But I thought we'd kick us off so we have enough time for discussion at the end. My name is Gaia Dowling, and I'm the Director of the Adolescent Brain Cognitive Development Study at the NIH. And I'm really excited to present or have a session today on the impact of the environment on adolescent development, finding from some BIPOC scholars in the ABCD Study Start Program. So for those of you who aren't familiar with ABCD, I thought I'd just give you a very, very brief introduction to the study. It's a longitudinal study of about 12,000 youth, beginning when they were ages nine and ten and following them through adolescence into early adulthood to assess many different factors that influence individual brain development and other trajectories. And as I mentioned, we enrolled close to 12,000 youth from across the country. We have 21 sites across the country. And did our best to match their demographics to the U.S. population. So here you can see the demographic makeup in terms of race, ethnicity, and sex assigned at birth. And we're collecting a large amount of data in many different domains. As you can imagine, when you're looking at the factors that influence adolescent development, you really want to understand all aspects of their world. So we collect information from both the youth and the caregivers about physical health, mental health, substance use, culture and environment. We also conduct neuroimaging and neurocognitive testing, collect some biospecimens. We're collecting information using a Fitbit on activity and sleep, as well as geocoded data which we can use to map with external data sets to bring in more information about the world in which these youth are growing up in. And as we do this, we began when they were nine and ten, and that was in 2016 to 2018. And we see them every year, and every other year we conduct the neuroimaging. And the plan is to see them through at least the age of 19. And we had many goals when we launched this program to understand adolescent development, to understand substance use, to understand mental health. But one of the things that we have recognized is that if you really want to understand the diverse presentation and all of the different contributors to these complex disorders, particularly with substance use and mental health, then you need diverse researchers who are using the data to study those various factors. And so Dr. Micah Johnson, who's at the end of the table, along with Dr. Hugh Garavan at the University of Vermont, piloted a program within ABCD called the Scientific Training in Addiction Research Techniques for Gifted Future Investigators from Historically Underrepresented and Underserved Backgrounds. And the idea for this program is to bring early-stage investigators, pre-docs, post-docs, and young investigators from underrepresented backgrounds into the ABCD cohort, consortium, to learn about the data, learn how to use the data, and bring their novel insights into using the data. And so today's session is going to be highlighting the work of three of these young scholars. Neo Gabrou is going to talk about relations among mental health conditions, familial environment, and facets of impulsivity in the ABCD study. Skye Bristol is going to talk about family conflict as a risk factor for alcohol expectancy among youth in the ABCD study. And Stacey Ryan-Pettis is going to talk about youth externalizing behavior explained through parental monitoring, parental inconsistent discipline, deviant peer affiliation, and level of neighborhood risk, a moderation mediation model. So all three of these presentations are looking at different aspects of the ABCD data set to really give us a better understanding about youth development. And then we'll end with Micah Johnson leading us in a discussion. Thanks Gaia. Thanks everyone for being here. My name is Neo. I'm a post-doc at Brown. And today I'll be talking to you about a project that I did using ABCD data that looked at relations among parental mental health conditions, family environment, and facets of impulsivity. And before I start, these folks were critical to the work that I'll be sharing with you today. So I just want to give a major shout out to folks both from the ABCD program and members of the START program that worked on this project with me. So we'll be looking at relations among parental mental health conditions, family environment, and facets of impulsivity, like I said. And I'm a visual person, so I've just taken them and put them in boxes here. And really the question is, how are these three things related to each other? And the research question I'll be trying to answer is, does family environment mediate relations between parental mental health outcomes and youth's impulsivity? So I'll just provide a brief background covering the literature that talks about how parental mental health we know affects children's outcomes. However, little is known about underlying mechanisms. And today, using data from the ABCD study, we'll see if family environment is one of those social contexts that are important for youth development. And then I'll go over the methods and results from that. So we'll be seeing this figure quite a bit today. And before jumping in, you might be wondering, why do we care so much about youth's impulsivity? Why do we care to go through all this trouble to predict it? And just so we're on the same page, impulsivity is a multi-faceted construct that's characterized overall by a rapid response to stimuli. And there's a very substantial literature now that shows that it's associated with several deleterious outcomes. And particularly among children and youth, when it comes to substance use, it's associated with both initiation, as well as acceleration of substance use, and engagement in other risk behaviors. I'm a substance use and HIV researcher, so I also look at sexual risk outcomes. So it's important that we understand factors that affect impulsivity. The literature thus far has looked at how parental mental health conditions are associated with children's impulsivity and substance use outcomes, and I'll talk about a study that's looked at that in detail in a minute. And growing literature is considering how being raised by parents that have mental health issues is sort of an environmental risk for children's outcomes. However, we still don't know how having depression or various mental health issues in the parent sort of ends up manifesting in the youths displaying impulsive traits. This was a study I really liked that came out a couple years ago from Julia Felton and colleagues. And here they looked at exposure to maternal depressive symptoms and growth in adolescent substance use, and the mediating role of impulsivity or delayed discounting here. And just to quickly summarize their findings from their abstract, the participants included 247 adolescents and their mothers in this study who were assessed annually over a six year period. And even though the mediation effects are often small, but they were significant in this case where they found that specifically maternal depressive symptoms are predicted increases in the child's delayed discounting, their impulsivity, which then predicted increase in adolescent substance use over time. So we know there's this association that having parental mental health issues leads to impulsivity to then youth substance use. But we still don't know how we go from parental mental health to increased substance use. The literature that's sought to disaggregate the effects of parental mental health issues on the youth's outcome has focused on its effects on parenting and the parent-child relationship. Research shows that more depressive symptoms are associated with more conflict. So that leads us to my current research question, which is, does parental mental health conditions lead to increased and family conflict that then lead to increased in youth impulsivity? So we used data from the ABCD data here, which had just under 12,000 adult children who are between nine and 10 at baseline. And for my X variable, so this was the parental mental health conditions, they were measured via interviews and following the DSM-5 protocol. And we had three scales for internalizing problems, externalizing problems, and total problems of the parents. And for anyone curious about the analyses, they were all skewed. And to address normality, they were all log-transformed. For our mediator, this was the parents or the family environment. This was measured via a youth report. This is a nine-item conflict subscale that's characterized by... Can you see the pointer? Yeah. Family members sometimes get so angry that they throw things at each other, or family members sometimes hit each other. So this is capturing... This is also from the youth reports, so this is capturing their perspective of the family environment. This was a bit skewed, but it had acceptable normality. And for our purposes, we looked at measuring youth's impulsivity using the UPS-P, which measures five facets of impulsivity, positive and negative urgency, sensation-seeking, and lack of perseverance and planning. And these are each