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Yale Psychiatry Grand Rounds: May 20, 2022

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Yale Psychiatry Grand Rounds: May 20, 2022

May 20, 2022

Lustman Awards

Tanner Bommersbach, MD, MPH; Dan Tylee, MD, PhD; Terrell Holloway, MD; Zach Harvanek, MD, PhD; and Nientara Anderson, MD, MHS

ID
7864

Transcript

  • 00:00Thank you Trisha and and welcome everybody.
  • 00:04The and welcome to the
  • 00:07Lussman Award celebration.
  • 00:09The Lussman Awards are just a wonderful.
  • 00:13Opportunity to acknowledge the incredible
  • 00:16work done by young scientists in
  • 00:19the Department of Psychiatry and the
  • 00:21Residency and Fellowship programs.
  • 00:23It's also a great time to celebrate
  • 00:25the the career and accomplishments
  • 00:28of Seymour Lassman and and Doctor
  • 00:30Pittenger will describe his
  • 00:32background in just a little bit.
  • 00:35But the Lussman family plays a
  • 00:37special role in the hearts of
  • 00:39the Department of Psychiatry.
  • 00:41It's a family that's been involved,
  • 00:43connected to the department
  • 00:44across 3 generations,
  • 00:46and I particularly want to add
  • 00:48my thanks to the the things that
  • 00:50I know that that Chris and and.
  • 00:53And perhaps others will express
  • 00:56to Susan and Jonathan Katz,
  • 00:59who've been really incredibly supportive
  • 01:02of our ability to continue the lesbian
  • 01:06awards over the last many years.
  • 01:09The last man awards have really emerged
  • 01:11as one of the nation's leading awards
  • 01:14for research done in the residency.
  • 01:18And if you go back over the list of honorees,
  • 01:21you'll see many people who
  • 01:23have emerged as leaders in the
  • 01:25Department of Symmetry here at Yale.
  • 01:27But really,
  • 01:28all across the country and and people
  • 01:32who've had whose impact has really.
  • 01:38Been measurable on the overall effort
  • 01:40to relieve the the public health burden
  • 01:44of psychiatric disorders and addictions,
  • 01:47so this is really an incredibly
  • 01:49exciting and special day and I
  • 01:51look forward to the presentations.
  • 01:53I just wanted to add one
  • 01:55thing before I close.
  • 01:56There's no grand rounds next week due to
  • 01:59more because of the Memorial Day holiday,
  • 02:01but the following Friday,
  • 02:03June 3rd will have the state of the
  • 02:06the state of the department address.
  • 02:08So I hope that we'll see everybody there
  • 02:11for the state of the department address.
  • 02:17Which is also another great
  • 02:18opportunity to reflect on the
  • 02:20year that we've all been through.
  • 02:22So without further ado,
  • 02:24let me introduce Doctor Chris
  • 02:26Bittinger who will get us underway.
  • 02:42Chris, you're muted.
  • 02:56There we go. You think that after two
  • 02:58years I have this figured out. That's OK.
  • 03:04So now I just need your
  • 03:05screen back slides back.
  • 03:19And multitude of slide decks,
  • 03:22it's all well. There we go.
  • 03:26Good alright, let me try again.
  • 03:30Welcome everyone.
  • 03:31It's a pleasure to have you all join
  • 03:33us for this year's last minute awards.
  • 03:35As John said,
  • 03:35this is really a special day in
  • 03:37the life of the department and one
  • 03:39of my favorite grand rounds of the
  • 03:41year as we celebrate our commitment
  • 03:43to training and the spectacular
  • 03:45work of some of our of some of our
  • 03:48trainees as well as our commitment
  • 03:50to mentorship and the participation
  • 03:52of mentors in the success of
  • 03:54these trainees and the history.
  • 03:57Of of Seymour Lessman,
  • 03:58who was a giant in in our department
  • 04:01and then the Child Study center years
  • 04:03ago and whose family has generously
  • 04:05supported this award since 1973.
  • 04:08As an in honor and continuation
  • 04:11of his legacy.
  • 04:13So, Seymour Lessman,
  • 04:14for those of you who aren't
  • 04:16familiar with him from previous from
  • 04:18previous lesson award celebrations,
  • 04:20had a remarkable career.
  • 04:22He served in the Army in World War Two.
  • 04:24Then he obtained his PhD in psychology
  • 04:26from the University of Chicago in
  • 04:28his MD at the University of Illinois.
  • 04:31And while at the University of
  • 04:33Illinois he became interested in the
  • 04:35Physiology and behavior of newborn infants.
  • 04:37This was a time when the field was rife
  • 04:39with arguments about nature versus nurture,
  • 04:42which I think we've long since transcended.
  • 04:43Because of course,
  • 04:44all interesting things.
  • 04:45Or both, but at that point this was a very,
  • 04:48you know, active point of of
  • 04:51disagreement and conflict in the field.
  • 04:53And that became the focus of
  • 04:56doctor Glassman's work.
  • 04:57He came to Yale in 1955,
  • 04:59where he completed psychiatry,
  • 05:01residency and Child fellowship,
  • 05:03and he joined the psychiatry faculty in 1962.
  • 05:06And then two years later,
  • 05:08he was promoted to the rank
  • 05:10of full professor.
  • 05:11I can clearly remember when I was
  • 05:12a trainee and John would make that
  • 05:14statement that he was promoted to full
  • 05:16professor just two years later and
  • 05:17John Pier out, all of us and and say,
  • 05:20let that be a model for you, but.
  • 05:23But truly remarkable remarkable
  • 05:26achievement on the faculty.
  • 05:28He was a dedicated teacher,
  • 05:29gifted clinician,
  • 05:30and a careful and creative scientist.
  • 05:32He became increasingly interested in
  • 05:35problems of impulse control and adolescence,
  • 05:37and among numerous other contributions.
  • 05:39He was a key member of a group of
  • 05:41scholars together with Al Solnit,
  • 05:42Anna Freud and Joe Goldstein,
  • 05:44who wrote a landmark text in the
  • 05:46field of child maltreatment beyond
  • 05:48the best interests of the child.
  • 05:51See,
  • 05:51we're lussman died tragically at
  • 05:53a young age in a boating accident
  • 05:55in the early 1970s and one of the
  • 05:57leading lights in our in our field was
  • 06:00taken from us and shortly thereafter in 1973.
  • 06:03His family created this award,
  • 06:05and it's been given continuously
  • 06:07every year since 1973 with I,
  • 06:08I think,
  • 06:09puts us at 49 years.
  • 06:12As John said,
  • 06:13if you look at the the
  • 06:15plaque of past winners,
  • 06:16you'll see quite a few
  • 06:18leading lights of psychic.
  • 06:19If you're both at our institution
  • 06:20and across the country,
  • 06:21and so are our awardees today are
  • 06:25joining an illustrious company.
  • 06:28As I said, we're not only
  • 06:30celebrating the awardees and the
  • 06:32accomplishments of our trainings here
  • 06:34in the Yale Department of Psychiatry,
  • 06:36but also of their mentors.
  • 06:38None of us succeed without the
  • 06:39support of our of our mentors.
  • 06:41They're modeling.
  • 06:42You know financial support, their guidance,
  • 06:45and so we're going to have each of our
  • 06:47awardees introduced by by a key mentor and.
  • 06:52And while the focus today is on
  • 06:54the trainees and their work,
  • 06:56we we applaud the mentors as well.
  • 06:59So with no, I'm sorry I should just be.
  • 07:02I've already thanked the the Lussman family.
  • 07:03I also want to thank the
  • 07:05Lussman Awards Review Committee,
  • 07:07group of faculty who joined us,
  • 07:09YOUNGSTON show Marina Picciotto.
  • 07:12Wow, if I just rattle them off
  • 07:13the top of my head,
  • 07:14I'm going to leave someone
  • 07:15out and that would be upset.
  • 07:16But just I appreciate the Group of the
  • 07:19Group of faculty who helped us review
  • 07:21these for the last several years.
  • 07:23So without further ado,
  • 07:25I will invite Bob Rosenheck guns to
  • 07:28introduce our first winner of us been
  • 07:31awarded first prize winner for 2022.
  • 07:34And that's the wrong one. All right?
  • 07:40So while we go ahead, go ahead.
  • 07:42I'm working out the technical.
  • 07:44Yeah well, while we fiddled with the slides,
  • 07:47I very happy to introduce Tanner
  • 07:49boomers back from Grand Forks, ND.
  • 07:54And of course, he has been a superstar
  • 07:57who published 15 papers as a resident.
  • 08:01And worked very closely with me and
  • 08:04a group that was Co led by Greg Lee,
  • 08:07who's a young investigator.
  • 08:08All of you should get to know.
  • 08:13Tanner, I thought his magnificent
  • 08:17productivity was a product of coming
  • 08:20to Yale, but in fact he was the superstar
  • 08:24before he came to Yale, graduating
  • 08:26summa *** laude from college and getting an
  • 08:30MPH from Hopkins and working with a number
  • 08:33of leading lights there.
  • 08:36His interests are broad.
  • 08:38His curiosity of is boundless,
  • 08:40and what I particularly would emphasize
  • 08:42is the not just the number of papers,
  • 08:46but the fact that he has emerged
  • 08:48as a very talented writer.
  • 08:50And I think we often don't recognize
  • 08:53how important it is to cultivate the
  • 08:57skills of clear scientific writing.
  • 08:59And he's become just a pleasure to
  • 09:02to read his work as it's developed.
  • 09:06And so without.
  • 09:08More ado, let me hand it over to Tanner,
  • 09:10who will present his paper that
  • 09:12appeared in JAMA Psychiatry.
  • 09:16Well, thank you so much Doctor
  • 09:19Rosenak and I just want to thank Bob.
  • 09:22You know, despite what he
  • 09:23says coming into residency,
  • 09:25I knew very very little about about
  • 09:27research and and most of what I've learned
  • 09:30can be attributed to Doctor Rosenak,
  • 09:32who's who's just been such an amazing
  • 09:35mentor to me and I really could
  • 09:37not have asked for a better mentor
  • 09:39when I came into to residency.
  • 09:41I also want to thank Gregory as.
  • 09:44Thompson, our senior author on this
  • 09:47paper who's been a friend and a mentor
  • 09:50to me over the last couple years,
  • 09:52especially.
  • 09:52And I also just want to thank
  • 09:54the the Lossman Foundation.
  • 09:55It was fun to hear more about about
  • 09:58Doctor Lossman for for their support
  • 10:00of of resident research and giving
  • 10:02us really the opportunity to share
  • 10:04our research with the department.
  • 10:06So thank you.
  • 10:08Turning to the the title of our paper
  • 10:10over the next 15 or 20 minutes or so,
  • 10:12I'm going to be talking about recent
  • 10:14trends in the national suicide attempt
  • 10:16rate and specifically looking at.
