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Speaker 1: Suicide is one of the leading causes of death around

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Speaker 1: the world, taking the lives of about a million people

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Speaker 1: each year around the world, taking more lives than all wars,

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Speaker 1: all homicide combines. We're each more likely to die by

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Speaker 1: our own hand than we are by someone else's.

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Speaker 2: The family of the teenager who died by suicide alleges

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Speaker 2: of Open AI's chagipts to play blackmailed with AI generated

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Speaker 2: nude photos that he died by suicide.

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Speaker 1: Doctor Matthew Knock, a world renowned expert on self harm,

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Speaker 1: pioneering new ways to understand and treat these behaviors.

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Speaker 2: What's the biggest myth about suicide that you think it's

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Speaker 2: important to dismantle.

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Speaker 1: If someone really wants to die, then we shouldn't try

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Speaker 1: and help them. It's destiny, not at all true. Ninety

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Speaker 1: percent of people who try and kill themselves say I

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Speaker 1: didn't want to die per se. I wanted to escape

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Speaker 1: from seemingly intolerable How.

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Speaker 2: Many people actually moved from suicidal thoughts to making a plan?

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Speaker 1: In the US, about fifteen percent of people think about suicide.

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Speaker 1: One third of people who ever think about suicide will

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Speaker 1: ever make a suicide attempt. Those who attempt and survive.

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Speaker 1: One in five will make another attempt.

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Speaker 2: For those people who have attempted suicide but then survived,

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Speaker 2: do they regret it?

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Speaker 1: Three quarters said the first thing they thought was they

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Speaker 1: regretted it immediately.

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Speaker 2: Two thirds of people who died by suicide told someone beforehand,

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Speaker 2: why aren't we catching those warning signs earlier?

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Speaker 1: The number one health and wellness podcast.

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Speaker 2: Jay sheid seelyet, Hey, everyone, welcome back to On Purpose,

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Speaker 2: the number one health podcast in the world. Thanks to

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Speaker 2: each and every one of you that come back every

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Speaker 2: week to listen, learn and grow. Now you know that

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Speaker 2: our mission is to make the world happier, healthier, and

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Speaker 2: more healed. And today's guest is someone who has dedicated

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Speaker 2: his life to do just that through his work. I

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Speaker 2: had the fortune of speaking to our guest a few

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Speaker 2: months back when I was interviewing him for a book

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Speaker 2: that I was writing, and this is the next book

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Speaker 2: that I'm working on. And while I was doing that,

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Speaker 2: I was so fascinated by his story, his research, the

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Speaker 2: insights he was sharing that I said I had to

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Speaker 2: have him on the podcast. Today's guest is doctor Matthew Knock,

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Speaker 2: a professor of psychology at Harvard University and director of

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Speaker 2: the Laboratory for Clinical and Developmental Research. Doctor Knock's work

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Speaker 2: focuses on understanding why people engage in self harm, with

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Speaker 2: a particular emphasis on suicide through large scale surveys, lab experiments,

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Speaker 2: and clinical studies. His research aims to uncover how suicidal

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Speaker 2: behaviors develop, how to predict them, and most importantly, how

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Speaker 2: to prevent them. Please welcome to On Purpose, doctor Matthew Knock. Matthew,

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Speaker 2: it's great to have you here.

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Speaker 1: Thank you so much for having me. Really really appreciate

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Speaker 1: you having me on the show.

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Speaker 2: Yeah, this is such an important issue. It's an issue

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Speaker 2: that I think is underspoken about. It still feels taboo.

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Speaker 2: It feels like it's stayed far away from the mainstream

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Speaker 2: and lessen until something happens in the space that then

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Speaker 2: puts a spotlight on it, and then it seems to

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Speaker 2: disappear again. I wanted to ask you what brought you

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Speaker 2: to do this work? How did you become passionate and

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Speaker 2: committed to doing this work in the first place.

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Speaker 1: This is a big problem. It's been around for a

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Speaker 1: long time. We don't talk about it a lot, so

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Speaker 1: just want to stay from the outset that I really

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Speaker 1: really appreciate you shining light on the problem of suicide.

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Speaker 1: I wasn't looking for it. I was actually I was

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Speaker 1: an undergraduate twenty years old, and I was studying, actually

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Speaker 1: in London, doing a semester abroad, and I was placed

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Speaker 1: in an externship sort of clinical practical placement in psychiatric hospital.

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Speaker 1: And I was assigned to a unit with self injurious, suicidal,

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Speaker 1: violent patients. And I was just really struck and captivated,

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Speaker 1: overwhelmed by the problem of suicide and self injury. And

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Speaker 1: there are patients there who were cutting themselves, burning themselves,

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Speaker 1: trying to kill themselves. And I was really alarmed. I

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Speaker 1: was confused, perplexed, inspired by the work of the staff,

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Speaker 1: and at the time wanted to be a clinician. I

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Speaker 1: wanted nothing. I do a lot of research now didn't

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Speaker 1: didn't like the idea of research. And I thought, if

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Speaker 1: I can understand suicide and know how to better treat it,

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Speaker 1: this is really, you know, for me jumping in the

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Speaker 1: deep end of the pool. Everything else should be easier

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Speaker 1: after this. And I, you know, fast forward thirty years later,

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Speaker 1: I haven't gotten out of the field. Well kept you

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Speaker 1: in it, but there are so much work to be done.

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Speaker 1: I mean, it's such a challenging problem, and it's it

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Speaker 1: grabbed me philosophically. I was a philosophy biology interested young

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Speaker 1: person and found psychology and suicide touches so many different

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Speaker 1: disciplines epidemiologically, public health wise, it's a huge taker of life. Philosophically,

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Speaker 1: it's something that virtually every major philosopher is focused on.

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Speaker 1: Camu called it the one truly serious philosophical problem, and scientifically,

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Speaker 1: there's just so much work to be done, and so

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Speaker 1: much impact to try and have, and so many people

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Speaker 1: to try and help, and so much suffering underlying all

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Speaker 1: of this. I got pulled into it and have not stopped,

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Speaker 1: and I feel like I can't stop, and we can't

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Speaker 1: stop because there's so much, so much more work we

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Speaker 1: have to do.

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Speaker 2: What's the biggest myth about suicide that you think it's

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Speaker 2: important to dismantle before we dive in.

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Speaker 1: One of the biggest ones is there's so many One

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Speaker 1: of the biggest ones is that if someone really wants

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Speaker 1: to die, then we shouldn't try and help them. That

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Speaker 1: you know someone wants to die, it's destiny and they're

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Speaker 1: going to kill themselves not at all true. Most people

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Speaker 1: who try and kill themselves are ambivalent, they don't want

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Speaker 1: to die. And I've talked to this point thousands of

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Speaker 1: people who've been struggling with suicidal thoughts. Ninety percent of

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Speaker 1: people who try and kill themselves say I didn't want

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Speaker 1: to die per se. I wanted to escape from seemingly

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Speaker 1: intolerable pain. And for most people, they're able to work

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Speaker 1: through that and survive. And most people who try and

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Speaker 1: kill themselves don't end up dying by suicide. So there's

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Speaker 1: a lot that we could do to better help people

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Speaker 1: who are having suicidal thoughts and who are a risk

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Speaker 1: for suicide.

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Speaker 2: How many of the people that attempt to commit suicide

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Speaker 2: actually not only go through with it, but ultimately complete

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Speaker 2: complete the belief.

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Speaker 1: I'll walk through the pathway. So about in the US,

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Speaker 1: about fifteen percent of people think about suicide. They say

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Speaker 1: they've had serious thoughts of suicide at some point in

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Speaker 1: their life. About five percent of people try to kill

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Speaker 1: themselves they make a suicide attempt, So only about one

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Speaker 1: third of people who ever think about suicide will ever

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Speaker 1: make a suicide attempt. Of those who attempt and survive,

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Speaker 1: twenty percent or so one in five will make another attempt,

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Speaker 1: and a small percentage we'll end up dying by suicide.

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Speaker 1: Some think five percent or se of five to ten percent.

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Speaker 1: So there's a lot more suffering with suicidal thoughts and

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Speaker 1: a lot more non lethless suicide attempts than there are

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Speaker 1: suicide deaths. At the same time, Suicide is one of

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Speaker 1: the leading causes of death in the US and around

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Speaker 1: the world. One of the most staggering facts, and I'll

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Speaker 1: mention too one is suicide takes more life than all wars,

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Speaker 1: all homicide, all interpersonal violence combined. So if you think

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Speaker 1: about it, we're each more likely to die by our

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Speaker 1: own hand than we are by someone else's, which every

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Speaker 1: time I think about that, everything I say is startling.

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Speaker 1: We worry a lot about you know, in the news,

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Speaker 1: there are wars happening. We lock our doors, we lock

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Speaker 1: our windows, We're concerned about people coming for us and

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Speaker 1: attacking us. We're more likely to die by our own

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Speaker 1: hand than we are by someone else's, And that continues

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Speaker 1: to really perplex me.

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Speaker 2: And how many people who attempt suicide will do it again.

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Speaker 1: About twenty percent of people who make a suicide attempt

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Speaker 1: and survive will go on to make another attempt, and

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Speaker 1: it's often within the next year. So when someone first

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Speaker 1: has thoughts of suicide in their life, that next year

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Speaker 1: is the highest risk time for making a suicide attempt.

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Speaker 1: When someone makes a suicidettempt, if they're going to make

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Speaker 1: another attempt, it's going to come right after that. And

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Speaker 1: the highest risk time for suicide death ever is in

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Speaker 1: the weeks after a person leaves a psychiatric hospitalization for

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Speaker 1: the treatment of suicidal thoughts or behaviors, which is little counterintuitive,

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Speaker 1: so you would think that a person just got treatment,

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Speaker 1: they should be okay, they're out of the woods. Not so.

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Speaker 1: A lot of times people go into the hospital and

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Speaker 1: get maybe an antidepressant does take two to four weeks

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Speaker 1: to have any effect, and people are discharged from the

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Speaker 1: hospitals today in a week or so. And we're good

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Speaker 1: at finding people at risk, we're not good at getting

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Speaker 1: them fully treated in the short period of time the

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Speaker 1: hospitalation is typically happening. So I would say keep a

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Speaker 1: close eye on people if someone you know or if

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Speaker 1: you yourself have been hospitalized for suicide risk. Just because

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Speaker 1: a person's release doesn't mean that things are totally fine.

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Speaker 1: Now keep an eye on them, stay in touch, engage

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Speaker 1: in treatment, make sure they're engaged in treatment.

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Speaker 2: Yeah, can you walk me through the different stages of

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Speaker 2: suicidal thoughts and behaviors and action so we can actually

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Speaker 2: understand it from a more detailed perspective, because I think

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Speaker 2: for anyone who's not aware, like myself, it seems like

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Speaker 2: there's suicidal thoughts and then there's the act. But what

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Speaker 2: does it really mean?

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Speaker 1: Like, so as we as researchers as clinicians think about

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Speaker 1: a few steps in the pathway to suicide, and the

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Speaker 1: big sort of sign post or stopped along the way

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Speaker 1: is first people think about suicide, so having suicidal thoughts

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Speaker 1: or what we call suicide ideation, having ideas about suicide,

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Speaker 1: and that's a big outcome we focus on. We try

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Speaker 1: and understand what gets some people to think about suicide

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Speaker 1: while others don't. Next is suicide planning, so actually formulating

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Speaker 1: a plan to kill yourself more intentional. Some people have

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Speaker 1: suicidal thoughts and it's really aversive to them, and they

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Speaker 1: don't have plans. You just have the thoughts. They might

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Speaker 1: have them involuntarily and be really spooked by them, but

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Speaker 1: some go on About a third go on to make

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Speaker 1: a suicide plan. They think of a place, a time,

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Speaker 1: method to kill themselves. And then the next is engaging

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Speaker 1: in behavior, engaging in a suicide attempt, taking steps to

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Speaker 1: intentionally end your own life. And as I mentioned, a

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Speaker 1: lot of people will do that and not die by suicide.

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Speaker 1: And then the next is, of course, dying by suicide.

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Speaker 2: For someone who dies by suicide, the making a plan

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Speaker 2: piece makes it believe that there is preparation and then premeditation. Yeah,

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Speaker 2: it's not something that happens at random.

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Speaker 1: There often is. There's a lot of variability here. So

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Speaker 1: some people will die by suicide in a really planful way.

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Speaker 1: They'll make a plan, they'll leave a note. Often the

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Speaker 1: notes are very practical. I made the last mortgage payment,

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Speaker 1: and so you know, here's where the keys are very

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Speaker 1: practical and to the point, not always, but a lot

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Speaker 1: of the time, a huge percentage of the time. They're

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Speaker 1: more impulsive. A person might have thought about suicide and

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Speaker 1: it's only in a few hours before the event that

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Speaker 1: they make a decision they're going to end their life.

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Speaker 1: It's rare that it comes out of nowhere that a

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Speaker 1: person's walking along living their life and all of a

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Speaker 1: sudden they have a thought of suicide and die by suicide.

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Speaker 1: It usually is a much slower build up that there's distress,

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Speaker 1: there's depression, there's anxiety, there's thoughts of suicide. Sometimes the

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Speaker 1: thoughts of suicide can last years before a person takes action.

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Speaker 1: Most of the time, though, if someone's going to make

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Speaker 1: a suicide attempt, it's within the first year after onset

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Speaker 1: of suicidal thoughts, so that the thoughts come on as

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Speaker 1: as the highest risk time, but it's not always planned out.

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Speaker 2: What are some of the most Looking at each of

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Speaker 2: those areas, what are some of the most common reasons

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Speaker 2: people find themselves having suicidal thoughts?

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Speaker 1: Far and away, the biggest reason is escape. If I

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Speaker 1: had to give one message and try and demystify suicide

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Speaker 1: for those who are struggling with who haven't had suicidal

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Speaker 1: thoughts and are struggling with understanding, why would someone ever

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Speaker 1: think about suicide again? Nine out of ten times it's

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Speaker 1: I don't want to be dead, per se. I want

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Speaker 1: to escape from this seemingly intolerable pain. People describe it

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Speaker 1: often like trying to get out of a burning room.

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Speaker 1: I don't want to die, I just I can't I

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Speaker 1: don't think I can take this pain anymore. And so

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Speaker 1: that guess people thinking a lot about suicide a lot

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Speaker 1: of the time. And what is that pain a lot

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Speaker 1: of time? It's depression. So depression is one of the

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Speaker 1: strongest predictors of having suicidal thoughts. And depression takes many

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Speaker 1: forms and manifests differently. Some people describe it as having

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Speaker 1: like a weighted vest on, some people describe it as

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Speaker 1: as just really psychological pain, as despair, But it is

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Speaker 1: one of the biggest drivers of having thoughts about suicide. Interestingly,

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Speaker 1: the things that predict who acts on their suicidal thoughts

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Speaker 1: are different. Depression doesn't really predict acting in your suicidal thoughts.

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Speaker 1: What does is anxiety, aggressiveness, poor behavioral control, drug use,

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Speaker 1: alcohol over alcohol use. These things predict acting on suicidal thoughts,

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Speaker 1: and it's the combination of these things that we think

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Speaker 1: really puts people at risk.

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Speaker 2: The symptoms of someone thinking about suicide are the different different, yeah,

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Speaker 2: to the ones that actually act on it.

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Speaker 1: Yeah, And I'll go a step further. This is one

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Speaker 1: of the more interesting findings I've come across. Your parent's

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Speaker 1: history of depression. If you have a parent with depression,

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Speaker 1: that increases your risk of thinking about suicide, and it

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Speaker 1: actually increases the length of your suicidal thoughts, the persistence

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Speaker 1: in years of your suicidal thinking, but doesn't predict you

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Speaker 1: acting on your suicidal thoughts. What does is your parent's

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Speaker 1: history of antisocial behavior panic disorder, so hyper arousal tendency

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Speaker 1: to act impulsively. This predicts you acting on your suicidal thoughts.

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Speaker 1: So we think these different pieces of the pathway to

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Speaker 1: suicide might be passed down differently, genetically familiarly.

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Speaker 2: When you talk about those almost extreme feelings of escaping, Yeah,

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Speaker 2: that idea of running out of a burning room. Is

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Speaker 2: there a correlation between that feeling and money more or

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Speaker 2: relationships or like life situation or is it across the

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Speaker 2: board And we don't have clarity on that yet.

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Speaker 1: Yeah, we don't have a lot of clarity. I think

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Speaker 1: pain manifests differently for different people. And one thing about

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Speaker 1: suicide is there are sociodemographic factors that predict who becomes suicidal.

