WEBVTT 1 00:00:01.210 --> 00:00:04.766 Hello, everyone. My name is Joanne Lockwood and I am your host for the 2 00:00:04.788 --> 00:00:08.526 Inclusion Bites podcast. In this series, I will be interviewing a 3 00:00:08.548 --> 00:00:12.254 number of amazing people and simply having a conversation around 4 00:00:12.292 --> 00:00:15.966 the subject of inclusion, belonging and generally making the 5 00:00:15.988 --> 00:00:19.726 world a better place for everyone to thrive in. If you would like 6 00:00:19.748 --> 00:00:22.606 to join me in the future, then please do drop me a line to 7 00:00:22.628 --> 00:00:24.480 jo.Lockwood@seechangehappen.co.uk. 8 00:00:30.250 --> 00:00:33.266 You'll be able to catch up with all of the episodes and shows on itunes 9 00:00:33.298 --> 00:00:37.026 and Spotify and of course, the usual places. So plug in your headphones, 10 00:00:37.138 --> 00:00:39.580 grab a decaf and let's get going. 11 00:00:40.350 --> 00:00:43.562 Today is episode seven with the title of 12 00:00:43.616 --> 00:00:46.742 Insights from the Science of Happiness and Positive 13 00:00:46.806 --> 00:00:50.074 Emotions. And I have the absolute honour and 14 00:00:50.112 --> 00:00:53.226 privilege to welcome my guest today, Nic 15 00:00:53.258 --> 00:00:56.686 Marks. And I met Nic randomly on 16 00:00:56.708 --> 00:00:59.934 LinkedIn, like you do. I think he was stalking me one day and we came 17 00:00:59.972 --> 00:01:03.630 across and we chatted. And now Nic is now on the podcast. 18 00:01:03.710 --> 00:01:06.846 Brilliant. So Nic is a statistician, a trained 19 00:01:06.878 --> 00:01:10.606 therapist and a ted speaker. A ted speaker. 20 00:01:10.638 --> 00:01:13.650 Gather. No, X. We're in the presence of royalty. 21 00:01:14.150 --> 00:01:17.886 Brene Brown's best friend, I'm sure, so well. 22 00:01:18.008 --> 00:01:21.558 And he's also the founder of the Friday Pulse and 23 00:01:21.644 --> 00:01:25.494 specialise in improving team morale and 24 00:01:25.532 --> 00:01:29.158 measuring it. So I asked Nic to describe his superpower 25 00:01:29.254 --> 00:01:32.682 and he said seeing the patterns between things 26 00:01:32.816 --> 00:01:36.570 and communicating simply without being simplistic. 27 00:01:36.990 --> 00:01:40.622 So, hello, Nic, welcome to the show. So, tell me more, what are 28 00:01:40.676 --> 00:01:43.710 insights from the Science of Happiness and positive emotions? 29 00:01:44.690 --> 00:01:47.998 Hi, Jo. So, yeah, I'm a 30 00:01:48.004 --> 00:01:51.594 statistician and I have, over the years, started to specialise 31 00:01:51.642 --> 00:01:55.200 in happiness and well being. I started off doing quality of life 32 00:01:55.570 --> 00:01:59.378 and I am a trained therapist. My mother was a 33 00:01:59.384 --> 00:02:02.898 family therapist, so I got quite interested in therapy when I was young. And 34 00:02:02.984 --> 00:02:06.174 although I was a statistician, I kind of end up with this mix 35 00:02:06.222 --> 00:02:09.942 between hard statistical skills and soft analytical ones, which 36 00:02:09.996 --> 00:02:13.666 probably makes it more interesting. And what are the insights 37 00:02:13.698 --> 00:02:17.238 from? I mean, there's so many insights from happiness and positive emotions, but 38 00:02:17.404 --> 00:02:21.130 most people tend to start by asking, what is happiness and 39 00:02:21.200 --> 00:02:24.714 is it different for different people? And in one 40 00:02:24.752 --> 00:02:28.186 way it's the same for us, and in other ways it's different in 41 00:02:28.208 --> 00:02:31.770 that happiness can be both thought of as an emotion. So I feel 42 00:02:31.840 --> 00:02:35.294 happy now, and also a thought I am happy with. And so 43 00:02:35.332 --> 00:02:39.022 there's a tension between how people use the word, so some people 44 00:02:39.076 --> 00:02:42.702 use it to mean contentment and quietness, and some people mean 45 00:02:42.756 --> 00:02:46.514 enthusiasm and joy. So the brilliant thing about the word happiness is 46 00:02:46.552 --> 00:02:50.114 that people can sort of project onto it lots of different things, 47 00:02:50.232 --> 00:02:53.646 and I kind of like that from an interpersonal 48 00:02:53.678 --> 00:02:57.106 perspective. But then when you get into how you measure it, you start getting more 49 00:02:57.128 --> 00:03:00.774 technical. So there's a lot of insights for them. But basically my 50 00:03:00.812 --> 00:03:04.230 work is about how the people live better lives. So when you talk about 51 00:03:04.300 --> 00:03:08.060 inclusion, belonging and creating better lives, that's kind of what I do. 52 00:03:09.150 --> 00:03:12.380 And I try and bring my statistical skills to that. 53 00:03:12.910 --> 00:03:16.342 Okay, I've always come from this inclusion 54 00:03:16.486 --> 00:03:20.054 concept about