  • 10:18The mental health utilization
  • 10:20of individuals who attempted
  • 10:22suicide from 2008 to 2019.
  • 10:25Suicide prevention has been an interest
  • 10:28of mine since since medical school,
  • 10:31and I think it's one of not only the greatest
  • 10:34challenges facing the field of psychiatry,
  • 10:36but also one of our greatest
  • 10:37current public health challenges.
  • 10:38And so I think it's a really important
  • 10:40topic that we need to continue to
  • 10:42invest research in next slide, please.
  • 10:47And the reason that it's such a challenge
  • 10:48for us currently is over the last two years,
  • 10:50we've seen a pretty precipitous rise
  • 10:52in deaths by suicide in our country.
  • 10:55Our national suicide attempt,
  • 10:56our national suicide rate over the
  • 10:58last two decades, has risen by 35%,
  • 11:01and that's in the context of declines
  • 11:04that we saw in the 1980s and the 1990s.
  • 11:07It's also very concerning because
  • 11:09over the last two decades,
  • 11:11other developed countries across the world,
  • 11:13especially countries in Europe,
  • 11:14have actually seen a decline
  • 11:16in their suicide rate.
  • 11:17While we've continued to see
  • 11:19a pretty steady increase.
  • 11:22Next slide,
  • 11:24please.
  • 11:25And when we're thinking about
  • 11:26suicide prevention,
  • 11:27it's not only important to
  • 11:28look at deaths by suicide,
  • 11:30but it's also important to look at
  • 11:32trends in all types of suicidal
  • 11:35behavior across the suicide continuum.
  • 11:37So this was data that was just
  • 11:39released by Samsa for last year.
  • 11:40For year 2021.
  • 11:41You can see at the bottom of the pyramid
  • 11:44here at 12.2 million adults are reported
  • 11:47serious thoughts of suicide last year,
  • 11:49and that corresponds to almost
  • 11:515% of the total US population,
  • 11:54one in 20.
  • 11:56Individuals 1.2% of the total US
  • 11:59population reported making suicide
  • 12:01plans in the last year .5% about 1.2
  • 12:04million reported suicide attempts
  • 12:06and a much smaller fraction of those
  • 12:09individuals died by suicide, about
  • 12:1146,000 so still way too high of a number.
  • 12:15Next slide, please.
  • 12:19And so while the majority of
  • 12:21individuals who attempt suicide
  • 12:22don't go on to die by suicide,
  • 12:24we know that suicide attempt
  • 12:26continues to remain the strongest
  • 12:28predictor of future suicide and is
  • 12:30an important group for us to study.
  • 12:32Longitudinal studies indicate that
  • 12:33anywhere from 7 to 13% of individuals
  • 12:36who attempt suicide will go on to
  • 12:39die by suicide in their lifetime,
  • 12:41and the majority of these deaths
  • 12:43estimated anywhere between 70
  • 12:45to 80% tend to occur in the 12
  • 12:47months after a suicide attempt.
  • 12:48And so we know this year after a
  • 12:51suicide attempt is a really critical
  • 12:53period of time for us to intervene
  • 12:55and prevention strategies really
  • 12:57rely on individuals receiving some
  • 12:59sort of mental health intervention
  • 13:01after a suicide attempt.
  • 13:03Yet we know that a fairly large
  • 13:06amount of individuals don't actually
  • 13:08receive services in the year after
  • 13:11a suicide as a suicide attempt,
  • 13:13and we don't know this percentage very well.
  • 13:16We don't actually have a
  • 13:17great understanding of what.
  • 13:19Percent of individuals actually
  • 13:21receive services in proximity to their
  • 13:25suicide attempt because most of the
  • 13:27studies that have been done on this
  • 13:29topic have been done either in fully
  • 13:31insured samples or in individuals who
  • 13:32receive care after a suicide after a
  • 13:35suicide attempt because they present
  • 13:36to emergency departments or they
  • 13:38get admitted to an inpatient unit.
  • 13:40Several studies that have been done
  • 13:42in a large HMO population of a fully
  • 13:45insured sample show that about 40%.
  • 13:49Suicide Attempters had a healthcare
  • 13:51visit within the week before
  • 13:53their attempt and 95% had a visit
  • 13:55within the preceding year.
  • 13:56Yeah,
  • 13:57like I said,
  • 13:57we know that a large percentage of
  • 13:59individuals actually don't receive
  • 14:01care in proximity to their attempt
  • 14:03and and looking at veterans and
  • 14:05the Veterans Health Administration
  • 14:06is a good example of this.
  • 14:08So in 2018 it was estimated that 63%
  • 14:11of veterans who died by suicide didn't
  • 14:14have an encounter within the VA in
  • 14:16the 12 months prior to their death.
  • 14:19And so.
  • 14:20An alternative way,
  • 14:21and perhaps a more accurate
  • 14:23approach to really understanding
  • 14:25how often individuals who attempt
  • 14:27suicide are receiving services
  • 14:28in proximity to their death,
  • 14:30maybe to use population based survey
  • 14:32data of individuals who are insured and
  • 14:35individuals who aren't individuals who
  • 14:36got care after their suicide attempt,
  • 14:39and individuals who have gotten no care,
  • 14:41and so that was the approach that
  • 14:43we wanted to take in our study.
  • 14:45So, next slide, please.
  • 14:49So this was the title of our paper that
  • 14:51was published this spring and we were
  • 14:53interested in looking at 4 main issues.
  • 14:56The first is what are recent trends in
  • 14:58past year suicide attempts from years
  • 15:002008 to 2019 among adults in the US.
  • 15:04We also wanted to know what risk
  • 15:06factors were associated with increased
  • 15:08suicide attempts over this time period.
  • 15:11Third, we wanted to understand that
  • 15:13amongst individuals who attempted suicide,
  • 15:15what were their self reported
  • 15:17trends in using mental health?
  • 15:18Services during the year of their
  • 15:20attempt and finally of individuals
  • 15:22who didn't receive services.
  • 15:25We wanted to know what were their self
  • 15:28reported barriers to receiving that care.
  • 15:30Next please.
  • 15:32So just a quick note on our method.
  • 15:34So we used a population based nationally
  • 15:36representative survey data from the
  • 15:38National Survey on Drug Use and Health,
  • 15:40which is a population based survey that's
  • 15:43administered annually by Samsa and it
  • 15:46administers computer questionnaires to
  • 15:48individuals at their household addresses,
  • 15:51or delivers in person questionnaires
  • 15:54by a trained interviewer,
  • 15:56and so our sample included adults
  • 15:58over the age of 18 from 2008 to 2019.
  • 16:01And the Nysda assesses suicide attempts
  • 16:04with a relatively simple question.
  • 16:07It asks in the last 12 months,
  • 16:09did you try to kill yourself?
  • 16:10So in this way it really tries to get
  • 16:12at suicide attempts with fatal intent
  • 16:14and it tries to screen out other types
  • 16:17of suicidal behavior such as non
  • 16:18suicidal self injury and this resulted
  • 16:20in us having a pretty large sample
  • 16:23of close to half a million adults.
  • 16:26Next slide please.
  • 16:28And so for our first question are
  • 16:30what are recent trends in past year
  • 16:33suicide attempts from 2008 to 2019?
  • 16:35The bottom line here is we found that
  • 16:37the suicide attempt rate increased
  • 16:40from 481 per 100,000 individuals to
  • 16:43564 per 100,000 individuals which
  • 16:45corresponded to about a 23% increase
  • 16:48when we adjusted for other changes in
  • 16:50the population over this time period.
  • 16:53And you can see the pretty precipitous
  • 16:55rise in the graph here from 2008 2009.
  • 16:58All the way to 2018-2019.
  • 17:02Next slide, please.
  • 17:04Secondly,
  • 17:04as I said,
  • 17:05we were interested in what risk
  • 17:07factors were associated with this
  • 17:09increase in suicide attempts and
  • 17:10we found a significant increases
  • 17:12in several different subgroups,
  • 17:14but especially among the unemployed,
  • 17:16the unemployed,
  • 17:17their suicide attempt rate more than
  • 17:19doubled over the course of the study.
  • 17:21We also saw a pretty large increases
  • 17:23among young adults aged 18 to 25
  • 17:26individuals with substance use
  • 17:28disorders and individuals who
  • 17:30were not currently married,
  • 17:32and after we tried to control for all these.
  • 17:34Factors and put them all
  • 17:35into a multivariate model.
  • 17:37We found that the time trend of increasing
  • 17:39suicide attempts over the course of
  • 17:41our study still remains significant,
  • 17:43which means that we weren't able
  • 17:45to identify all of the factors
  • 17:48that were responsible for this
  • 17:49rise in suicide attempt,
  • 17:51and there's likely other factors
  • 17:52that we didn't have access to
  • 17:55that were likely contributing
  • 17:56to this increase in suicide
  • 17:58attempts. Next slide, please.
  • 18:01Now, turning to mental health
  • 18:02service use in the last year.
  • 18:04We wanted to know what were the
  • 18:06trends among individuals who attempted
  • 18:08suicide in their use of past year,
  • 18:10mental health services and what we found
  • 18:12was that there was no significant change
  • 18:14in any of the services we looked at.
  • 18:16We looked at outpatient inpatient
  • 18:18and psychotropic medication use
  • 18:20from 2008 to 2019 and if you can
  • 18:22see the the dark blue line here,
  • 18:25this was prescription medication use.
  • 18:26So this was the most common type of
  • 18:28mental health service received by
  • 18:30individuals who attempted suicide.
  • 18:31Anywhere from 40 to 50% of individuals
  • 18:34who attempted suicide in our study
  • 18:36reported receiving some sort of
  • 18:38psychotropic medication in the last year.
  • 18:40Outpatient services were then the
  • 18:42next most common and right around
  • 18:4440% of individuals reported
  • 18:46receiving outpatient services.
  • 18:48A smaller amount received inpatient
  • 18:50services and a much smaller amount.
  • 18:52Received substance use services.
  • 18:54Next slide, please.
  • 18:57And so finally we wanted to know what were
  • 18:59the percent of individuals who reported
  • 19:01needing services but did not get services.
  • 19:03And so in this most recent year in 2019,
  • 19:06we found that 45% almost half of
  • 19:09individuals who attempted suicide reported
  • 19:11needing services but not receiving them.
  • 19:14And when we looked at the
  • 19:16most common reported reasons
  • 19:17that they didn't receive care,
  • 19:18about half of individuals said
  • 19:20they didn't receive care because
  • 19:21they couldn't afford the cost,
  • 19:23about 1/4 of individuals said they simply
  • 19:25didn't know where to go for treatment and 16.