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Speaker 1: For instance, for gender, women are more likely to have

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Speaker 1: suicidal thoughts and engage in not only though suicidal behavior.

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Speaker 1: Men are likely to die by suicide by a ratio

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Speaker 1: of about four to one and that's true and virtually

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Speaker 1: every country around the world. There's a lot of other

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Speaker 1: things that go into suicidal thoughts and behaviors that put

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Speaker 1: a person at risk, that lead to that sort of

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Speaker 1: that feed that fire. And it's different for different people.

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Speaker 1: So relationship problems predict, legal problems predict, but suicide knows

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Speaker 1: no bounds. Where it comes to income, there aren't buying

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Speaker 1: large big financial differences. People at all income levels are

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Speaker 1: almost equally at risk. So socioeconomic factors, education levels, income levels,

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Speaker 1: suicide doesn't really discriminate. It's a problem for all, almost

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Speaker 1: all members of society.

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Speaker 2: What does that tell us?

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Speaker 1: There's a lot of roads leading to rome. I mean,

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Speaker 1: there's a lot of ways to put a person at

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Speaker 1: risk for suicide. And again, I've been trying to figure

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Speaker 1: out what is the thing, what is the motivator? It's

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Speaker 1: this burning room, it's this fire. So that's where I

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Speaker 1: usually start scientifically and where I start clinically. I'm a

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Speaker 1: licensed psychologist, so I have worked with patients over the

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Speaker 1: years try and figure out the motivation and what is

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Speaker 1: it for this person that's leading them to want to escape?

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Speaker 1: What are they trying to escape from? What is the

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Speaker 1: pain for this person. I think attempts to try and

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Speaker 1: find a silver bullet of Oh, its relationship or oh

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Speaker 1: it's finance, or oh it's a mental illness are a

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Speaker 1: little bit misguided. They're one piece of the puzzle. I

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Speaker 1: think we've got to start or I think it's helpful

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Speaker 1: to start with. What is a person's experience is? What

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Speaker 1: are they trying, what's making them suicidal, What's what's making

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Speaker 1: them not want to live anymore? What is it for them?

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Speaker 1: Let's try and understand that and see if we can

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Speaker 1: figure out some way to solve that problem, help them

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Speaker 1: tolerate with their experience without dying, and then work backwards

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Speaker 1: from there.

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Speaker 2: Yeah, that makes a lot of sense, Like the idea

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Speaker 2: of seeing everyone's experience is unique to them and recognizing

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Speaker 2: what their burning room is right and not projecting an

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Speaker 2: external value or belief onto that and why it exists. Yeah,

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Speaker 2: you spoke a bit about this a couple of moments ago.

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Speaker 2: What are the key differences between how men and women

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Speaker 2: think and approach suicide?

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Speaker 1: As I said, there's big gender differences. So women are

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Speaker 1: much more at risk for thinking about suicide and for

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Speaker 1: engaging in suicidal behavior. Men are much more at risk

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Speaker 1: for dying by suicide, and we think that's that different

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Speaker 1: is due to women being much having much higher rates

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Speaker 1: of anxiety and depression, which are more closely linked with

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Speaker 1: suicidal thoughts, men having higher rates of alcohol and drug

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Speaker 1: use disorders and aggressive behavior and impulsive behavior being more

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Speaker 1: linked with impulsive aggressive action, and we think those are

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Speaker 1: two of the big drivers of why we see those

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Speaker 1: gender differences and why they persist almost everywhere everywhere around

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Speaker 1: the world. There are some common allities across genders. In

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Speaker 1: terms of age, suicide is pretty rare in young people

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Speaker 1: meaning children in every country we've looked at around the world,

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Speaker 1: and we've looked at dozens of them. Suicide rates and

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Speaker 1: rates of suicidal thinking skyrocket and adolescents every country. They

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Speaker 1: even out in young adulthood, and then they go up

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Speaker 1: again later in life, and that increase later in life

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Speaker 1: is especially prominent among men. We think this is because women,

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Speaker 1: these are generalities, tend to be more socially connected, have

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Speaker 1: more friends, have more close relationships, tend to have fewer

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Speaker 1: of them, and later in life, when people hit retirement age,

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Speaker 1: men tend to be less connected. And we think this

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Speaker 1: lack of social connectedness, lack of reaching out for help

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Speaker 1: is what leads people to have this increase in suicide

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Speaker 1: later in life.

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Speaker 2: Wow. And so looking at the different ages, the first

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Speaker 2: was adolescens. Yeah, and the key reasons for that was we're.

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Speaker 1: Still trying to figure it out scientifically. What is it

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Speaker 1: about adolescence that increases risk. One of the leading explanations

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Speaker 1: is this imbalance that we see in adolescence in brain development,

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Speaker 1: where this is a little bit of an oversimplification. Parts

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Speaker 1: of the brain involved with emotionality, impulsive action, the limbic

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Speaker 1: system are ramping up in adolescence, but the breaks the

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Speaker 1: prefront the cortex isn't fully online until early adulthood, and

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Speaker 1: so we see huge increases in risk taking behavior, aggressive behavior,

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Speaker 1: alcohol use, drug use in adolescence. We also see huge

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Speaker 1: increases in depressed illness, anxiety disorders. We also see increases

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Speaker 1: in bipolar disorder, which is a huge contribt ter to

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Speaker 1: risk psychotic illness. So inadolescents, aspects of adolescent brain development

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Speaker 1: are coming online, likely leading to increases in psychopathology, leading

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Speaker 1: to increases in suicide risk.

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Speaker 2: Is there any difference between countries and ages, and.

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Speaker 1: No, there's differences in rates. So rates of suicidal thoughts

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Speaker 1: and behaviors and suicide death vary around the globe, and

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Speaker 1: we're still trying to understand why they're not explained by geography.

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Speaker 1: They're not explained by high, middle low income countries, so

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Speaker 1: we're trying to understand how, undoubtedly religion and culture player role.

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Speaker 1: There's also differences in reporting, so a lot of the

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Speaker 1: numbers we have, we think aren't completely accurate. Suicide is

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Speaker 1: still illegal in many countries around the world, and that's

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Speaker 1: going to influence how it gets reported.

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Speaker 2: Do you think we should be talking about suicide at

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Speaker 2: school because I was thinking about an analogy that you

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Speaker 2: gave around being in a burning room. Yeah, and I

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Speaker 2: was thinking that we were all trained what to do

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Speaker 2: in the event of a fire. We were all trained

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Speaker 2: what to do if you live in a country that

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Speaker 2: experienced earthquakes, And again, those two things are pretty not

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Speaker 2: many people are going to experience those, but we train

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Speaker 2: people because we believe it's a possibility. Yeah, when you're

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Speaker 2: saying fifteen percent of people are going to have suicidal thoughts,

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Speaker 2: do you think it's important that we almost equip everyone

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Speaker 2: with a safety plan or with the idea of what

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Speaker 2: to do when that happens.

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Speaker 1: Yeah, I do. You know, you look at what's happening

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Speaker 1: with school shootings in the US, and it's you know,

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Speaker 1: training of what to do. If there's a shooter, it's

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Speaker 1: more likely there's going to be someone who's suicidal, was

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Speaker 1: going to die by suicide, who's going to try and

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Speaker 1: kill themselves. So there's going to be a suicide cluster,

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Speaker 1: a number of kids who try and kill themselves. Again,

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Speaker 1: we know that asking about suicide, talking about suicide does

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Speaker 1: not make people suicidal. There are programs that go into

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Speaker 1: schools and do a little mini educational module about suicide

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Speaker 1: in health class or out of how class. Here's what

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Speaker 1: suicidal thoughts are, here's the suicidal behaviors are. Here's what

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Speaker 1: you can do to keep yourself safe. Here's effective interventions.

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Speaker 1: Here's what you do if someone you know is struggling

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Speaker 1: with suicdal thoughts. It's something that is being done on

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Speaker 1: a small scale. Now I think it'd be wonderful to

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Speaker 1: see it done on a much larger scale. Could help

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Speaker 1: save lives.

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Speaker 2: Yeah, it just sounds like because it's something that fifteen

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Speaker 2: percent of people are going to think about at some point,

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Speaker 2: and if you thought about any of the other things

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Speaker 2: we get trained to do. It just feels like it

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Speaker 2: would be useful. Absolutely, it would be really absolutely.

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Speaker 1: I think again, it's taboo, it's stigma. It's fear that's

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Speaker 1: keeping it away from more more common use. And we've

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Speaker 1: shown over and over again there's no reason to be scared.

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Speaker 1: It's where it's not going to do harm. And again,

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Speaker 1: continued experimentation will be our friend here and we can

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Speaker 1: see are there some versions of this that do harm?

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Speaker 1: If so, then we won't do them. Are there ones

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Speaker 1: that work and help keep kids safe and prevent loss

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Speaker 1: of life due to suicide? Wonderful. Let's expand those and

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Speaker 1: make them available that people don't needlessly lose their kids

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Speaker 1: to suicide, or their friends or their loves.

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Speaker 2: When you talk about adolescents, I mean, I just came

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Speaker 2: across this story in the New York Times a couple

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Speaker 2: of months back. I'm sure you saw it, but it

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Speaker 2: was the family of a teenager who died by suicide

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Speaker 2: alleges open Aiyes, chat GPT is to blame. And for

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Speaker 2: those who don't know, I'm reading from the New York

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Speaker 2: Times article. It says the parents of Adam Rain who

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Speaker 2: died by suicide in April, claim in a new lawsuit

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Speaker 2: against Open AI that the teenager used chat GPT as

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Speaker 2: his suicide coach, and it goes on to say that

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Speaker 2: you know, after the suicide, they were searching through his

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Speaker 2: phone desperately looking for clues about what could have led

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Speaker 2: to the tragedy. They say, we thought we were looking

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Speaker 2: for Snapchat discussions, or Internet search history or some weird cult,

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Speaker 2: but they were led to find his conversations with CHATGBT.

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Speaker 2: I mean, I can't it's so tragic. And you know,

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Speaker 2: when you see Adam, it's this picture of him, it's

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Speaker 2: so hard to wrap your head around it. And when

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Speaker 2: I was reading that, I was just thinking, I can't

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Speaker 2: imagine being a parent right now where you're already scared

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Speaker 2: about bullying and how that affects children. You're scared about

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Speaker 2: online bullying to the level of whatever this gentleman was

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Speaker 2: sadly going through then leading to actually using AI as

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Speaker 2: his suicide coach. Walk me through how you think about

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Speaker 2: that when you read something like this.

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Speaker 1: It's tragic. As I mentioned, I think, as a parent

435
00:22:57,080 --> 00:23:02,320
Speaker 1: of three, I find it difficult to imagine anything more

436
00:23:03,000 --> 00:23:06,760
Speaker 1: tragic horrible than gut wrenching than losing a child to suicide.

437
00:23:06,760 --> 00:23:08,680
Speaker 1: So that's the first thing that comes to my mind. Always,

438
00:23:08,800 --> 00:23:12,560
Speaker 1: still having worked in this area for over twenty five years,

439
00:23:12,600 --> 00:23:15,679
Speaker 1: it's still a gut punch and a feeling like we

440
00:23:15,720 --> 00:23:19,399
Speaker 1: need to do more. It's an interesting time to be

441
00:23:19,440 --> 00:23:22,600
Speaker 1: a little cliche, but in terms of the possibilities of

442
00:23:23,320 --> 00:23:26,080
Speaker 1: machine learning, of generative AI, of all the data points

443
00:23:26,080 --> 00:23:31,080
Speaker 1: that we're getting, I think there's huge promise in these advances,

444
00:23:31,359 --> 00:23:34,119
Speaker 1: but there's also a lot of dangers, and for me,

445
00:23:34,359 --> 00:23:38,880
Speaker 1: it's very early days and it's tragic when we see

446
00:23:38,960 --> 00:23:41,200
Speaker 1: instances like this where and if you read through the

447
00:23:41,240 --> 00:23:44,120
Speaker 1: article which I saw as well, you can see pretty

448
00:23:44,160 --> 00:23:48,080
Speaker 1: clearly how the AI went, how things went awry, and

449
00:23:48,119 --> 00:23:52,919
Speaker 1: how things were missed, and how it's amazing how human

450
00:23:53,080 --> 00:23:56,359
Speaker 1: like these technologies currently are, but they're not human, and

451
00:23:56,400 --> 00:23:59,000
Speaker 1: they're missing things and in some cases. There's a number

452
00:23:59,000 --> 00:24:00,800
Speaker 1: of two or three store is this week on this

453
00:24:00,840 --> 00:24:03,920
Speaker 1: topic in the New York Times and other leading outlets.

454
00:24:04,400 --> 00:24:09,080
Speaker 1: The AI right now often gets it wrong, misses opportunities

455
00:24:09,080 --> 00:24:11,800
Speaker 1: to jump in humans missed them to but misses pretty

456
00:24:11,840 --> 00:24:14,480
Speaker 1: clear ones and in some cases encourages people and says, yeah,

457
00:24:14,520 --> 00:24:16,679
Speaker 1: it's based on what you're experiencing. It sounds like this

458
00:24:16,720 --> 00:24:19,960
Speaker 1: is a logical solution to your problem. And so it's

459
00:24:20,000 --> 00:24:24,080
Speaker 1: grewing up majorly and I think huge changes are needed

460
00:24:24,119 --> 00:24:27,840
Speaker 1: and how it's being used general of AI. Again, I

461
00:24:27,880 --> 00:24:30,680
Speaker 1: know it sounds cliche, but it's true. Is a tool,

462
00:24:31,160 --> 00:24:33,560
Speaker 1: and like a sharp knife, it can be used to help,

463
00:24:33,600 --> 00:24:36,720
Speaker 1: but it could be used to harm. And we haven't

464
00:24:36,800 --> 00:24:39,720
Speaker 1: yet figured out how to use generative AI to help

465
00:24:40,200 --> 00:24:43,720
Speaker 1: in this instance, and in some cases it's harming, no doubt.

466
00:24:43,720 --> 00:24:46,080
Speaker 1: In a lot of cases, generative AI large language models

467
00:24:46,080 --> 00:24:50,280
Speaker 1: are helping people one problem with suicide or problem with

468
00:24:50,600 --> 00:24:53,320
Speaker 1: one problem suicide. Overall, it's a huge taker of lives

469
00:24:53,480 --> 00:24:56,119
Speaker 1: and many people don't have access to care, and so

470
00:24:56,160 --> 00:24:59,480
Speaker 1: there's great potential here to use gener of AI to

471
00:24:59,520 --> 00:25:04,760
Speaker 1: help people, but it's not developed for this purpose and

472
00:25:05,280 --> 00:25:07,760
Speaker 1: it's going awry and it's contributing to the problem in

473
00:25:07,760 --> 00:25:08,360
Speaker 1: many cases.

474
00:25:08,520 --> 00:25:10,720
Speaker 2: I've seen so many people who heard of so many people,

475
00:25:10,800 --> 00:25:15,040
Speaker 2: have so many friends who use CHAGPT as therapy and

476
00:25:15,160 --> 00:25:18,359
Speaker 2: finding it very useful, finding it very smiful, and finding

477
00:25:18,480 --> 00:25:20,359
Speaker 2: very practical. And then you see this side and it

478
00:25:20,400 --> 00:25:25,680
Speaker 2: almost seems like there's a great need for guardrails connecting

479
00:25:25,680 --> 00:25:28,920
Speaker 2: to a human as soon as possible. I mean, yeah,

480
00:25:29,000 --> 00:25:31,640
Speaker 2: finding care before it goes away, because.

481
00:25:31,480 --> 00:25:33,760
Speaker 1: Yeah, there's from my perspective, there's a need for research.

482
00:25:34,000 --> 00:25:38,119
Speaker 1: So as in any area, everyone here I'm sure is

483
00:25:38,119 --> 00:25:40,640
Speaker 1: well intended. I'm sure open a high as well intended.

484
00:25:40,680 --> 00:25:42,280
Speaker 1: And a lot of the digital mental health startups that

485
00:25:42,280 --> 00:25:44,120
Speaker 1: are popping up all over the place are well intended.

486
00:25:44,400 --> 00:25:47,720
Speaker 1: But intentions in themselves don't always leave the positive outcomes,

487
00:25:47,720 --> 00:25:51,240
Speaker 1: and there's instances. I'll mention one platform that I won't

488
00:25:51,280 --> 00:25:54,480
Speaker 1: mention the name of had this wonderful app where it

489
00:25:54,560 --> 00:25:57,440
Speaker 1: could find people online who were suicidal and it would

490
00:25:57,440 --> 00:26:00,000
Speaker 1: inform their friends reach out to this person their struggle.