avoiding stereotypes, avoiding 55 00:03:20.102 --> 00:03:23.310 grouping people and creating in groups and out groups. But I guess 56 00:03:23.380 --> 00:03:26.926 statisticians, you're trying to use data to create groups of 57 00:03:26.948 --> 00:03:30.714 people. So how do you see the individual within that statistics 58 00:03:30.762 --> 00:03:32.670 rather than seeing people as a lump? 59 00:03:34.690 --> 00:03:38.094 It's very interesting. So you can use statistics in different ways, but mainly 60 00:03:38.142 --> 00:03:41.822 statistics, even the word comes from states, so it came from population 61 00:03:41.886 --> 00:03:45.438 surveys. That's the root of the word. And so, yes, was 62 00:03:45.464 --> 00:03:48.982 generally looking at populations, but not always. You're often looking to 63 00:03:49.036 --> 00:03:52.326 identify subpopulations and groups within that. And 64 00:03:52.348 --> 00:03:55.894 there's one, you see patterns sometimes you see 65 00:03:55.932 --> 00:03:59.574 patterns where all humans move in the same direction, and some patterns you see where 66 00:03:59.612 --> 00:04:03.306 different groups of people act differently. So you do start to see that, and there's 67 00:04:03.328 --> 00:04:06.966 a different analysis that you can do for that that starts identifying 68 00:04:06.998 --> 00:04:10.502 those. And there's some ways that when you're doing population 69 00:04:10.566 --> 00:04:14.286 statistics, the averages are very disappointing because you 70 00:04:14.308 --> 00:04:17.710 miss that variance. And actually all of us know in our own lives 71 00:04:17.780 --> 00:04:21.040 that people are different, and yet we're the same. 72 00:04:22.290 --> 00:04:25.870 There's two things going on. There's something generically about being human and then there's 73 00:04:25.950 --> 00:04:29.726 the variability within it. And actually stats is really quite good at identifying 74 00:04:29.758 --> 00:04:33.460 both of those things. So we can see 75 00:04:34.070 --> 00:04:37.714 if you're tracking people through time, you see some people becoming happier, some people 76 00:04:37.752 --> 00:04:41.446 becoming less happier, some people bouncing back, some people staying going know, you 77 00:04:41.468 --> 00:04:44.486 can see all of those patterns in it. And there is a lot of individual 78 00:04:44.588 --> 00:04:48.058 stories in there. I mean, a very classic one is that 79 00:04:48.144 --> 00:04:51.846 when population researchers look at happiness compared 80 00:04:51.878 --> 00:04:55.354 to age, you find that the least happy age is 81 00:04:55.392 --> 00:04:59.146 42, which I'm sure Douglas Adams would 82 00:04:59.168 --> 00:05:02.026 be delighted with that that was the answer to it. But that's roughly where it 83 00:05:02.048 --> 00:05:05.786 comes, early 40s. But of course there's many very happy 42 year olds 84 00:05:05.818 --> 00:05:09.338 and there's very many unhappy 60 year olds, and there's unhappy 20 year olds. 85 00:05:09.354 --> 00:05:13.054 So the means always hide a lot of stories. And 86 00:05:13.092 --> 00:05:16.206 I think that's one of the things you have to be careful about with statistics 87 00:05:16.238 --> 00:05:19.998 is that you don't hide that individual variability. Yeah, because we look at this bowel 88 00:05:20.014 --> 00:05:23.778 curve of normality, aren't we? This midpoint, and I 89 00:05:23.784 --> 00:05:27.414 suppose you got your upper percentiles and lower percentiles. What 90 00:05:27.452 --> 00:05:31.222 is normal? It's such a waffle thin part 91 00:05:31.276 --> 00:05:35.126 because everyone's normality is different, isn't it? It must be 92 00:05:35.148 --> 00:05:38.650 really hard to try and find typical human A or typical human 93 00:05:38.720 --> 00:05:42.026 B from a statistical point of view. You could probably plot it that 94 00:05:42.048 --> 00:05:45.254 I'm average height, maybe, but not average 95 00:05:45.302 --> 00:05:48.300 breadth. So many different factors around 96 00:05:48.670 --> 00:05:51.050 human makeup and opinions. 97 00:05:53.310 --> 00:05:56.542 We often talk in statistics about bell curve and we've talked about standard 98 00:05:56.596 --> 00:06:00.254 deviations. And one of my favourite stories about that is that 99 00:06:00.372 --> 00:06:04.206 they took these Buddhist monks and they were looking at brain scans of them, 100 00:06:04.308 --> 00:06:07.742 and they got them to meditate, and they were looking at these brain scans, 101 00:06:07.806 --> 00:06:11.506 and they were four standard deviations away from the mean of 102 00:06:11.528 --> 00:06:14.798 what other people's brain scans, which means it's entirely impossible they existed. 