thought to capture sort of the second-order factors of impulsivity. So mostly, the literature is focused on emotion-based rash action, so those are the urgency-based items, and deficits and conscientiousness. And these are just sample items for that. So this is looking at when each of our variables were measured. So in green, these are the parental mental health conditions. They were measured at baseline, at one-year follow-up, and then at two-year follow-up. Our mediator family conflict was also measured at all timelines. Here, as I'll show you, I conducted lagged or prospective mediation to maintain the temporal sequence. So the mediator here is from year one, and where did the pointer go? And then the outcome is at year two. Oh. Oh, cool. Okay. All right, so we talked about normality. I looked at correlations. I won't go too much into them, but they were all significantly correlated. And then I conducted these mediation analyses. When I started the START program, I didn't know how to use R, so I ran them in SPSS macro, and then I've now ran them in R. Results are all the same. And like I said, these are prospective models, so our X variables are at baseline, our mediator is at year one, and our outcome is at year two. So this is just some sample characteristics. And this is meant to be a nationally representative sample. So it's just under half of the samples is female. There's good distributions of race, but majority white. And the parents' marital status, majority were from a married household. The parental education, most had a college degree or higher, but there was a good distribution in income ranging from less than $25,000 to over $200,000. So this is the model that we ran that we are going to be looking at. So for our X variable parental mental health at baseline, there's three different variables, internalizing, externalizing total problems. And then each of them are predicting one of these, each of these five impulsivity facets in a separate model. And family conflict is always our mediator, so it's 15 models total. And for each of those, because these were all prospective, we controlled for a whole bunch of covariates. We controlled for all demographics, sex, age, household income, parental education, and marital status. And having this large data set really allows us to control for all of these variables that may be of interest. We also controlled for the mediator, family environment at baseline, as well as the outcome. So for each facet of these and models that were predicting them, they were also controlled for. And because they're siblings in the ABCD study, we included the random effect of family ID. So I'll start going through the results. And first we'll look at internalizing problems as our mediator. So this is internalizing problem to negative urgency at time two. I'll just label them for the first one here. So we see that there's a significant total effect. And when we add family conflict in, the mediation is still significant. And for mediation analyses, what we talk about is proportion that's mediated through that mediator. So that's dividing the indirect with the total effect. And that gets us about 15% of the total effect of parental mental health that has on negative urgency. 15% of it is through family conflict. And we see a similar pattern when we look at, now I'm changing the Y variable. So now it's positive urgency at time two. And for that, it's 16%. Lack of planning at time two, about 18%, excuse me. And lack of perseverance at time two as well, about 12%. And cessation seeking was consistently not significantly associated with any of the predictors here. So that was the internalizing problems as the X variable. Now looking at the externalizing problems, we see a similar pattern, but the proportion mediated is a little bit more than was internalizing problems. And this would be expected since we're looking at conflict and externalizing problems. So for negative urgency, it was about 20% that was through family conflict, 19% for positive urgency, 23% for lack of planning, and 16% lack of perseverance. And sensation seeking was also not significant here. So we see the same pattern of findings across all three parental mental health. So this is, I just put the range of the proportion mediated there. The lowest number for all of them was lack of perseverance is the lowest number of that range. And the highest number for each of those was lack of planning. And as you see here, the externalizing problems has a higher proportion mediated as we'd expect. And then sensation seeking was not significant for any of those models. So what to make of all of this? One interesting takeaway for me is that difficulties in family functioning are an important social context for youth development that really do have an effect on these measurable outcomes, even at such a young age, because these are pre-adolescents. I'm excited to see, not that I'm excited to see the samples start using substances, but when they start growing up and we start seeing these behaviors, I'm excited to see how these will manifest in future analyses. But it points us to family functioning being a really important intergenerational mechanism that really connects parental mental health conditions with their children outcome. It's not all. There's a line of literature that's sought biological mechanisms of transmission, and this is just yet another way, an environmental mechanism. And this findings extends previous literature in this area that's largely focused on mothers and largely focused on depression by looking at the whole household, by looking at both parents and also looking at different mental health conditions to see that these map onto other conditions as well. And effective family interventions that have shown efficacy in other dimensions could be tested in this area to see if we can disrupt that progression to impulsivity or disrupt that progression to substance use. So it's important to point out that there were no results with sensation seeking. This re-invites some consideration about what we mean by impulsivity, which is a conversation I'm happy to have after this. But this might suggest that there might just be unique pathways that lead to different outcomes, even though there might be similar situations. And just a couple of limitations from this. There's a possibility that there's reciprocal relations here, that having a high impulsive child leads to more conflict that may lead to different outcomes. So I'm excited to model these cross-lag models in the future to disaggregate that. And then we used self-reports for all of these measures. So ABCD has a rich data set that they have biological cognitive tasks and even exploring the brain as a mediator. So yeah, looking forward to that. Yeah, thank you for your attention and thank you to the ABCD program and the START program that allowed us to do this. So yeah, thank you. Thank you. We could take one or two clarifying questions if there are any. Can you go to the mic, please? Oh, yeah. Thank you so much for your excellent presentation. I think it's very exciting to see that you're looking into this topic. I think it's absolutely very important. I had one thought about, have you considered to look into attachment patterns with the children? Because we know that there is, I think, a strong connection with attachment patterns and how they regulate or dysregulate their emotions. That's a really good question. I have not looked at that. So I don't know if you have thoughts, but I will definitely look and let you know. So I can just comment that within ABCD, we don't have direct measures of parent-child bonding or attachment. We might have some self-report measures. But there's another study that's just getting off the ground called the Healthy Brain and Child Development Study, HBCD, that starts at birth and is going to be following the kids until they're 9 and 10. And that's going to have direct measures of parent-child interaction that could be able to get it. Thank you. Where is the cursor? There it is. Hi, everyone. My name is Skye Bristol, and I'm a third-year PhD candidate at the University of South Florida in the College of Behavioral and Community Sciences in the Department of Mental Health Law and Policy. Today, I'm going to be sharing with you some of my research and findings on family conflict as a risk factor for problematic alcohol expectancy in the ABCD study. So a little bit of background on this topic and understanding why we should be concerned about alcohol use among adolescents. Alcohol use is one of the most commonly misused substances among adolescents, and it's a major public health concern in the United States. Approximately 1.8 million adolescents initiated alcohol use in 2021. So with alcohol use among adolescents, it increases that likelihood of alcohol-related problems and disorders into adulthood, and it's associated with a few different adverse outcomes, such as social problems and the misuse of other substances, which would be considered polysubstance use, such as marijuana, cocaine, as well as alterations in brain development with some long-term effects. So