Good afternoon, everyone, and welcome to the IUPUI Center for Translating Research into Practice, our monthly conversation with a translational scholar. My name is Steve Veg. I'm the Associate Director of the Center, and it's a pleasure to welcome you here and have you with us to explore some topics of translational research. We'd like to give a shout out to our founding director Sandra Pio, whose brain child was to have this opportunity to highlight, to honor, to name, to find, and expand. The amount of translational research going on here at I EPI. And one of the ideas that Sandra had long ago was to create spaces where people could come together to share ideas. And so this is one outcome, perhaps positive outcome of the pandemic where we're able to use this medium, Zoom, where we can come together and hear from one of our colleagues at IEPY, to share with us some information and then have a conversation about what this means for us in many different ways. Allow me to share my screen with you this morning to share a few important announcements and topics about what we need to do to be prepared to have Veronica begin our conversation. So first, as you know, we're in Zoom, so I'll remind everybody about Zoom etiquette and to please keep your microphone muted. We're happy for you to leave your cameras on, especially when we get to the conversation portion of our meeting, and you are welcome to put some questions into the chat box as we go along. We'll help monitor those. But we hope that you feel comfortable to unmute as we get to the conversation portion of our event today. So you know this whole event is being recorded and we'll make that available for future viewing if that makes a difference about whether you wish to be seen on camera. We're going to also send you a post Meeting evaluation. We hope that you'll take a few minutes to answer a few questions on one of those Andy Dandy surveys to give us some feedback about this opportunity and questions about future events. If you are interested, we also have CEUs available for this whole series. If you just check out, are you expand, you can learn more. But please share this opportunity with our community partners too. Sometimes folks are looking for ways to expand their education and get credit for. And this is one way you can do it. Interested in knowing all the other great things that are going on with the center for translating research into practice. We encourage you to follow us on our social media pages. You can check in with Twitter or Facebook or Instagram, but we also have events like this housed on our YouTube channel. So please check back and follow us and share it with your friends and colleagues and community partners. One of our other amazing opportunities is for you as a a community member to be able to access the information and works that our scholars do in something called Scholar works. If you go to our website to the IPY website, you'd be able to go to our featured scholar pages and you could scroll down and see those that we have already up on our list. You could check on Veronica, for example, today, find out more about her research and ways to contact her and to learn more about what she does. And then you could actually click on her first so you could find out her scholar works presentations, the ones that she has that are particularly about this research, or click on the Scholar Works link, and you can find out more about her work. It's an easy way for you to find out without having to go to a lot of different locations, what work is there. So upcoming, we want to make sure that you have if you've not heard already that we have invited President Pamela Witton, our new president at IU, to share her translational work at our annual keynote address. This will be a virtual event, and it's just coming up in a couple of weeks on Friday, February 25 at noon. She'll be talking about Telemedicine, a journey through the evolution of translational research. It's very easy for you to sign up for this. Just go to our website and go to the Events page, and please join us for this very informational opportunity. Then next month in our continuing opportunity with our conversation, Well, we're inviting doctor Devon Hensel, who has a joint appointment in Pediatrics in the School of Medicine, as well as in Sociology in the School of Liberal Arts, and she'll be sharing her research and information at these monthly events. Today, let's wait no longer to hear from our colleague, Professor Veronica Derrick, who is in the Department of Psychology. Today, she's talking about the topic of understanding the effects of information targeting Black Americans. We're delighted to have you here with us today, Veronica. I'm going to unshare and let you share your screen and turn on your camera and your microphone so we can hear from you. We're looking forward to hearing about this work and then having a conversation with you. Thank you so much for the wonderful introduction. Let me just go ahead and share my screen. Does that look good? Yes. Looks. Perfect. Thank you again, so much for having me today. I'm delighted to share my work with you. And so I started here at IUPUI in fall 2020. And so the work that I'll be sharing today is some work that I started during my doctoral studies, but that I've since continued developing since I've been here at IUPUI. And so to go ahead and get started, within the United States, statistics have revealed persistent racial health disparities, such that Black Americans experience worse physical and mental health outcomes compared to White Americans. And specifically, reports show that white Americans have a higher life expectancy than Black Americans, that Black Americans are more likely to report feelings of