103 00:06:14.894 --> 00:06:18.626 But all ten of the Buddhist monks were similar. And what that basically meant, they 104 00:06:18.648 --> 00:06:22.454 started to realise, was that you can change the shape of your brain by your 105 00:06:22.492 --> 00:06:26.002 behaviour and your meditation. So the fact they'd done 20 years of meditation 106 00:06:26.146 --> 00:06:29.946 had actually created different patterns in their brain than we'd seen in 107 00:06:29.968 --> 00:06:33.546 a normal American, particularly population, before. 108 00:06:33.728 --> 00:06:37.082 And that wasn't that they were forced standard deviation, it's just that they had not 109 00:06:37.136 --> 00:06:38.620 met people like them before. 110 00:06:40.750 --> 00:06:44.538 Sometimes, statistically, you box things in too much and you have to 111 00:06:44.544 --> 00:06:47.662 watch out for that. So when we talk about things like 112 00:06:47.716 --> 00:06:51.566 bias and stereotyping and all these sort of things we do as humans for 113 00:06:51.588 --> 00:06:55.218 our own safety and protection, what you're saying basically, is the brain is learning a 114 00:06:55.224 --> 00:06:58.926 lot of this stuff and the plasticity of the brain. Society evolves 115 00:06:59.038 --> 00:07:01.940 based on your environment. Is that what you're trying to say here? 116 00:07:02.790 --> 00:07:06.558 Yes, we're definitely able to shape the plasticity of our brain. 117 00:07:06.654 --> 00:07:10.390 I mean, it happens with brain injuries, which you can sue people, and it 118 00:07:10.460 --> 00:07:14.246 happens with diseases such as Alzheimer's and dementia, but you 119 00:07:14.268 --> 00:07:18.066 can see it also with mindfulness and meditation that actually people start 120 00:07:18.108 --> 00:07:21.658 improving and how calm you are. I mean, I'm not a 121 00:07:21.664 --> 00:07:25.382 neuroscientist, so I just read some neuroscience. It's not my speciality. 122 00:07:25.446 --> 00:07:29.270 But if you ask about biases, 123 00:07:29.430 --> 00:07:33.194 then that's actually something different, really, because we have these two big 124 00:07:33.232 --> 00:07:36.366 systems. I don't know if you know Daniel Kahneman's work. Have you ever read his 125 00:07:36.388 --> 00:07:40.094 book? It's called thinking fast and thinking. Oh, yes, yeah. Fast 126 00:07:40.132 --> 00:07:43.954 brain slow, yeah, yes. And the fast brain is very 127 00:07:43.992 --> 00:07:47.006 emotional. It's looking for immediate signals, it's 128 00:07:47.118 --> 00:07:50.946 intuitive, it's biassed. And a 129 00:07:50.968 --> 00:07:54.290 typical way of thinking about it is that we have a very 130 00:07:54.360 --> 00:07:57.880 strong signal when we meet someone for new, 131 00:07:59.210 --> 00:08:02.678 we make a judgement about them straight away. And basically, from an 132 00:08:02.684 --> 00:08:06.534 evolutionary perspective, it's friend or foe. Should I approach this person? 133 00:08:06.572 --> 00:08:09.926 Should I avoid them? That's the most basic thing. And of 134 00:08:09.948 --> 00:08:13.690 course, if somebody looks like you, if somebody 135 00:08:13.760 --> 00:08:17.354 feels like they come from your tribe, they're a friend. And if they're different, they 136 00:08:17.392 --> 00:08:20.670 look different. Different colour, skin, different type of person, different 137 00:08:20.740 --> 00:08:24.206 accent, then they feel more like a 138 00:08:24.228 --> 00:08:27.946 foe. If you look at friendship groups, 139 00:08:27.978 --> 00:08:31.102 for example, you find that people have very strong 140 00:08:31.156 --> 00:08:34.974 friendship networks with the people that they grew up with because they've learned that 141 00:08:35.012 --> 00:08:38.606 friendship thing. Very strong friends with someone, the same accent. 142 00:08:38.718 --> 00:08:42.542 If you meet someone from your hometown later in life with an accent 143 00:08:42.686 --> 00:08:46.418 that's the same, you have an immediate trust. Even though it could just be a. 144 00:08:46.424 --> 00:08:49.846 Bad person, as a good person for someone, but you instinctively feel it and so 145 00:08:49.868 --> 00:08:52.680 there's all those biases going on all the time. And so 146 00:08:53.770 --> 00:08:57.574 that's just part of our speedy response, because if we 147 00:08:57.612 --> 00:09:01.354 had to assess everybody from route one every time, 148 00:09:01.392 --> 00:09:05.178 it would take too long and we wouldn't get anywhere completely. 149 00:09:05.344 --> 00:09:08.700 It's a very good way of putting it and explaining it, isn't it? 150 00:09:09.470 --> 00:09:13.306 Some of the challenges we face when we try and explain biases to people, where 151 00:09:13.328 --> 00:09:17.086 they root. And I often find that when we talk about bias, it always 152 00:09:17.108 --> 00:09:20.670 seems a negative thing. We actually have positive biases. We can actually favour 153 00:09:20.740 --> 00:09:24.558 people as well as discriminate or outgroup people. So it can 154 00:09:24.564 --> 00:09:27.842 work both ways, can't it? Yeah, well, I mean, I think it is that 155 00:09:27.896 --> 00:09:31.170 sorting it's a sort of Harry Potter sorting algorithm, isn't 156 00:09:31.510 --> 00:09:33.940 people, some people into gryffindor, some whatever. 