  • 19:27Percent were either concerned about
  • 19:28the opinions of others or were
  • 19:30concerned about confidentiality,
  • 19:31which both are related to mental
  • 19:34health stigma related concerns
  • 19:36about seeking care for.
  • 19:38For suicidality.
  • 19:40Next slide.
  • 19:40So when we look at a summary of our findings,
  • 19:45the first point is there's been a
  • 19:46substantial increase in suicide attempts,
  • 19:48about a 23% rise in suicide
  • 19:50attempts from 08 to 2019 without any
  • 19:53corresponding increase in service use.
  • 19:55We found that while mental illness was
  • 19:57highly associated with suicide attempts,
  • 19:59the greatest increase has actually occurred
  • 20:00among individuals without mental illness.
  • 20:02It's occurred among individuals who
  • 20:04are unemployed and young adults.
  • 20:06Individuals with substance use disorders,
  • 20:08or individuals who are never married.
  • 20:11We also found that only 40% of
  • 20:13individuals who attempted suicide.
  • 20:14At any sort of outpatient mental
  • 20:16health visit in the past year and
  • 20:18nearly half of individuals reported
  • 20:20an unmet need for treatment,
  • 20:22which was largely due to cost barriers or
  • 20:25not knowing where to go to obtain care.
  • 20:28So turning now to the implications,
  • 20:30the first implication of our study
  • 20:34next bullet.
  • 20:37Was that service use in our study was
  • 20:39significantly less than in other studies
  • 20:41that have looked at fully insured samples.
  • 20:44So like I said in our study,
  • 20:45only about 40% reported an outpatient visit,
  • 20:49where in the previously studied insured
  • 20:52samples upwards of 95% reported an
  • 20:55outpatient mental health visit,
  • 20:56and so when we're thinking about research,
  • 20:59it's important to to think and to
  • 21:01remember that that these insured
  • 21:03samples are fully treatment,
  • 21:05seeking samples of individuals who receive.
  • 21:07Care and emergency departments after
  • 21:09their attempt may actually overestimate
  • 21:11the percent of individuals who are
  • 21:13receiving care after a suicide attempt.
  • 21:15But perhaps more importantly,
  • 21:16I think it's concerning.
  • 21:17Given that most of our current
  • 21:20suicide prevention strategies
  • 21:21really rely on healthcare,
  • 21:22contact, our most common prevention
  • 21:24strategies right now.
  • 21:26Include things like a
  • 21:28routine suicide screening,
  • 21:30making sure individuals experiencing
  • 21:32suicidality receive evidence based treatment,
  • 21:34and making sure individuals receive
  • 21:36safety planning before they leave.
  • 21:37Training patient units or our
  • 21:39emergency departments,
  • 21:40but it's impossible to really do any of
  • 21:43these evidence based interventions unless
  • 21:44people are walking through the doors,
  • 21:47and unless we're seeing them
  • 21:48in our healthcare settings.
  • 21:49And So what I'd like to talk
  • 21:51about next is really,
  • 21:52I think,
  • 21:53a potential need to diversify our
  • 21:55suicide prevention interventions
  • 21:56to not only focus on high risk
  • 21:59individuals who frequently have contact
  • 22:01with us in the healthcare system,
  • 22:03but to also look at more public,
  • 22:04health oriented interventions that
  • 22:06begin to address the social conditions.
  • 22:09Which people live?
  • 22:11Next point,
  • 22:12our findings also just demonstrate a
  • 22:14very large unmet need for treatment
  • 22:16during the most high risk period for
  • 22:18fatal reattempts, and so we know,
  • 22:21based on prior literature,
  • 22:22that the most high risk time for
  • 22:24dying after a suicide attempt is in
  • 22:27the year after that suicide attempt.
  • 22:29Yet our study found that nearly half
  • 22:31of individuals are reporting an unmet
  • 22:33need for treatment during this time,
  • 22:35which really speaks to.
  • 22:38Just how big of an issue
  • 22:39access continues to be,
  • 22:41and I know that this is
  • 22:42something that all of you know,
  • 22:43especially those of you who who
  • 22:45work in our emergency departments
  • 22:46or in inpatient units and try
  • 22:48to get care in the community for
  • 22:50individuals after they're discharging.
  • 22:52That access continues to remain a
  • 22:54significant issue and specifically
  • 22:56cost was cited as the number one
  • 22:59barrier to care in our study.
  • 23:01It's also important to note that
  • 23:02most of the data in our study was
  • 23:04collected after implementation of the
  • 23:06Affordable Care Act when we had a lot of.
  • 23:08Different policies and insurance
  • 23:10expansions that were really
  • 23:12targeted at lowering the cost
  • 23:14of care and improving access,
  • 23:16but it is discouraging to see that
  • 23:19cost still remains such a barrier
  • 23:21to care for folks next slide.
  • 23:24And so when we're looking at potential
  • 23:27interventions to to work on in the future,
  • 23:30I think it's important that there's
  • 23:31really kind of two potential
  • 23:32areas that we can look at.
  • 23:34The first is interventions within
  • 23:36the formal healthcare system.
  • 23:38Next slide. And so there are a
  • 23:42number of evidence based strategies
  • 23:43within the formal healthcare system
  • 23:44that we can continue to focus on.
  • 23:46Like I said, routine suicide screening,
  • 23:48not only in psychiatric settings
  • 23:50but also in medical settings.
  • 23:52There's been a fair amount of evidence
  • 23:54to show that brief interventions in
  • 23:56the emergency department and follow
  • 23:58up contact through postcards or phone
  • 24:00calls after patients are discharged
  • 24:02from our emergency departments,
  • 24:04can lower suicide attempts and
  • 24:06suicide rates after discharge,
  • 24:08and we know that suicide safety
  • 24:09planning is a.
  • 24:10And it's based intervention,
  • 24:11so I think we need to continue to make
  • 24:14sure that our emergency departments
  • 24:16and healthcare systems are equipped to
  • 24:18really implement these interventions.
  • 24:20But I think we also need next slide,
  • 24:24public health oriented interventions
  • 24:26outside of the healthcare system.
  • 24:29Interventions that really begin
  • 24:30to address the social conditions
  • 24:32in which people are living and the
  • 24:34social conditions that we know
  • 24:35precede suicidal behavior.
  • 24:36And so in our study,
  • 24:37for example,
  • 24:38individuals who were unemployed
  • 24:40showed the greatest.
  • 24:41Increase in suicide attempts over
  • 24:44the study period.
  • 24:45There's been a fair amount of
  • 24:47evidence to suggest that states
  • 24:49with more generous unemployment
  • 24:51benefits actually so reduced suicide
  • 24:54rate at the state level after those
  • 24:56more generous unemployment benefits
  • 24:59are implemented next.
  • 25:02The same can be true for anti poverty.
  • 25:04Income supports things like temporary
  • 25:06assistance for needy families
  • 25:07or TANF benefits.
  • 25:09There's a fair amount of evidence
  • 25:11to support that states with more
  • 25:13generous TANF benefits actually
  • 25:15see a reduction in their suicide
  • 25:17rate at the state level.
  • 25:19One particularly interesting modeling
  • 25:21study from economist estimated
  • 25:23that we may be able to reduce 3000
  • 25:26suicide deaths in our country.
  • 25:27That's one in nine suicide deaths each year.
  • 25:29If we were to improve.
  • 25:31Increased tanaff benefits by
  • 25:34a relatively marginal amount.
  • 25:36Next slide,
  • 25:37I think we need to continue to
  • 25:38invest in Community based crisis
  • 25:40response which is receiving a lot
  • 25:41of attention right now to make sure
  • 25:43that we're reaching people during
  • 25:45times of crisis and referring them
  • 25:47to an appropriate level of care.
  • 25:50Next,
  • 25:50we need to continue to expand
  • 25:52gatekeeper trainings to make sure that
  • 25:54lay individuals in schools and in churches,
  • 25:56people that frequently come into
  • 25:58contact with suicidal individuals,
  • 26:00feel comfortable doing a basic suicide
  • 26:03risk assessment and referring individuals
  • 26:05to an appropriate level of care next.
  • 26:09We need to continue to look at means
  • 26:11control when we look at systematic
  • 26:13reviews and meta analysis of effective
  • 26:15suicide interventions means control
  • 26:17consistently demonstrates the most
  • 26:19amount of evidence at being able to
  • 26:22reduce our suicide rates and and so
  • 26:24this is mainly focused on firearm
  • 26:27restriction for higher high risk
  • 26:29individuals and also focusing on
  • 26:31safe firearm storage for individuals
  • 26:34who possess firearms.
  • 26:35And finally,
  • 26:36this would be a talk on epidemiology
  • 26:38or health services.
  • 26:40If we didn't focus on data and really
  • 26:42improving our our surveillance systems.
  • 26:43Right now, the CDC is only.
  • 26:47Tracking and monitoring deaths
  • 26:48by suicide and we don't really
  • 26:51have any monitoring systems or surveillance
  • 26:53data on other types of suicidal behavior.
  • 26:56Things like non suicidal self
  • 26:58injury or suicide attempts.
  • 27:00And so my last slide.
  • 27:02I just like to talk a little bit
  • 27:04about these surveillance systems.
  • 27:06And so this is a map of the current
  • 27:09CDC state level surveillance,
  • 27:10and so you can see on this map that
  • 27:13CDC basically tracks which states
  • 27:15have the highest rates of suicides,
  • 27:18and in this map it's the
  • 27:20states with dark blue.
  • 27:22But this sort of map isn't
  • 27:23really all that actionable.
  • 27:25It doesn't really tell us what might
  • 27:27be occurring at the state level.
  • 27:29What might be the high risk populations
  • 27:31in these States and so one alternative
  • 27:33approach would be to really expand
  • 27:35our ability to do county level.
  • 27:37Surveillance next slide.
  • 27:40And so an example of of county
  • 27:42level surveillance may be
  • 27:43something that looks like this.
  • 27:44This was a a recent geographic analysis
  • 27:46that we did trying to identify high
  • 27:49risk counties in the US for suicide.
  • 27:51So all the counties in red are actually
  • 27:54the 50 counties in the US whose suicide
  • 27:56rates are over triple the national
  • 27:58average and whose rates continue to
  • 28:00increase at a rate much at a rate
  • 28:02much higher than the national average.
  • 28:04And so this type of data,
  • 28:06I think,
  • 28:06is much more actionable.
  • 28:07It would allow us to really
  • 28:09target our interventions.
  • 28:10Or grant funding to these particular
  • 28:12counties to begin to understand what
  • 28:14is happening at these counties.
  • 28:16What are the high risk populations and
  • 28:18what might we target to begin to reduce
  • 28:21the suicide rates in these counties?
  • 28:23Next slide.