sadness and hopelessness compared to White Americans, and that Black Americans are over three times more likely to be hospitalized for preventable conditions. Racial disparities have been particularly pronounced for certain health conditions such as HIV. We know that Black Americans make up about 13% of the US population, but they account for 40% of new HIV diagnoses, as well as people living with HIV. Importantly, this disparity has persisted for decades, despite the development of health programs and interventions that have been specifically designed to address this gap. One approach to reducing racial health disparities and health disparities generally is getting relevant information to high risk audiences and ensuring that they attend to it. And so use of this approach is consistent with research showing that leveraging relevance is beneficial. And so in the context of messaging, past research has shown that high message relevance can facilitate persuasion. It can direct and increase attention to self relevant stimuli, can increase recall of information, can produce more favorable evaluations of the message source or message provider, and it can also facilitate approach behavior to health goals. We often see health promotion efforts that leverage relevance to appeal to different groups. Here we have images that were used to signal relevance of information about flu, about breast cancer, and about HIV specifically for Black Americans. In my work, I focus on information targeting, which is a relevance intervention where information is disseminated specifically to high risk audiences. For example, doctors might give information about osteoporosis specifically to older adults because older adults are at higher risk for developing osteoporosis. The expectation is that when individuals are targeted, the recipient sho perceive the relevance of the information and targeting should facilitate persuasion, increased uptake of recommended behavior, elicit other types of benefits. But despite psychological theories showing that relevance has beneficial and campaigns utilizing relevance as a health promotion tool, it's important to understand how message recipients actually respond to these efforts. Although extensive research has highlighted the benefits of relevance, we theorize that efforts to leverage relevance may backfire in context where it elicits social identity threat. Social identity threat is a psychological phenomenon that emerges when people suspect or anticipate being devalued or negatively judged on the basis of their group membership. Within prior literature, experiencing social identity threat has been associated with a number of negative psychological, physiological and behavioral outcomes. So in our work, we expect that targeting can be consequential because our identities don't operate in a vacuum. Targeting doesn't just activate that relevant identity, but also all of the thoughts, experiences, and stereotypes that are associated with that identity. Receiving information about osteoporosis, when it just activate my older adult identity, but also the thoughts, experiences, and stereotypes that are associated with that older adult identity. And so similarly, we expected that signaling relevance through racial identities can activate race based experiences and stereotypes that can subsequently elicit social identity threat and undermine health behavior engagement. As a first step in this work, we wanted to examine how medical practitioners evaluated information targeting. We recruited 79 medical practitioners, and so I included physicians, physicians assistants, nurse practitioners, and we surveyed them about information targeting, which we defined for them as giving brochures to subgroups of the population at higher risk for a disease. To analyze practitioner's responses, we used a 17 scale that range from strongly disagree to strongly agree, and we compared practitioners responses to a neutral scale midpoint of four, which indicated neither agree nor disagree. And so the findings overall showed that practitioners reported positive evaluations of information targeting. Specifically, they believe that it would be a useful and efficient method of information dissemination. That they were significantly likely to agree, that it would show patients that they care about them. And they agreed that it would show patents that it would increase patients attention to any type of health information that they were giving to them. Additionally, practitioners were significantly likely to disagree that targeting would lead to worse relationships between doctors and patients or that targeting would increase feelings of distrust among patients. Then next we looked at practitioners engagement and information targeting, and we found that about 85% of practitioners reported having targeted in the past 30 days, as well as intentions to target information of patients in the future. Then lastly, we looked at the dimensions on which practitioners reported a willingness to target information. We found that about 67% of our practitioners reported a willingness to target based on a visible identity like race, gender, age, or weight status, compared to 77% who reported a willingness to target on medical history. In summary, study one show that medical practitioners reported expectations that information targeting would be useful and efficient. They would increase patient's attention to the information, and they disagreed that targeting would produce distrust or lead to worse physician patient relationships. Additionally, we found that practitioners targeted information based on both physical social identities as well as medical history. Next, we were interested in investigating how Black Americans versus