with alcohol use, it's also associated with poor neurocognitive performance, alterations in gray and white matter, brain structures, and discrepant functional brain activation patterns. This is important specifically for the gray and white matter because of the significant roles that gray and white matter play into the human body. So for gray matter, it controls movement, memory, and emotions, while white matter is important for learning and brain functions and communication between the different regions in the brain. Research has also established that alcohol expectancy is a key predictor of future alcohol use among adolescents. And what specifically is alcohol expectancy? Alcohol expectancy, it's the positive and negative attitudes of an individual's perceived outcomes when they consume alcohol. So positive expectancies, they may act as motivators, while negative alcohol expectancies may act as deterrents to alcohol use. Family conflict is also a risk factor of alcohol use, and the literature shows that family factors are associated with alcohol use in adolescents, such as parental monitoring, parent-child relationship quality, parental support, and parent-child communication. Family conflict, familiar environments may act as a framework for alcohol expectancy, such as parental drinking patterns. And that familiar environment is correlated to neighborhood quality and characteristics as well, such that family environments may be negatively correlated when residing in poor quality or deprived neighborhoods due to those different stressors and challenges that they may experience. With the neighborhood measures for quality and characteristics, that would include area deprivation index or the social vulnerability index. And for this specific study, we're going to be looking at the area deprivation index, also known as the ADI measure. Although past research has shown a link between immediate social environment, such as that familiar environment and alcohol expectancy, to our knowledge, there's been no research to actually examine the familiar environment that's conceptualized as family conflict. So overall, there has been substantial research on alcohol experiences, expectancies, and as predictors of future alcohol use. But there's a gap in that literature exploring those factors that contribute to the different expectancies. And there's also little that's known about racial differences and the direct impact of family conflict on alcohol expectancy. So for this specific study, it builds on some previous findings that I did in the beginning of the program to explore the interaction of family conflict and race to predict alcohol expectancy. And what we found was that higher family conflict predicted lower results in youth, basically being that they may be less afraid of the consequences associated with alcohol use, specifically among black youth. So we wanted to expand more on these findings and find out why is that. So this is just a model that shows the original research question of the first study. And the research question was, does the relationship between family conflict at time one and alcohol expectancy at time three vary by race and ethnicity while controlling for alcohol expectancy at time one, child sex at birth, age, and family SES? And based on the findings that the relationship between family conflict and alcohol expectancy differs for individuals of different races, which we'll discuss a little bit more specifically in the result, I wanted to explore if those differences could be explained by some other social factors, such as neighborhood quality, to examine how that neighborhood quality may act as a covariate for family conflict and alcohol expectancy, or if there's some other social factors that channel systemic racism, as systemic racism may have these distal effects that alter familial conflict and that vary by racial groups. So for the current study, this model shows that the two racial groups that were statistically significant, which were black and white youth, the next steps were to add in that area deprivation index for a three-way interaction and explore if those racial differences were dependent on neighborhood quality. So let's talk about the methods. For the data used for this study, it was the ABCD data set, and we used the linked external data from the 4.0 release. And the sample of this study for the specific research question included youth who had data on family conflict at time one, alcohol expectancy at both times one and time three, and area deprivation at baseline, which resulted in a total sample population of 6,231. For the outcome variable, it was alcohol expectancy, which was measured at time three. In alcohol expectancy, it's assessed using the adolescent brief version of the alcohol expectancy questionnaire. So it's a seven-item questionnaire, and it's a five-point Likert scale from strongly disagree to strongly agree, and it assesses youth expectancy about both the positive and negative effects on their attitudes of alcohol. So some sample statements would be alcohol helps a person feel more relaxed, feel happy, feel less tense, and can keep a person's mind off of mistakes at school or work, or alcohol can hurt how well a person gets along with others and makes people mean to others. For the family environment scale, family conflict, it was assessed using that family environment scale, which was already discussed by NEO. And then the new variable that was added into that new model, so that three-way interaction model was area deprivation index. An area deprivation index, it's part of the linked external data to the ABCD dataset, and it's a composite index of the census tract's socioeconomic disadvantage, and it's based on income, education, employment, and housing quality, using data specifically from the American Community Survey, or ACS. With the ADI variable, higher values of that index means that they experience greater disadvantage in their neighborhood. So specifically in this dataset, the raw data was a weighted sum from 0 to 125.8, and it's on the census tract level. But what I did was I converted it into percentiles so that we were able to get a more nuanced understanding of the relative positions in those different areas within the distribution of the ABCD dataset. For the control variables, it was sex assigned at birth, age, and months. Family SES, it was conceptualized using the highest level of parental education, and then alcohol expectancy at time one. And for the moderations, it was youth, race, and area deprivation index. I used SPSS and Stata 17 in order to analyze the data, and the different procedures that were conducted on the model was descriptive statistics, a correlation matrix, as well as that three-way multilinear regression to examine that relationship between family conflict, race, and area deprivation to predict alcohol expectancy among black youth and white youth. So for the results, the descriptive statistics, it's stratified by race and sex, and as you can see, black youth had the lowest mean scores for positive and negative alcohol expectancy and the highest mean summary scores for family conflict and area deprivation index. So this table is the first interaction multiple regression from the original research question among black youth. If the relationship between family conflict at time one and alcohol expectancy at time three varies by race and ethnicity while controlling for sex, age, family SES, and alcohol expectancy at time one. So with the interaction, I did it for each racial group, white, black, Hispanic, Asian, and other, and it was statistically significant for black youth, specifically for negative alcohol expectancy. So these findings, it shows that for every one standard deviation increase in family conflict for black youth, there was a negative alcohol expectancy score decrease by 0.074, and that's while controlling for sex, age, family, I don't know why it changed, there was a decrease in sex, age, family SES, and negative alcohol expectancy at time one. And then we found some opposite findings for white youth, and it was in positive alcohol expectancy. So what we found here was that for every one standard deviation higher for family conflict among white youth, there was a positive alcohol expectancy increase by 0.056. So with these findings for black and white youth being that only those interactions were significant and not the main effects, it suggests that that relationship between family conflict and race highlights that importance in considering those combined influence of family conflict and race. So for the three-way interaction between family conflict, race, and area deprivation, it wasn't statistically significant, but the individual predictors for the main effects of those three factors was statistically significant. So this differs from the interaction model of family conflict and black youth because it showed a negative relationship with negative alcohol expectancy, which may be described as a protective factor or that black youth may have developed a coping mechanism to the stress from family conflict. So what do these findings actually