157 00:09:36.630 --> 00:09:40.134 You're putting people in boxes because we can't deal with the whole person, so we 158 00:09:40.172 --> 00:09:43.762 categorise and we stick them there. And that is useful, 159 00:09:43.826 --> 00:09:47.206 but it's not a holistic approach. And of 160 00:09:47.228 --> 00:09:51.046 course you can't pay attention to everybody that you meet. You just 161 00:09:51.068 --> 00:09:54.730 be overloaded too much information. Yeah, you have to. Philtre 162 00:09:56.510 --> 00:10:00.154 we're recording this right in the middle of the new norm, this 163 00:10:00.192 --> 00:10:03.982 unprecedented times, whatever adjective we want to describe our current 164 00:10:04.036 --> 00:10:07.374 situation in. But the reality is that the world's changed for a lot of people 165 00:10:07.412 --> 00:10:10.894 in various ways. I mean, myself and many people we probably 166 00:10:10.932 --> 00:10:14.654 know. So as a statistician, you must be looking at the 167 00:10:14.692 --> 00:10:17.918 news, looking at the figures that come out of government, the graphs they're 168 00:10:17.934 --> 00:10:21.746 producing. Is that kind of like a busmat holiday for you? Is 169 00:10:21.768 --> 00:10:25.406 that kind of things that you really love? Or is it shouting at the telly, 170 00:10:25.438 --> 00:10:28.866 going, come on, these stats are telling a lie. How do you see the stats 171 00:10:28.898 --> 00:10:32.120 that are coming out? Well, it's interesting. I mean, 172 00:10:32.490 --> 00:10:36.182 talking about bias, there's something called a negativity bias in 173 00:10:36.236 --> 00:10:40.034 psychology, which is we pay attention to negative news and negative 174 00:10:40.082 --> 00:10:43.740 signals. And the reason why, again, evolutionary reason, is that 175 00:10:44.510 --> 00:10:48.298 threats can kill us and you only die once. So we pay a lot more 176 00:10:48.304 --> 00:10:51.914 attention to anything that could possibly kill us, because life is long and 177 00:10:52.032 --> 00:10:55.742 death comes once, whereas positive things happening are not so interesting 178 00:10:55.796 --> 00:10:59.246 to us because they keep coming along. So we don't report very much on 179 00:10:59.268 --> 00:11:02.462 weddings and things like that. We report on deaths, we report on bad 180 00:11:02.516 --> 00:11:06.094 stuff. And so what is going on is that there is 181 00:11:06.132 --> 00:11:09.762 such an overload of bad news at the moment that it's actually 182 00:11:09.816 --> 00:11:13.106 very difficult for us to process. So if you want to look after your own 183 00:11:13.128 --> 00:11:16.418 mental health, then one of the first things you should be doing is listening to 184 00:11:16.424 --> 00:11:20.038 less news, because it's outside of your locus of control, 185 00:11:20.124 --> 00:11:23.954 most of this. And so you're taking negative signals 186 00:11:24.002 --> 00:11:27.334 that you can't really act on. So, of course there are things we can act 187 00:11:27.372 --> 00:11:30.986 on. And actually, I think Britain is doing an 188 00:11:31.008 --> 00:11:34.826 extraordinary is actually people are really taken on 189 00:11:34.848 --> 00:11:37.658 board the message that we need to stay at home and protect the NHS and 190 00:11:37.664 --> 00:11:41.466 save lives. It's like duck and cover of the old, isn't it? We all 191 00:11:41.488 --> 00:11:44.046 know we've got to climb under the dining room table to save ourselves from the 192 00:11:44.068 --> 00:11:47.646 nuclear bomb. We're now, as you say, stay at home, protect the 193 00:11:47.668 --> 00:11:50.400 engine. No one's ever going to forget that. It's kind of 194 00:11:51.170 --> 00:11:54.978 but it's like also what's really happening 195 00:11:55.064 --> 00:11:58.866 is that death rates have doubled, and 196 00:11:58.888 --> 00:12:02.514 that's really bad for those people that have died and 197 00:12:02.552 --> 00:12:06.130 for their families. Some of those people, maybe two thirds, were probably 198 00:12:06.200 --> 00:12:09.906 likely to die in the next six months. Twelve months, anyway. They had multiple 199 00:12:09.938 --> 00:12:13.238 conditions. Some are absolutely new deaths and that's absolutely 200 00:12:13.324 --> 00:12:16.774 tragic. But what that means is that 201 00:12:16.892 --> 00:12:20.374 pretty much the shape of the curve of people's deaths is roughly the 202 00:12:20.412 --> 00:12:24.186 same as our normal risk of dying. It means