White Americans might respond to health information when they perceive that they're being targeted based on their identities. For Study two, we recruited 343 adults using Amazon Mechanical Turk, also known as Turk. This is an online study platform where US adults can complete online studies and surveys in exchange for money. We recruited 186 White Americans and 157 Black Americans, and we used it two by two between subjects design. The first factor that we manipulated in this study is whether participants were targeted or in the control condition. Then the second factor in the study was participants race, whether they were white or black. And so in terms of the procedure, all participants were randomly assigned to either the control or the targeting condition. And so in the control condition, participants were told that they were receiving health information due to chance. Then they read HIV information. They responded to our dependent measures, and then they provided their demographic information at the end. To signal targeting and the targeting condition, participants provided their demographic information, so their race, their age, their gender, and their socioeconomic status. Then we told participants that they were receiving health information due to the demographics they had provided. Then they received the HIV information and responded to the dependent measures at the end. I'll quickly note that the HIV information was information that was adapted from the CDC and described what HIV is, consequences of developing HIV, as well as treatment options that are associated with HIV. Moving into the results. First, we looked at participants self reported attention to the message. And so we found a marginal interaction effect. And so the pattern of means showed is that for Black Americans, being in the targeting condition to report decreased attention to the message compared to when Black Americans were in the control condition. But for White Americans, there was no significant effect of the targeting manipulation. Next, we looked at participants level of trust in the information provider, and we saw the same pattern of findings. Again, for Black Americans, being in the targeting condition led to less trust in the information provider, compared to when they were in the control condition. For White Americans, there was no significant effect of the targeting manipulation. In Study two, we found that Black Americans who received the targeted information reported decreased attention to the information, as well as less trust in the information provider. White Americans, however, did not show negative effects in response to being targeted. To extend Study two, we were interested in understanding why targeting might elicit negative consequences for Black Americans but not for white Americans. What we expected was that for Black Americans being targeted might activate experiences of being stereotyped based on their race, that would elicit social identity threat or perceptions of being unfairly judged. Whereas for White Americans in contrast, we theorized that these experiences of race based stereotyping when it be activated, and as a result, negative consequences in response to targeting when it emerge. What we proposed is that targeting would increase perceptions of being unfairly judged specifically for Black Americans, and that feeling unfairly judged would predict reduced attention to the information and decreased trust in the information provider. We recruited a 401 adulta in MTurk. It was pretty evenly split about 200 White Americans and 200 Black Americans in our sample, and the design and procedure was the same as in Study two. And so consistent with our hypothesis is, what we found is that when Black Americans were in the targeting condition, they reported greater perceptions of being unfairly judged compared to when they were in the control condition. And again, for White Americans, there was no significant effect of the targeting manipulation. And so next, we looked at our proposed model, and as we just observed in the ANOVA, targeting increased perceptions of being unfairly judged specifically for Black and Americans, and feeling unfairly judged in turn predicted reduced attention to the information as well as decreased trust in the information provider. We also found that the self report measures predicted behavior, and I'm happy to talk about some of the additional outcomes that we've looked at following the presentation. In summary, we find that targeting increased perceptions of being unfairly judged for Black Americans, but not for white Americans. Then feeling unfairly judged in turn predicted reductions in attention to the information, as well as less di trust in the information provider. And so in Study four, we expected that one reason why targeting might have produced negative effects for Black Americans is because they inferred that they were being unfairly judged by information providers who did not share their racial identity. And so in Study four, we were specifically interested in how the race of the information provider might impact Black Americans responses to targeted information. I study four, we recruited 515 Black Americans on prolific academic. Prolific academic is just another online platform, very similar to MTurk, where you can recruit adult participants to participate in studies for money. We again use the two by two between subjects design. The first factor that we manipulated is whether participants were targeted again in a controlled condition. To manipulate race of the information provider, we provided a physician provider who was either black or white. The design and procedure that we used in study for replicated the previous studies with two exceptions. First, we