mean? Based on the theme of this year's conference to innovate, collaborate, motivate, charting the future of mental health, the practical significance of these findings for mental health and clinicians include identifying risk factors, utilizing multilevel interventions, cultural competence and cultural considerations, enhanced treatment planning, addressing health disparities, and collaboration with other professionals. So for risk factors, identifying those risk factors, family conflict, it's a known risk factor for mental health issues and understanding that interaction effect can actually aid in identifying those vulnerable populations and those vulnerable individuals to provide some guided targeted interventions for adverse outcomes as it relates to alcohol attitudes and use. For that multilevel intervention to effectively address those challenges and support vulnerable individuals like black youth, interventions need to happen at both the family and community level. So this would mean implementing different programs and services that promote positive interactions, they offer recreational opportunities and help to overcome negative effects of those disadvantaged neighborhoods. For cultural competence and considerations, it's crucial for actually enhancing treatment effectiveness by acknowledging and addressing the unique experiences and cultural factors impacting the population. And then you're able to create that safe and supportive therapeutic environment. As far as implementing enhanced treatment planning, you're then able to adopt a trauma-informed approach and recognize the influence of trauma that stems from family conflict and neighborhood disadvantage on the individual's mental health. To address health disparities, it's essential to advocate for equitable access to care and implement interventions that then target systemic factors that could contribute to unequal mental health outcomes among these different populations. And then the complexity of these findings, it shows that it's important for both doctors, psychiatrists, and other professionals to all work together to support those vulnerable populations such as black youth. And this means collaborating with social workers, community organizations, and schools to address these challenges in order to create a more comprehensive treatment and to address their concerns. So next steps for me would be to include examining additional systemic factors such as experience of racial discrimination as well as exploring some other statistical approaches such as structural equation modeling in order to address different measurement errors as well as increasing the accuracy of the analysis. I wanted to give a special thank you to Dr. Nora Volkow and NIDA for allowing me this opportunity. Thank you to Dr. Dowling and Dr. Johnson as well as my START mentors and my START cohort. Thank you. Time for one or two clarifying questions. Thank you so much for that great presentation. Something came to my mind. So I'm part of a community in Kansas City, Missouri, part of an African community that they're African Americans, black Americans, they're also Muslim, they also identify as Muslims as well. So a minority within a minority. And I'm wondering if one of the factors like spirituality or faith or religion is ever kind of considered because there are different ways that different groups of communities identify. So for this particular community, and there's a number of them, Somali, Sudan, Kenya, and they don't identify so much with, they identify a lot with faith in their parents coming over to the U.S. And so I'm wondering if that could be a consideration in these studies as well. How would it be similar or different when considering other minority communities that are people of color as well? I think that's a good point to consider because religion is part of that cultural aspect for youth. So I think for some future research, it could be considered as maybe a stratified model for different religions in order to see what those outcomes may be. That's a really good point. Thank you. I'll just add to that that in the ABCD dataset, we collect information about religious affiliation as well as information about acculturation for immigrant communities and perceived discrimination as Skye mentioned. So there are a lot of different dimensions to being part of these different communities that can be explored in the dataset. Thank you. Hello, my name is Stacey Ryan-Pettis. I am an assistant professor at Baylor University. Thank you guys for coming to our session today. The title of my talk is The Association Between Parental Monitoring and Externalizing Behavior, Mediating and Moderating Factors. There are some established associations in the literature that guide this work, and those associations include poor parental monitoring is reliably, consistently well-established in the literature as a risk factor for externalizing behavior in youth. There's also strong research that's established showing that deviant peer affiliation mediates this relationship between poor parental monitoring and externalizing behavior. There's also some research, though less well studied consistently, showing that inconsistent discipline is related to externalizing behavior in youth. And then there's also neighborhood crime. This variable tends to show a little bit more inconsistent results, but largely, usually, it seems that youth who reside in high-crime neighborhoods or at-risk neighborhoods, these relationships can be exacerbated. So what I was interested in is building a model from these established associations to look at more nuanced associations. So largely in the literature, current research kind of focuses on these variables independently or in simple mediation and simple moderation analyses. I was interested in building on the literature to bring in a second parenting variable. Parenting constructs can go together. We are increasing our attention to looking at multiple parenting variables in a model, but largely haven't been consistent with that. In my work with adolescents, I study kids with behavior problems. So consistent discipline and monitoring are important constructs. So how those interact are important and of interest to me. And so bringing that research in, along with trying to get a handle on why the influence of at-risk neighborhoods can bring about inconsistent results. So folding that into the model. So after looking at the literature, I built this conceptual model. And what you're looking at here is a model that proposes that neighborhood crime may moderate the mediation effect of deviant peer affiliation at each of the paths. At the indirect path and at the direct path. And then also hypothesizes that inconsistent discipline here may further moderate that relationship. And it seems like my pointer is already out of charge, sorry. For the purposes of this presentation, I'm going to present results that really focus on those two paths there. Path A and path B in the mediation analysis, just for the sake of time. Here I break down that model a little bit more so you can see conceptually a little bit clearer what's going on. In addition to showing the statistical model. So in the first model that you see there on the left, the conceptual model, I am hypothesizing a moderated, moderated mediation analysis there at the initial path. And the specific hypothesis is that poor monitoring will be associated with deviant peer affiliation and that this association will be stronger in higher crime neighborhoods. And inconsistent discipline will further moderate or intensify this association. The second hypothesis is that we will find the same mediation analysis as we typically do in the literature. The other side of the full model that you're looking at here is a moderated mediation view in that I am hypothesizing that residing in a high crime or higher levels of crime will moderate this relationship between deviant peers and externalizing behavior such that the relationship will be stronger in higher crime neighborhoods. For the methodology, I used the 4.0 data release of the ABCD study. I also used data from the ABCD social development study. This is a sub-study within the ABCD study that collects additional variables on kids at five of the sites of the ABCD study. It began about one year after the ABCD study began, so my kids in this sample have a mean age of 11. They're a little bit older. And I also used linked data from the uniform crime report. For selecting kids and caregivers for this study, they had to reside in the dwelling at both time points. Since I was collecting data from the ABCD study and then the sub-study, I wanted to try to get data on the same parents, same kids, living in the same home. So try to get them all basically try to establish the same assessment point. So the parent had to be the same parent reporting on the kid's behavior at both baseline for ABCD and baseline for ABCD social development study. The data set also includes twins and triplets, so I did a random selection of one twin and one triplet. That gave me a sample size of about 1,574. The sub-study is much smaller than