that basically most of us have 203 00:12:24.208 --> 00:12:27.254 got twice the chance of dying this year than we did. If we get COVID 204 00:12:27.302 --> 00:12:30.378 if we don't get COVID, I'm not quite sure if it's coronavirus, we get or 205 00:12:30.384 --> 00:12:34.166 COVID, but if we don't get the virus, then we're our normal 206 00:12:34.198 --> 00:12:37.438 probability. But if we get it, we've got twice the chance of dying than we 207 00:12:37.444 --> 00:12:41.054 would have done. Well, I'm 55 year old male and my 208 00:12:41.092 --> 00:12:44.874 chances of death this year about 0.8%, so they probably increased 209 00:12:44.922 --> 00:12:48.500 about 1.6% this year. That still means 210 00:12:48.870 --> 00:12:52.594 98.4% chance of survival this year, so I don't feel 211 00:12:52.632 --> 00:12:55.874 too bad about it. But it's putting it in perspective, I think, is quite hard 212 00:12:55.912 --> 00:12:59.400 for a lot of people. And of course, the government wants to 213 00:13:00.570 --> 00:13:04.166 get us to comply, quite rightly. And so there's a lot of 214 00:13:04.188 --> 00:13:07.462 emphasis on the deaths to help us sort of do it. So it's an interesting 215 00:13:07.596 --> 00:13:10.666 trade. There's a statistician looking at it, I understand the 216 00:13:10.688 --> 00:13:14.474 statistics. I said it very early on to 217 00:13:14.512 --> 00:13:18.234 people in my team that actually this looks like a pandemic. I said that right 218 00:13:18.272 --> 00:13:22.010 back in February, and it could spread very 219 00:13:22.080 --> 00:13:25.866 wide, but that's actually always been humanity's 220 00:13:25.898 --> 00:13:29.294 lots. I think we've got a little bit complacent that, you know, we're sort of 221 00:13:29.412 --> 00:13:31.710 superheroes and we're never going to get it. To quote 222 00:13:33.010 --> 00:13:36.546 in the early stages, I was expecting this kind 223 00:13:36.568 --> 00:13:40.386 of new world to be more visible and obvious. You look out the 224 00:13:40.408 --> 00:13:44.142 window and we haven't got alien creatures 225 00:13:44.206 --> 00:13:47.878 running down the street, fighting and attacking people, demolishing stuff like you see in the 226 00:13:47.884 --> 00:13:51.286 movies. We haven't got this dark sun appears or this big 227 00:13:51.308 --> 00:13:55.046 hovering spacecraft, so people are looking around going, the 228 00:13:55.068 --> 00:13:58.866 world looks the same to me. Nothing's really changed, so it's really confusing. 229 00:13:59.058 --> 00:14:02.486 In the apocalypse, we're supposed to see all this stuff. We've got this Hollywood 230 00:14:02.518 --> 00:14:05.722 bias going on, haven't we? We know what a pandemic is supposed to feel 231 00:14:05.776 --> 00:14:09.350 like, riots and burning and looting 232 00:14:09.510 --> 00:14:13.180 and Will Smith running around shooting zombies or 233 00:14:13.730 --> 00:14:17.518 kind of we haven't got any of that thing to be 234 00:14:17.524 --> 00:14:21.278 scared of. We've almost got an unknown enemy, haven't we? Is that 235 00:14:21.364 --> 00:14:24.814 part of the problem people are feeling? It is. I think, actually, in some ways, 236 00:14:24.852 --> 00:14:28.514 we've been primed for the apocalypse, haven't actually. This is something that goes 237 00:14:28.552 --> 00:14:32.306 way back, earlier than recent movies. It goes right back to 238 00:14:32.328 --> 00:14:36.146 the New Testament and Revelations. Four 239 00:14:36.168 --> 00:14:39.618 horses of the apocalypse. And the idea that the world will come to the end 240 00:14:39.624 --> 00:14:43.366 of the world is not coming to an end. We've got a nasty disease and 241 00:14:43.388 --> 00:14:47.094 it's killing people that shouldn't be dying, but 242 00:14:47.132 --> 00:14:50.966 it's not going to wipe out humanity. The plague took out a 243 00:14:50.988 --> 00:14:54.826 third of the UK population. At the worst, this is going to take 244 00:14:54.848 --> 00:14:58.554 out 1% of the population. But of course, that's still tragic and I'm not against 245 00:14:58.592 --> 00:15:01.914 the lockdown or anything like that, but it is 246 00:15:01.952 --> 00:15:05.774 unlikely to affect me personally and so therefore I shouldn't get 247 00:15:05.812 --> 00:15:09.226 too anxious in the senses. I'm trying to say something which is about our mental 248 00:15:09.258 --> 00:15:12.878 health and about our attitude towards this, and I 249 00:15:12.964 --> 00:15:16.706 think for most of us, the likely thing is that we get away with 250 00:15:16.728 --> 00:15:20.126 it and there'd be a vaccine, but of course, for some it isn't. 251 00:15:20.318 --> 00:15:23.940 And my mum's 85 and of course I worry about her, 252 00:15:25.590 --> 00:15:29.222 but she is safely locked down with my sister, so she's probably 253 00:15:29.276 --> 00:15:31.880 fine. She definitely should avoid getting it because 254 00:15:33.050 --> 00:15:36.678 she's actually relatively healthy. 