  • 28:25And so finally, I just want to acknowledge
  • 28:27my my mentors on this project.
  • 28:29Again.
  • 28:30Doctor rosenak.
  • 28:32Doctor Reed and again give special
  • 28:33thanks to the to the Seymour Lossman
  • 28:36Foundation for sponsoring this award.
  • 28:38So thank you so much.
  • 28:45Thank you Tanner. That was great.
  • 28:47Such an important topic and
  • 28:49really very clearly presented.
  • 28:51We do have because in addition to his
  • 28:53other manifold talents that you've
  • 28:55heard about Tanners proven himself
  • 28:57to be a master of time control,
  • 28:59and so we have a minute or
  • 29:00two here for questions.
  • 29:01If anyone has questions or comments
  • 29:04before we go on to our next top.
  • 29:07Power. How much of a factor
  • 29:10do you think that since cost
  • 29:12seems to be so much of an issue?
  • 29:15How big an issue and how much
  • 29:17of a role does the fact that
  • 29:20psychiatrists frequently don't even
  • 29:21don't take insurance must much less?
  • 29:23Medic, Medicare or Medicaid?
  • 29:29Yeah, I think I think that's a really,
  • 29:30really important issue and I think
  • 29:33most of us you know who who take care
  • 29:36of patients on this call know that
  • 29:37it's not necessarily our patients with
  • 29:38public insurance that we have a hard
  • 29:40time finding out patient care for,
  • 29:41but it's our patients with private
  • 29:43insurance and our patients who are
  • 29:44uninsured and that actually in this
  • 29:46particular study we found that suicide
  • 29:48attempt rates have been increasing
  • 29:49amongst those two populations.
  • 29:51Individuals with private insurance
  • 29:53and individuals who are uninsured
  • 29:55and and so the access problem,
  • 29:57I think, really is.
  • 29:59Was focused on on those two two
  • 30:01groups of individuals.
  • 30:08And are you noted that your strongest
  • 30:10predictors of the OR correlates
  • 30:11of the increased suicide rates,
  • 30:13weren't mental health diagnosed?
  • 30:14They were age and unemployment and
  • 30:16the other factors that you listed.
  • 30:18But did you look at mental health?
  • 30:20Did mental health diagnosis
  • 30:22increase in parallel?
  • 30:24And if you look at them as a mediator,
  • 30:26maybe unemployment leads to
  • 30:27an increase in depression,
  • 30:28which mediates the increase.
  • 30:30Made of suicide.
  • 30:33Good question, good question.
  • 30:34We didn't look at it as a mediator and
  • 30:37one of the limitations of the the NIS.
  • 30:40That data set is it? It doesn't.
  • 30:42It's focused on substance.
  • 30:43Use mainly doesn't focus on mental health
  • 30:45and so we only know kind of in the data
  • 30:48set of major depressive episodes as
  • 30:50well as serious psychological distress
  • 30:52which is a nonspecific kind of marker
  • 30:55or indicator of psychological distress.
  • 30:57In the last year.
  • 30:58So it doesn't give us a lot of
  • 31:00information about mental illness.
  • 31:02We did find that.
  • 31:03Individuals with depression and and
  • 31:05serious psychological distress or highly
  • 31:08associated with attempting suicide.
  • 31:09But we didn't actually see
  • 31:11increases in the suicide attempt
  • 31:14rate amongst these populations.
  • 31:16That was more focused on
  • 31:17individuals who are unemployed.
  • 31:18Individuals with substance use disorders.
  • 31:20Like I said,
  • 31:21or individuals who were never married.
  • 31:24Right? Thank you and congratulations again
  • 31:27Tanner for your for your first place.
  • 31:30Last minute award you will be receiving
  • 31:33both a certificate and and a cache award.
  • 31:35Can't give it to you in person today,
  • 31:37but that will be on its way to you.
  • 31:40All right, I'd now like to invite Renato
  • 31:44Pallanti to introduce the first of our
  • 31:47Co 2nd place awardees Daniel Tiley.
  • 31:51Good morning everyone. It's
  • 31:53a pleasure to introduce Doctor
  • 31:55Daniel Kelly. He's a third year
  • 31:57resident and role in the NRP program.
  • 32:01After completing his MDPC training at
  • 32:04the SUNY Upstate Medical University,
  • 32:07under the mentorship of Doctor
  • 32:09Steven and Steven Paul. Then
  • 32:12join my group in December 2019 and since
  • 32:14then it became a key member of my team,
  • 32:18leading several analysis and
  • 32:19contributed to many projects.
  • 32:21Going to happen.
  • 32:23He did all of these also having
  • 32:25a very busy clinical schedule.
  • 32:28Because of his accomplishment this
  • 32:30year, then received the Chairs Choice Award
  • 32:33from the Society of Biological
  • 32:35Psychiatry additionally into
  • 32:372020 also received the D3 Award
  • 32:39from our department to work on
  • 32:42a study to extract high quality
  • 32:44depression digital phenotypes
  • 32:46from the Yale New Haven Health System.
  • 32:48Electronical triggers today
  • 32:51is going to present his work
  • 32:53recently published in JAMA Psychiatry,
  • 32:55where we showed the complex
  • 32:56dynamics linking. Psychopathology
  • 32:59and immune function using genetic data. So
  • 33:02without further ado please then.
  • 33:07Thank you Renato for that
  • 33:09really generous introduction.
  • 33:11I want to make sure y'all can see my
  • 33:14screen that I think I've done it wrong.
  • 33:22So if I do this, can you see my slides?
  • 33:26Presenter View presenter view. How about now.
  • 33:30Hang on one SEC there we go perfect. OK,
  • 33:34so the work I'm going to be
  • 33:36presenting to you today is in the
  • 33:39area of genetic epidemiology and
  • 33:42it's specifically cross disorder,
  • 33:44genetic epidemiology.
  • 33:45Looking at relationships between psychiatric
  • 33:47disorders and some related phenotypes,
  • 33:50not quite disorders, personality traits,
  • 33:53and basically representative.
  • 33:56Sample available sample of autoimmune
  • 33:59diseases, allergic conditions
  • 34:01and inflammatory conditions.
  • 34:03So kind of like running the gamut.
  • 34:06Two things that are important to
  • 34:08know about this is that this is
  • 34:10basically leveraging GWAS data.
  • 34:12So genome Wide Association study
  • 34:14data which looks at the effects of
  • 34:17changes in the letter, the base,
  • 34:19the letter base pair at different positions,
  • 34:22positions in the genome in
  • 34:24association with the disorder.
  • 34:25So these are basically data
  • 34:27that were generated elsewhere,
  • 34:29usually by large consortia,
  • 34:30and I'm using the data,
  • 34:32repurposing it and putting it
  • 34:34together for some novel analysis.
  • 34:40This is the the sort of the citation.
  • 34:44If you're interested in
  • 34:44learning more of the details,
  • 34:45we won't be able to get into many of
  • 34:47the details today with the limited time.
  • 34:50But for some context,
  • 34:51if you search the literature,
  • 34:54you'll find no shortage of
  • 34:56reviews and meta analysis.
  • 34:57Looking at epidemiologic associations
  • 35:00between different immune related conditions
  • 35:03and different psychiatric conditions.
  • 35:06What what I think is not clear yet
  • 35:08is whether there are specificity in
  • 35:10these relationships across disorders,
  • 35:12or whether the patterns are really
  • 35:14more or less the same across disorders.
  • 35:16It's sort of an open question
  • 35:18and something that we're we're
  • 35:20using genetic data to look at.
  • 35:22So epidemiologists are interested
  • 35:24in explaining these associations,
  • 35:26and there's different possible explanations.
  • 35:29One thing that might be happening is there
  • 35:31could be a causal effect of 1 disorder,
  • 35:34increasing the risk for another.
  • 35:36Of course,
  • 35:37it's really hard to demonstrate causal
  • 35:39effects on a population scale, really.
  • 35:41You need good experiments to
  • 35:43to demonstrate causal effects,
  • 35:45and that's just not possible here.
  • 35:48In general, you know,
  • 35:49so one hypothesis is that immune disorders
  • 35:51are causing psychiatric disorders,
  • 35:52and we have some basis to to say
  • 35:55that that might be possible.
  • 35:58So we know from clinical observations that
  • 36:00immune diseases that infiltrate the CNS,
  • 36:03so things like multiple sclerosis,
  • 36:05lupus vasculitis and also auto
  • 36:09antibody mediated encephalitis,
  • 36:12we see those with autoimmune disease,
  • 36:13but also after infections like
  • 36:16COVID and paraneoplastic syndrome,
  • 36:17so these can cause.
  • 36:19Neuropsychiatric syndromes,
  • 36:20but it's important to know that
  • 36:23they're relatively quite rare,
  • 36:25and also usually there are other
  • 36:29neurological findings changes in mental
  • 36:31changes in overall mental status,
  • 36:33fluctuating level of consciousness.
  • 36:35People are ill when they have these.
  • 36:37Oftentimes it's very,
  • 36:38very rare for them to present
  • 36:40with only psychiatric symptoms.
  • 36:44And then we know from experimental
  • 36:46data in humans and in animals that if
  • 36:50you administer an immune disturbance,
  • 36:52if you administer cytokines,
  • 36:53or if you administer bacterial endotoxin,
  • 36:56basically you can induce behaviors
  • 36:58in people and in animals that
  • 37:01that are sickness behavior.
  • 37:03And these are also accompanied by
  • 37:06emotional and cognitive changes,
  • 37:07some of which seem to recapitulate features
  • 37:11of depression depending on who you ask.
  • 37:14And then from animal
  • 37:15models of adult exposure,
  • 37:17but also gestational exposure to
  • 37:19different types of immune disturbance,
  • 37:21we know that there are
  • 37:23neurodevelopmental effects and there
  • 37:24are social behavioral effects.
  • 37:26The figures that I'm showing here
  • 37:29so that the top right is a pet FDG
  • 37:33study looking at it was actually a
  • 37:36a pet dopamine binding study looking
  • 37:39at changes before and after the
  • 37:41administration of of interferon alpha.
  • 37:44In the context of treating hepatitis
  • 37:46CI believe and the bottom is looking
  • 37:48at newborn neurons in a mouse model.
  • 37:53I another hypothesis is that psychiatric
  • 37:56disorders are somehow causing immune
  • 37:58disorders or contributing causally.
  • 38:04Clinical observation points to the idea
  • 38:07that stress might be important here.
  • 38:10We know that acute psychological stress,
  • 38:13a laboratory stressor like the tree
  • 38:15or social stressor produces autonomic
  • 38:18changes and neuroendocrine changes,
  • 38:20and also measurable changes
  • 38:22in peripheral immune markers.
  • 38:24So when you stress a healthy participant,
  • 38:25there are transient increases
  • 38:27in I-1 beta IL 6 TNF alpha.