491
00:26:00,400 --> 00:26:02,960
Speaker 1: Very well intented, very logical. It was pulled down in

492
00:26:03,040 --> 00:26:05,119
Speaker 1: just a few days because it's totally backfired and it

493
00:26:05,160 --> 00:26:08,080
Speaker 1: was finding kids online who were being bullied and informing

494
00:26:08,080 --> 00:26:10,400
Speaker 1: people in the network, including the bully who is then

495
00:26:10,400 --> 00:26:12,320
Speaker 1: bullying them more. I see your suicidal, you should go

496
00:26:12,320 --> 00:26:14,280
Speaker 1: and kill yourself. And so the platform, to their credit,

497
00:26:14,560 --> 00:26:17,479
Speaker 1: pulled it down pretty quickly. Just one instance of the

498
00:26:17,520 --> 00:26:20,320
Speaker 1: contentions are good, the idea is a good one, but

499
00:26:20,440 --> 00:26:24,719
Speaker 1: without testing without experimentation, lots of bad stuff is going

500
00:26:24,760 --> 00:26:26,240
Speaker 1: to be put out there, and lots of ineffective things,

501
00:26:26,240 --> 00:26:27,760
Speaker 1: lots of harmful things. So this is where I think

502
00:26:27,760 --> 00:26:30,480
Speaker 1: science has to come in to evaluate things and see

503
00:26:30,520 --> 00:26:32,800
Speaker 1: what's working, what's not working. Let's pull down the things

504
00:26:32,800 --> 00:26:35,439
Speaker 1: that are not working, improve the things that are, and

505
00:26:35,480 --> 00:26:37,000
Speaker 1: get them to people so they can be helped.

506
00:26:37,280 --> 00:26:39,359
Speaker 2: Yeah, I mean, bullying isn't a new issue, but I

507
00:26:39,400 --> 00:26:43,320
Speaker 2: was reading some statistics that I was saying that cyber

508
00:26:43,400 --> 00:26:48,160
Speaker 2: bullying makes someone over three times more likely to contemplate suicide,

509
00:26:48,760 --> 00:26:51,720
Speaker 2: and then general in person bullying makes it two to

510
00:26:51,840 --> 00:26:57,359
Speaker 2: nine times more likely to consider suicide. It seems like humans,

511
00:26:57,920 --> 00:27:00,520
Speaker 2: especially at the adolescent age, when I feel like bullying is,

512
00:27:00,760 --> 00:27:03,359
Speaker 2: you know, the most prevalent. Sure, it seems like we

513
00:27:03,440 --> 00:27:06,840
Speaker 2: still haven't figured out a way to help young people

514
00:27:07,720 --> 00:27:09,560
Speaker 2: curb their desire to bully others.

515
00:27:09,960 --> 00:27:13,040
Speaker 1: No, it's a it's a I'm sure a perennial issue,

516
00:27:13,160 --> 00:27:17,800
Speaker 1: a timeless issue where we see it in non human animals,

517
00:27:17,840 --> 00:27:21,280
Speaker 1: where adolescent elephants will bully other elephants and the bully

518
00:27:21,320 --> 00:27:25,359
Speaker 1: other animals if there's not parents around constantly. Zoos have

519
00:27:25,480 --> 00:27:28,199
Speaker 1: sort of address this when it occurs. So it's a

520
00:27:28,200 --> 00:27:31,280
Speaker 1: problem and a lot of animals, a lot of organisms.

521
00:27:31,480 --> 00:27:34,040
Speaker 1: It's not new then it's not caused by the Internet

522
00:27:34,080 --> 00:27:37,280
Speaker 1: and AI, but it manifests in new ways, and it

523
00:27:37,320 --> 00:27:40,360
Speaker 1: manifests in ways. Bullying manifests in ways that parents don't

524
00:27:40,359 --> 00:27:43,879
Speaker 1: really know about. What kids are doing online is unknown

525
00:27:43,880 --> 00:27:46,480
Speaker 1: to parents, and the bullying now is taking new forms,

526
00:27:47,080 --> 00:27:49,840
Speaker 1: and it's undoto clinicians, it's undoto parents, and so it's

527
00:27:50,320 --> 00:27:53,800
Speaker 1: more insidious, and it's more around the clock it used

528
00:27:53,800 --> 00:27:55,640
Speaker 1: to be when I was young. Perhaps when you were young,

529
00:27:55,680 --> 00:27:58,800
Speaker 1: you go to school and you get bullied, or maybe

530
00:27:58,800 --> 00:28:01,080
Speaker 1: you bully or and then you go home and it's over.

531
00:28:01,200 --> 00:28:04,440
Speaker 1: And now it's round the clock, and that lack of

532
00:28:04,480 --> 00:28:06,840
Speaker 1: ability to escape, we think can be really problematic for

533
00:28:07,160 --> 00:28:10,320
Speaker 1: a lot of kids. And so here too, it's a tool,

534
00:28:10,359 --> 00:28:12,040
Speaker 1: and we've got to figure out how to best use

535
00:28:12,080 --> 00:28:13,840
Speaker 1: it and how to use it for good and for

536
00:28:13,920 --> 00:28:16,840
Speaker 1: improving well being and for improving mental health. We did

537
00:28:17,160 --> 00:28:21,400
Speaker 1: a qualitative study with suicidal adolescence in a local hospital

538
00:28:22,040 --> 00:28:24,160
Speaker 1: and we asked them about their social media use, their

539
00:28:24,200 --> 00:28:29,520
Speaker 1: online use, and what they describe was, yeah, there's bullying

540
00:28:29,680 --> 00:28:32,359
Speaker 1: there's social comparison. I see what other people have and

541
00:28:32,400 --> 00:28:35,280
Speaker 1: I don't. I feel really bad about myself. I'm learning

542
00:28:35,320 --> 00:28:37,640
Speaker 1: new ways to cut myself in ways that it can't

543
00:28:37,680 --> 00:28:40,480
Speaker 1: be discovered. So there's a lot of bad happening, there's

544
00:28:40,560 --> 00:28:42,640
Speaker 1: just as much good. And they're saying I'm learning skills,

545
00:28:42,640 --> 00:28:45,440
Speaker 1: I'm learning how to be mindful. I'm learning about ways

546
00:28:45,440 --> 00:28:47,600
Speaker 1: I can help calm myself down when I'm upset. So there's,

547
00:28:47,720 --> 00:28:50,440
Speaker 1: as with any tool, there's good and bad happening. We

548
00:28:50,480 --> 00:28:53,760
Speaker 1: just need to do a better job clinically, parentally, societally

549
00:28:53,800 --> 00:28:57,640
Speaker 1: scientifically at catching up and learning how to use this

550
00:28:57,680 --> 00:28:59,880
Speaker 1: in ways that are helpful and can improve mental health

551
00:29:00,440 --> 00:29:04,760
Speaker 1: and decrease with guardrails or otherwise the harms that it's

552
00:29:04,760 --> 00:29:05,400
Speaker 1: clearly doing.

553
00:29:05,560 --> 00:29:08,120
Speaker 2: This was the other one I saw on AI that

554
00:29:08,280 --> 00:29:13,000
Speaker 2: was heartbreaking. Was teen was blackmailed with AI generated nude

555
00:29:13,000 --> 00:29:16,720
Speaker 2: photos of himself. Then he died by suicide, and so

556
00:29:18,200 --> 00:29:22,000
Speaker 2: Eli died by suicide on February twenty eighth, twenty twenty five,

557
00:29:22,400 --> 00:29:26,120
Speaker 2: after receiving alarming texts to send a threatned to send

558
00:29:26,160 --> 00:29:29,200
Speaker 2: AI generated nude photos of the sixteen year old to

559
00:29:29,320 --> 00:29:32,480
Speaker 2: friends and family if he didn't hand over three thousand

560
00:29:32,520 --> 00:29:36,760
Speaker 2: dollars in the led sextortion scam. Sextortion often targets teens

561
00:29:36,760 --> 00:29:40,240
Speaker 2: and children and is becoming increasingly dangerous. According to the FBI.

562
00:29:40,320 --> 00:29:43,880
Speaker 2: The article read and so, yeah, it's such a I

563
00:29:43,920 --> 00:29:49,120
Speaker 2: mean again, I think as a parent, it's such a

564
00:29:49,160 --> 00:29:54,200
Speaker 2: stressful time. What have you seen have been What are

565
00:29:54,200 --> 00:29:58,400
Speaker 2: things parents can do to help to be involved in

566
00:29:58,440 --> 00:30:02,160
Speaker 2: the conversation, to be useful. What have you seen through

567
00:30:02,200 --> 00:30:06,600
Speaker 2: research that parents can shift and change about their behavior, attitude.

568
00:30:06,680 --> 00:30:09,960
Speaker 1: It's a great question. Reach out and have the conversation.

569
00:30:10,120 --> 00:30:13,520
Speaker 1: So talk about suicide. Talk with your child about suicide,

570
00:30:13,560 --> 00:30:16,640
Speaker 1: about what they're experiencing about their mental health. Suicide is

571
00:30:16,640 --> 00:30:20,480
Speaker 1: still incredibly taboo, and one of the biggest myths that

572
00:30:20,600 --> 00:30:23,560
Speaker 1: I hear is if I talk about suicide, if I

573
00:30:23,640 --> 00:30:25,920
Speaker 1: ask my child, or ask my spouse or ask my

574
00:30:25,960 --> 00:30:28,360
Speaker 1: friend about suicide, it's going to give them the idea

575
00:30:28,720 --> 00:30:30,720
Speaker 1: and make them suicidal. And so I'm not going to

576
00:30:30,720 --> 00:30:34,520
Speaker 1: say anything. And that's been shown experimentally time and again

577
00:30:34,680 --> 00:30:37,280
Speaker 1: to not be true. Oh, it doesn't does not happen.

578
00:30:37,360 --> 00:30:39,840
Speaker 1: And people have done experiments where they ask some kids

579
00:30:39,840 --> 00:30:42,400
Speaker 1: if they're suicidal and don't ask others and follow them up.

580
00:30:42,680 --> 00:30:45,040
Speaker 1: Kids who get asked about suicide, middle school students, high

581
00:30:45,040 --> 00:30:48,440
Speaker 1: school students, adults are not more distressed, They're not more suicidal.

582
00:30:48,600 --> 00:30:52,520
Speaker 1: If talking about suicide, asking about suicide made someone suicidal.

583
00:30:53,040 --> 00:30:54,680
Speaker 1: I've been talking about every day for the past twenty

584
00:30:54,680 --> 00:30:57,280
Speaker 1: five years. Our team has clinicians have I've talked with

585
00:30:57,280 --> 00:31:00,760
Speaker 1: my kids about suicide. It does not. The research shows

586
00:31:00,800 --> 00:31:03,120
Speaker 1: does not make people suicidal. So I would encourage parents

587
00:31:03,160 --> 00:31:06,440
Speaker 1: to have these conversations. I'd encourage any younger folks listening

588
00:31:06,640 --> 00:31:09,440
Speaker 1: have these conversations. If you think someone might be at risk,

589
00:31:10,120 --> 00:31:12,920
Speaker 1: ask them. Even if they're not at risk, ask them.

590
00:31:13,440 --> 00:31:16,320
Speaker 1: Have the conversation, and it signals. It communicates to your child,

591
00:31:16,400 --> 00:31:18,440
Speaker 1: to your friend, but it's okay to talk about this,

592
00:31:18,480 --> 00:31:19,800
Speaker 1: and that I'm a person that you can come to

593
00:31:19,920 --> 00:31:22,680
Speaker 1: and talk about what's happening with you, whether it's suicide

594
00:31:22,720 --> 00:31:23,280
Speaker 1: or mental health.

595
00:31:23,320 --> 00:31:25,920
Speaker 2: More broadly, what age did you have that conversation?

596
00:31:26,040 --> 00:31:28,160
Speaker 1: You have three kids?

597
00:31:28,360 --> 00:31:31,360
Speaker 2: Three? Okay? Three? Yeah? Are they old teenagers?

598
00:31:31,520 --> 00:31:36,640
Speaker 1: Our youngest is twelve, our oldest is nineteen, probably around

599
00:31:36,640 --> 00:31:37,160
Speaker 1: ten or so.

600
00:31:37,680 --> 00:31:38,840
Speaker 2: Wow, that's WoT.

601
00:31:39,120 --> 00:31:41,880
Speaker 1: It used to be the common thinking that kids can

602
00:31:42,080 --> 00:31:46,120
Speaker 1: even contemplate the idea of death until age ten twelve.

603
00:31:46,640 --> 00:31:52,280
Speaker 1: We're now seeing suicide among younger people, among children increasing dramatically,

604
00:31:53,000 --> 00:31:55,080
Speaker 1: and the US National in Student of perilf has put

605
00:31:55,080 --> 00:31:57,400
Speaker 1: a call for research on this problem with child suicide

606
00:31:57,400 --> 00:31:59,920
Speaker 1: to try and figure out what's happening and why is

607
00:31:59,920 --> 00:32:02,640
Speaker 1: it that younger people are now thinking about suicide and

608
00:32:02,680 --> 00:32:06,200
Speaker 1: dying by suicide more than they have been historically. And

609
00:32:06,280 --> 00:32:09,560
Speaker 1: so it's probably around h ten or so. I let

610
00:32:09,560 --> 00:32:12,680
Speaker 1: my kids know what I do and have conversations about

611
00:32:12,720 --> 00:32:16,120
Speaker 1: them and ask them questions about have they ever had

612
00:32:16,200 --> 00:32:20,560
Speaker 1: feelings of depression or anxiety or thoughts about suicide, perhaps

613
00:32:20,600 --> 00:32:22,600
Speaker 1: earlier than other parents. This is what I study, and

614
00:32:22,640 --> 00:32:24,640
Speaker 1: so this is what's on my mind a lot. But

615
00:32:24,720 --> 00:32:27,920
Speaker 1: I also have had instances personally professionally, I've seen instances

616
00:32:27,920 --> 00:32:30,520
Speaker 1: of people missing, missing the opportunity to talk to someone

617
00:32:30,560 --> 00:32:33,920
Speaker 1: about suicide, losing someone to suicide, and as we all

618
00:32:33,960 --> 00:32:38,000
Speaker 1: do if you've lost one to suicide, torture ourselves thinking back,

619
00:32:38,040 --> 00:32:40,040
Speaker 1: could I have said anything I, should I have asked?

620
00:32:40,040 --> 00:32:42,600
Speaker 1: Should I have done something differently? And knowing that it's

621
00:32:42,640 --> 00:32:45,000
Speaker 1: not harmful to ask someone about suicide it's not going

622
00:32:45,000 --> 00:32:47,200
Speaker 1: to increase their risk, just as it wouldn't if you

623
00:32:47,200 --> 00:32:49,760
Speaker 1: ask someone are you thinking about killing someone? If they're not,

624
00:32:50,200 --> 00:32:53,120
Speaker 1: they're very unlikely to now go out and want to

625
00:32:53,160 --> 00:32:56,360
Speaker 1: kill someone because you raise the idea. It's the same

626
00:32:56,440 --> 00:32:58,440
Speaker 1: kind of situation.

627
00:32:58,640 --> 00:33:01,000
Speaker 2: Well, how did that conversation go? Because I can imagine

628
00:33:01,040 --> 00:33:04,800
Speaker 2: that maybe when kids attend they maybe I've been listening.

629
00:33:04,880 --> 00:33:07,959
Speaker 2: Of course, you're a researcher and an expert in the field.

630
00:33:08,920 --> 00:33:10,200
Speaker 2: What about when kids are kind of like I don't

631
00:33:10,200 --> 00:33:12,160
Speaker 2: want to talk about that. Mom and dad like I'm

632
00:33:12,200 --> 00:33:14,720
Speaker 2: not interested in having this conversation with you, which seems

633
00:33:14,760 --> 00:33:17,200
Speaker 2: like a natural teenage response. I'm thinking, Yeah, if my

634
00:33:17,240 --> 00:33:19,200
Speaker 2: parents had asked me that at fourteen fifteen, i'd just

635
00:33:19,200 --> 00:33:20,520
Speaker 2: been like, what's wrong with you?