changed the information used in this study. In this study, all participants read information about COVID 19 instead of HIV. Then we also used a different targeting manipulation. We used another targeting technique that is typically used in this study was information that emphasized racial disparities in COVID 19 rates. And just give you a sense of what our new targeting manipulation looked like. In the targeting condition, participants read an article that basically emphasized racial health disparities in COVID 19 rates. This information basically highlighted that Black Americans were disproportionately affected by COVID 19. And then in the control condition, participants read an article that basically explained that COVID 19 is affecting Americans generally. Again, this work was adapted from information from the CDC and the NIH, explained what COVID 19 is, the consequences of COVID 19, as well as different treatment options or behaviors that people can engage in to prevent the development or contracting COVID 19. And then to manipulate physician race, we either again, had a black physician or a white physician who sensibly wrote this information. And so you can see the black physician on the left, Donel Johnson, and then the white physician on the right, who is Luke Johnson. And so in terms of our result, what we found was that when Black participants received the targeted or the non targeted message from the Black physician, it did not significantly impact their feelings of trust in the physician. However, receiving the targeted message from the white physician led to less trust in the physician compared to receiving that control message. We also looked at participants' attitudes towards the message. Again, when participants got the targeted information from the Black physician, it had no significant impact on their attitudes towards the message. But receiving the targeted message from the white physician led to more negative attitudes towards the message. Perceiving the message to be less useful and less important compared to the control message. And so Study four, we saw that targeted information backfires for Black Americans when the information is provided by a white physician or a racial outgroup member. Specifically, our Black American participants reported less trust in the information provider, as well as more negative attitudes towards the message. Additionally, we found that receiving the targeted information from a Black physician did not elicit these negative outcomes. And so thisqu demonstrates how the use of identity based targeting as an intervention can backfire. Specifically, we find that these efforts to leverage relevance through racial identities can elicit negative outcomes for Black Americans due to perceptions of being unfairly judged. Additionally, study four show that negative responses to targeting are likely to emerge for Black Americans when the information provider does not share their racial identity. Specifically, again, we looked at a white physician in this context. Given this previous research showing the negative consequences of targeting health information, my colleagues and I became interested in how we could improve the delivery of targeted messages about HIV prevention for Black Americans. In current research, we're developing a set of messaging strategies that can reduce perceptions of being unfairly judged, and that would be more likely to foster trust. To develop the preliminary intervention messages, we used messaging strategies that were informed by both theory, as well as empirical research. And so we piloted these messages with 40 Black Americans. We recruited on prolific academic, and participants saw one of four targeted HIV prevention messages. And so in this pilot, we asked participants to imagine that they were receiving this message from doctor Eric Smith, and this message was given to them while they were discussing the sexual activity. And so each one of the messages contained about three to four messaging strategies and highlighted the racial disparities in HIV rates specifically for Black Americans. And as part of this pilot, we asked participants to describe what they liked and what they disliked about the message. And so with regard to what participants disliked about the message. I've just included a few responses. You can get a sense of what participants were saying. And so one participant says, his targeting of the Black community and reference to safe sex is racist. Other groups also experience high HIV rates, but he references the Black community as if it's only isolated to that group. He failed to acknowledge the socioeconomic disparities and medical racism that impacts the Black community, which is why rates are high. Another person said, I don't think I like that they brought up my race, that has little to do with the reason why many Black Americans have HIV. Seems a little surface level and like a generalization that places the blame on Black Americans and not the lack of education surrounding poorer communities, the lack of trust doctors have with Black Americans, and other racial and socioeconomic factors leading to the disproportional health crisis. You can probably detect from these responses, there were a few common themes that emerged about what participants disliked from the messages. Specifically, some themes that emerged for feeling like Black Americans are being blamed for the disparity. And along with that, ignoring the role of external and structural factors, such as socioeconomic status that can also contribute to these racial disparities. Another theme that emerged was feeling like Black Americans were being singled out and especially compared to other social groups. Then the third theme that