85 year old. I was trying to work out the 255 00:15:36.684 --> 00:15:40.522 stats on it because that's what I do and she has a 15% 256 00:15:40.576 --> 00:15:43.660 chance of dying anyway this year. That's up to 30, 257 00:15:44.830 --> 00:15:48.106 but that's age appropriate and that's what it 258 00:15:48.128 --> 00:15:51.774 is. As you're talking about this double the 259 00:15:51.812 --> 00:15:55.182 chance of dying this year, statistically, through this, 260 00:15:55.236 --> 00:15:58.990 COVID my brain is now going off on a tangent, thinking, 261 00:15:59.140 --> 00:16:02.814 well, my risk factors from other things have gone 262 00:16:02.852 --> 00:16:06.562 down. So I'm not travelling, I'm not crossing the road, 263 00:16:06.696 --> 00:16:10.386 I'm not doing other dangerous things that humans do where I could 264 00:16:10.408 --> 00:16:14.194 get randomly killed by another event. So I'm doing less of those dangerous things 265 00:16:14.312 --> 00:16:18.098 or risky things and more at risk from COVID So there's got to 266 00:16:18.104 --> 00:16:21.526 be an amalgamation of those figures to say, well, actually, my risk profile will go 267 00:16:21.548 --> 00:16:24.546 down because of this, but go up because of this. Or are you saying it's 268 00:16:24.578 --> 00:16:28.038 double overall? I mean, there must be a 269 00:16:28.044 --> 00:16:31.402 sophisticated calculus you could do. So, yes, 270 00:16:31.456 --> 00:16:34.714 accidents on the road have gone down, but possibly accidents at home have gone 271 00:16:34.752 --> 00:16:38.186 up, possibly domestic violence has gone 272 00:16:38.208 --> 00:16:41.630 up. We don't know about suicide rates. 273 00:16:44.050 --> 00:16:47.694 We. Do know about suicide, that a lack of hope is 274 00:16:47.732 --> 00:16:51.566 very difficult in suicide, and I think there must be 275 00:16:51.588 --> 00:16:55.138 some people that feel very hemmed in and helpless at the moment, stuck in a 276 00:16:55.144 --> 00:16:58.402 difficult relationship, stuck alone, stuck at home, made 277 00:16:58.456 --> 00:17:02.258 unemployed or feeling like there's nothing to work. And if 278 00:17:02.264 --> 00:17:06.098 they were already on the borderline, suicide. I don't know what the 279 00:17:06.104 --> 00:17:09.670 stats are there, but I would imagine that we'll have a spike in 280 00:17:09.740 --> 00:17:13.446 severe mental health problems and suicide. I imagine we'll have 281 00:17:13.468 --> 00:17:16.806 some post traumatic stress that comes out of this for people that have 282 00:17:16.828 --> 00:17:20.674 got difficult situations and we'll see what's called post traumatic 283 00:17:20.722 --> 00:17:24.054 growth for some people. This isn't going to be evenly 284 00:17:24.102 --> 00:17:27.802 distributed about how people respond to it, but many, many 285 00:17:27.856 --> 00:17:31.366 people, if you're sort of middle class and you've got financial security and emotional 286 00:17:31.398 --> 00:17:34.942 security, are going, wow, maybe I should travel 287 00:17:34.996 --> 00:17:38.766 less, maybe I should quieten down. They're going to get quite mindful experiences of 288 00:17:38.788 --> 00:17:42.566 that. But of course, again, that's likely to be what we call the social gradient, 289 00:17:42.618 --> 00:17:46.450 where the people that are already secure are going to 290 00:17:46.520 --> 00:17:50.190 have better experiences and the ones that are already insecure financially, 291 00:17:50.270 --> 00:17:53.870 emotionally, physically, are likely to have worse. 292 00:17:54.030 --> 00:17:57.666 So there's likely to be some increases inequalities of experience, I would 293 00:17:57.688 --> 00:18:01.366 think. Yeah, I've heard people saying, well, we're not all in the 294 00:18:01.388 --> 00:18:04.914 same boat, but we're on the same river in different boats, 295 00:18:05.042 --> 00:18:08.646 so we're on a similar journey but having different experiences. Some of us have got 296 00:18:08.668 --> 00:18:12.458 lovely boats with outboards and sun decks and some of us are 297 00:18:12.464 --> 00:18:16.138 on a raft with a paddle experience. So yeah, completely, 298 00:18:16.304 --> 00:18:20.134 it's a variability of lived experience. I also think there's a lot of people 299 00:18:20.192 --> 00:18:22.590 who have acquired 300 00:18:24.450 --> 00:18:28.254 problems through it. So I'm thinking about people who were 301 00:18:28.292 --> 00:18:31.614 previously well off, had great 302 00:18:31.652 --> 00:18:35.426 jobs, or owned their own business, or had a security of 303 00:18:35.448 --> 00:18:39.198 income commission. Now they're finding that they're 304 