636
00:33:20,600 --> 00:33:22,840
Speaker 1: Yeah? And so my kids never want to talk to me,

637
00:33:22,880 --> 00:33:26,800
Speaker 1: So it's hard to tease that one. Yeah, I think

638
00:33:26,800 --> 00:33:29,479
Speaker 1: that's okay. I think it again. It still signals that

639
00:33:29,560 --> 00:33:32,680
Speaker 1: you're open to having that conversation with them. So even

640
00:33:32,680 --> 00:33:34,960
Speaker 1: if it seems to not go well and your child

641
00:33:35,040 --> 00:33:36,920
Speaker 1: says or your friend says, I don't want to talk

642
00:33:36,920 --> 00:33:39,800
Speaker 1: about it, you've at least let them know that it

643
00:33:39,920 --> 00:33:41,360
Speaker 1: is okay for them to come to you and that

644
00:33:41,400 --> 00:33:43,840
Speaker 1: you're someone who's open to talking about this. I've also

645
00:33:43,920 --> 00:33:46,240
Speaker 1: seen instances of kids saying I'm thinking about suicide and

646
00:33:46,240 --> 00:33:47,520
Speaker 1: the parents that we're not going to talk about this,

647
00:33:48,000 --> 00:33:51,200
Speaker 1: or you're just doing that for attention. That's a missed

648
00:33:51,200 --> 00:33:53,920
Speaker 1: opportunity to talk. And if the child's doing it for attention,

649
00:33:54,040 --> 00:33:56,760
Speaker 1: if I need to tell you that I'm going to

650
00:33:56,880 --> 00:33:59,880
Speaker 1: hurt myself or kill myself to communicate my pain, maybe

651
00:34:00,000 --> 00:34:02,800
Speaker 1: it's pain worth attending to and talking with the person about.

652
00:34:03,080 --> 00:34:06,000
Speaker 2: So even if someone's joking about it or laughing about

653
00:34:06,000 --> 00:34:08,200
Speaker 2: it or puts it in that kind of frame, it's

654
00:34:08,200 --> 00:34:10,560
Speaker 2: not something that should be disregarded because it's so extreme.

655
00:34:10,760 --> 00:34:14,200
Speaker 1: I'd follow up. I'd ask about it. About two thirds

656
00:34:14,200 --> 00:34:16,680
Speaker 1: sixty six percent of the time when people die by suicide,

657
00:34:16,719 --> 00:34:20,840
Speaker 1: they told someone ahead of time. They mentioned I'm thinking

658
00:34:20,840 --> 00:34:23,759
Speaker 1: about death, they might have joked about it, They've talked

659
00:34:23,760 --> 00:34:26,400
Speaker 1: about it in some way. So people are putting those

660
00:34:26,440 --> 00:34:28,799
Speaker 1: signals out there. I think it's worth following up and

661
00:34:28,840 --> 00:34:31,799
Speaker 1: asking someone, are things so bad that you're actually thinking

662
00:34:31,800 --> 00:34:34,359
Speaker 1: about suicide? Have you thought about taking your life? Even

663
00:34:34,360 --> 00:34:36,440
Speaker 1: if they're joking you don't need to every time. If

664
00:34:36,440 --> 00:34:38,000
Speaker 1: it's a clear joke, it's a clear you know it's

665
00:34:38,000 --> 00:34:40,120
Speaker 1: a joke. But if you have the thought, have the

666
00:34:40,120 --> 00:34:42,560
Speaker 1: feeling to ask about it, I would ask about it. Yeah,

667
00:34:43,239 --> 00:34:45,200
Speaker 1: it's hard. Admittedly it's still hard to do. I've been

668
00:34:45,200 --> 00:34:47,120
Speaker 1: doing this for decades and it's still I still have

669
00:34:47,160 --> 00:34:51,000
Speaker 1: a little hesitation before I ask friends, family members. But

670
00:34:51,200 --> 00:34:53,959
Speaker 1: I ask because I know the consequences of not asking,

671
00:34:54,040 --> 00:34:56,040
Speaker 1: and I know the statistics, and I know that we've

672
00:34:56,040 --> 00:34:58,360
Speaker 1: done studies asking people who've tried to kill themselves. Is

673
00:34:58,360 --> 00:35:00,440
Speaker 1: there anything that could have prevented you I'm trying to

674
00:35:00,520 --> 00:35:02,960
Speaker 1: kill yourself, And the top two things people say are

675
00:35:03,600 --> 00:35:05,400
Speaker 1: if there was some way to make the pain go away,

676
00:35:05,680 --> 00:35:07,200
Speaker 1: and if I was able to talk with someone else

677
00:35:07,200 --> 00:35:10,680
Speaker 1: about what is experiencing. So I know firsthand and I

678
00:35:10,719 --> 00:35:13,960
Speaker 1: know scientifically that lack of connection, that lack of communication

679
00:35:14,080 --> 00:35:17,360
Speaker 1: can be deadly. And so push through the anxiety, pushed

680
00:35:17,360 --> 00:35:21,200
Speaker 1: through the uncomfortability of asking someone and ask them. Invariably,

681
00:35:21,440 --> 00:35:23,360
Speaker 1: in almost every experience I've had, I can't think of

682
00:35:23,360 --> 00:35:25,319
Speaker 1: one where this hasn't been the case. It's gone well

683
00:35:25,600 --> 00:35:27,560
Speaker 1: and the person has either said yes, I am thinking

684
00:35:27,560 --> 00:35:29,400
Speaker 1: about it, and I'm glad you asked, or no, I'm not.

685
00:35:29,880 --> 00:35:32,080
Speaker 1: And now they know that if they do have those thoughts,

686
00:35:32,160 --> 00:35:34,080
Speaker 1: or if those thoughts intensify, I'm some one they can

687
00:35:34,520 --> 00:35:36,400
Speaker 1: talk with. And I think the bigger the network of

688
00:35:36,440 --> 00:35:39,560
Speaker 1: people that one has, the more likely they are to

689
00:35:40,200 --> 00:35:41,239
Speaker 1: not die by suicide.

690
00:35:42,120 --> 00:35:44,360
Speaker 2: So let's say parents or your friend, You've had the

691
00:35:44,360 --> 00:35:47,640
Speaker 2: conversation with them. Yeah, you're worried about them. Yeah, what

692
00:35:47,680 --> 00:35:50,200
Speaker 2: do you do next? And where should people go? Parents

693
00:35:50,320 --> 00:35:53,239
Speaker 2: or friends of kids teens who are listening right now,

694
00:35:53,280 --> 00:35:56,439
Speaker 2: and yeah, they go, I think someone's struggling. I don't

695
00:35:56,440 --> 00:35:57,719
Speaker 2: fully know what do I do?

696
00:35:57,800 --> 00:36:01,240
Speaker 1: Yeah? I like to think about Acronyms can be helpful

697
00:36:01,440 --> 00:36:04,360
Speaker 1: giving a person air ai R. So ask the question,

698
00:36:04,560 --> 00:36:07,160
Speaker 1: if you think someone might be at risk, ask them,

699
00:36:07,440 --> 00:36:12,080
Speaker 1: initiate a conversation, initiate support. There's a tendency for people

700
00:36:12,080 --> 00:36:14,840
Speaker 1: to pull away and the person who asks and not

701
00:36:14,920 --> 00:36:17,440
Speaker 1: to follow up and are for refer. Don't try and

702
00:36:17,440 --> 00:36:19,400
Speaker 1: do it all on your own, refer them. So aire

703
00:36:19,600 --> 00:36:22,239
Speaker 1: ask the question, and I usually try and ease into it,

704
00:36:23,480 --> 00:36:27,200
Speaker 1: and I ask, and we teach us our doctoral students

705
00:36:27,200 --> 00:36:29,600
Speaker 1: who are learning to be clinical psychologists asking a calm,

706
00:36:29,600 --> 00:36:32,840
Speaker 1: dispassionate demeanor. Are things so bad that you've thought about suicide?

707
00:36:32,880 --> 00:36:34,960
Speaker 1: And I'll lead into it with think asking about depression.

708
00:36:35,239 --> 00:36:37,320
Speaker 1: Have you have thoughts of death? Have you have thoughts

709
00:36:37,320 --> 00:36:40,560
Speaker 1: of suicide? So you can ease into it, and if so,

710
00:36:40,680 --> 00:36:44,800
Speaker 1: initiate a conversation. Initiate support. As with death, as with funerals,

711
00:36:44,800 --> 00:36:46,840
Speaker 1: people get uncomfortable and they don't want they don't know

712
00:36:46,880 --> 00:36:49,480
Speaker 1: what to say, and so they pull back, lean in,

713
00:36:49,480 --> 00:36:52,280
Speaker 1: initiate a conversation, initiate support, be there for the person,

714
00:36:52,600 --> 00:36:55,040
Speaker 1: but also always refer. Don't try and do it all

715
00:36:55,040 --> 00:36:58,719
Speaker 1: on your own. Bring a person to professional care. There

716
00:36:58,719 --> 00:37:01,640
Speaker 1: are hotlines. There are crisis lines in most countries around

717
00:37:01,640 --> 00:37:03,960
Speaker 1: the world. In the US it's nine eight eight. You

718
00:37:04,000 --> 00:37:07,560
Speaker 1: can find these easily on a search online. A lot

719
00:37:07,600 --> 00:37:10,239
Speaker 1: of them operate twenty four seven. You don't need to

720
00:37:10,280 --> 00:37:12,360
Speaker 1: bring a person to the hospital. You can if the

721
00:37:12,360 --> 00:37:15,880
Speaker 1: person's thinking about killing themselves today, I would take them

722
00:37:15,920 --> 00:37:18,120
Speaker 1: to the hospital and have them I'm getting evaluation. But

723
00:37:18,160 --> 00:37:20,080
Speaker 1: you can call nine eight eight, you can call it

724
00:37:20,160 --> 00:37:22,960
Speaker 1: a you can text the text line. Refer the person

725
00:37:23,000 --> 00:37:25,040
Speaker 1: for help. A lot of Probably the most common thing

726
00:37:25,040 --> 00:37:27,040
Speaker 1: I've seen is a person will say, yeah, I've thought

727
00:37:27,080 --> 00:37:30,040
Speaker 1: about suicide, but please don't tell anyone. Promise me you

728
00:37:30,080 --> 00:37:32,839
Speaker 1: won't tell anyone. I wouldn't promise. I would say I

729
00:37:32,920 --> 00:37:35,120
Speaker 1: care about you and I want you to stay alive,

730
00:37:35,600 --> 00:37:37,680
Speaker 1: and I value your life even more than I value

731
00:37:37,719 --> 00:37:39,279
Speaker 1: our friendship. And if you're not going to be my

732
00:37:39,280 --> 00:37:42,720
Speaker 1: friend anymore because I shared someone, then so be it. Again.

733
00:37:42,840 --> 00:37:44,799
Speaker 1: I can't emphasize enough how important it is to try

734
00:37:44,840 --> 00:37:47,200
Speaker 1: and take that step, and how got wrenching it is

735
00:37:47,239 --> 00:37:49,799
Speaker 1: to lose a person to suicide and to struggle with

736
00:37:49,840 --> 00:37:52,160
Speaker 1: the question of could I have done more? Should I

737
00:37:52,160 --> 00:37:53,600
Speaker 1: have taken one more step?

738
00:37:53,840 --> 00:37:59,879
Speaker 2: Yeah, Matt, Why are suicide rates especially high among white men?

739
00:38:00,280 --> 00:38:04,560
Speaker 1: It's a great question. That's there's a lot about suicide

740
00:38:05,160 --> 00:38:09,000
Speaker 1: that are sort of perennial statistics that we just don't understand,

741
00:38:09,040 --> 00:38:11,120
Speaker 1: and and this is one of them. So I mentioned

742
00:38:11,200 --> 00:38:13,600
Speaker 1: the men part of that. We think that the rates

743
00:38:13,600 --> 00:38:16,440
Speaker 1: are higher among men than women because men tend to

744
00:38:16,560 --> 00:38:18,759
Speaker 1: use tend to be more aggressive, more impulsive, to use

745
00:38:18,760 --> 00:38:20,920
Speaker 1: more lethal means. In the US, much more local use

746
00:38:20,960 --> 00:38:25,000
Speaker 1: firearms than women are. Women tend to use means that

747
00:38:25,120 --> 00:38:28,719
Speaker 1: tend to be less lethal cutting, overdose, and so on.

748
00:38:29,160 --> 00:38:31,600
Speaker 1: Why white men, we're not sure. That's been a statistic

749
00:38:31,600 --> 00:38:34,600
Speaker 1: that's been prevalent in the US for a really long time,

750
00:38:34,640 --> 00:38:38,960
Speaker 1: and we don't fully understand it. Another really striking statistic

751
00:38:39,160 --> 00:38:43,400
Speaker 1: is the rate of suicidal behavior among black teens in

752
00:38:43,440 --> 00:38:46,200
Speaker 1: the US is skyrocketing in the past few years, among

753
00:38:47,400 --> 00:38:50,359
Speaker 1: black male youth in particular, And that's not the one.

754
00:38:50,400 --> 00:38:53,480
Speaker 1: We don't fully understand, and there's ideas about why this

755
00:38:53,520 --> 00:38:56,319
Speaker 1: might be. But there's a lot of science happening right

756
00:38:56,360 --> 00:38:57,480
Speaker 1: now to try and better understand this.

757
00:38:57,920 --> 00:39:00,759
Speaker 2: It's such important research and so needed. Is this area

758
00:39:00,800 --> 00:39:01,960
Speaker 2: of research underfunded.

759
00:39:02,200 --> 00:39:07,360
Speaker 1: It's wildly underfunded. Suicide is one of the leading causes

760
00:39:07,400 --> 00:39:10,080
Speaker 1: of death in the US. Around the world, it's the

761
00:39:10,120 --> 00:39:13,400
Speaker 1: second leading cause of death among people ages ten to

762
00:39:13,560 --> 00:39:17,799
Speaker 1: thirty four, behind only accidents. So among young people, it

763
00:39:17,880 --> 00:39:21,400
Speaker 1: takes more lives than anything other than accidence, and overall

764
00:39:21,480 --> 00:39:25,760
Speaker 1: the fourth leading cause or contributor to years of life

765
00:39:25,880 --> 00:39:28,040
Speaker 1: lost because it takes so many young people of all

766
00:39:28,080 --> 00:39:32,360
Speaker 1: causes of death, Yet it is almost at the end

767
00:39:32,400 --> 00:39:34,800
Speaker 1: of the list in terms of funding. There's about a

768
00:39:34,920 --> 00:39:38,120
Speaker 1: we need to triple the funding for suicide research to

769
00:39:38,160 --> 00:39:41,759
Speaker 1: even become close to the causes of death that surround it.

770
00:39:42,560 --> 00:39:47,680
Speaker 1: So there's just an incredible dearth of scientific research being

771
00:39:47,760 --> 00:39:50,000
Speaker 1: done on suicide relative to the scope of the problem.

772
00:39:50,400 --> 00:39:53,520
Speaker 1: And it's not for lack of want. I think it

773
00:39:53,560 --> 00:39:56,080
Speaker 1: has to do with stigma. That again, people don't like

774
00:39:56,120 --> 00:39:59,319
Speaker 1: talking about suicide. It's a taboo topic. There's a fear

775
00:39:59,360 --> 00:40:00,719
Speaker 1: that if I talk ab about it, if I shine

776
00:40:00,719 --> 00:40:03,360
Speaker 1: a light on it, it's going to make things worse. And

777
00:40:03,400 --> 00:40:05,239
Speaker 1: I think this trickles down to funding as well, and

778
00:40:05,280 --> 00:40:07,040
Speaker 1: so we're not funding it at the rate that we

779
00:40:07,080 --> 00:40:10,080
Speaker 1: should be. Another myth about suicide is it's an epidemic.

780
00:40:10,800 --> 00:40:13,320
Speaker 1: The rates have skyrocketed. They haven't. The suicide rate in

781
00:40:13,360 --> 00:40:15,920
Speaker 1: the US now is virtually identical to what it was

782
00:40:16,360 --> 00:40:20,120
Speaker 1: one hundred years ago. Contrast that with many of the

783
00:40:20,200 --> 00:40:23,719
Speaker 1: other leading causes of death that have dropped precipitously over

784
00:40:23,719 --> 00:40:29,480
Speaker 1: the past hundred years, heart disease, accidents, tuberculosis, pneumonia, HIV, AIDS,

785
00:40:29,520 --> 00:40:33,160
Speaker 1: most recently COVID. We dedicate science to these things. We

786
00:40:33,239 --> 00:40:36,200
Speaker 1: do medical research, we disseminate the results. We're really good

787
00:40:36,320 --> 00:40:39,520
Speaker 1: humans are really good at applying scientific studies to big

788
00:40:39,560 --> 00:40:42,680
Speaker 1: problems and decreasing the mortality rate. We haven't done that

789
00:40:42,719 --> 00:40:45,520
Speaker 1: to suicide. The suicide rate is pretty flat over one

790
00:40:45,560 --> 00:40:49,120
Speaker 1: hundred years, and so I loved why. I'm really excited

791
00:40:49,120 --> 00:40:51,359
Speaker 1: that you're focusing on this problem and bringing attention to it,

792
00:40:52,160 --> 00:40:54,359
Speaker 1: shining a light on it. We need more research on

793
00:40:54,360 --> 00:40:58,160
Speaker 1: this topic because there's these huge questions about why young

794
00:40:58,239 --> 00:41:01,640
Speaker 1: black males, why older white men, how can generative aib us,

795
00:41:02,080 --> 00:41:04,640
Speaker 1: on and on and on. There's so much opportunity that's

796
00:41:04,680 --> 00:41:07,480
Speaker 1: not realized because we don't have enough research on the topic.