emerged was feeling like the use of race was unnecessary or irrelevant, especially in light of other factors that could be contributing to these disparities and likely have a much stronger role than a person's racial identity. And this feedback uncovered some ways that we could reframe the message content and identify some additional strategies that could be used to improve the intervention messages. Next, we looked at participants responses about what they liked about the messages. And so one participant said, I liked how he explicitly stated at the end that he thinks my health is important, which is why he's sharing the information with me. He also referenced research and explained why the statistics are the way that they are. Another participant said, I like that he placed the information in line with my own goals of well being, broader societal goals, and the shared goal of our doctor patient relationship, framing safer sex behaviors as a positive choice rather than shaming the past behavior. I also like that he mentioned systemic issues and didn't try to put all of the responsibility on me as an individual while still being informative about things that I could do independent of those external factors. And so some themes that came up from these responses about what participants liked, or feeling that their doctoring the doctor was genuinely concerned about them, as well as their health. They also liked feeling like the doctor was using research and statistics to inform the conversation rather than relying on their opinion. And finally, they liked when the doctor acknowledged external factors, factors outside of the individual that can also be contributing to these disparities. And so based on prior research in the pilot data, we've developed a list of several strategies that have been either theoretically and or empirically supported to reduce perceptions of feeling unfairly judged. And I've included a few strategies here. And so the first one is acknowledging that everyone and not just Black Americans are susceptible to developing HIV or contracting HIV. The second is highlighting progress that's been used to reduce racial disparities in HIV rates, and so using an asset rather than a deficit based framing when talking about HIV disparities. The third is acknowledging system level factors, such as systemic racism in the health care system, that can contribute to these disparities. Again, focusing solely on personal behaviors can increase perceptions or concerns about being negatively judged. Then finally, expanding the dimensions on which recipients are targeted. Specifically highlighting other personal characteristics, such as health goals, that might make this information relevant to patients. And so to give you an example of what one of the targeted messages looks like following this pilot study. Again, each of the messages uses a few different strategies. And so for this particular message, it starts by acknowledging the fact that every anybody can develop HIV and that these rates are just particularly high in the Black community. The next highlighted strategy in red. It describes the role of systemic racism and HIV disparities and reasons why these disparities might exist. So black patients not being routinely screened, as well as doctors not making sure that patients have all of the information needed to make important decisions about their health. Then at the end, we highlight a reference to the patient's values as well as shared goals around health. The idea that it's clear that your health is important to you, so I want to make sure that we work together to keep you healthy. We also included some behavioral recommendations such as using condoms with partners and getting screened for HIV and other STIs at least once a year. And so in ongoing research, we're about to start conducting some interviews with block adults. During these interviews, we're particularly interested in how black adults typically talk to their doctors about HIV. And so what are the challenges and barriers that are coming up to these discussions? What is the content of these conversations? What's being said? And we're also really interested in getting their feedback about our new intervention messages, what they like, what they dislike about the messages, and specifically, how can these messaging strategies be improved? We're also going to be conducting interviews with primary care physicians and specifically interested in understanding the best way to implement these messaging strategies enter their practice. And so what types of resources would be most useful for physicians to be able to navigate these conversations effectively. And we're also interested in talking to physicians about what would make them more likely to implement these messaging strategies. And given everything else that has to happen during a visit, what would make them more likely to spend 30 seconds or a minute focusing in on HIV screening. The overarching goal of this work is that we'll develop a set of messaging strategies that both effectively foster a sense of trust among black adults, and that also are strategies that physicians feel comfortable using in primary care settings. Eventually, these strategies will be implemented by physicians in primary care settings with a goal of increasing rates of HIV screening and participants for patients engagement in HIV prevention behaviors. And so we hope to improve communication related to HIV and really encourage uptake of recommended behaviors to address the disparities in HIV rates and most importantly facilitate more equitable care. So I just want to acknowledge my collaborators as well as my funding sources. So doctors Ali Earl, Iva Pietri and India Johnson, who are my collaborators