00:18:39.214 --> 00:18:42.786 now in a position where they're financially struggling that they've never been in before. So 305 00:18:42.888 --> 00:18:46.658 there's a great levelling for some people. As you said, there's a whole group of 306 00:18:46.664 --> 00:18:50.454 people who are secure, happy, they're just getting bored at home. 307 00:18:50.492 --> 00:18:53.782 There's a whole load of people that have lost significant part 308 00:18:53.836 --> 00:18:57.494 of what they believed was their life and they must be really 309 00:18:57.532 --> 00:19:01.240 struggling right now, I guess. Yeah, I think there are 310 00:19:02.090 --> 00:19:05.802 whole sectors that have shut down. And there'd been people 311 00:19:05.856 --> 00:19:09.638 that I read something on some news website of the guy said, I haven't 312 00:19:09.654 --> 00:19:13.370 even opened my coffee shop and I've gone bust. And he must have worked towards 313 00:19:13.440 --> 00:19:17.246 that passion to do something in his own control and worked out 314 00:19:17.268 --> 00:19:20.778 where he was renting and then he's gone bust before he's even opened his doors. 315 00:19:20.954 --> 00:19:24.000 And so I think there's going to be all sorts of personal, 316 00:19:24.610 --> 00:19:28.066 real challenges. And I've got a lot of friends that have 317 00:19:28.248 --> 00:19:31.746 been furloughed. I've got one of my kids has been furloughed, actually, to be honest, 318 00:19:31.768 --> 00:19:35.618 he's dead happy with being furloughed because he's trying 319 00:19:35.624 --> 00:19:38.918 to pick up a new skill and do web design or whatever like that. And 320 00:19:39.004 --> 00:19:42.262 he's getting paid. I've got 80% of my pay 321 00:19:42.316 --> 00:19:45.974 and he's quite happy. But other people, 322 00:19:46.012 --> 00:19:49.320 that's not a happy experience at all and it's a very insecure experience. 323 00:19:51.150 --> 00:19:53.498 I think this is great and I see it in my team. I have a 324 00:19:53.504 --> 00:19:56.540 team of twelve and the ones with young children 325 00:19:57.070 --> 00:20:00.714 are preschool are starting to struggle after 326 00:20:00.912 --> 00:20:04.526 six, seven weeks into lockdown when we're recording this, and it's a 327 00:20:04.548 --> 00:20:08.366 cumulative effect going on for them. The first three, four weeks we 328 00:20:08.388 --> 00:20:10.880 all had a shock, but we sort of bounced back and then 329 00:20:12.790 --> 00:20:15.746 I think that that's where quite a lot of people 330 00:20:15.928 --> 00:20:18.500 are at this very moment. 331 00:20:21.830 --> 00:20:25.342 There's this initial kind of panic, worry, anxiety, 332 00:20:25.486 --> 00:20:29.174 and then there's something to focus on. Now we're into this tailing off 333 00:20:29.212 --> 00:20:32.680 into sort of this set in reality. Is that what you're saying? 334 00:20:33.050 --> 00:20:36.758 There's no end date. There's nothing to look forward to. There's no light at the 335 00:20:36.764 --> 00:20:39.800 tunnel. Whatever analogy we want to use. 336 00:20:41.290 --> 00:20:44.460 Someone said the light of the tunnel is a train coming towards you. 337 00:20:44.910 --> 00:20:48.666 I think that's some expression from the Vietnam War or something. But I'm a 338 00:20:48.688 --> 00:20:52.362 statistician, so I do look at data. And actually, Friday pulse my business. 339 00:20:52.416 --> 00:20:56.250 What we do is we ask employees 340 00:20:56.330 --> 00:20:59.886 how their week has been. How have you felt at work this week? Are you 341 00:20:59.988 --> 00:21:03.246 very unhappy? Through to very happy and the idea is to pick up that good 342 00:21:03.268 --> 00:21:06.946 bad signal a bit like the friendFO signal it's like is it going 343 00:21:06.968 --> 00:21:10.578 well? My work is it not? So we've got clients across the world, but the 344 00:21:10.584 --> 00:21:14.242 US, the UK mainly, some other places. I've never 345 00:21:14.296 --> 00:21:17.874 ever had a pattern in my data across all of our 346 00:21:17.912 --> 00:21:21.522 clients before, because clients do different things, they've got different challenges 347 00:21:21.586 --> 00:21:25.302 setbacks going on at different times. We get a very small seasonal effect 348 00:21:25.356 --> 00:21:28.898 where the summer is slightly happier than the other times because we're 349 00:21:28.914 --> 00:21:32.346 mainly northern hemisphere. We have got some hemisphere clients, but 350 00:21:32.368 --> 00:21:36.182 mainly but you've got a massive drop middle of March 351 00:21:36.246 --> 00:21:39.914 across every one of our clients. So we have an index from zero 352 00:21:39.952 --> 00:21:43.610 to 100. Most of our clients run along on average about 70. 353 00:21:43.680 --> 00:21:46.798 We obviously have some clients of 50, some 80, but that's where they're going along. 