797
00:41:07,840 --> 00:41:12,680
Speaker 2: Yeah, if you are advising AI companies right now, how

798
00:41:12,680 --> 00:41:14,319
Speaker 2: would you encourage them to think about it?

799
00:41:14,840 --> 00:41:18,279
Speaker 1: A commitment to the scientific process. Again, it's one thing

800
00:41:18,320 --> 00:41:20,000
Speaker 1: to have a good idea, a really clever idea, a

801
00:41:20,000 --> 00:41:22,960
Speaker 1: good idea and well intentions. You have to do the research,

802
00:41:23,000 --> 00:41:26,359
Speaker 1: you have to do the experiments. I would encourage AI

803
00:41:26,400 --> 00:41:30,799
Speaker 1: companies to collaborate with scientists, academic researchers who are independent,

804
00:41:31,440 --> 00:41:35,160
Speaker 1: 're working closely with and do studies on the best ideas,

805
00:41:35,600 --> 00:41:38,560
Speaker 1: see what works, see what doesn't, Disseminate the things that work,

806
00:41:38,800 --> 00:41:40,759
Speaker 1: and drop out the things that don't. One thing that

807
00:41:40,840 --> 00:41:44,799
Speaker 1: give me great hope about the problem of suicide and

808
00:41:44,840 --> 00:41:48,120
Speaker 1: the potentials that there. This is although it's a leading

809
00:41:48,160 --> 00:41:51,239
Speaker 1: cause of death, it's a low base rate problem, and

810
00:41:51,280 --> 00:41:53,880
Speaker 1: we have been able to predict it and target it

811
00:41:53,920 --> 00:41:55,880
Speaker 1: for treatment because we've had a lack of data. It's

812
00:41:55,960 --> 00:41:58,480
Speaker 1: kind of like I often think about tornado prediction or

813
00:41:58,520 --> 00:42:02,080
Speaker 1: hurricane prediction, where tornadoes hurricanes have been around as long

814
00:42:02,120 --> 00:42:04,239
Speaker 1: as the earth has been here, and for a long time,

815
00:42:04,239 --> 00:42:07,160
Speaker 1: we have these sort of mystical religious explanations for why

816
00:42:07,200 --> 00:42:09,320
Speaker 1: they exist. And as we've got more and more data

817
00:42:10,280 --> 00:42:12,640
Speaker 1: and better science and better statistical models, we can predict

818
00:42:12,680 --> 00:42:14,319
Speaker 1: them and we know when they're going to occur, and

819
00:42:14,320 --> 00:42:17,680
Speaker 1: we get warnings weeks ahead for hurricanes, hours ahead for tornadoes,

820
00:42:17,719 --> 00:42:20,880
Speaker 1: and we save lives. We now have a lot of

821
00:42:20,960 --> 00:42:23,440
Speaker 1: data on people. We all have cell phones and wearable devices,

822
00:42:23,480 --> 00:42:26,080
Speaker 1: and we're online and there's all these digital breadcrumbs all

823
00:42:26,120 --> 00:42:30,440
Speaker 1: around us. We can predict and we can tailor using

824
00:42:30,520 --> 00:42:33,480
Speaker 1: genera AI two people better than we ever could in

825
00:42:33,560 --> 00:42:36,880
Speaker 1: human history. And so there's so we're right there. I

826
00:42:36,920 --> 00:42:39,440
Speaker 1: think we've got all the tools to be able to

827
00:42:39,440 --> 00:42:42,080
Speaker 1: have a big impact, but we're not doing it. So

828
00:42:43,040 --> 00:42:45,800
Speaker 1: I could send a message to the big AI companies

829
00:42:45,800 --> 00:42:49,120
Speaker 1: and be collaborate with researchers on this, lean into the

830
00:42:49,160 --> 00:42:54,799
Speaker 1: problem and experiment and find ways to use the incredible

831
00:42:54,840 --> 00:42:59,440
Speaker 1: tools that we now have to help young people to

832
00:42:59,480 --> 00:43:02,360
Speaker 1: improve health, to decrease suffering, to save lives.

833
00:43:03,640 --> 00:43:06,920
Speaker 2: I also saw that new mothers can actually struggle with

834
00:43:06,960 --> 00:43:09,880
Speaker 2: suicidal thoughts. Yeah, yeah, that fascinated me.

835
00:43:10,080 --> 00:43:12,680
Speaker 1: Yeah, it's a really interesting pattern in the data where

836
00:43:13,080 --> 00:43:17,719
Speaker 1: new mothers have huge increases in suicidal thoughts, which you're

837
00:43:17,760 --> 00:43:20,800
Speaker 1: having young kids to be stressful. It makes sense that

838
00:43:20,840 --> 00:43:23,640
Speaker 1: you have perhaps increased depression, post part of depression and

839
00:43:23,640 --> 00:43:26,520
Speaker 1: anxiety and thoughts of suicide. Young mothers have a huge

840
00:43:26,560 --> 00:43:29,600
Speaker 1: decrease and risk of suicide death. So I think there's

841
00:43:29,760 --> 00:43:32,600
Speaker 1: reason to not take your life if you've got young kids.

842
00:43:32,640 --> 00:43:35,040
Speaker 1: And so although there's an increase in suicidal thoughts, there's

843
00:43:35,040 --> 00:43:38,280
Speaker 1: a decrease in suicide death. Having young kids is protective.

844
00:43:39,400 --> 00:43:41,480
Speaker 2: Yeah, I feel like and that I can't imagine how

845
00:43:41,560 --> 00:43:44,600
Speaker 2: much stress that puts on someone, Like the reason you're

846
00:43:44,600 --> 00:43:47,080
Speaker 2: having suicidal thoughts is because there's some sort of extreme

847
00:43:47,120 --> 00:43:49,920
Speaker 2: stress in your life. Yeah, I'm assuming there's then an

848
00:43:49,960 --> 00:43:54,680
Speaker 2: associated stress of having suicidal thoughts. Almost like the double

849
00:43:54,800 --> 00:43:57,759
Speaker 2: guilt and shame of Yeah, I can't believe I'm having

850
00:43:57,760 --> 00:44:00,120
Speaker 2: suicidal thoughts. I just gave birth, or I can't believe

851
00:44:00,120 --> 00:44:02,800
Speaker 2: I'm having suicidal thoughts. Have to take care of my family,

852
00:44:02,800 --> 00:44:05,000
Speaker 2: and that almost feels like a vicious psychle Yeah.

853
00:44:05,320 --> 00:44:08,239
Speaker 1: Yes, And people often feel really isolated and they pull

854
00:44:08,280 --> 00:44:10,160
Speaker 1: back from others because they're afraid to tell other people

855
00:44:10,200 --> 00:44:11,960
Speaker 1: how they're feeling. And if I've got a young child

856
00:44:12,000 --> 00:44:13,960
Speaker 1: at home and I'm thinking about suicide and communicate that

857
00:44:14,000 --> 00:44:16,120
Speaker 1: someone else, are people going to fear for the safety

858
00:44:16,120 --> 00:44:18,440
Speaker 1: of my child. There's a lot of guilt, there's a

859
00:44:18,440 --> 00:44:21,239
Speaker 1: lot of shame that people report when they have thoughts

860
00:44:21,239 --> 00:44:27,440
Speaker 1: of suicide. Many people often also often report relief when

861
00:44:27,440 --> 00:44:30,360
Speaker 1: they have thoughts of suicide, almost like imagining a vacation

862
00:44:30,480 --> 00:44:34,360
Speaker 1: from their problems, imagining an escape from their situation, and

863
00:44:34,400 --> 00:44:37,160
Speaker 1: so it brings temporary relief to someone, so it's reaving.

864
00:44:37,160 --> 00:44:39,600
Speaker 1: The thoughts can be reinforcing, and we think lead them

865
00:44:39,640 --> 00:44:40,200
Speaker 1: to persist.

866
00:44:40,480 --> 00:44:43,520
Speaker 2: But overall, you two sort of thoughts are dangerous even

867
00:44:43,560 --> 00:44:44,799
Speaker 2: if they're seen that way, or.

868
00:44:45,000 --> 00:44:48,200
Speaker 1: They're dangerous insofar as they can lead to suicide death.

869
00:44:49,400 --> 00:44:52,279
Speaker 1: But again fifteen percent of people have thoughts of suicide.

870
00:44:52,680 --> 00:44:54,919
Speaker 1: Two thirds of people who have thoughts of suicide will

871
00:44:54,960 --> 00:45:01,880
Speaker 1: never act on them, so they in themselves they're incredibly distressing.

872
00:45:02,800 --> 00:45:05,360
Speaker 2: Is the goal to never have a suicidal thought? Again?

873
00:45:05,680 --> 00:45:07,799
Speaker 2: For someone who's having suicidal thoughts.

874
00:45:07,600 --> 00:45:09,640
Speaker 1: I think that would be the ideal goal is to

875
00:45:09,640 --> 00:45:12,440
Speaker 1: not have suicetal thoughts to begin with. Interestingly, most treatments

876
00:45:12,480 --> 00:45:15,560
Speaker 1: that most psychological treatments that show an effect for preventing

877
00:45:15,600 --> 00:45:20,399
Speaker 1: suicidal behavior, they don't work by decreasing suicidal thoughts. They

878
00:45:20,440 --> 00:45:24,440
Speaker 1: work by decreasing people's likelihood of acting on their suicidal thoughts.

879
00:45:24,480 --> 00:45:27,399
Speaker 1: So we're not really good yet scientifically clinically at getting

880
00:45:27,400 --> 00:45:29,960
Speaker 1: people to not think about suicide. What we can do

881
00:45:30,080 --> 00:45:32,720
Speaker 1: through psychotherapy is get them to not act on those thoughts.

882
00:45:33,560 --> 00:45:36,480
Speaker 1: Targeting depression, target anxiety doesn't seem to work as well

883
00:45:36,480 --> 00:45:38,640
Speaker 1: as you thought it would for getting rid of suicidal thoughts.

884
00:45:38,960 --> 00:45:44,719
Speaker 2: What does that program look like? Yeah, to stop that transition? Yeah.

885
00:45:44,760 --> 00:45:46,960
Speaker 1: So some of the best evidence we have is for

886
00:45:47,040 --> 00:45:51,279
Speaker 1: interventions like cognitive therapy, cognitive behavior therapy or a newer

887
00:45:51,360 --> 00:45:54,960
Speaker 1: version called dialectical behavior therapy, which is basically cognitive therapy

888
00:45:54,960 --> 00:45:57,759
Speaker 1: but with an Eastern Buddhist influence. Cognitive therapy is a

889
00:45:57,800 --> 00:46:01,480
Speaker 1: lot about change dialectical behavior. The your DBT is acceptance

890
00:46:01,520 --> 00:46:05,640
Speaker 1: and change, so accepting the thoughts, the feelings that you have,

891
00:46:05,800 --> 00:46:08,279
Speaker 1: noticing them and not acting on them. And so those

892
00:46:08,320 --> 00:46:11,839
Speaker 1: interventions are a lot about helping people to understand when

893
00:46:11,880 --> 00:46:15,080
Speaker 1: their risk is increasing and what skills they can develop

894
00:46:15,160 --> 00:46:19,520
Speaker 1: and use to get through those periods and try and

895
00:46:19,840 --> 00:46:22,520
Speaker 1: ultimately decrease the likelihood of having thoughts of suicide. But

896
00:46:22,760 --> 00:46:26,239
Speaker 1: our interventions aren't quite there yet, So they're teaching skills

897
00:46:26,280 --> 00:46:30,759
Speaker 1: of distressed tolerance. When you have thoughts of suicide, when

898
00:46:30,800 --> 00:46:32,760
Speaker 1: you feel that fire, when you feel that intense pain,

899
00:46:33,320 --> 00:46:35,239
Speaker 1: what can you do to try and tolerate it, What

900
00:46:35,239 --> 00:46:37,239
Speaker 1: can you do to try and distract from it, either

901
00:46:37,239 --> 00:46:42,040
Speaker 1: by using some skill cognitive reframing, taking a shower, going

902
00:46:42,080 --> 00:46:45,640
Speaker 1: for a walk, reading, doing some mindfulness practices, or reaching

903
00:46:45,640 --> 00:46:49,120
Speaker 1: out to someone else, getting good at reaching out to

904
00:46:49,160 --> 00:46:52,000
Speaker 1: your friends, your family when you're at risk, or taking

905
00:46:52,040 --> 00:46:54,319
Speaker 1: a step further and reaching out for professional help when

906
00:46:54,360 --> 00:46:55,000
Speaker 1: you're at risk.

907
00:47:11,719 --> 00:47:16,400
Speaker 2: Not for those people who have attempted suicide but then survived,

908
00:47:16,719 --> 00:47:17,640
Speaker 2: do they regret it?

909
00:47:18,480 --> 00:47:21,040
Speaker 1: Most do, so there are some data on this, and

910
00:47:21,200 --> 00:47:24,320
Speaker 1: about three quarters of people who there's one study on

911
00:47:24,680 --> 00:47:27,120
Speaker 1: the Golden Gate Bridge, which is if you jump from

912
00:47:27,160 --> 00:47:30,160
Speaker 1: a really tall bridge, it tends to be lethal, so

913
00:47:30,200 --> 00:47:33,160
Speaker 1: people who jump off and survive are rare. And there

914
00:47:33,200 --> 00:47:36,920
Speaker 1: was an interview done with people who jumped off and survived,

915
00:47:36,920 --> 00:47:39,359
Speaker 1: in three quarters said the first thing they thought when

916
00:47:39,360 --> 00:47:42,319
Speaker 1: they jumped was they regretted it immediately. And when we

917
00:47:42,360 --> 00:47:44,279
Speaker 1: followed up and asked people who have made to au

918
00:47:44,280 --> 00:47:48,160
Speaker 1: set attempts and survived how they felt afterwards, the majority

919
00:47:48,239 --> 00:47:52,799
Speaker 1: report feeling shame and guilt and disappointment that they had

920
00:47:52,800 --> 00:47:55,960
Speaker 1: made suicidal they had engaged into a side of behavior.

921
00:47:56,400 --> 00:47:58,440
Speaker 1: And so that's a message that I would hope that

922
00:47:58,480 --> 00:48:00,520
Speaker 1: could be heard by people who are thinking about those

923
00:48:00,520 --> 00:48:04,000
Speaker 1: who have taken the step to try and kill themselves.

924
00:48:04,560 --> 00:48:08,480
Speaker 1: Most immediately regret it, and in the longer term continue

925
00:48:08,480 --> 00:48:10,160
Speaker 1: to regret it and feel bad and wish they didn't

926
00:48:10,360 --> 00:48:13,879
Speaker 1: try and kill themselves, And the majority verbalize that they

927
00:48:14,760 --> 00:48:16,279
Speaker 1: wish they had someone they could have talked to, or

928
00:48:16,320 --> 00:48:18,480
Speaker 1: wish they talked to someone about what they're experiencing ahead

929
00:48:18,480 --> 00:48:21,160
Speaker 1: of time. And some people say after the fact, when

930
00:48:21,160 --> 00:48:24,320
Speaker 1: they're in the hospital. They didn't realize how much people cared.

931
00:48:24,360 --> 00:48:27,560
Speaker 1: They didn't realize how much treatment is available and how

932
00:48:27,640 --> 00:48:29,759
Speaker 1: much better things could be. So I would hope that

933
00:48:29,800 --> 00:48:31,680
Speaker 1: if people are listening to this who are struggling with

934
00:48:31,680 --> 00:48:33,439
Speaker 1: thoughts of suicide, that they would keep that in mind

935
00:48:33,480 --> 00:48:36,359
Speaker 1: that there is help out there. People who have taken

936
00:48:36,400 --> 00:48:41,000
Speaker 1: these steps wish they hadn't, So please do reach out

937
00:48:41,040 --> 00:48:41,319
Speaker 1: for help.