with the experimental studies. I'd also like to acknowledge doctors Adam Hirsch and Marian Mathias, who I am currently collaborating with as we're developing this HIV prevention Communication Intervention. I'd also like to thank my funding sources, including the Indiana CTSI who is currently funding the development of this intervention. I'd like to thank you all for listening. So thank you so much for your time today. T hank you Veronica for sharing all this amazing information. And we'll open it up now and ask our friends out in our audience to share questions and comments, and we invite you to go ahead and turn on your cameras and let us know if you'd like to ask a question or make a comment. I can either raise your hand or just mute, I'll try to notice that. Go ahead. Thank you. Thank you. So The topic, you know, with the focus on HIV, and because there have historically been some, negative commutations associated with having HIV like lifestyle choices, it does make sense that that could impact targeting. I'm wondering if there's any evidence or if you have any thoughts about whether these mechanisms might be in place for other health conditions that don't have that baggage, I guess. So for example, we do work with health communication messaging for parents of children with sleep apnea. So yeah, I just would love to hear your thoughts about how much it matters the condition itself that you're targeting about. Yeah, that's a great question. So far, we have not seen a difference based on information based of the health condition that's used. We've see the same effects when we target flu information. We see similar outcomes with the COVID 19 information. Some other work that I've done has looked at targeting information about obesity to people with higher body weights and similarly, feeling unfairly judged is a mechanism that comes up. And so all of these conditions tend to have specifically a behavioral, a strong behavioral component. But I have not yet tested is whether having a health condition that has a larger genetic component will impact receptivity to targeted health information. And it's possible that if you focus on the role that genes might have, that it might reduce perceptions of being unfairly judged, but I have not tested that yet. It's possible that if you are talking about a health condition, let's say sleep apnea, and you're still talking about Black Americans and say that sleep apnea does have this genetic component, that you might still get that flavor of feeling unfairly judged because how is my race relevant to this health condition? But if we're talking about like sickle cell, then that might be a context where you don't see that backfiring effect emerge. But I do think that this effect does generalize across information content or health conditions. Though I will note that I have not tested it with Health conditions that have a larger genetic component. Are there other comments or questions? And a question. Yeah, great talk, great work, Veronica. Really impressive. So Scotty thinking making the leap from tailored messages to tailored behavioral interventions and whether this work if there's a relationship there and whether it might extend. And something that's being found with like culturally adapted psychotherapy, CBT is that the culturally adapted versions perform better, have greater efficacy than the non adapted versions. And it's just got me thinking now people are trying to do that with Internet CVTs, right? So where there's less there's no human, right? And it's kind of like a tailored messaging platform and training platform. So I wondered what your thoughts are on kind of tailored interventions and whether your work extends to that and why those sort of backfire in a similar way, especially internet based interventions where there's no provider, and there can be no matching or mismatching on race or culture. Yeah. These are interesting questions. My work focuses specifically on race based or identity based targeting. My understanding is that tailoring provides a more individualized approach to delivering information. The work that's been done on cultural tailoring shows that tailoring the messages based on religiosity, for example, would be more effective than a message that is not tailored based on culture. The work related to cultural targeting is a little bit more mixed. And it's unclear if that's because that information. There's different ways that people are defining cultural targeting. And so it gets a little bit murky in terms of the cultural targeting versus cultural tailoring. But I think my work doesn't really focus on that culture piece. It's focused more on like that identity piece. And I think that is part of the reason why we see this back crying or effect because it's like, how is my identity relevant to these disparities? Whereas the cultural tailoring might say, if this group is higher in religiosity or collectivism, then perhaps we have a message that incorporates those aspects. And so less of a focus specifically on identity, unless you are suspicious of the message and might say, Is everybody getting this message about religiosity? Do you think all Black people are religious? What do I take from that? I think that there is a potential for that firing effect to happen. But my initial thought is that would be weaker than this race based targeting that I've been looking at. Well, that's interesting too. Thank you. As I think about the apps and the way they're being designed. I think they look more like like the race targeting that you presented, then the cultural adaptations that are being done with a face to face therapist, which is more based on culture, just the way they're designing them. So I guess we'll see what the data tell