yourself. Like Kelly mentioned, maybe you didn't start out as a research assistant. You can't go back in time to being undergrad or change your career route. You don't want to do that. But I would say that also to me. I participated in many trials at IU School of Medicine, IU school of dentistry. It gave me recruitment ideas. It gave me ideas that sometimes I'd bring to Kelly, where I talk about, well, this is really interesting, or, this was a super innovative, or, wow, they're using mailchimp to send birthday emails to their subjects. I never. Okay, this is another thing we can do for subjects, and it's not biasing anything. You're just wishing them happy birthday and again, adding that human element. But that's something that you've never participated in a trial yourself, but you're writing protocols, designing trials. Make time for it. It is very revealing on. You'll get to. And it gives you that insider's view of how they have it set up. Might give you ideas, but it also gives you a lot of respect and perspective on the whole process.

Etienne Nichols: Kelly, what about you?

Kelly Palmer: Yeah, I think my takeaway centers around kind of a lot of what Stephanie said, and that I really believe in a team approach, and that even as the PI, you know, everyone has equal role on. On the team, and everyone's about everyone's value, and everyone's perspective and contributions should be valued equally, and in that, you need everybody right. To get it done. And so you should be listening to the voices of everybody on the team, the research assistants, the coordinators, the PI, the statistician, and the participants. Right. So, like, you have your data points that you want to collect and things to answer your research question, but I always say context is queen. And there's a lot of context in the nuanced pieces of the data that you didn't anticipate or that you didn't plan for, that you weren't really looking for. But there is gold in the. In those, you know, in between the data points, right? So, like Stephanie said, just listening to the participants as they're filling out this survey, they're dropping little extras, right. Things that can help either refine the data collection, the approach, or even the overall research question. You hear things from them, and you're collecting weight, you're collecting what do they eat? But you're hearing other things, and now you're like, oh, we didn't think about that. Right. So the next study, let's make sure we include that aspect, right? So every voice is important in research, from the PI down to the participants and everyone in between. Context remains queen, and everyone's perspective should be valued and included.

Etienne Nichols: Fantastic. Thank you so much. Kelly, I really appreciate you coming on the podcast. Stephanie, thank you so much for connecting us and bringing her on the podcast as well. Really appreciate both of you so much sharing your experiences, those you've been listening. You've been listening to the global medical device podcast. We'll let you get back to it. But everybody, until next time, take care. Thank you so much for listening. If you enjoyed this episode, can I ask a special favor from you? Can you leave us a review on iTunes? I know most of us have never done that before, but if you're listening on the phone, look at the iTunes app. Scroll down to the bottom where it says leave a review. It's actually really easy. Same thing with computer. Just look for that. Leave a review button. This helps others find us, and it lets us know how we're doing. Also, I'd personally love to hear from you on LinkedIn. Reach out to me. I read and respond to every message because hearing your feedback is the only way I'm going to get better. Thanks again for listening, and we'll see you next time.