the main study, and so with those additional criteria, it reduced the sample. And then the characteristics for caregivers and youth are there as shown. The average age for caregivers was about 41. For youth was 11 and a half boys. And for participating caregivers, we have about 88% women. These are the measures that were used to look at this model. All of them well validated, highly used in the literature to study, oh, there we go, to study parenting, the Alabama Parenting Questionnaire. I used the subscale deficient monitoring and inconsistent discipline. I've worded those in the direction of the scores, so higher scores mean more deficient monitoring, higher scores mean more inconsistent discipline. The deviant delinquent behavior items from the youth report, which was part of the Rochester Youth Study, was used, and higher scores mean more deviant peer behavior is reported. For both Alabama Parenting Questionnaire and the delinquent behavior scale, the youth reported on those. The CBCL was reported on by parents in the ABCD study. Higher scores mean more externalizing behavior. And then I used the external linked data, Uniform Crime Report, which was gathered at three-year average from 2010-2012. I used the process model macro, the process macro from Hays, Model 69, and to test the sample significance, I used the bootstrapping method. The product terms were centered, and I controlled for youth gender or sex assigned at birth, age and race. And to probe any significant interactions, I used one standard deviation above the mean mean and one standard deviation above, just keeping in mind since the data were centered, that means that the mean is zero. So for that first part of the model, where I was hypothesizing a moderated-moderated mediation, what we see here is that, oh, okay, so it's going in and out. I'm sorry. I did kind of color-code it. I know it's kind of hard to see. Poor parental monitoring was related to more deviant peer affiliations, that direct relationship, that standard in the literature. We continue to see that. There was a trend toward significance for that moderation to be, or for that direct relationship to be moderated by neighborhood crime levels, such that it was stronger in families living in more crime areas with higher crime levels. The three-way interaction, where we have inconsistent discipline and moderating that moderation, was not significant. So this hypothesis was partially supported. And here is a view of the interaction term. I have the slopes in a later slide if you guys are interested in seeing that. But basically what we see here is that we see a steeper increase. So those living in higher crime areas where the score is higher, if there's deficient monitoring, we see a steeper slope in then affiliating with deviant peers than when youth are residing in lower crime neighborhoods or at the mean. So deficient monitoring matters a whole lot, is what this means, if you're living in an area with high crime rates, in terms of affiliating with deviant peers. The mediation analysis were significant. I know I'm near out of time, so I'm going to go past this, but this is consistent with the literature. So then what this model is showing is that poor parental monitoring increases affiliation with deviant peers, which in turn increases externalizing behavior. The model did show that poor parental monitoring with this mediation analysis continued to predict externalizing behavior. So while the indirect effects were significant, which suggests a mediation, it also suggests that it doesn't fully account for the relationship and there are other variables to consider. So then this shows the other side of that conceptual model, which would be the moderated mediation hypothesis. And what you are seeing here is that there was a significant interaction between neighborhood crime levels and deviant peer affiliation in predicting externalizing behavior. So affiliating with deviant peers increased the likelihood of externalizing behavior, and that path was moderated by neighborhood crime levels. And there on the other side of the model, you see the interaction pictured for you there. So the red line are what we are looking at here then is that deviant peer affiliation, as that increases, and youth are residing in high crime neighborhoods, then there is a pretty steep increase in externalizing behavior. So kind of similar to the other interaction at this end. Now because we have significant mediation and the higher order interaction term was also significant, then one would assume or hypothesize that this model, we do have a significant moderated mediation analysis. So then for a little bit of reflection on the results, it is clear that parental monitoring is an important predictor variable in externalizing behavior and that it interacts with other contextual variables that are also important in predicting deviant peer affiliation and externalizing behavior. What the results also show is that other parenting variables may be important to consider as well. I didn't highlight the inconsistent parenting and residing in high crime areas because it wasn't a direct hypothesis, but that interaction was significant and we probably need to explore that a bit more, even though that higher level three-way interaction with deficient monitoring was not significant. The role of deviant peer affiliation in this model shows very strong. We have a moderated mediation analysis and we still continue to have a direct effect or some remaining variance that needs to be accounted for when considering deviant peer affiliation and the role in externalizing behavior. Deficient monitoring or, I guess, addressing monitoring is not going to completely change the picture for these youth. Peers are very important at this age. If you guys are working with families in the community, you probably know that you can do a whole lot with the family, but peers are a proximal, proximal, proximal part of the process and it's actually one of the key processes that we don't really have a good way of addressing in therapy other than just remove them from the environment and we can't do that all the time, unfortunately. So inconsistent discipline may exacerbate these relationships, but this model doesn't quite make clear how that could be just yet. So limitations of this research, this was all cross-sectional. It was my initial attempt at looking at these variables related in this way. There are other things I'd like to do with the model before expanding it to a longitudinal model, including separating out the racial groups and looking within to see if there are any differences in how these variables are associated within different race groups because we know parenting is highly contextual and highly cultural factors play a role. Minority youth are more likely to reside in high crime neighborhoods and that process is just different and so splitting that apart and then also introducing some of those other variables that might serve as a higher order moderating effect. I just want to say thank you for Drs. Johnson and Dowling for inviting us for this session and to the ABCD Start cohort and my mentor and my graduate students in the lab that helped clean the data. Do we have any questions for Stacey before we launch into the discussion? Okay, so parental and inconsistent parental discipline and monitoring issues, and we're looking at the relationships between that and the peer affiliation and the externalized behavior. So those two things, inconsistent discipline as well as just poor parental monitoring, to me these seem like symptoms and not a cause. These seem like a symptom of something. I think your discussion slide mentioned there's a, the discussion slide, it says, for example, there's complexity in monitoring due to multiple mediating and moderating factors. So I guess my question is, what is, so poor monitoring and inconsistent discipline are a symptom of something, something, what is that? What are those factors? And do, have you thought, you know? That's a good question. So clinically we try to address parents monitoring and discipline style. So more monitoring, more consistency in your discipline. Attacking both don't always work, especially in certain neighborhoods, at certain ages, and given what parents might be dealing with. If you try to intervene on too many factors, they get overwhelmed, they withdraw, and they don't engage. But oftentimes if we attack monitoring and get them to do that really well, it kind of generalizes and things get easier broadly. And so that was one of the reasons I was interested in bringing in consistent discipline was to just to see, well, to have the protective effects of monitoring on outcome, do we need to have consistent discipline? Or is it not related? So that was kind of one of the questions there. And you're absolutely right in that for symptom versus cause, like for poor parental monitoring, we, in this model, it's an independent variable, predictor variable. It could also actually serve as a moderating variable for the other end of the model. So, yeah, I agree it doesn't capture everything well. And we know that