938
00:48:41,400 --> 00:48:45,040
Speaker 2: Now, are you seeing people who die by suicide have

939
00:48:45,160 --> 00:48:49,719
Speaker 2: a mental health disorder? Is that a connection that you see.

940
00:48:49,760 --> 00:48:52,400
Speaker 1: It's a huge connection. So ninety to ninety five percent

941
00:48:52,400 --> 00:48:56,359
Speaker 1: of people who die by suicide had a diagnosable mental

942
00:48:56,360 --> 00:49:01,640
Speaker 1: disorder before they died. So depression, anxiety disorders, bipolar disorder.

943
00:49:01,800 --> 00:49:04,120
Speaker 1: Twenty percent of people with bipolar disorder will die by

944
00:49:04,120 --> 00:49:08,120
Speaker 1: suicide one in five. Psychotic illness. Is virtually every mental

945
00:49:08,120 --> 00:49:10,200
Speaker 1: disorder in the DSM, all the ones that we study

946
00:49:10,200 --> 00:49:13,279
Speaker 1: on a regular basis, increase risk of suicide when they

947
00:49:13,280 --> 00:49:16,520
Speaker 1: start to pile up. Risk really increases when a person

948
00:49:16,880 --> 00:49:20,280
Speaker 1: having two disorders we call comorbidity, three or more disorders

949
00:49:20,360 --> 00:49:24,120
Speaker 1: multi morbidity. Multi morbidity is associated with a huge increase

950
00:49:24,160 --> 00:49:25,480
Speaker 1: in risk of suicidal behavior.

951
00:49:26,360 --> 00:49:30,640
Speaker 2: It's clear what people are experiencing when it comes to

952
00:49:30,680 --> 00:49:35,399
Speaker 2: suicidal thoughts. You talked about the connections that you make

953
00:49:35,440 --> 00:49:38,760
Speaker 2: to actually people who die by suicide, that it's hard

954
00:49:38,800 --> 00:49:39,920
Speaker 2: to predict.

955
00:49:39,480 --> 00:49:42,520
Speaker 1: It really hard to predict. Another thing that gives me

956
00:49:42,520 --> 00:49:46,040
Speaker 1: optimism is we're getting better at prediction with the increasing

957
00:49:46,280 --> 00:49:48,680
Speaker 1: amount of data that we have. We'll give a few examples.

958
00:49:50,120 --> 00:49:53,480
Speaker 1: Fifty percent five zero of people who die by suicide

959
00:49:53,680 --> 00:49:57,360
Speaker 1: saw a clinician within the month before their death. People

960
00:49:57,360 --> 00:49:59,280
Speaker 1: are coming at half of people who die are coming

961
00:49:59,320 --> 00:50:02,360
Speaker 1: in to a clinic, to a hospital, primary care doctor.

962
00:50:02,360 --> 00:50:06,520
Speaker 1: They're psychologist, psychiatrist, social worker. They're not always saying actually,

963
00:50:06,560 --> 00:50:08,759
Speaker 1: they're rarely saying doctor, I'm going to kill myself. They're

964
00:50:08,760 --> 00:50:12,160
Speaker 1: coming in saying I'm depressed, I can't sleep. Sleep problems

965
00:50:12,200 --> 00:50:15,200
Speaker 1: are strongly linked with suicidal behavior. Something's just not right.

966
00:50:15,840 --> 00:50:18,319
Speaker 1: So half the people are coming in. We're really bad

967
00:50:18,400 --> 00:50:20,640
Speaker 1: clinically at knowing which people coming in at high risk.

968
00:50:20,680 --> 00:50:23,200
Speaker 1: But here's where I have hope. With a switch to

969
00:50:23,400 --> 00:50:25,919
Speaker 1: electronic health records. It used to be you go see

970
00:50:26,120 --> 00:50:27,640
Speaker 1: your doctor and they write down some things on a

971
00:50:27,680 --> 00:50:29,040
Speaker 1: piece of paper and they put it in a folder

972
00:50:29,080 --> 00:50:31,040
Speaker 1: and put it in a filing cabin. Now it's all digital.

973
00:50:31,760 --> 00:50:35,480
Speaker 1: We can use machine learning algorithms to find in the

974
00:50:35,760 --> 00:50:37,799
Speaker 1: huge amounts of data we have on every patient who's

975
00:50:37,840 --> 00:50:40,680
Speaker 1: at risk for suicide, and we can identify for thing

976
00:50:40,719 --> 00:50:42,759
Speaker 1: about predicting suicide as like looking for a needle in

977
00:50:42,760 --> 00:50:47,400
Speaker 1: a haystack. We can put patients into risk bins, and

978
00:50:47,440 --> 00:50:50,200
Speaker 1: the top five percent of patients account for fifty percent

979
00:50:50,239 --> 00:50:51,800
Speaker 1: of all the suicides are going to happen. So we

980
00:50:51,840 --> 00:50:56,040
Speaker 1: can find these concentrations of risk where we have patients

981
00:50:56,040 --> 00:50:57,960
Speaker 1: who are really high risk for suicide, and so we

982
00:50:58,000 --> 00:51:00,799
Speaker 1: can target them with interventions. We're also doing a lot

983
00:51:00,840 --> 00:51:04,520
Speaker 1: of work now over the past almost ten years, giving

984
00:51:04,600 --> 00:51:08,960
Speaker 1: patients apps on their smartphones and asking them questions each

985
00:51:09,000 --> 00:51:11,920
Speaker 1: day about how they're feeling, how they're doing, collecting passive

986
00:51:11,960 --> 00:51:14,960
Speaker 1: data with their consent from their GPS, from their accelerometer,

987
00:51:15,040 --> 00:51:17,719
Speaker 1: or getting sleep information, and we're getting pretty good at

988
00:51:17,800 --> 00:51:21,640
Speaker 1: predicting among patients at risk who's going to make a

989
00:51:21,640 --> 00:51:23,920
Speaker 1: suicide attempt in the next few days. So we're getting

990
00:51:23,920 --> 00:51:26,359
Speaker 1: better identifying which patients are at risk and now most

991
00:51:26,400 --> 00:51:29,279
Speaker 1: recently in the past few months, when they're at risk,

992
00:51:29,640 --> 00:51:33,240
Speaker 1: and we now have apps that we can, with people's consent,

993
00:51:33,560 --> 00:51:37,480
Speaker 1: give them on their phones that help decrease risk of

994
00:51:37,520 --> 00:51:40,239
Speaker 1: suicide in time and place, so we don't have to

995
00:51:40,280 --> 00:51:43,120
Speaker 1: have someone coming into the hospital when they're at risk.

996
00:51:43,280 --> 00:51:44,920
Speaker 1: We still want people to do that, coming in to

997
00:51:44,960 --> 00:51:46,880
Speaker 1: see their clinician once a week, whatever the case is,

998
00:51:46,880 --> 00:51:48,800
Speaker 1: we still want them to do that those in between

999
00:51:48,880 --> 00:51:51,680
Speaker 1: times when risk increases. What does a person do. We're

1000
00:51:51,680 --> 00:51:54,880
Speaker 1: getting better at identifying when those are going to happen

1001
00:51:55,000 --> 00:51:56,640
Speaker 1: and how we can help keep people safe.

1002
00:51:56,880 --> 00:51:59,839
Speaker 2: Yeah, because all of that is what you hoped. There's

1003
00:52:00,000 --> 00:52:04,920
Speaker 2: clinicians did afterwards. Fifty percent of those people but by suicide,

1004
00:52:05,000 --> 00:52:06,680
Speaker 2: right whereas.

1005
00:52:06,280 --> 00:52:08,960
Speaker 1: But it's hard to know. It's hard. So I mentioned earlier,

1006
00:52:09,000 --> 00:52:11,200
Speaker 1: two thirds of people who die by suicide told someone

1007
00:52:11,239 --> 00:52:13,000
Speaker 1: ahead of time they were thinking about suicide. What I

1008
00:52:13,000 --> 00:52:16,839
Speaker 1: didn't mention is seventy eight percent of those people explicitly

1009
00:52:16,880 --> 00:52:22,319
Speaker 1: denied suicidal intentions in their last communication before dying. And

1010
00:52:22,360 --> 00:52:24,560
Speaker 1: this is a really common pattern that people will say

1011
00:52:25,400 --> 00:52:28,200
Speaker 1: I'm thinking about killing myself, and then they'll recant and

1012
00:52:28,200 --> 00:52:30,960
Speaker 1: say I'm no longer thinking about killing myself, and a

1013
00:52:31,000 --> 00:52:33,600
Speaker 1: lot of the cases they're not. It's really hard to

1014
00:52:33,640 --> 00:52:36,680
Speaker 1: know when is a person who has suicidal thoughts going

1015
00:52:36,680 --> 00:52:38,920
Speaker 1: to act on those thoughts. And when we do studies

1016
00:52:38,960 --> 00:52:41,200
Speaker 1: where we interview people and ask when did you know

1017
00:52:41,280 --> 00:52:43,319
Speaker 1: you're going to make a suicide attempt, it's usually the

1018
00:52:43,440 --> 00:52:46,840
Speaker 1: hours before. So people have thoughts of suicide maybe for

1019
00:52:46,960 --> 00:52:49,920
Speaker 1: a year or so, and it's the same day that

1020
00:52:49,920 --> 00:52:51,520
Speaker 1: they make a decision they're going to kill themselves. So

1021
00:52:51,520 --> 00:52:53,239
Speaker 1: if you see your clinician once a week, once every

1022
00:52:53,280 --> 00:52:56,440
Speaker 1: two weeks, and twice a week, those in between times

1023
00:52:56,440 --> 00:52:58,719
Speaker 1: we haven't had access to. But now again with smartphones,

1024
00:52:58,719 --> 00:53:01,879
Speaker 1: with social media platforms, social media apps, we now have

1025
00:53:01,960 --> 00:53:03,879
Speaker 1: people in the in between times. And there's a lot

1026
00:53:03,880 --> 00:53:07,279
Speaker 1: of people saying these are it's bad, we're on our

1027
00:53:07,360 --> 00:53:09,520
Speaker 1: phones too much, we're on social media too much, and

1028
00:53:09,560 --> 00:53:11,839
Speaker 1: there's a case to be made there. But these they're

1029
00:53:11,880 --> 00:53:13,560
Speaker 1: tools and they can be used for good, and they

1030
00:53:13,560 --> 00:53:15,960
Speaker 1: can help us find people when they're in distress, and

1031
00:53:15,960 --> 00:53:18,480
Speaker 1: we're getting better at doing that and reaching out to people.

1032
00:53:18,640 --> 00:53:21,080
Speaker 2: What have you found of the top reasons why people

1033
00:53:21,160 --> 00:53:24,800
Speaker 2: don't tell people they are having suicidal thoughts.

1034
00:53:25,040 --> 00:53:28,640
Speaker 1: I thought I could handle on my own. I didn't

1035
00:53:28,680 --> 00:53:30,759
Speaker 1: want anyone to bring me to the hospital, call the

1036
00:53:30,760 --> 00:53:33,000
Speaker 1: police to make a big deal out of it, depending

1037
00:53:33,000 --> 00:53:35,399
Speaker 1: on population. College students are afraid they're gonna get kicked

1038
00:53:35,400 --> 00:53:37,359
Speaker 1: out of school. We do a fair amount of work

1039
00:53:37,400 --> 00:53:41,360
Speaker 1: with with the military, and a lot of service members

1040
00:53:41,480 --> 00:53:43,920
Speaker 1: fear that, and police fear they're going to have their

1041
00:53:43,920 --> 00:53:45,719
Speaker 1: firearm taken away from them, They're going to lose their job,

1042
00:53:45,760 --> 00:53:47,800
Speaker 1: they're going to get demoted. I don't want my health

1043
00:53:48,560 --> 00:53:50,600
Speaker 1: insurance company to figure out are my rate's going to

1044
00:53:50,640 --> 00:53:53,759
Speaker 1: go up? So there's a whole plethora of reasons that

1045
00:53:53,760 --> 00:53:56,799
Speaker 1: people don't tell others. It's logical. It makes sense that

1046
00:53:56,840 --> 00:53:59,040
Speaker 1: you know, if you fear bad things are going to happen.

1047
00:53:59,040 --> 00:54:00,759
Speaker 1: If I tell someone this, I'm going to try and

1048
00:54:00,800 --> 00:54:03,440
Speaker 1: handle it on my own and muscle through it. I

1049
00:54:03,520 --> 00:54:06,600
Speaker 1: understand that why people would do that, but they're missing

1050
00:54:06,600 --> 00:54:07,919
Speaker 1: an opportunity to get to get help.

1051
00:54:08,520 --> 00:54:11,759
Speaker 2: And it's hard because it's how do you convince that

1052
00:54:11,840 --> 00:54:15,560
Speaker 2: individual to seek help and be okay with me?

1053
00:54:15,960 --> 00:54:19,880
Speaker 1: Yeah, and admittedly our care could be better. We have

1054
00:54:19,960 --> 00:54:22,839
Speaker 1: a long way to go. I mentioned we have interventions

1055
00:54:22,840 --> 00:54:25,719
Speaker 1: that can decrease people's risk of suicidal behavior. A lot

1056
00:54:25,760 --> 00:54:29,000
Speaker 1: of them have waitlists, a lot of Our focus right

1057
00:54:29,000 --> 00:54:30,799
Speaker 1: now is if someone's at risk for suicide, we bring

1058
00:54:30,800 --> 00:54:33,560
Speaker 1: them to the hospital. We're just learning now that hospital

1059
00:54:33,640 --> 00:54:36,680
Speaker 1: treatment for people at risk for suicide does seem to

1060
00:54:36,680 --> 00:54:39,360
Speaker 1: help some people, it's less helpful for other people, and

1061
00:54:39,400 --> 00:54:42,600
Speaker 1: it seems to potentially harm some people. They get worse,

1062
00:54:42,680 --> 00:54:45,880
Speaker 1: have to get hospitalized. This is a study published just

1063
00:54:45,920 --> 00:54:47,759
Speaker 1: in the past year. So we're in the process of

1064
00:54:47,760 --> 00:54:49,680
Speaker 1: trying to get better and figure out how can we

1065
00:54:49,760 --> 00:54:52,480
Speaker 1: better help people, how can we tailor interventions to people

1066
00:54:52,680 --> 00:54:55,560
Speaker 1: to figure out who's likely to benefit from which intervention.

1067
00:54:56,080 --> 00:54:59,279
Speaker 1: So again, we're making progress, but there's still a long

1068
00:54:59,320 --> 00:54:59,719
Speaker 1: way to go.

1069
00:55:00,040 --> 00:55:04,520
Speaker 2: Are there some careers that are predisposed to suicidal suicide?

1070
00:55:04,719 --> 00:55:07,759
Speaker 1: It's hard to tease apart from race and ethnicity. So

1071
00:55:07,840 --> 00:55:10,719
Speaker 1: physicians are at high risk. Police officers are at high risk.

1072
00:55:11,440 --> 00:55:15,360
Speaker 1: There's a big concern. A few years back, there was

1073
00:55:15,360 --> 00:55:17,600
Speaker 1: a spike in suicides in New York City police officers.

1074
00:55:18,080 --> 00:55:20,200
Speaker 1: We did study on this. New York City police officers

1075
00:55:20,200 --> 00:55:23,520
Speaker 1: are mostly white men, and there was a blip up

1076
00:55:23,560 --> 00:55:25,600
Speaker 1: in one year, but it came right back down. Actually,

1077
00:55:25,600 --> 00:55:28,840
Speaker 1: female police officers had a higher risk, even when accounting

1078
00:55:28,840 --> 00:55:33,120
Speaker 1: for age and race and ethnicity, occupations where a person

1079
00:55:33,160 --> 00:55:36,120
Speaker 1: has access to means. This is another explanation for why physicians,

1080
00:55:36,400 --> 00:55:41,440
Speaker 1: why police officers, why soldiers, army soldiers, service members do

1081
00:55:41,560 --> 00:55:45,480
Speaker 1: have a significantly higher risk of suicide. Access to means,

1082
00:55:45,600 --> 00:55:48,240
Speaker 1: we think, we think plays a role. Access to access

1083
00:55:48,280 --> 00:55:53,200
Speaker 1: to lethal means, firearms, medications.