354 00:21:46.884 --> 00:21:50.718 And the whole average just dropped down to 45 in the 355 00:21:50.724 --> 00:21:54.174 middle of the week. And now we're back to 60, 65, but we're not back 356 00:21:54.212 --> 00:21:57.886 to 70, 72 where they were. There's 357 00:21:57.918 --> 00:22:01.426 been some bounce back, but there's absolutely a gap from where they were. And our 358 00:22:01.448 --> 00:22:05.154 clients are clients that are very already very interested in their employee well being, 359 00:22:05.192 --> 00:22:07.640 otherwise they wouldn't be using us. So 360 00:22:08.810 --> 00:22:12.614 they've no doubt got better experiences going on than many out 361 00:22:12.652 --> 00:22:16.246 there, and they've got this huge gap. And that, as a 362 00:22:16.268 --> 00:22:19.874 statistical story is very interesting because basically that's 363 00:22:19.922 --> 00:22:23.366 resilience in action, which is that you're seeing people's weekly 364 00:22:23.398 --> 00:22:26.838 experience. They have a setback, how do they come back? And what we're seeing, we're 365 00:22:26.854 --> 00:22:30.394 seeing a partial comeback but not a full comeback at the moment. 366 00:22:30.592 --> 00:22:34.346 This is kind of that buzzword of probably 510, 15 years ago, that bounce 367 00:22:34.378 --> 00:22:37.790 back ability, or what we called it, isn't it? This resilience, tenacity 368 00:22:39.970 --> 00:22:43.566 stiff up, a little British sort of stoicism, whatever you want to call it, 369 00:22:43.668 --> 00:22:47.362 this ability to take challenges and bounce back 370 00:22:47.416 --> 00:22:51.186 through them, if you like, isn't it? Well, when a psychologist, my 371 00:22:51.208 --> 00:22:54.514 understanding resilience. I'm not an expert in resilience, but well, I think of it that 372 00:22:54.552 --> 00:22:58.246 statistically, but there's different ways you can think about so you can think about being 373 00:22:58.348 --> 00:23:01.846 a bouncy ball and a hard wall, and the ball comes and hits the 374 00:23:01.868 --> 00:23:05.606 wall, the wall stays absolutely solid, so it 375 00:23:05.628 --> 00:23:08.858 is resilience and the ball comes back. The way the ball deals with it is 376 00:23:08.864 --> 00:23:12.666 it absorbs the shock and then moves away. So 377 00:23:12.688 --> 00:23:16.534 there's two types of resilience. There's the firm sort of resistant resilience, 378 00:23:16.582 --> 00:23:20.266 and then there's the absorption one. And I think 379 00:23:20.288 --> 00:23:23.766 that what we're seeing is the absorption one working with people, they've 380 00:23:23.798 --> 00:23:27.166 absorbed the shock, they're coming back, they're putting a brave face on it and then 381 00:23:27.188 --> 00:23:30.814 they're finding, well, remote working isn't as easy as being with other 382 00:23:30.852 --> 00:23:34.394 people. There's some loss with that, there's some gains, there's some losses. 383 00:23:34.522 --> 00:23:38.306 It depends on how they can set up their home office. Mine is 384 00:23:38.328 --> 00:23:42.034 in the corner of my bedroom because we've got two teens in the house. 385 00:23:42.072 --> 00:23:44.946 And when I used to work at home, I did often work at home on 386 00:23:44.968 --> 00:23:48.066 a Friday, they were a university or school, and I'd sit on the kitchen table 387 00:23:48.098 --> 00:23:51.846 and be quite happy now. Well, I'm quite happy, actually, but I'm in my 388 00:23:51.868 --> 00:23:54.920 corner of my bedroom. I've got pushed to the corner, but 389 00:23:56.570 --> 00:24:00.326 there's different experiences. One of my team, she 390 00:24:00.348 --> 00:24:03.178 works from downstairs, but when she wants to take a call, she has to go 391 00:24:03.184 --> 00:24:06.554 up to her bedroom. She hasn't got a proper desk, her back's aching after five 392 00:24:06.592 --> 00:24:10.326 weeks, and her young child doesn't understand she's got a three year old, doesn't 393 00:24:10.358 --> 00:24:14.126 understand what's going on. So there's so many different strains, and some 394 00:24:14.148 --> 00:24:17.694 of them are cumulative, some of them are starting to build up now and to 395 00:24:17.732 --> 00:24:21.310 really get under people's skin. So it's hard. It's hard for some people, 396 00:24:21.380 --> 00:24:24.942 yeah. I try and talk about this. Almost. 397 00:24:24.996 --> 00:24:28.674 Imagine when you first left home all those many years ago. And 398 00:24:28.712 --> 00:24:31.794 you move into your first home. Or you live on your own. You move into 399 00:24:31.992 --> 00:24:35.426 your bed sit wherever you did. And the first couple of weeks you live on 400 00:24:35.448 --> 00:24:39.218 baked beans, on toast or the odd jacket potato. You think. And then one 401 00:24:39.224 --> 00:24:42.198