some parents are inconsistently disciplining their kids because they're stressed, they're overwhelmed, they can't be home, and so they can't keep track if the kid has followed through on the rules and all of those things. And so, yeah, it's a complex, yeah. Thank you. Can you look into that for me, please? Okay. You just got to keep pressing it? Okay, you got to be, it has to be line of sight? Okay. I was just curious. I'm not going to use it. Thank you, sir. Well, just to sort of the takeaway of all these different topics, these studies sort of illuminate the importance of social determinants. Some of the questions in the Q&A, and hopefully you guys will have more questions after this brief discussion piece, kind of speak to that. You know, where does it start? Are these symptoms? And some of the symptoms, some of the predictors are rooted in those social determinants. So this is kind of, these studies sort of illuminate the importance, the nuances, the complexities that must be taken into account. So these scholars explored these complex mechanisms by which these sort of sociological and social determinant factors impact adolescent health and behavior. And this is extraordinarily important, because we're getting at these important topics of social determinants, but also health disparities, and how do we do that? What are ways that we can creatively explore these issues of health disparities affecting these populations, which is extraordinary? So there are multidimensional social contexts, including the family context, the neighborhood context, and these are critically important. From Neal's work, we see that family conflict in this family context is extremely important, and this is an intergenerational mechanism, quoting his work, linking parental mental health to youth impulsivity. Again, his work underscores the importance of these contexts, the meso and the micro, but also the macro-level forces that influences those meso-level predictors, the symptoms. Skye's research indicates that neighborhood contexts may be important, and this may be a mechanism by which family conflicts influences alcohol expectancy. So we start to point all of these studies, and again, Stacey's looks at parenting, but may be exacerbated by poor parenting and monitoring in these high-crime neighborhoods, and of course, parenting and those dynamics being rooted within these social contexts and these social determinants as well. So all of these studies start to point toward the importance of thinking sociologically and thinking contextually about these issues. Family-level interventions and community-driven and action-oriented research to address not the individual level, but also truly the social context and the complexities that underscores these issues that we see. And these individual-level perspectives, when trying to understand these issues or when trying to treat particular health outcomes, may be insufficient. This work requires a more nuanced, complex sociological approach to treatment, to intervention, and to science and research. So I want to thank these scholars for presenting this remarkable work, and I want to talk to you a little bit more about the program that they represent. So you heard at the beginning, some folks came in a little later, but you heard in the beginning a little bit about the START program, Scientific Training in Addiction Research Techniques. This program allows us to recruit and work with, develop, learn from brilliant scholars in different fields. This is truly a recruitment, retention, and interdisciplinary program. We get to benefit from the brilliance, the expertise from diverse fields. We get to provide some service, some value in the ABCD day-to-day training, but without their unique perspectives, their experiences, their passions, their interests, we wouldn't be able to ask the right questions. We wouldn't have the right know-how to do this work. So this underscores the importance of what some folks call research training or research education programs. Essentially, how do we ensure that we have a competent, capable, scientific workforce to tackle the issues of the future? And programs like this are ways to do that. So again, you heard a little bit about the background of the START program tied to the ABCD consortia, but I want you to know that we fly in trainees from all over the country, different universities, and we fly them into the ABCD START facility in Vermont, and these scholars receive information on the study history, recruitment, data collection processes, et cetera. They participate, they learn intensive training program, and we invest in that experiential learning, we invest in mentorship, we invest in community building, we invest in giving them the tools, including a rich network and community by which they can lean on, giving them the tools, equipping them to tackle the challenges of the future, and ask the right questions. So I just want to say a little bit about their cohort. These are three scholars representing the first cohort of 12. Four pre-docs, four post-docs, four early faculty members. Together, these 12 scholars represent over a dozen different disciplines, 10 different universities, 9 different underrepresented minoritized groups, 6 different countries of origin of birth. As a cohort, they've achieved over 160 publications in high-impact journals, over 200 presentations at scientific meetings, and 12 original ABCD projects looking at health disparities broadly, but also tackling issues ranging from brain imaging to racial differences. These programs create well-trained communities of scholars equipped to address the social problems of today and of tomorrow. With that, I'm going to conclude my discussion piece and open up the floor for any other questions and discussion bits, any comments that you may have. We'd like to open the floor for any other questions or comments, particularly kind of tying these threads together. As Micah was saying, there are common themes about family conflict, the impulsivity, which again leads to the alcohol expectancies. I'm cutting in and out, aren't I? Mic check. And then the important role of the environment, so looking at area deprivation, looking at neighborhood crime and how that all kind of comes together. And to one point that Micah didn't say about the START program is not only was it a great opportunity to give these young scholars access to these tools, but we learned a lot from them, and as we do in these kinds of venues, in terms of are we capturing the right information for these youth to be able to answer these questions? What are the questions that need to be asked, and do we have the measures in order to do that? And we've really expanded upon this environmental component. So to your point about whether it's a symptom or a cause, I think a lot of the data sets that we've brought into ABCD that look at environmental causes, in addition to area deprivation or crime, really enrich and help us get at what are the root causes, and whether they may be structural causes that therefore result in family conflict or poor parental monitoring that are upstream of those things. So I just wanted to put that as a context, if anybody else had any questions or comments in that area. Yeah, okay Yeah That's the really broken that's the one with this this was a little better than Check 1 2 1 2 1 2 1 2 gotta use that voice you gotta use Check check check okay, I want to speak on the comment about religiosity and Islam The community you described in Missouri you said it was black American or was it African? Was it an African based community was it African American? Right yeah, okay, so they'll be okay and So his question earlier his point was have do we have the capacity to look at if? There is particularly when we're dealing with racial disparities particularly among black populations Racial disparities among blacks do we have the capacity to look at religiosity as a protective factor? specifically when you're looking at Islam versus other types of faith traditions or religious foundations Okay, well for any type There's a there's there's a good amount of science that shows that religiosity both as an institution and as faith Practices a strong protective factor in the african-american community But we know less much less about the differences specifically Islam. We know anecdotally there's been Narratives that Islam in the black community has been highly protective against crime addiction poor health risky behavior but that's a You know that's a really limited body of research that we have But we do know in general religiosity mostly looking at the Christian faith But we do know that it's protected So I just want to comment on that and I just want to let you know that I think that's a really interesting study Unfortunately, we don't have the data But it'd be great if we can get the data and analyze that to see how protective Some of these faith traditions are in these communities. I appreciate that comment I'm sorry, I'm interested in this area. I can only speak anecdotally, but I've also seen qualitatively and observationally. And I think you mentioned, I think