1084
00:55:53,640 --> 00:55:57,759
Speaker 2: Yeah, and that, of course, yes, sadly is widely accessible

1085
00:55:57,760 --> 00:56:00,440
Speaker 2: as well, right, and yeah, I.

1086
00:56:00,400 --> 00:56:02,920
Speaker 1: Mean there's also big geographic differences in the US, So

1087
00:56:03,320 --> 00:56:07,319
Speaker 1: suicide rates our highest out west, if you look sort

1088
00:56:07,320 --> 00:56:09,279
Speaker 1: of north and south of Las Vegas. People call this

1089
00:56:09,280 --> 00:56:13,840
Speaker 1: a suicide built there's access to firearms, there's not ready

1090
00:56:13,880 --> 00:56:17,319
Speaker 1: access to good hospital care, good treatments. You might have

1091
00:56:17,320 --> 00:56:20,520
Speaker 1: to drive three four hours to go see a clinician.

1092
00:56:20,840 --> 00:56:23,560
Speaker 1: And there's low population density, so you don't have contact

1093
00:56:23,600 --> 00:56:24,839
Speaker 1: with a lot of people day to day. So if

1094
00:56:24,880 --> 00:56:27,840
Speaker 1: you're having thoughts of suicide and you don't have people

1095
00:56:27,920 --> 00:56:30,160
Speaker 1: right around you, you don't have access to care, and

1096
00:56:30,200 --> 00:56:31,880
Speaker 1: you have access to firearms, we think this is a

1097
00:56:31,880 --> 00:56:36,600
Speaker 1: pretty lethal. Cocktail rates are lowest historically in New York,

1098
00:56:36,680 --> 00:56:38,640
Speaker 1: New Jersey. From New Jersey, I think this might be

1099
00:56:38,719 --> 00:56:41,920
Speaker 1: high quality of life. People might disagree, but there's high

1100
00:56:41,960 --> 00:56:44,520
Speaker 1: population density and there's a lot of people around. It's

1101
00:56:44,560 --> 00:56:48,040
Speaker 1: pretty easy to find a hospital, to find a clinician

1102
00:56:48,040 --> 00:56:51,600
Speaker 1: where you can get treatment. So we think these factors

1103
00:56:52,120 --> 00:56:54,759
Speaker 1: to play a role, so not just occupation, but where

1104
00:56:54,800 --> 00:56:57,680
Speaker 1: you live and what access you have again, which is

1105
00:56:57,719 --> 00:57:01,359
Speaker 1: another reason why I think online care generative AI has

1106
00:57:01,360 --> 00:57:03,400
Speaker 1: a great role to play here. If you can access

1107
00:57:03,400 --> 00:57:05,759
Speaker 1: the Internet, you can now access care and so this

1108
00:57:05,960 --> 00:57:07,600
Speaker 1: changes the playing field quite a bit, or has the

1109
00:57:07,600 --> 00:57:08,120
Speaker 1: potential to.

1110
00:57:08,520 --> 00:57:11,040
Speaker 2: Matthew, I know when we spoke on zoom a few

1111
00:57:11,040 --> 00:57:14,080
Speaker 2: months back, you shared a personal story with me that

1112
00:57:14,160 --> 00:57:17,600
Speaker 2: really resonated with me because of the incredible work you do,

1113
00:57:18,200 --> 00:57:19,960
Speaker 2: but then the personal experience you have. Would you be

1114
00:57:20,000 --> 00:57:23,400
Speaker 2: comfortable sharing that with us? Sure, because I'd love my

1115
00:57:23,480 --> 00:57:28,240
Speaker 2: listeners to just recognize just how complex and layered this

1116
00:57:28,280 --> 00:57:31,720
Speaker 2: subject is not just for you, but in the experience

1117
00:57:31,760 --> 00:57:33,880
Speaker 2: of it for anyone who goes through as well.

1118
00:57:34,200 --> 00:57:37,240
Speaker 1: When I first became interested in suicide in the hospital

1119
00:57:37,800 --> 00:57:41,200
Speaker 1: in tuting back in London Springfield Hospital, I didn't know

1120
00:57:41,240 --> 00:57:45,200
Speaker 1: anybody who was suicidal. It was a clinical human interest.

1121
00:57:45,600 --> 00:57:49,040
Speaker 1: Over the years, I've had friends and Filamy members who

1122
00:57:49,080 --> 00:57:52,360
Speaker 1: have struggled with thoughts of suicide and have died by suicide.

1123
00:57:52,440 --> 00:57:56,240
Speaker 1: And actually one of my best friends, Dan Dan Eisenbud

1124
00:57:56,280 --> 00:57:58,440
Speaker 1: I met in London when I was working in this

1125
00:57:58,440 --> 00:58:00,920
Speaker 1: hospital and became very close friends. We became roommates where

1126
00:58:00,960 --> 00:58:04,800
Speaker 1: roommates through my graduate studies, and just a few years

1127
00:58:04,840 --> 00:58:11,080
Speaker 1: back we lost him to suicide and it it wrecked

1128
00:58:11,080 --> 00:58:14,600
Speaker 1: me and I continue to struggle with with the loss.

1129
00:58:15,760 --> 00:58:17,520
Speaker 1: He was one of my dear friends. And I went

1130
00:58:17,560 --> 00:58:19,440
Speaker 1: back and looked at my notes and looked at my emails.

1131
00:58:19,480 --> 00:58:23,400
Speaker 1: He was living in Israel working as a journalist, was

1132
00:58:23,440 --> 00:58:25,600
Speaker 1: planning and coming back to the US, and I was

1133
00:58:25,640 --> 00:58:27,760
Speaker 1: reading over his emails. Hey, I'm coming back. Maybe I

1134
00:58:27,840 --> 00:58:30,200
Speaker 1: moved to Boston looking for apartments? Can you help me out?

1135
00:58:30,240 --> 00:58:32,200
Speaker 1: And I was looking for any clues what might I

1136
00:58:32,200 --> 00:58:34,200
Speaker 1: have missed? Nothing I didn't. I didn't see anything in

1137
00:58:34,760 --> 00:58:37,480
Speaker 1: the emails. But it was I think, just an example

1138
00:58:37,520 --> 00:58:40,320
Speaker 1: of how difficult it can be, not just to lose someone,

1139
00:58:40,360 --> 00:58:42,680
Speaker 1: but then to struggle with, you know, wanting to have

1140
00:58:42,760 --> 00:58:46,920
Speaker 1: done more for him, for his family, for for his friends.

1141
00:58:47,360 --> 00:58:49,880
Speaker 1: It's a tough problem. It's a perplexing problem, it's a

1142
00:58:49,920 --> 00:58:53,240
Speaker 1: gut wrenching problem. And I think just for me, it's

1143
00:58:53,320 --> 00:58:56,240
Speaker 1: motivation to do better and to not rest and to

1144
00:58:56,280 --> 00:58:58,080
Speaker 1: keep trying to get better at doing this.

1145
00:58:59,000 --> 00:59:02,240
Speaker 2: Thank you for sharing that. How do people even begin

1146
00:59:02,360 --> 00:59:05,200
Speaker 2: to recover from that feeling that they let someone down

1147
00:59:06,320 --> 00:59:10,080
Speaker 2: or that they missed a sign or that they could

1148
00:59:10,120 --> 00:59:13,560
Speaker 2: have done more? Because I imagine that's a very heavyweight

1149
00:59:13,600 --> 00:59:18,520
Speaker 2: to carry, and it can be really difficult when, like

1150
00:59:18,560 --> 00:59:21,960
Speaker 2: in your case, there were no signs that you could spot. Yeah,

1151
00:59:22,080 --> 00:59:24,760
Speaker 2: and you're someone who's trained to do that. Yeah, when

1152
00:59:25,040 --> 00:59:26,360
Speaker 2: we're not trained.

1153
00:59:26,320 --> 00:59:30,640
Speaker 1: I think giving yourself that grace that I would say,

1154
00:59:30,680 --> 00:59:32,640
Speaker 1: you know, those of us who I've been trained to

1155
00:59:32,640 --> 00:59:34,160
Speaker 1: do this, I've spent the past few decades of my

1156
00:59:34,200 --> 00:59:36,400
Speaker 1: life trying to do this. I can't do it. I

1157
00:59:36,440 --> 00:59:39,880
Speaker 1: can't predict accurately who's at risk and who's not. If

1158
00:59:39,920 --> 00:59:42,480
Speaker 1: I can't do it, chances are those among us who

1159
00:59:42,520 --> 00:59:45,120
Speaker 1: haven't spent their life trying to do this probably can't

1160
00:59:45,120 --> 00:59:46,640
Speaker 1: do it either. So don't expect that you should have

1161
00:59:46,640 --> 00:59:50,440
Speaker 1: been able to do it. People grieve differently. There's a

1162
00:59:50,440 --> 00:59:52,640
Speaker 1: lot of misconceptions about the stage. There are stages of grief,

1163
00:59:52,680 --> 00:59:55,960
Speaker 1: and we almost go through them in this linear way

1164
00:59:56,120 --> 00:59:58,440
Speaker 1: that's not true. We all grieve differently, and I think

1165
00:59:58,440 --> 01:00:01,000
Speaker 1: it's important for people to do what's right for them.

1166
01:00:01,240 --> 01:00:03,840
Speaker 1: Here too, I would say reach out to others. There

1167
01:00:03,840 --> 01:00:07,240
Speaker 1: are groups of survivors. There's an organization, the American Foundation

1168
01:00:07,280 --> 01:00:12,040
Speaker 1: for Suicide Prevention AFSP dot org has survivor groups support

1169
01:00:12,120 --> 01:00:15,120
Speaker 1: groups in every state in the US. These exist in

1170
01:00:15,160 --> 01:00:17,600
Speaker 1: other countries around the world, where you can go as

1171
01:00:17,640 --> 01:00:19,720
Speaker 1: you want and meet with other people who have lost

1172
01:00:19,760 --> 01:00:22,640
Speaker 1: loved ones to suicide, or do this online, or do

1173
01:00:22,720 --> 01:00:26,800
Speaker 1: this among your friends and family, but use the supports

1174
01:00:26,840 --> 01:00:29,880
Speaker 1: you have around you to try and work through whatever

1175
01:00:29,920 --> 01:00:33,160
Speaker 1: way makes sense for you. But here too, again, I

1176
01:00:33,160 --> 01:00:35,320
Speaker 1: would encourage people to reach out and to communicate with

1177
01:00:35,360 --> 01:00:37,880
Speaker 1: others about what they're experiencing. It can be powerful to

1178
01:00:38,440 --> 01:00:40,720
Speaker 1: know other people who have been through what you've been

1179
01:00:40,760 --> 01:00:45,040
Speaker 1: through and to share with them.

1180
01:00:45,080 --> 01:00:47,360
Speaker 2: When someone dies by suicide, what does it do to

1181
01:00:47,440 --> 01:00:50,800
Speaker 2: their family? What have you seen happen to people friends

1182
01:00:50,800 --> 01:00:53,680
Speaker 2: and family? From a research perspective.

1183
01:00:53,600 --> 01:00:57,200
Speaker 1: Yeah, losing someone to suicide increases the risk, So having

1184
01:00:57,200 --> 01:01:01,080
Speaker 1: a family member died by suicide increases a relative's risk

1185
01:01:01,200 --> 01:01:05,240
Speaker 1: of suicide death. It's not destiny, but there is statistically

1186
01:01:05,240 --> 01:01:09,160
Speaker 1: an increased chance of suicide, and it just leads to

1187
01:01:09,680 --> 01:01:14,200
Speaker 1: often not always, a lot of psychological distress is an

1188
01:01:14,280 --> 01:01:18,480
Speaker 1: understatement turmoil. There's a loss, as there is if you

1189
01:01:18,560 --> 01:01:20,960
Speaker 1: lost someone to a car accident, So there's a tremendous

1190
01:01:21,000 --> 01:01:24,320
Speaker 1: loss of life, and that is gut wrenching to anyone

1191
01:01:24,360 --> 01:01:28,160
Speaker 1: who's ever lost a family member. It's disorienting. It changes,

1192
01:01:28,240 --> 01:01:31,160
Speaker 1: it can change people are different, can change your whole world,

1193
01:01:31,280 --> 01:01:35,600
Speaker 1: your world orientation, your own mental health. When someone dies

1194
01:01:35,640 --> 01:01:38,600
Speaker 1: by their own hand, it's often so much worse because

1195
01:01:38,640 --> 01:01:42,800
Speaker 1: there's there's often guilt. There's questions about should I have

1196
01:01:42,800 --> 01:01:44,520
Speaker 1: done more? Could I have done more? Did I play

1197
01:01:44,560 --> 01:01:46,920
Speaker 1: some role in this? Was? Was I not nice enough

1198
01:01:47,000 --> 01:01:48,560
Speaker 1: last time I saw the person? Did I not reach

1199
01:01:48,600 --> 01:01:51,320
Speaker 1: out enough. There's a lot of second guessing, a lot

1200
01:01:51,360 --> 01:01:55,760
Speaker 1: of beating oneself up. So it can be really, really difficult.

1201
01:01:55,800 --> 01:01:58,720
Speaker 1: But again, people people respond differently. Some people respond by

1202
01:01:58,720 --> 01:02:01,600
Speaker 1: never talking about it, respond by getting closer to those

1203
01:02:01,600 --> 01:02:05,600
Speaker 1: around them. Some respond by becoming an advocate and trying

1204
01:02:05,640 --> 01:02:08,520
Speaker 1: to decrease the likelihood that this happens to other people

1205
01:02:08,520 --> 01:02:11,280
Speaker 1: in the future, which always always blows me away and

1206
01:02:11,320 --> 01:02:12,440
Speaker 1: I find really inspiring.

1207
01:02:12,920 --> 01:02:16,360
Speaker 2: Is there any truth in the feeling that people who

1208
01:02:16,360 --> 01:02:19,360
Speaker 2: die by suicide believe that everyone will be better off

1209
01:02:19,400 --> 01:02:21,480
Speaker 2: without me or is that a man?

1210
01:02:21,600 --> 01:02:26,440
Speaker 1: Yeah, not a myth feeling like. There's a brilliant psychologist

1211
01:02:26,520 --> 01:02:28,600
Speaker 1: named Thomas Joyner who's got a wonderful book called Why

1212
01:02:28,600 --> 01:02:31,560
Speaker 1: People Die by Suicide? And he lost his file to

1213
01:02:31,600 --> 01:02:34,760
Speaker 1: suicide and as a leading scientist in this problem, and

1214
01:02:35,200 --> 01:02:39,400
Speaker 1: in his theory on suicide, he says, feeling like a

1215
01:02:39,440 --> 01:02:42,600
Speaker 1: burden to others is a key piece, and you feeling

1216
01:02:42,640 --> 01:02:44,880
Speaker 1: like you don't belong is the other key piece, and

1217
01:02:44,920 --> 01:02:47,400
Speaker 1: that those two things together, I'm a burden to others.

1218
01:02:47,440 --> 01:02:49,480
Speaker 1: They'd be better off if I wasn't here, and I

1219
01:02:49,520 --> 01:02:53,360
Speaker 1: don't really belong with anyone or to anyone. Those things

1220
01:02:53,400 --> 01:02:56,160
Speaker 1: get a person thinking about suicide. And then the other

1221
01:02:56,200 --> 01:02:59,040
Speaker 1: piece of the puzzle from his perspective is what he

1222
01:02:59,080 --> 01:03:03,160
Speaker 1: calls an acquired ability to die by suicide. It's not

1223
01:03:03,240 --> 01:03:07,560
Speaker 1: an easy thing psychologically to take your life, and it

1224
01:03:07,600 --> 01:03:09,840
Speaker 1: takes he says in his book, he used to call

1225
01:03:09,880 --> 01:03:12,440
Speaker 1: it courage, but courage isn't quite right, and now he

1226
01:03:12,480 --> 01:03:15,080
Speaker 1: calls it an acquired capability that we have to build up,

1227
01:03:15,440 --> 01:03:18,160
Speaker 1: an ability to like we have the bill up and

1228
01:03:18,200 --> 01:03:20,640
Speaker 1: ability to hurt someone else, to hurt ourselves. And this

1229
01:03:20,720 --> 01:03:25,800
Speaker 1: is why he thinks maybe physicians and police officers, prostitutes

1230
01:03:25,840 --> 01:03:28,280
Speaker 1: are at higher risk. That it's if you've been injured,

1231
01:03:28,560 --> 01:03:32,840
Speaker 1: if you've injured, you've now acquired the ability to hurt yourself,

1232
01:03:33,160 --> 01:03:36,000
Speaker 1: and that this increases a person's risk. Feeling a burden,

1233
01:03:36,040 --> 01:03:38,000
Speaker 1: feeling you don't belong certainly resonates, and there are good

1234
01:03:38,080 --> 01:03:40,320
Speaker 1: data on this that this does increase a person's risk. Again,

1235
01:03:40,400 --> 01:03:43,040
Speaker 1: thinking about the pathway, this increases your risk of thinking

1236
01:03:43,040 --> 01:03:45,440
Speaker 1: about suicide but not acting. You need this other component

1237
01:03:46,080 --> 01:03:47,120
Speaker 1: to get you to act.