us, but thank you. That's Insightful. Yeah. I think also your question about what if there is no source, what if your source is the computer or an algorithm. It's been a question that's been in my mind. I've talked with a few people about it and do you just say racist algorithm? What do you do with that information? It would be interesting to see when there isn't an actual person, how people are responding to the targeted message. But I would expect you still get the backfiring effects, but there's just nobody to really direct your negative energy towards in that circumstance. I noticed that doctor Varma Nelson had a comment earlier? Do you want to say something? You're on mute still. There we go. Yeah. Thanks for such an interesting presentation, Veronica, it was great. I was just wondering if similar work has been done in politics. I imagine there's a lot of interest in targeting political messages, and what has been found, do you know? Yeah, that's another great question. There was a time when we had some studies developed to look specifically at targeting and political contexts. I don't think it's been studied extensively, but I think that it may be able to explain some of what I see as being back firing effects in terms of voting behavior. Thinking about Hillary Clinton, making direct appeals to women, for example, and then women in turn not voting for her. You can think about political candidates, even in most recent election, using language, making direct appeals to different groups, and looking at the effects there. Again, I similarly expect that you'll find of these backfiring effects, especially from out group members that are directly targeting groups like Black Americans or any type of minoritized group where you would see disengagement with that person. Of course, things get a little bit trickier when we're in the primary election and you only have two or three candidates. But what might happen there is that you just get people who just don't vote. And so then voter engagement becomes low because your only alternative is to vote for somebody who you feel like stigmatized you. And so I think it's really important to consider targeting in the context of politics, and It is something that is constantly done. But again, I don't have actual empirical data for support, but just based on the work that we've done, looking at targeting and health context. Recently, we've done some work looking at targeting and organizational contexts. So Leslie, Ash Bernardo, Iva Pietri, and India Johnson, and similarly refining that targeting and so having job advertisements that are directed towards Black Americans increase concerns about being tokenized, decreased intentions to want to work for that organization, reduce attraction towards that organization. And so we are finding similar effects kind of of targeting outside of health context. So yeah, I think you definitely see similar effects there. It just seemed to me that Biden used targeting quite effectively when he said he will appoint a Black Supreme Court justice, you know? So it seems like it could be used I mean, C lburn was behind that, you know, so it seems like it can be used effectively. It just depends on what matters to the community. Yeah. It's an interesting case because there have also been contexts where Biden has said things that have increased social identity threat or perceptions of being judged. I think that there are some instances of targeting that people can see through, but they say at least we're increasing the representation of Black people in government in these domains. And so I support that. But may not necessarily increase trust or liability of Biden himself. Because you know that the intention behind this is to get elected or to have these targeted appeals to get my vote. But again, if the outcome is beneficial for your group, you might still vote because we're getting more representation or we're benefiting in some way. So yeah. And the alternative is terrible, right? Yes. And what are you going to do? But I really about the question that was posed is thinking about, how does the work that you're doing, doctor Derrick translate to other kinds of questions and whether this is a good thing to try or not a good thing to try. And it sounds like you know there's potential, like to explore that, but also to think about it from what's the perspective. So that's one of the beautiful things about these conversations is that we spark thinking across different disciplines, different sectors, different ideas. And the work that you're doing is certainly really relevant to today's conversations. Very, very pleased that you were able to be here with us today. We're aware of the time, and we want to be cognizant that people are experiencing Zoom meetings back to back to back to back, and we're here today over the lunch hour. So what we'll want to do is officially thank doctor Derrick today for sharing today. Invite you to have more conversation with her beyond this. I'm sure she would love the opportunity to chat with you or collaborate with you in some way, or if you're a community partner and have interest, please reach out to us and let us know. We will stay online for a little bit. We know if you have to leave and need to get ready for you 1:00, thank you for coming. We want to remind you to please join us for the keynote address in two weeks from today with President Pamela Witton. And then next month again for our regular conversation. We're glad to see so many new faces here with us today, and we will give up our thanks to doctor Derrick. And then we'll stay online if people do want to say something afterwards, and we'll just hang out for a few minutes. But otherwise, thank you for joining us. Thank you so much for coming.