what we'll find is the underpinning is the community. So the faith itself builds a very strong community. And not just about going to worship and tradition, it's about community. And I think that's one of those powerful protective pieces. And so what we learn is not that we should convert all these youth to Islam. I mean, maybe, maybe not, right, I don't know. But how do we replicate that sense of community? And how do we replicate that, what it is, is a commitment to a way of life. It's not just about a tradition, it's about a commitment to a way of life. And how do we replicate that? So what we learn, anecdotally only, again, is that perhaps building these cohesive, tight-knit, healthy communities where elders of value, you still have structure, is another way to foster resilience in the context of extreme disadvantage. Because I have seen thriving Muslim communities, black and otherwise, who thrived in the context of extreme disadvantage and extremely difficult circumstances. So if I could just build on that, you know, I think in ABCD we do have measures of community risk and protective factors. We do have measures of religiosity. But one of the drawbacks of ABCD is that because it's this large, diverse cohort, and we're asking so many questions, it's really hard to delve very deep in any one area. And I think one thing that we miss from ABCD that we hope other studies will build on things coming out of ABCD to create is to be able to go deep in certain communities. So like the goal of ABCD was to have a cohort that represented the diversity of the country, but you can't go in a lot of depth there. But if you were to then take some of the measures in ABCD and enhance them to look in specific communities that you know are suffering from the disadvantages, but also thriving, then you might be able to create a profile, right, that could be extrapolated to other communities. So I think one of the things that I would like to see happen is for people to go start with ABCD and then go beyond that to develop other cohorts that are community specific. Because we know that each of the populations that are within the cohort have their own profiles that have positives and negatives, and we won't really understand it until we delve deep in those communities to understand them. And then pull back and see if we can take those lessons learned to other communities. And so that's kind of a next order stage that we'd like to see with this kind of work. And actually, I'll give another plug since I'm up here with the mic. So I mentioned briefly earlier this healthy brain and child development studies. So one of the challenges with ABCD was, you know, we were particularly interested in substance use and mental health outcomes when we launched ABCD. And for that reason, we started when the youth were 9 and 10 years old so that we would see them transition to substance use in the development of mental disorders relatively soon. What that didn't give us is those first 10 years of life. And we know that some of the factors that we're talking about today, those begin having influences much earlier in life. And we can capture that retrospectively. But that's clearly not as good as if we were to do it prospectively like we do for other measures in ABCD. So we are launching, this should begin recruitment soon, this healthy brain and child development study, which is enrolling mothers when they are in the second trimester of pregnancy and then following them and their children for the first 10 years of life. And it's specifically designed to oversample substance using pregnant women and then people from matched socioeconomic backgrounds, as well as having a kind of population-based cohort so that you can really drill down into those early life experiences that can influence later trajectories and do so in a prospective way. So I think a lot of the questions that we talk about in ABCD or a lot of the studies that are coming out of ABCD where we're seeing these differences, we're seeing the impacts of some of these environmental factors, but we don't really know when they're initially causing. The goal with ABCD is to start young so that we could look at brain development before they start using substances and see that, but we don't know where it started, right? And so I just want to put that out there as something that's going to be coming down the road that we will be able to look at some of these early life factors and how they contribute to these different trajectories later in life. Taking something from the other end of the perspective, I work with a bunch of 16, 17-year-olds who have already been through the judicial system or have a short-term residential treatment, short-term meaning six months to a year, and the question is always, these kids are doing very well at that point, but how would they do if they returned to their community, and which one should be permanently elsewhere? I don't know whether you have some thoughts about what you look for in the individual late adolescent at that point to say, well, what's their resilience, what's their ability to returning, and when returning to a community that inspired their acting out, how are they going to be able to resist that? I appreciate that question. It's a hard one to answer, as you know, and I know for the same reason that you know it's hard. That's my clinical population as well, kids in the juvenile probation system who are using, oftentimes removed from their homes and so forth. That's a hard question to answer for many reasons. Oftentimes kids lack the insight to really kind of go through therapy in a way that will help them to adjust in more healthier ways once they get back home, but then also they've grown up in a system, their household, their neighborhood, and have established that coercive interaction pattern with family and with friends and with teachers to get their needs met, quite honestly, and those are very triggering interactions, and so even after a good course of therapy, going back into the environment where the others around them have not received therapy can be very triggering, even if they do work really hard and make a lot of gains. It's difficult, as you know, to treat these kids. A lot of our treatment approaches they reject and so it takes a lot of creativity for them to accept them, but what we tend to find is that kids who can grow in their psychological flexibility do a little bit better when they go back home, so they are able to regulate their emotions a bit more. They're able to think of the gray, not just the white and the black, and they are able to find a protective caregiver in the environment, not always their parent or their immediate guardian, but it could be a teacher, some protective element we see the kids do a little bit better, but I also tell the students that I supervise is that we're oftentimes planting seeds because the environment is so tough for them, we may not see the results right away, but we could have very well charted a different course for them where they are more likely to grow out of their problem behavior in their early 30s, maybe not right now, maybe not tomorrow, but maybe in their early 30s. I don't know if that helps any. Well, I mean, it's interesting how many of these kids choose not to return to their environment. Oh, yes. Yeah. Yeah, we see that too. Yeah. It's a cry for help. My students are often, I supervise clinical doctoral students, they get really worked up when they have to make a CPS call, but these families, these kids are very, very smart. If you are learning information that deserves a CPS call, it's because they want you to make a CPS call. They want to be removed. They want help, basically, or they want their parents to get help so that they can be in a safe home. Yeah. They're really smart kids. If I have your permission to add on a little bit. If this mic keeps cutting in and out, I'm just going to scream. So I want to just reiterate the question here, rooted in, obviously, years of experience. The comment and the discussion is around this idea of when you have youth that come from extremely difficult environments, the types of poor neighborhoods that produce a lot of these issues we've discussed, addiction, behavioral health, they go into this system. Many of them do better for the simple fact that they have basic needs met, water, clean water. They're removed from violence in the household, violence in the community. Some of them have structure for the first time in their lives. Some of them have mentorships and relationships for the first time in their lives with correctional officers and things like that. And many of them, for the very first time in their lives, they end up meeting people that are called dentists, psychologists for the first time in their lives. Not that the juvenile justice system is a pleasant place to be. It's just emphasizing how difficult these neighborhoods are. And his question is, what becomes of these youth when they have to get reentry back into those communities? And this is a major issue. One of the problems is this idea of reentry programs is relatively new in the past decade or