1238
01:03:47,400 --> 01:03:50,800
Speaker 2: It's interesting that you said that suicide rates haven't really

1239
01:03:51,680 --> 01:03:54,720
Speaker 2: gone up, because I guess we'd assume that because of

1240
01:03:54,720 --> 01:03:58,960
Speaker 2: social media, because of online bullying, because of the news cycle. Yeah,

1241
01:03:59,040 --> 01:04:03,680
Speaker 2: there's almost so much much more overexposure to depressive, negative,

1242
01:04:03,720 --> 01:04:07,080
Speaker 2: difficult thoughts. Yeah, why is that? How do you even

1243
01:04:07,080 --> 01:04:07,640
Speaker 2: explain that?

1244
01:04:07,760 --> 01:04:10,320
Speaker 1: Yeah, the suicide rate does ebb and flow. If you

1245
01:04:10,360 --> 01:04:12,280
Speaker 1: look back and we've mapped it out over the past

1246
01:04:12,320 --> 01:04:14,600
Speaker 1: one hundred years, you see a little up and down,

1247
01:04:14,720 --> 01:04:17,000
Speaker 1: and it's crept up in the past twenty years, but

1248
01:04:17,000 --> 01:04:19,120
Speaker 1: it crept down the twenty years before that, and people

1249
01:04:19,120 --> 01:04:22,440
Speaker 1: will say, well, it's because of social media breakdown of

1250
01:04:22,480 --> 01:04:24,919
Speaker 1: the field. There's always post hoc explanations we can give,

1251
01:04:26,160 --> 01:04:28,000
Speaker 1: but again, it's the same now as it was one

1252
01:04:28,080 --> 01:04:30,840
Speaker 1: hundred years ago, and I don't think the explanation is

1253
01:04:30,880 --> 01:04:34,400
Speaker 1: as simple. As we now have social media. Social media bad,

1254
01:04:35,280 --> 01:04:37,840
Speaker 1: it's making kids suicidal. I think it's a tool and

1255
01:04:38,040 --> 01:04:41,000
Speaker 1: things that happen on social media can put people at risk.

1256
01:04:41,320 --> 01:04:42,680
Speaker 1: There are things that happen on social media that can

1257
01:04:42,680 --> 01:04:45,960
Speaker 1: also decrease risk. And so again I think it's incumbent

1258
01:04:46,080 --> 01:04:47,720
Speaker 1: upon us to try and figure out how do we

1259
01:04:47,840 --> 01:04:51,080
Speaker 1: use these tools that are here to stay for good

1260
01:04:51,160 --> 01:04:53,040
Speaker 1: and allow them to be used for evil.

1261
01:04:53,200 --> 01:04:55,360
Speaker 2: Not to thank you so much, it's been so useful

1262
01:04:55,360 --> 01:04:57,640
Speaker 2: and insightful talking to you today, and thank you for

1263
01:04:57,680 --> 01:05:01,480
Speaker 2: your work. And I look forward to hoping our listeners

1264
01:05:01,640 --> 01:05:04,560
Speaker 2: support your work, whether it's sharing it with a friend,

1265
01:05:04,640 --> 01:05:08,000
Speaker 2: passing this episode on to a family member, or directly

1266
01:05:08,040 --> 01:05:09,800
Speaker 2: supporting the work that you're doing there in the lab.

1267
01:05:09,880 --> 01:05:12,080
Speaker 2: So thank you so much. I'd be really grateful for

1268
01:05:12,120 --> 01:05:12,920
Speaker 2: your time and energy.

1269
01:05:12,960 --> 01:05:14,760
Speaker 1: Thank you so so much for focusing on this problem,

1270
01:05:14,760 --> 01:05:17,040
Speaker 1: for shining a light on it, and I'm hoping that

1271
01:05:17,120 --> 01:05:20,400
Speaker 1: this podcast and the work you're doing can help save lives.

1272
01:05:20,440 --> 01:05:20,880
Speaker 1: So thank you.

1273
01:05:21,440 --> 01:05:23,800
Speaker 2: I've learned so much today, man, And it's one of

1274
01:05:23,840 --> 01:05:27,560
Speaker 2: those subjects that I feel like needs to be talked about,

1275
01:05:27,720 --> 01:05:31,320
Speaker 2: needs to be trained in, needs to be spoken about.

1276
01:05:31,480 --> 01:05:34,080
Speaker 2: Just with I mean with the couple of new stories

1277
01:05:34,120 --> 01:05:36,320
Speaker 2: I shared today, one more as well that I saw

1278
01:05:37,840 --> 01:05:41,720
Speaker 2: was I think this was like, Yeah, dad struggling with

1279
01:05:41,800 --> 01:05:45,960
Speaker 2: money pressures, leaves behind wife, baby son, after taking own life,

1280
01:05:46,800 --> 01:05:50,520
Speaker 2: you know, battling with financial stress, everything turned upside down,

1281
01:05:50,560 --> 01:05:53,280
Speaker 2: the family said, and then eventually led to that like

1282
01:05:53,320 --> 01:05:56,760
Speaker 2: when you see the multitude of reasons, even in the

1283
01:05:56,840 --> 01:06:00,560
Speaker 2: couple of stories that I've found and shared, Yeah, it's

1284
01:06:00,600 --> 01:06:04,440
Speaker 2: an area that I just feel like we can't leave

1285
01:06:04,440 --> 01:06:08,240
Speaker 2: in the dark anymore, because, like you said, the fact

1286
01:06:08,240 --> 01:06:11,240
Speaker 2: that you can't predict it perfectly means we should be

1287
01:06:11,280 --> 01:06:16,360
Speaker 2: more vigilant and more aware because someone literally could appear

1288
01:06:16,880 --> 01:06:21,440
Speaker 2: to not be struggling at all and then, you know,

1289
01:06:21,600 --> 01:06:22,840
Speaker 2: potentially take their life.

1290
01:06:23,040 --> 01:06:25,560
Speaker 1: Absolutely, closing our eyes to it is not making it

1291
01:06:25,640 --> 01:06:28,640
Speaker 1: go away. That's not going to solve the problem. We're

1292
01:06:28,640 --> 01:06:31,640
Speaker 1: getting better at predicting it. We can't predict it perfectly,

1293
01:06:31,760 --> 01:06:34,960
Speaker 1: but that doesn't mean we should stop again. You think

1294
01:06:34,960 --> 01:06:38,240
Speaker 1: about the weather app that's on your phone. It can

1295
01:06:38,240 --> 01:06:41,800
Speaker 1: tell us with a startling degree of accuracy when it's

1296
01:06:41,800 --> 01:06:43,680
Speaker 1: going to start, raining, when it's going to stop, what

1297
01:06:43,720 --> 01:06:46,320
Speaker 1: the temperature is going to be in any time and place.

1298
01:06:47,520 --> 01:06:50,880
Speaker 1: That's a model. It's a simple analogy. But there's a

1299
01:06:51,000 --> 01:06:53,200
Speaker 1: lot more we could do. There's a lot greater accuracy

1300
01:06:53,200 --> 01:06:56,320
Speaker 1: we could have in predicting who's at risk and when,

1301
01:06:56,640 --> 01:06:58,160
Speaker 1: and there's a lot more we could do to try

1302
01:06:58,160 --> 01:07:00,440
Speaker 1: and keep people safe. We just need to try and

1303
01:07:00,480 --> 01:07:02,959
Speaker 1: stop the stigma around it, talk about the problem more,

1304
01:07:03,320 --> 01:07:05,360
Speaker 1: and allocate resources to try and get it done.

1305
01:07:05,640 --> 01:07:09,000
Speaker 2: Has there been a not wanting to sound reductive in

1306
01:07:09,080 --> 01:07:11,959
Speaker 2: any way, but has there been Seeing as you've spent

1307
01:07:12,800 --> 01:07:16,240
Speaker 2: decades studying this, now, what keeps you going, what motivates you,

1308
01:07:16,400 --> 01:07:21,560
Speaker 2: what allows you to feel potentially positive about the future

1309
01:07:21,560 --> 01:07:21,800
Speaker 2: of this.

1310
01:07:22,720 --> 01:07:29,280
Speaker 1: I'm increasingly hopeful about our ability to better understand, predict

1311
01:07:29,360 --> 01:07:32,040
Speaker 1: and prevent suicide because of the people who are doing

1312
01:07:32,040 --> 01:07:34,919
Speaker 1: this work, the people who have lost loved ones to suicide,

1313
01:07:34,960 --> 01:07:41,120
Speaker 1: who support research on suicide, the clinicians, the researchers, the

1314
01:07:41,280 --> 01:07:43,200
Speaker 1: progress that has been made in the past ten to

1315
01:07:43,280 --> 01:07:47,640
Speaker 1: fifteen years. I mentioned, we're now better able to identify

1316
01:07:47,680 --> 01:07:49,920
Speaker 1: who's at risk and when they're at risk. Our interventions

1317
01:07:49,960 --> 01:07:52,840
Speaker 1: are getting better and more numerous. There's newer interventions coming

1318
01:07:52,880 --> 01:07:55,560
Speaker 1: out all the time. So we're seeing a lot of traction,

1319
01:07:56,240 --> 01:07:59,240
Speaker 1: a lot of positive progress. So that keeps me optimistic.

1320
01:08:00,160 --> 01:08:02,840
Speaker 1: And I also continue to see people die by suicide

1321
01:08:02,880 --> 01:08:06,280
Speaker 1: and continue to see how big of a problem it is,

1322
01:08:07,560 --> 01:08:09,880
Speaker 1: and I see the opportunity for us to do a

1323
01:08:09,920 --> 01:08:12,880
Speaker 1: lot better. And so those things together, how bad we're

1324
01:08:12,880 --> 01:08:16,000
Speaker 1: doing and the instances what we're losing life, but also

1325
01:08:16,080 --> 01:08:18,960
Speaker 1: the positive steps we're making give me hope that with

1326
01:08:19,000 --> 01:08:21,439
Speaker 1: more of a push, with more resource, with more effort,

1327
01:08:21,920 --> 01:08:24,360
Speaker 1: there's reason to be optimistic. There's reason to be hopeful.

1328
01:08:25,040 --> 01:08:27,479
Speaker 1: And this is a problem where we hopefully in the

1329
01:08:27,520 --> 01:08:31,120
Speaker 1: coming years, can start to see the needle bend and

1330
01:08:31,160 --> 01:08:36,080
Speaker 1: the suicide rate drop, especially given how connected we all

1331
01:08:36,120 --> 01:08:39,320
Speaker 1: are now we have the ability to find people at risk.

1332
01:08:39,680 --> 01:08:41,120
Speaker 1: If we can just figure out how to use these

1333
01:08:41,160 --> 01:08:45,519
Speaker 1: tools in a more positive way, I think we'll really

1334
01:08:45,520 --> 01:08:46,120
Speaker 1: make an impact.

1335
01:08:46,360 --> 01:08:48,280
Speaker 2: Yeah, Matthew, thank you so much. Is there anything I

1336
01:08:48,280 --> 01:08:50,400
Speaker 2: haven't asked you that you think would be important to

1337
01:08:50,439 --> 01:08:52,840
Speaker 2: ask you about this, So, anything you haven't shared that

1338
01:08:52,880 --> 01:08:54,599
Speaker 2: you think would be useful for us to know.

1339
01:08:54,920 --> 01:08:57,719
Speaker 1: I think no. I think we covered a lot of

1340
01:08:58,280 --> 01:09:00,600
Speaker 1: the most important things. I think the most important thing

1341
01:09:00,680 --> 01:09:02,760
Speaker 1: is what you're doing, which is shining a light on

1342
01:09:02,800 --> 01:09:06,640
Speaker 1: the problem, talking about it, encouraging others to talk about it.

1343
01:09:07,400 --> 01:09:10,200
Speaker 1: Knowing that their resources out there, and knowing what to

1344
01:09:10,240 --> 01:09:12,000
Speaker 1: say to someone or having a sense of what to

1345
01:09:12,000 --> 01:09:13,800
Speaker 1: say to someone who you think is at risk, you

1346
01:09:13,840 --> 01:09:15,719
Speaker 1: can take steps to try and help them.

1347
01:09:15,880 --> 01:09:19,640
Speaker 2: Yeah, any other resources or any other directions or practices

1348
01:09:19,680 --> 01:09:22,240
Speaker 2: that you'd recommend that we got to share with people today.

1349
01:09:22,320 --> 01:09:25,040
Speaker 1: So if people want to get involved in support this

1350
01:09:25,160 --> 01:09:26,880
Speaker 1: cause in some way, there's a number of ways to

1351
01:09:26,920 --> 01:09:29,280
Speaker 1: do so. I would definitely recommend reaching out to the

1352
01:09:29,280 --> 01:09:34,479
Speaker 1: American Foundation for Suicide Prevention AFSP dot org, which supports

1353
01:09:34,479 --> 01:09:38,320
Speaker 1: research on suicide and also supports educational programs. They have

1354
01:09:38,439 --> 01:09:41,240
Speaker 1: great resources if you've lost someone to suicide, if you're

1355
01:09:41,240 --> 01:09:42,920
Speaker 1: looking for a support group, So I would definitely look

1356
01:09:42,960 --> 01:09:44,840
Speaker 1: at them as a resource. And if you want to

1357
01:09:44,840 --> 01:09:48,800
Speaker 1: give to support research on suicide, we'd be grateful. If

1358
01:09:48,800 --> 01:09:50,640
Speaker 1: you did, you can do so by reaching out to

1359
01:09:50,800 --> 01:09:53,639
Speaker 1: Harvard University. You can reach out to our lab directly

1360
01:09:53,680 --> 01:09:57,600
Speaker 1: and donate through our labs website. If you google my

1361
01:09:57,720 --> 01:10:02,080
Speaker 1: name or look at knock Lab fas dot Harvard edu,

1362
01:10:02,400 --> 01:10:05,760
Speaker 1: you can support our works work directly. You can also

1363
01:10:05,800 --> 01:10:09,719
Speaker 1: support the Center for Suicide Research and Prevention at Harvard

1364
01:10:09,800 --> 01:10:13,479
Speaker 1: University in Nationeneral Hospital, which is a center devoted to

1365
01:10:14,160 --> 01:10:17,200
Speaker 1: conducting research on suicide to try and prevent the loss

1366
01:10:17,200 --> 01:10:19,320
Speaker 1: of life due to suicide. So any of those would

1367
01:10:19,360 --> 01:10:21,880
Speaker 1: be amazingly helpful to support this work.

1368
01:10:22,080 --> 01:10:24,400
Speaker 2: Amazing Yeah, very usefully. I'm sure there's so many people

1369
01:10:24,400 --> 01:10:28,519
Speaker 2: who've been affected directly indirectly by someone in their life,

1370
01:10:28,520 --> 01:10:30,439
Speaker 2: and I'm sure i'm sure there'll be people who want

1371
01:10:30,479 --> 01:10:33,360
Speaker 2: to support. So thank you for sharing those And yeah,

1372
01:10:33,479 --> 01:10:35,360
Speaker 2: I'm really grateful for the work you're doing and the

1373
01:10:35,439 --> 01:10:37,960
Speaker 2: light you're shining on it, and just your ongoing commitment

1374
01:10:37,960 --> 01:10:41,000
Speaker 2: and dedication. If you love this episode, you'll enjoy my

1375
01:10:41,120 --> 01:10:44,240
Speaker 2: interview with doctor Daniel Ahman on how to change your

1376
01:10:44,280 --> 01:10:45,960
Speaker 2: life by changing your brain.

1377
01:10:46,439 --> 01:10:51,400
Speaker 1: If we want a healthy mind, it actually starts with

1378
01:10:51,479 --> 01:10:54,680
Speaker 1: a healthy brain. You know, I've had the blessing or

1379
01:10:54,720 --> 01:10:59,200
Speaker 1: the curse to scam. Over one thousand convicted felons and

1380
01:10:59,320 --> 01:11:03,080
Speaker 1: over one hundred murderers and their brains are very damaged.