  • 38:30What's really?
  • 38:31I think interesting.
  • 38:32That individual differences in the
  • 38:35subjective experience of that stressful
  • 38:37experience actually are correlated
  • 38:41with different different aspects
  • 38:43of the changes in the peripheral
  • 38:45immune milieu and and the anti
  • 38:47inflammatory cortisol and milieu.
  • 38:51We also know from human studies that
  • 38:54self reported stress or objective
  • 38:57measures of deprivation or poverty are
  • 39:00predictive of symptom severity in humans.
  • 39:03For a number of immune related disorders,
  • 39:05and we know from animal models of
  • 39:07immune related disorders that if you
  • 39:09if you subject those animals to stress,
  • 39:11it worsens the histological
  • 39:13progression of disease.
  • 39:15And that's probably best understood for
  • 39:17asthmatic conditions and and inflammatory.
  • 39:20Health conditions in
  • 39:21intermetallic conditions.
  • 39:24And there's also the possibility
  • 39:27of bidirectional effects.
  • 39:29That's actually suggested by
  • 39:30some of the longitudinal studies
  • 39:32that look at the temporal.
  • 39:34You know the temporal patterning
  • 39:35of these associations,
  • 39:37and then I wanted to mention
  • 39:39here that there's a large
  • 39:41body of literature looking at.
  • 39:43Psychiatric samples people as
  • 39:45seen for psychiatric disorders,
  • 39:47and they show group differences in a
  • 39:51variety of peripheral immune markers,
  • 39:54so it's not really clear what
  • 39:55the significance of that is.
  • 39:56We're so we're sort of left with
  • 39:57a chicken or egg problem there.
  • 40:00There are other explanations too.
  • 40:03Another possibility is that there's
  • 40:05some shared underlying biology,
  • 40:06so maybe there's a shared
  • 40:08pathological mechanism,
  • 40:09or there could also be
  • 40:11correlated genetic mechanisms.
  • 40:12So so different mechanisms,
  • 40:13but they travel together on the genome
  • 40:15because they're so close to each other.
  • 40:17It's also possible that there's
  • 40:19some external causal factors.
  • 40:21Some third variable effects going on.
  • 40:24If things that come to mind
  • 40:25are environmental exposures,
  • 40:26social determinants of health.
  • 40:29And a related hypothesis is that.
  • 40:33There is actually a true causal factor
  • 40:35that's just correlated with one of
  • 40:38your phenotypes and causal for the
  • 40:40second or mediation is possible,
  • 40:42so one phenotype may cause may cause.
  • 40:47As the actual causal phenotype
  • 40:49leading to the outcome,
  • 40:51and so when I think about this possibility,
  • 40:53I think about things like
  • 40:55health related behaviors.
  • 40:57So substance use aspects of BMI,
  • 41:01exercise, diet, sleep,
  • 41:02duration,
  • 41:03but also social connectedness and then
  • 41:06the social determinants of health.
  • 41:08And then individual differences in
  • 41:10the stress response.
  • 41:11Also possible mediator here.
  • 41:16For completion, it's also possible that
  • 41:19mediating or confounding effects are
  • 41:21happening in the other direction too.
  • 41:23So these are relevant for
  • 41:25understanding the next.
  • 41:27The next slide here.
  • 41:29So what we did was we assessed genetic
  • 41:33correlations between psychiatric
  • 41:34and immune related disorders,
  • 41:36and we did this using the LD
  • 41:38score regression method.
  • 41:39So this method basically looks at all
  • 41:41of the positions on the genome and
  • 41:44looks at the association for disorder
  • 41:46A&B and and looks to see if they're
  • 41:49significant and if they're in the same
  • 41:51or opposite directions of effect.
  • 41:52And it kind of.
  • 41:54That summarizes that data
  • 41:56across the whole genome.
  • 41:57To describe the proportion of shared
  • 42:01heritability between the disorders,
  • 42:03I know that's a lot.
  • 42:05I'm going to kind of walk you
  • 42:07through it because the slide is busy,
  • 42:09so we found a predominance of
  • 42:12positive genetic correlations.
  • 42:14They were modest in strength.
  • 42:16The correlation coefficients were between,
  • 42:18you know, point.
  • 42:20Basically,
  • 42:21.8 to point .20.
  • 42:24.08 I'm sorry to .2 and we saw kind
  • 42:29of a clustering of correlations
  • 42:31involving the inflammatory bowel
  • 42:33disorders but also one of the
  • 42:36biliary disorders and lupus,
  • 42:38and those seem to be positively
  • 42:40related to schizophrenia and
  • 42:42mood and anxiety disorders.
  • 42:44We also saw predominance of positive
  • 42:46relationships for asthma and hypothyroidism,
  • 42:48and those included a slightly
  • 42:50different set of psychiatric
  • 42:52phenotypes for some immune phenotypes.
  • 42:55Like celiac disease and another
  • 42:57of the biliary diseases we saw
  • 42:59sort of a mixed pattern across
  • 43:01disorders with some positive and
  • 43:04some negative correlation across
  • 43:06different psychiatric traits.
  • 43:07And then some of the immune
  • 43:09related disorders seem to have a
  • 43:12predominantly negative correlation
  • 43:13across across the psychiatric traits.
  • 43:15At least the ones that were
  • 43:17available to measure.
  • 43:19And.
  • 43:20Another thing that we did here
  • 43:22is we included genetic data for
  • 43:24these additional risk factors that
  • 43:26I showed you on the last slide.
  • 43:28So the health related behaviors,
  • 43:29the sleeping behaviors,
  • 43:30and what we found was that many of
  • 43:35these potentially confounding or
  • 43:37mediating phenotypes show significant
  • 43:40genetic correlations with both
  • 43:43immune and psychiatric disorders.
  • 43:45The effect sizes were stronger for
  • 43:47the psychiatric disorders on average.
  • 43:52So the next thing we did was we wanted
  • 43:55to use genetic data to try to answer
  • 43:58the question of whether whether a is
  • 44:01causing B or B is causing A and the
  • 44:03way we did that was with a method
  • 44:05called Mendelian randomization,
  • 44:07and it's a complex method.
  • 44:09I can't explain all the details of it, but.
  • 44:12The brief version is that if we assume
  • 44:15that the causal loci for phenotype,
  • 44:19if we assume that we know the
  • 44:20cause of LOCI for phenotype A,
  • 44:22we can then look at phenotype B.
  • 44:24Those same positions on the genome,
  • 44:26and we can.
  • 44:27We can ask, do those also show risk
  • 44:30for free and type B in those positions?
  • 44:33And if that's true,
  • 44:34there might be a causal effect
  • 44:35in that direction,
  • 44:36and we can ask the opposite question.
  • 44:38The causal loci for phenotype B?
  • 44:40Do they show any evidence
  • 44:42of effects in phenotype a?
  • 44:43So it's a it's a more directional analysis.
  • 44:46So for all of the 44 correlations
  • 44:48I showed you in the last slide,
  • 44:50we basically performed this
  • 44:53analysis bidirectionally.
  • 44:54So testing both directions of
  • 44:55effect and we found a total of
  • 44:58nine significant effects here,
  • 44:59and again I'll walk you through
  • 45:01this slide because it's a bit busy.
  • 45:03So eight of these effects were
  • 45:06effects of psychiatric.
  • 45:08Patrick phenotypes on immune phenotypes
  • 45:10and seven of them were positive,
  • 45:12so the solid Red Arrows that you
  • 45:15see on the figure are all pointing
  • 45:19from various psychiatric phenotypes
  • 45:22to various immune phenotypes.
  • 45:26Specifically,
  • 45:26we saw effects involving major depression,
  • 45:29schizophrenia,
  • 45:30and also this process disorder phenotype,
  • 45:33which is composed of I think,
  • 45:358 different psychiatric disorders.
  • 45:37But but depression and schizophrenia
  • 45:39figure heavily in those because
  • 45:40they're some of the largest samples,
  • 45:42so the effects are modest.
  • 45:44The average odds ratio was 1.1.
  • 45:47The largest effect that we saw was
  • 45:49an effective depression on asthma
  • 45:52and then the smallest effect was
  • 45:54the cross disorder affect on.
  • 45:56Asthma,
  • 45:56so the way to understand these
  • 45:59is the genetic liability for the
  • 46:02psychiatric trait increases increases
  • 46:04the genetic liability for the immune
  • 46:06related trade and the window when
  • 46:08you'd like to do it.
  • 46:11One of these, one of these
  • 46:13relationships was negative,
  • 46:14so risk tolerance was associated
  • 46:17with decreased genetic liability
  • 46:19to allergic rhinitis for hay fever.
  • 46:25And we had some effects that did not
  • 46:28survive the sensitivity testing and
  • 46:31then the multivariable adjustment.
  • 46:33So you can see that sort of
  • 46:36dashed blue line on the bottom.
  • 46:38It's dashed because the relationship
  • 46:40was interrupted and the things that
  • 46:42interrupted it were all of the Gray
  • 46:43phenotypes on the bottom that have
  • 46:45little lines pointing toward it.
  • 46:46So body mass index,
  • 46:48cognitive processing all of those
  • 46:49seem to attenuate the relationship,
  • 46:51suggesting that the relationship could
  • 46:53potentially be mediated by other factors.
  • 46:56Right?
  • 46:57It's up to him. Can I ask people to
  • 47:01mute please? Other than that, thanks,
  • 47:03yeah we had time.
  • 47:06We we saw one we saw one effect
  • 47:10of hypothyroidism on MDD.
  • 47:11It was it was not significant
  • 47:14after multivariable adjustment so.
  • 47:16And so we didn't make.
  • 47:17We didn't consider it a robust basically.
  • 47:21So interpretation discussion.
  • 47:24Basically, these genetic analysis
  • 47:26find stronger support for the
  • 47:28idea that psychiatric disorders
  • 47:30might be contributing causally
  • 47:32to immune related disorders.
  • 47:34We found relatively little
  • 47:35evidence in the opposite direction.
  • 47:39There are a number of limitations
  • 47:41that I don't necessarily think
  • 47:43we need to get into here,
  • 47:44but in context, so there is.
  • 47:47There is epidemiologic
  • 47:48support for MDD and asthma.
  • 47:50There is less consistent epidemiologic
  • 47:52support for schizophrenia and the
  • 47:54inflammatory bowel disorders and there's
  • 47:57really no literature linking risks
  • 47:59risk taking behavior to hay fever.
  • 48:01And we do replicate the results of some
  • 48:04prior Mendelian randomization studies,
  • 48:06which is encouraging.
  • 48:09Our results do need to be reconciled with.