so. We've thought about this very question as far as the juvenile justice system, the criminal justice system. What are we doing when we're throwing people right back into the same environments that lended them here? And what is our responsibility as far as facilitating reentry into their communities? So that's one of the problems. This idea of reentry is fairly new. The second part of the problem is a lot of these issues, you start to, when you want to deal with these issues, you get into this realm of social change and social justice. For example, you talked about so many kids want to leave their communities. That's something that comes up a lot in my work. You know, how do I escape my environment? Now this becomes a problem about housing. Their community is probably already being gentrified. If they want to go to a nicer community or a less violent community, it's probably going to cost a ton of money. And many of them don't have mechanisms to do that. So this idea of being trapped in the environment is a serious issue. So the first thing we probably need to do, I would say, is develop reentry programs for youth that are entering the system so they can have a positive transition back into the community. But also, secondly, intervention needs to think about this social context. We need to think about how to improve these communities in the first place. So this is where I start to talk about action-oriented research and community-driven research, research that truly partners with the community to change the conditions within that community and empower community members using data, using evidence-based practices and partnerships in universities. But that's hard. That's tough. It can be expensive. It's not as popular, as integrated within the scientific field as it should be. So the next step, the most immediate step, is what Stacy talked about. We could do the best we can to equip these youth with some skills to survive and make healthy decisions and to heal. One way would be exactly what she said, how to regulate your emotions, some of those social-emotional skills, but also the family. So if we could sort of create protective, if we could transform, give the individual some tools and transform that household into a more protective environment as opposed to one associated with risk, then we can at least give them a chance to fight and dream and have optimism as they deal with the challenges in their communities. Thank you. Thank you, Stacy. I'll just add one more thing to that. One of the well-established treatments for kids on juvenile probation engaged in heavy substance use, risk of being removed from their homes is multisystemic therapy, brief strategic family therapy, functional family therapy. I'm not sure if you guys have heard of those particular treatment packages, but one of the rate-limiting factors in getting those out to the community is that they cost a lot and oftentimes requires grant funding from the Office of Juvenile Justice Department or local, state, and government. So participating in getting services into the community that way by partnering with universities to write a grant to get the funds to then start a program that's very common to get those started in that way, or state and local governments. In Texas, where I'm from, there's a new initiative to increase multisystemic therapy in the communities, but we're having a really hard time getting service providers on board with learning these additional tools to help kids. So yeah, lots of kind of grassroots efforts in that way as well. I'll just say that to speak to the bigger issues that Micah was just talking about, one of the goals of the ABCD study is also to develop that science that can inform some of those policy changes that are really needed in communities in order to provide the resources that communities need and families need in order to thrive. And there was a recent study that came out of ABCD that was looking at disparities in both brain volume and mental illness between low-income and high-income families in states that had high cost of living, between states that had high cost of living and had Medicaid expansion, had strong TANF programs and the Earned Income Tax Credit. And they found that having those anti-poverty programs reduced those disparities between high-income and low-income families. So there are policy changes that are emerging from some of this work or indications that these types of policies can improve outcomes that we are hoping will then be taken by policymakers to help make some of those changes. I think we're getting down to the end of the session. Are there any other thoughts as we're getting ready to close or any other comments or questions from the audience? Go for it. Have we thought about, so there's obviously expensive and time-consuming types of solutions. How about structures that are already in place? I see a church on every block, right? There are a lot of faith communities. Have we thought about training clergy, training congregational care leaders in, maybe they won't be able to take a two-year master's, or maybe they will if they're interested enough, but maybe using the institutions that are already there and to equip them to like, hey, the community comes to you. They can find mentorship. If we can train some faith community leaders, they can perhaps give back to their community by, first of all, education, awareness, and then giving them a purpose. We talk about a place, people, and purpose. We talk a lot about relationships and communities and a safe place for healing. We don't talk enough about purpose and the existential stuff. Churches can do that. Can we make a program to train faith leaders for reentering back into the community? Yes. We can, I think. We call that task shifting and implementation research, which is just giving a new task, a different kind of job and role to an established person in the community. There's currently a research team at Baylor who is doing that exact thing with clergy, giving just very basic kind of skills and information to help serve the local community because absolutely there's not enough mental health services around the ones that are around. There are lots of barriers for families to make it into treatment. Providers may not look like them or there are just a lot of barriers and people want to see themselves reflected in the office and in their provider, rightfully so, and just building in services where families are already going, like in the pediatrician's office as well. There is a big push for that. It takes a lot of community building, a lot of relationship building, which is another reason why a program like the ABCD starts program is ideal because then bringing in scholars that can then go back into the community to help serve and keep them in the research industry is very important to help diversify the field to get these things out. I just wanted to share, I work in remote Alaska, primarily serving Alaska Native people, and we actually use, since we have such a dearth of providers, village-based counselors and paraprofessionals, which we call clinical associates, so some of them have their bachelors but many of them don't. I believe the requirement is an 8th grade education, but we train them to provide kind of like psychoeducation and really simple counseling type skills. So they can't do therapy, but they can provide that service so we can reach more people since we're so limited. Yeah. I was going to suggest that not all families in the community are involved with church, but everybody goes to a hairdresser. I can't speak to diverse groups, but I know when you're talking about black and Latino communities across the country, they are doing just that. The church is playing a role in many of the issues we're talking about when it comes to juvenile justice, recidivism, and addiction. There's all sorts of examples of cool work where the clergy is actually leading the therapeutic efforts and the outreach in their communities, but there's a lot more room for growth. I mean, I don't think it's as widespread as it should be, and I don't think that was just a joke. I think that he knows that there's a lot of folks that the barbershops are playing a larger role, too, in trying to do stuff around mentorship and outreach. A lot more could be done, specifically in the black and brown communities, with using the barbershops and using the churches. More could be done. So I'd just like to thank Micah Johnson for starting the START program, which has really been hugely beneficial, I think, to ABCD and a nice start that we hope is going to bring in many, many more underrepresented scholars into science and to do this work, because as you've heard today, they really bring a unique perspective to the work, which enhances all of the research that we do. And then, of course, to our three scholars that came and presented their work today, and thank you for joining us.

Adolescent Development

ABCD Study

Environmental Impact

Substance Abuse

Mental Health

BIPOC Scholars

START Program

Family Conflict

Youth Impulsivity

Parental Monitoring

Neighborhood Quality

Community Research