  • 48:12A lot of epidemiologic studies that find
  • 48:15that a prior immune disorder increases the
  • 48:17risk for a subsequence like yatrik disorder,
  • 48:20so the temporal patterning in these
  • 48:22studies is opposite what we what.
  • 48:24What our data suggests so.
  • 48:28I was trying to think about
  • 48:29ways to explain that,
  • 48:30and one of the the line of thinking
  • 48:33that I followed is that you know
  • 48:35on the whole these immune,
  • 48:37these immune related disorders,
  • 48:39particularly like the inflammatory
  • 48:40bowel disorders.
  • 48:41They're rare, whereas psychiatric
  • 48:43symptoms are relatively common.
  • 48:46And it's possible that people who are
  • 48:49being ascertained for an immune disorder
  • 48:52have some amount of subclinical,
  • 48:54undiagnosed psychiatric illness
  • 48:56ahead beforehand that that is
  • 48:59likely just based on the how common
  • 49:02psychiatric symptoms are.
  • 49:06We also have to reconcile our work
  • 49:08with some some studies that look
  • 49:11at cytokine concentrations and
  • 49:13psychiatric disorders that seem
  • 49:14to suggest the cytokines are are
  • 49:16causal for psychiatric disorders.
  • 49:20And then future studies in this
  • 49:23in this area are going to need
  • 49:26to include these third variable
  • 49:28confounding or mediating phenotypes.
  • 49:30And because they exert outsize
  • 49:33effects on the data in the future,
  • 49:35I would love to integrate markers of HP,
  • 49:38a access functioning inflammatory markers,
  • 49:41immune cell counts,
  • 49:42there's GWAS data for these sorts of things.
  • 49:44And then of course, it's possible that
  • 49:47larger data sets may actually yield.
  • 49:50May actually yield bidirectional effects or
  • 49:53effects of immune on psychiatric disorders.
  • 49:56So that.
  • 49:57It's my study and thank you for listening.
  • 50:01Thanks for the department and the
  • 50:04Lesbian Foundation and family and.
  • 50:07The award the the panel who
  • 50:10made the decisions.
  • 50:11Yeah and thanks Renato and
  • 50:12my lab mates for getting you
  • 50:14know making this possible.
  • 50:17Thank you Dan.
  • 50:18Really interesting work with some
  • 50:21some provocative and counterintuitive.
  • 50:23Things to think about in
  • 50:26the interest of time,
  • 50:26we're going to move straight on.
  • 50:27Can I ask you into?
  • 50:31To close your smile. Yeah.
  • 50:37And we will move on.
  • 50:42So our other Co Co 2nd place
  • 50:45winners are a pair of of of cranes,
  • 50:49Zach Harvey Neck and Terrell Holloway,
  • 50:52and they've asked me to
  • 50:54briefly introduce them.
  • 50:55Terrell and Zach are both senior
  • 50:58residents in the Neuroscience Research
  • 51:00Training program and have really been
  • 51:02wonderful members of the program,
  • 51:03not only with the the
  • 51:05science that you'll hear,
  • 51:06but also as clinical leaders and also
  • 51:09as just wonderful citizens and and and
  • 51:12and leaders in the residency as a whole.
  • 51:14In the NTP in particular.
  • 51:16Terrell did his bachelor's at
  • 51:18Brown and his MD at Mount Sinai
  • 51:21before and during his MD.
  • 51:22He did some really first
  • 51:24rate basic science work.
  • 51:25Looking at neurotransmitter
  • 51:27mechanisms with with relevance
  • 51:28to some of our recent interests
  • 51:31in psychedelics interesting.
  • 51:33And then when he came here,
  • 51:34he shifted his focus to to what
  • 51:36you're going to hear about today,
  • 51:38which is the focus of social
  • 51:40determinants of health and in particular
  • 51:42race and racism on psychiatric
  • 51:44outcomes and this combination.
  • 51:46Of a focus on social determinants
  • 51:48of health and a deep understanding
  • 51:50of underlying molecular mechanisms.
  • 51:52Puts Terrell in a really special
  • 51:54position to be able to do syncratic
  • 51:56synergistic work with the type
  • 51:58you're going to hear about today.
  • 52:00So I Carbanak did his bachelor's at Duke
  • 52:03in biomedical engineering and biology,
  • 52:04and then he did his PhD in at Michigan,
  • 52:08where he studied the aging in the
  • 52:10lowly fruit fly chrysocolla and when
  • 52:12he came to the NTP here at Yale,
  • 52:14he he kept that focus on aging.
  • 52:17But switched to something we like to
  • 52:19think of as a little bit less slowly
  • 52:21that the human power human mechanisms
  • 52:23of aging and how they're influenced
  • 52:25by stress and psychiatric phenotypes.
  • 52:29I love that the two of them
  • 52:31Co submit this paper.
  • 52:32I can't remember that happening
  • 52:34in the previous last minute.
  • 52:35Last minute words,
  • 52:36but it it speaks to this this strength
  • 52:39not only of their science but also
  • 52:41of their their collaborative spirit,
  • 52:44and it's great to see to see their
  • 52:47work synergizing like it does here.
  • 52:49I know they're going to acknowledge
  • 52:50their mentors during the talk,
  • 52:52but I want to give a shout out
  • 52:53to Derrick Gordon.
  • 52:54Would you just Sinha and could shoot?
  • 52:57Metric this one.
  • 52:58Terrell is that take you awhile.
  • 53:01Thank you very much for the introduction,
  • 53:03Chris. And thank you all for
  • 53:06taking part in this presentation.
  • 53:07Zach and I will be alternating the
  • 53:10slides throughout and so you know just
  • 53:12as a means of just giving you a sense of
  • 53:14how this is going to go back and forth.
  • 53:16Just presenting that,
  • 53:16could you go to the next slide, please?
  • 53:20We have no disclosures to to share in
  • 53:22regards to any conflicts of interest and
  • 53:25and just as it means of like how big
  • 53:28this slide this this presentation was,
  • 53:30we had to curtail it a little
  • 53:32bit just to accommodate time.
  • 53:33And so to start off.
  • 53:35As we all know,
  • 53:36there's been a lot of epidemiologic
  • 53:38data that has demonstrated this
  • 53:40long standing mortality gap
  • 53:41between black and white Americans.
  • 53:43As we can see on the slide on
  • 53:45the the graph below to the left,
  • 53:47we see that though that there's
  • 53:49been a decreasing.
  • 53:50Uh, decreasing age and mortality,
  • 53:52or decreasing deaths per 100,000 over
  • 53:54the years that have gone on since 2014.
  • 53:58But we still see is a persistent
  • 53:59gap between the life expectancy
  • 54:01of black and white Americans.
  • 54:03Similarly looking to their right
  • 54:05and the CDC as reported in 2020,
  • 54:07this health life expectancy
  • 54:10gap has actually persisted.
  • 54:11And also in light of the the
  • 54:14pandemic has actually increased.
  • 54:15And so.
  • 54:17Given the fact that there have also been
  • 54:20external factors such as differential
  • 54:22access to care and institutional bias,
  • 54:24that may inform some of these,
  • 54:26these disparities growing
  • 54:28literature has shown that increase,
  • 54:30increasingly,
  • 54:31that biomarkers of health also are different,
  • 54:34and these two different populations,
  • 54:36just to name a few as.
  • 54:39Doctor Tylee House was able to
  • 54:42introduce earlier sciatic kinds of
  • 54:43health and signatory cytokines.
  • 54:44In particular have been shown to be
  • 54:46increased in African American populations.
  • 54:48In addition to.
  • 54:51Increases and changes in.
  • 54:55Methylation and also in telomere length
  • 54:58in regards to how short and telling
  • 55:01your life like in African American
  • 55:03populations and so in trying to understand
  • 55:06what it is that's driving this,
  • 55:08this mortality gap.
  • 55:09One of the ways we're that we were
  • 55:11looking at what we were interested in
  • 55:13looking to see is how epigenetically
  • 55:14if this will also pan out to
  • 55:16show these differences and may
  • 55:18inform this mortality gap.
  • 55:20Next slide please.
  • 55:23Estrel so one way we can conceptualize
  • 55:26these health disparities is is
  • 55:29a accelerated biological aging.
  • 55:31Because black individuals in
  • 55:32America might be dying earlier
  • 55:34because they're aging faster.
  • 55:36Prior work has shown that that
  • 55:38life experiences like trauma and
  • 55:40life lifetime adversity can lead to
  • 55:42accelerated biological aging and and
  • 55:44we know that black Americans face
  • 55:46higher levels of stress and trauma.
  • 55:48Recent development developments and
  • 55:50epigenetics have led to epigenetic clocks,
  • 55:53one of which is called brimmage,
  • 55:54that we'll be using here,
  • 55:56which are sets of epigenetic markers
  • 55:58that have really been trained to
  • 56:00predict aging related outcomes and
  • 56:02allow us to estimate a biological
  • 56:04age even in healthy populations.
  • 56:06Next slide.
  • 56:09So taking both of those things
  • 56:11together and we were interested
  • 56:12in in a Community example here in New Haven,
  • 56:14in analyzing to see whether or not there
  • 56:17was any difference in this genetic clock
  • 56:19between black and white Americans,
  • 56:21and also what potential factors may
  • 56:24inform this difference in aging rate.
  • 56:26And so if you could go to the next slide,
  • 56:28please we actually through
  • 56:30the yellow stress Center,
  • 56:32had recruited a cohort of about 400 healthy
  • 56:37volunteers and essentially had assessed.
  • 56:40Various psychological managers through
  • 56:42the cumulative adversity inventory which
  • 56:44is 140 interview survey that assessed
  • 56:47traumatic life offense chronic stress,
  • 56:50major life events and recent life events.
  • 56:53In addition, that's not shown here.
  • 56:54We had assessed health through self
  • 56:57reported Cornell Medical Index survey,
  • 56:59which is another 195 battery question
  • 57:02assessing their health in addition to.
  • 57:04Collecting biological samples,
  • 57:06whole blood,
  • 57:07from which we we we extracted
  • 57:10DNA and also cortisol,
  • 57:12ACTH and other biomarkers of health.
  • 57:17Next slide, please.
  • 57:19And so, like Trell was saying,
  • 57:22we wanted to do this in
  • 57:23a in a healthy cohort,
  • 57:24we this population has no chronic diseases,
  • 57:27no substance use outside of nicotine or no
  • 57:31substance use disorders outside of nicotine.
  • 57:33They're not on any prescription medications.
  • 57:35We did limit our analysis to only
  • 57:38individuals who identified as black or white
  • 57:40through the sample size considerations,
  • 57:42and these groups did have some
  • 57:44notable differences in in BMI,
  • 57:46alcohol use, and years of education,
  • 57:48but they were similar in gender.
  • 57:50Age, income and current health
  • 57:52status and I do want to emphasize
  • 57:54that health status aspect.
  • 57:56Uh, you know.
  • 57:56The Cornell Medical Index is is a
  • 57:58very comprehensive questionnaire of
  • 58:00medical and psychiatric symptoms,
  • 58:01and we saw no significant
  • 58:03difference between black and white
  • 58:05participants on these measures.
  • 58:07Next slide.
  • 58:09So when we look at the psychological
  • 58:11measures and compare the two,
  • 58:12what we find is that black participants
  • 58:14report more stress and more trauma in
  • 58:17comparison to their white counterparts.
  • 58:19Next slide, please.
  • 58:20And when we then correlate
  • 58:22that with the biological data,
  • 58:24what we see in the left side is that
  • 58:27what we know that that grim age is
  • 58:29correlated with advanced health in
  • 58:31both black and white populations.
  • 58:33But when we are actually doing
  • 58:35the linear correlation of this,
  • 58:37we find that actually race
  • 58:39accounts for about a one point.
  • 58:42UH-75 year different or one point
  • 58:44scuse me my side is acting up about
  • 58:48a 1.73 year difference between
  • 58:50black and white participants.
  • 58:51Again echoing Zach's point of
  • 58:53this being a pretty much like a
  • 58:5630 year old healthy population.
  • 58:58This is a significant difference
  • 58:59between the two groups.
  • 59:01Next slide please.
  • 59:02And so similarly when we look at trauma,
  • 59:05what we find is a similar thing of that.
  • 59:07Essentially black Americans
  • 59:09also report more trauma.
  • 59:11And when we subcategorize the
  • 59:13trauma by type next slide, please.
  • 59:15What we find is that there is an increase on.
  • 59:18There's an increase in all four
  • 59:19of these different categories.
  • 59:20Assault of violence being 1D for
  • 59:24the second one being other injury or
  • 59:26shocking event warning of traumas,
  • 59:28or death of a relative or loved one.
  • 59:30We wanted to separate these by
  • 59:32subtype only just to get a nature of
  • 59:34the trauma and to see whether or not
  • 59:36there are any differences in regards
  • 59:38to the nature of the trauma and how
  • 59:40it informed this type of aging.
  • 59:43Next slide,
  • 59:43please.
  • 59:47And since we're seeing these differences
  • 59:49in lifetime stress and and trauma
  • 59:51and epigenetic aging between our
  • 59:52our black and white participants,
  • 59:54we we next wanted to ask whether
  • 59:56stress overall on the left and
  • 59:58traumatic events in particular on
  • 01:00:00the right predicted a grim image in
  • 01:00:03both black and white participants.
  • 01:00:05And the answer is is yes,
  • 01:00:06we see that a higher stress and
  • 01:00:09and trauma predict higher grim age.
  • 01:00:12But as these plots emphasize,
  • 01:00:13the black participants had higher stress,
  • 01:00:15higher trauma.
  • 01:00:16And grim age when compared to
  • 01:00:20white participants next slide.
  • 01:00:22So next we used mediation analysis
  • 01:00:24to ask whether the higher levels of
  • 01:00:26stress and trauma were responsible,
  • 01:00:28at least in part for the differences
  • 01:00:30in grim age between black and
  • 01:00:33white participants.
  • 01:00:33And to give a brief
  • 01:00:35orientation to these diagrams,
  • 01:00:36the indirect effect explains
  • 01:00:38how much of the relationship,
  • 01:00:40basically how many of those years
  • 01:00:42are explained of the relationship
  • 01:00:44between race and grammage is
  • 01:00:46explained by the mediator.
  • 01:00:48The numbers by the arrows are the
  • 01:00:50coefficients in the model and the
  • 01:00:51direct effect is how much of the
  • 01:00:53relationship is unexplained by the mediator.
  • 01:00:55Now,
  • 01:00:55while both are are highly significant,
  • 01:00:57you'll notice that when comparing
  • 01:00:59the magnitude of the indirect effect,
  • 01:01:02the trauma subscale is essentially.
  • 01:01:04Equal to that of the total
  • 01:01:07cumulative adversity inventory,
  • 01:01:08and it's notable that these
  • 01:01:10results hold hold true when after
  • 01:01:13we account for differences in BMI
  • 01:01:15alcohol use in years of education,
  • 01:01:18we went on to do some further analysis
  • 01:01:20that we don't have time to show you today,
  • 01:01:22but those really demonstrate
  • 01:01:23that assaultive trauma,
  • 01:01:24in particular when when Terrell is
  • 01:01:26breaking down those categories,
  • 01:01:27was a particularly powerful mediator of
  • 01:01:30this relationship between race and age.
  • 01:01:32Acceleration next slide.
  • 01:01:35So to to summarize our study,
  • 01:01:37we've shown you today that black
  • 01:01:39participants have higher grim age
  • 01:01:41and face more cumulative stress,
  • 01:01:43and in particular traumatic stress
  • 01:01:45when compared to white participants.
  • 01:01:47And these higher levels of trauma
  • 01:01:50partially explained the increased
  • 01:01:52scrimmage we observe in black participants.
  • 01:01:55It's worth noting that these
  • 01:01:56findings are in a relatively young
  • 01:01:58and remarkably healthy population,
  • 01:02:00suggesting that the biological
  • 01:02:01embedding of stress and trauma in the
  • 01:02:03epigenome is occurring prior to the onset of.
  • 01:02:06Of illness,
  • 01:02:07and it's also worth noting that there's
  • 01:02:09specificity of these findings to trauma.
  • 01:02:12We didn't see differences between
  • 01:02:13black and white participants in
  • 01:02:15recent life events or or sort
  • 01:02:18of the chronic daily stressors.
  • 01:02:19And while black participants had a
  • 01:02:21higher prevalence in all categories
  • 01:02:23of traumatic events,
  • 01:02:24assaultive trauma was a particularly
  • 01:02:26potent mediator of the relationship between
  • 01:02:29race and increased scrimmage acceleration.
  • 01:02:31Next slide.
  • 01:02:33And so the the implications of
  • 01:02:35these findings are are very broad.
  • 01:02:37And first of all,
  • 01:02:38given our limited sample size,
  • 01:02:40we're only able to compare
  • 01:02:42black versus white Americans.
  • 01:02:43And so and also as described
  • 01:02:45previously mentioned,
  • 01:02:46this is one of the first to actually compare
  • 01:02:48this specific clock grim age in a young,
  • 01:02:51healthy cohort sample.
  • 01:02:53These health disparities, though,
  • 01:02:55that they're so observed later in life
  • 01:02:57this this study has emphasized the fact
  • 01:03:00that essentially that these epigenetic
  • 01:03:02changes happen a lot sooner than.
  • 01:03:04When we start seeing these burdens
  • 01:03:06of disease start to take hold in
  • 01:03:08late adulthood and then furthermore,
  • 01:03:10I think kind of point to adolescence as a
  • 01:03:14means of an intervention point in trying to.
  • 01:03:18To try to like start to slow down
  • 01:03:20some of these insults from taking
  • 01:03:22hold in regards to epigenetic age,
  • 01:03:23in particular in regards to the second point,
  • 01:03:27these are particularly relevant
  • 01:03:28and amongst African Americans who
  • 01:03:31are 22% more likely experience of
  • 01:03:32violent crime and more than twice the
  • 01:03:34likely to experience a violent and
  • 01:03:36lethal encounter with law enforcement
  • 01:03:38and in particular to the events of
  • 01:03:40the of what happened last weekend.
  • 01:03:42Understanding how these affect
  • 01:03:44personal health would be one of
  • 01:03:46the things that is paramount.
  • 01:03:48Understanding how this life expectancy gap
  • 01:03:50persists over such a long period of time.
  • 01:03:53Furthermore,
  • 01:03:54as as we have kind of alluded to,
  • 01:03:56given the fact that these there's
  • 01:03:59still a persistent direct effect
  • 01:04:01of of race on accelerated aging,
  • 01:04:04it opens the door for us understanding
  • 01:04:06and house how some of these more complex
  • 01:04:08sociological interactions like racial
  • 01:04:10trauma and experience discrimination,
  • 01:04:12also impact health.
  • 01:04:13And since in this study we weren't
  • 01:04:16able to actually assess or ask about.
  • 01:04:18People's experiences as a turn
  • 01:04:20as it related to discrimination.
  • 01:04:21I think one of the things of which
  • 01:04:23that would be really interesting to
  • 01:04:25look at is how bees unique experiences
  • 01:04:27also affect the genetic age and age.
  • 01:04:31Next slide, please.
  • 01:04:33And so with that.
  • 01:04:34As we've rushed through
  • 01:04:36this this very dense paper,
  • 01:04:39we would like to thank our mentors,
  • 01:04:41Derek Gordon, Michael Black also
  • 01:04:43helped support us in the in this.
  • 01:04:46In this sax mentors.
  • 01:04:48If you.
  • 01:04:51And also Chris said and young
  • 01:04:53son also have have been.
  • 01:04:55Instrumental in regards to helping
  • 01:04:57guide us in regards to kind of
  • 01:04:59developing this project and and what
  • 01:05:00steps to do after this project is
  • 01:05:02complete and finally we would like
  • 01:05:04to thank the the lesson family and
  • 01:05:06foundation for this opportunity and
  • 01:05:08both of our financial grants in
  • 01:05:10regards to supporting this work.
  • 01:05:17Thank you both for a great presentation.
  • 01:05:19And again, I applaud not only the
  • 01:05:21the science, but the collaboration.
  • 01:05:23Well done, we are in the interest of
  • 01:05:26time going to go straight on to our
  • 01:05:29last presentation on our honorable
  • 01:05:30mention to the loss of an award.
  • 01:05:32And I want to invite broad right
  • 01:05:35to introduce the entire Anderson.
  • 01:05:40Thank you so much
  • 01:05:41and good morning.
  • 01:05:42My name is Darwin Boatwright and
  • 01:05:44I and assistant professor in the
  • 01:05:46Department of Emergency Medicine,
  • 01:05:47and I've studied bias and
  • 01:05:48discrimination and medical education.
  • 01:05:50Today I have the distinct honor of
  • 01:05:52introducing doctrine and Tara Anderson,
  • 01:05:53who will present some of our work
  • 01:05:54on the prevalence and influence of
  • 01:05:56microaggressions in medical school.
  • 01:05:58Doctor Anderson has been a long
  • 01:06:00standing member of the old community,
  • 01:06:02having graduated from Yale University,
  • 01:06:03Yale School of Medicine,
  • 01:06:05and is now a member of the illustrious
  • 01:06:07Department of Psychiatry at Yale.
  • 01:06:08I thought the honor to collaborate.
  • 01:06:10And learn from Doctor Anderson.
  • 01:06:11Since we first met in 2015 and we
  • 01:06:13began discussing the possibility of
  • 01:06:15science and medical literature examining
  • 01:06:17racism and medicine
  • 01:06:18and brainstorming ways we could
  • 01:06:20address this gap in knowledge.
  • 01:06:21These discussions produce some
  • 01:06:22of the work Doctor Anderson
  • 01:06:23will share with you today.
  • 01:06:25Examining the prevalence of
  • 01:06:27microaggressions and their
  • 01:06:28association with medical
  • 01:06:29student mental health and also
  • 01:06:31medical student satisfaction.
  • 01:06:32Doctor Anderson.
  • 01:06:36Hello everyone, we're happy to be here and
  • 01:06:38we'll get started on the presentation.
  • 01:06:40It's going to be a quick one
  • 01:06:42so next slide please Chris.
  • 01:06:45So I want to start with
  • 01:06:47psychiatrist Chester Pierce,
  • 01:06:48who originally defined microaggressions
  • 01:06:50directly quoting from him.
  • 01:06:51He defined them as the subtle, stunning,
  • 01:06:54often automatic and nonverbal exchanges
  • 01:06:56which are put downs of blacks by offenders.
  • 01:06:59The offensive mechanisms used
  • 01:07:01against blacks are often innocuous.
  • 01:07:03The cumulative weight of their
  • 01:07:05never ending burden is the major
  • 01:07:06ingredient in black white interactions.
  • 01:07:08Today migrations are regarded as casual,
  • 01:07:11verbal or nonverbal slides,
  • 01:07:13whether intentional or unintentional,
  • 01:07:14which communicate.
  • 01:07:15Rogatory messages based on the targets
  • 01:07:18modules, marginalized group membership,
  • 01:07:19and here are some examples of
  • 01:07:22different types of microaggressions,
  • 01:07:24illustrated from the I2 hashtag
  • 01:07:27I2M Harvard campaign.
  • 01:07:28So you can see them here.
  • 01:07:31So our study objectives.
  • 01:07:33Next slide please.
  • 01:07:35We sought to characterize the experiences of
  • 01:07:37microaggressions for US medical students.
  • 01:07:39How frequently did they occur,
  • 01:07:41and who was most likely to experience them?
  • 01:07:43Next slide.
  • 01:07:46We wanted to know if microagressions
  • 01:07:47we want to test the association
  • 01:07:50between microaggressions and medical
  • 01:07:51student well being and mental health.
  • 01:07:54Next slide.
  • 01:07:55We also wanted to assess the
  • 01:07:58association between microaggressions
  • 01:07:59and medical school satisfaction.
  • 01:08:01Next slide,
  • 01:08:02we distributed a cross sectional
  • 01:08:04Internet based anonymous survey
  • 01:08:06to medical students in the US
  • 01:08:08between 2016 and 2017.
  • 01:08:09Questions on microaggressions were
  • 01:08:11adapted from the racial ethnic
  • 01:08:13microaggression scale and we asked
  • 01:08:15if respondents had experienced
  • 01:08:16various types of microaggressions
  • 01:08:17how frequently they occurred and the
  • 01:08:19reasons they believe they were targeted.
  • 01:08:21These questions did not directly mention
  • 01:08:24racism, prejudice, or demographics.
  • 01:08:26And participants were instructed to
  • 01:08:28include microaggressions committed by
  • 01:08:30fellow students, residents and faculty,
  • 01:08:31and so here's an example of one of
  • 01:08:34those questions. Next slide, please.
  • 01:08:38Questions on medical school satisfaction,
  • 01:08:40like this one, were adapted from the
  • 01:08:43Institutional Betrayal Questionnaire
  • 01:08:44and then afterwards respondents filled
  • 01:08:46out the PHQ 2 PHQ 2 depression screen,
  • 01:08:49which is 2 item depression screen
  • 01:08:51and their demographic information.
  • 01:08:53Next slide. Here are the demographics
  • 01:08:55of our final sample.
  • 01:08:57We had 759 respondents from
  • 01:08:59over 100 medical schools,
  • 01:09:01so it was a substantial sample.
  • 01:09:03Next slide.
  • 01:09:05What we found the experience of
  • 01:09:08microaggressions was incredibly common.
  • 01:09:1098.7 participants reported
  • 01:09:12having experienced at least one
  • 01:09:13microaggression in medical school,
  • 01:09:1733.9% reported having experienced
  • 01:09:18a microaggression almost daily
  • 01:09:20in medical school.
  • 01:09:22Next slide.
  • 01:09:24The most common attributions of
  • 01:09:25the reasons people felt they were
  • 01:09:27experiencing microaggressions were gender,
  • 01:09:29race, ethnicity, and age.
  • 01:09:31As you can see here next slide.
  • 01:09:35So respondents also described the
  • 01:09:37microaggressions they had experienced,
  • 01:09:38so here's 1 the respondents said
  • 01:09:40I had an older male physician
  • 01:09:42as a first year mentor.
  • 01:09:44I shattered him every other week in his
  • 01:09:45clinic for my intro to clinical medicine.
  • 01:09:47Required course he would regularly
  • 01:09:49introduce me to patients as a pretty
  • 01:09:51face to talk to while you wait.
  • 01:09:53Next slide,
  • 01:09:54I choose to wear my hair and it's
  • 01:09:56natural state sometimes and one
  • 01:09:57of my professors made a comment.
  • 01:09:59Did you get electrocuted after that
  • 01:10:01comment was made him and another
  • 01:10:03professor preceded to laugh.
  • 01:10:04Next slide.
  • 01:10:09Next slide, please.
  • 01:10:12So here are the result and more on
  • 01:10:15the experiences of microaggressions.
  • 01:10:17About half the respondents experienced
  • 01:10:19at least one microaggression a week.
  • 01:10:21So we divided the cohort into two groups,
  • 01:10:23a higher exposure group which experienced
  • 01:10:25microaggressions at least once a week and
  • 01:10:28a lower exposure group which experienced
  • 01:10:29microaggressions less frequently.
  • 01:10:31As you can see,
  • 01:10:32students who identified as black,
  • 01:10:34Asian, multiracial and being a
  • 01:10:35female sex were the most likely to
  • 01:10:37be in the higher exposure group.
  • 01:10:39We also performed an intersectional.
  • 01:10:40Analysis of race and sex assigned
  • 01:10:42at birth which showed that white
  • 01:10:44males reported the lowest average
  • 01:10:46microaggression frequency scores and
  • 01:10:48black females reported the highest
  • 01:10:50mean microaggression frequency scores
  • 01:10:52within all racial or ethnic groups.
  • 01:10:56Mean microaggression scores were
  • 01:10:57lower for meals than for females.
  • 01:11:00Next slide please.
  • 01:11:02So here also this is the correlation
  • 01:11:04between the the PHQ 2 depression screen
  • 01:11:07and the frequency of microaggression.
  • 01:11:09So we divided the microaggression
  • 01:11:11frequency score into 4 quartiles,
  • 01:11:12and we found that as the frequency of
  • 01:11:16experiencing microaggressions increased,
  • 01:11:17the likelihood of respondent having a
  • 01:11:19positive depression screen increased
  • 01:11:21quite substantially in a dose response
  • 01:11:23relationship even after adjusting
  • 01:11:25for demographic factors such as race,
  • 01:11:27ethnicity, sex, SES,
  • 01:11:29urine, medical school,
  • 01:11:30clinical experience, etcetera.
  • 01:11:32Next slide,
  • 01:11:33please.
  • 01:11:35Compared to the lower exposure group,
  • 01:11:37respondents with higher microaggression
  • 01:11:38exposure were less likely to recommend
  • 01:11:41their medical school to friends
  • 01:11:42less likely to donate to their
  • 01:11:44medical school after graduation,
  • 01:11:45and less likely to consider staying
  • 01:11:47at their institution for residency.
  • 01:11:49Next slide, please.
  • 01:11:51In addition,
  • 01:11:52higher exposure respondents were over
  • 01:11:53three times more likely to have this.
  • 01:11:56This is past behavior three times more
  • 01:11:58likely to have missed class because
  • 01:12:01the environment was unwelcoming.
  • 01:12:02They were also four times,
  • 01:12:04nearly four times.
  • 01:12:05More likely to consider medical school
  • 01:12:07transfer and medical school withdrawal
  • 01:12:09compared to the lower exposure residents.
  • 01:12:12Next slide please.
  • 01:12:14So implications increase frequency
  • 01:12:17of experiencing microaggressions
  • 01:12:19may impact medical students
  • 01:12:21health mental health negatively.
  • 01:12:23They are common experience and
  • 01:12:24bipac and female medical students
  • 01:12:26experience them more frequently and
  • 01:12:29students with multiple marginalized
  • 01:12:30identities such as black women
  • 01:12:32are impacted the most next slide.
  • 01:12:36As our data on avoiding class or
  • 01:12:38considering withdrawal from medical
  • 01:12:39school suggests the experience of
  • 01:12:40microaggressions may increase the
  • 01:12:42attrition of diverse medical trainees,
  • 01:12:44which would imperil efforts to
  • 01:12:45diversify the physician workforce,
  • 01:12:47possible interventions to decrease
  • 01:12:49microaggressions include education,
  • 01:12:51improved reporting and remediation,
  • 01:12:53and incorporating racial attitudes
  • 01:12:55assessments into admissions and hiring.
  • 01:12:58And finally,
  • 01:12:58we want to propose reevaluating
  • 01:13:00the use of the word microaggression
  • 01:13:02and replacing it with specific
  • 01:13:04terms such as racism or sexism.
  • 01:13:06Our findings show serious associations
  • 01:13:09between microaggressions and
  • 01:13:10outcomes for medical student,
  • 01:13:12and we hope our research helps
  • 01:13:13dispel the ideas that these
  • 01:13:15microaggressions are a lower priority
  • 01:13:17or or an inconsequential issue in
  • 01:13:19medical education and training.
  • 01:13:21Next slide you can click
  • 01:13:23through the references.
  • 01:13:25There's about 3-4 pages,
  • 01:13:26so I want to thank thank my mentors,
  • 01:13:28down Boatwright and Anna Reisman,
  • 01:13:30the Lussman Family Foundation
  • 01:13:32and award committee.
  • 01:13:34Of course, our illustrious coauthors.
  • 01:13:37Especially the brilliant doctor let
  • 01:13:39and you can go to the last slide.
  • 01:13:42And also of course,
  • 01:13:43thank you to my friends and family,
  • 01:13:44especially my mom and dad who
  • 01:13:46are actually tuning in from Sri
  • 01:13:48Lanka and who are pictured here.
  • 01:13:49So and thank you to you all for listening.
  • 01:14:01Thank you so much the Antara rounding
  • 01:14:05out our presentations. And I see your.
  • 01:14:08I see your parents there welcome.