1 00:00:05,230 --> 00:00:06,500 Very much, everybody. 2 00:00:06,520 --> 00:00:16,450 I'm delighted to welcome Trish Greenhouse, professor of Primary Care, Health Sciences and the Department of Primary Care Health Sciences at Oxford. 3 00:00:16,750 --> 00:00:21,850 We, Trish, joined our team sort of this year and we're absolutely delighted to have her expertise. 4 00:00:22,360 --> 00:00:31,689 Trish studied medicine, medical, social and political sciences at Cambridge and Clinical Medicine at Oxford before training as an academic GP. 5 00:00:31,690 --> 00:00:38,919 And so she's one of those people who can marry the social sciences as a trained social scientist with the medical studies. 6 00:00:38,920 --> 00:00:44,590 And she's going to be talking tonight about theorising with narrative about storytelling, 7 00:00:44,590 --> 00:00:52,210 how careful analysis of stories can help us rise above the ontological disorder behaviour change research possibility. 8 00:00:52,750 --> 00:00:56,530 Right. Thank you very much. So my name's Trish Greenhouse. 9 00:00:56,570 --> 00:00:58,540 Going to talk about theorising with narrative. 10 00:00:58,540 --> 00:01:07,600 And when I was waiting to give this lecture, three of you came up to me and said, It's a bit of a scary title, isn't it? 11 00:01:08,800 --> 00:01:14,740 And one person said this word ontological added to words like epistemological and triangulation. 12 00:01:14,740 --> 00:01:20,890 It's things I've got to put into Google and learn about. So I wouldn't worry too much about the word ontological. 13 00:01:20,960 --> 00:01:26,770 What it means is what's going on. You know what's going on here, what is the nature of reality? 14 00:01:27,430 --> 00:01:30,950 And add that to epistemology, which is how do we know what's going on? 15 00:01:32,110 --> 00:01:38,050 So what I mean by the Ontological Desert is a lot of behaviour change research doesn't really go very deep, 16 00:01:38,470 --> 00:01:41,290 it doesn't isn't very rich about what's going on. 17 00:01:41,290 --> 00:01:45,760 You know, the very nature of behaviourism is all about stimulus and response and all that kind of thing. 18 00:01:45,910 --> 00:01:51,670 And the trouble is in certain areas when you've got very complex social determinants of health, 19 00:01:51,670 --> 00:01:57,460 socio cultural influences, behaviour, change, your research just doesn't get you very far. 20 00:01:57,670 --> 00:02:04,510 That's, that's my personal view. Before I say anything more, I want to acknowledge funding from, 21 00:02:04,510 --> 00:02:11,739 particularly from the European Framework seven program actually, and also from the National Institute for Health Research. 22 00:02:11,740 --> 00:02:14,890 You very kindly give me some money for being a senior investigator, 23 00:02:15,100 --> 00:02:21,790 but also the many members of the team that I've been working with on something called the gift study, and I've got a list of them later. 24 00:02:23,290 --> 00:02:25,960 Okay then. So this is about storytelling. 25 00:02:26,090 --> 00:02:32,080 Four days into a five day qualitative research course, we all know that a narrative is a story, but what's the story? 26 00:02:32,890 --> 00:02:36,430 Oh, a collection of reflections on something someone's been through. 27 00:02:36,580 --> 00:02:45,100 So the idea that a story is told retrospectively and it's about events that unfolded, great start. 28 00:02:45,490 --> 00:02:49,750 What else in stories usually has a beginning and sometimes often end. 29 00:02:50,530 --> 00:02:54,400 Brian Jones is fond of saying that story is something with a beginning, a middle and an end. 30 00:02:55,570 --> 00:02:59,860 And actually the muddle is quite important, isn't it? I mean, you know, it doesn't have to be Harry Potter. 31 00:02:59,860 --> 00:03:03,010 It could be anything. But this is what Aristotle called trouble. 32 00:03:03,280 --> 00:03:10,780 Something happens to make it a story, because if you just kind of dum, da dum, da dum, everything just carries on. 33 00:03:11,170 --> 00:03:15,370 It's not a story, really, that has become some some trouble in the middle of it. 34 00:03:15,550 --> 00:03:18,910 And then it's how you got out of the trouble. What else about stories? 35 00:03:20,050 --> 00:03:23,340 Yeah. Journey. Journey. Go on. 36 00:03:23,370 --> 00:03:28,740 Tell us more. So. So it's events unfolding in an order? 37 00:03:29,280 --> 00:03:34,330 Yes. Yes, it's sequential. It's events unfolding in an order quite like that. 38 00:03:34,350 --> 00:03:38,430 Yeah. Okay. Well, I got down then. 39 00:03:38,910 --> 00:03:42,330 Too much audience participation. I'll go off my script. Okay. 40 00:03:42,480 --> 00:03:47,430 So Aristotle said there's five defining features of narrative. 41 00:03:47,700 --> 00:03:50,640 The first is chronology, the unfolding over time. 42 00:03:51,420 --> 00:03:56,360 The second is some kind of setting, you know, once upon a time, in the middle of a big world, whatever. 43 00:03:57,960 --> 00:04:04,020 The stage on which the drama unfolds. Thirdly, characters. 44 00:04:04,200 --> 00:04:07,229 People. Animals. Robots. 45 00:04:07,230 --> 00:04:11,970 These days, androids who get in and out of trouble and then trouble. 46 00:04:12,750 --> 00:04:16,990 A breach from the expected. And finally, plots. 47 00:04:17,250 --> 00:04:24,690 You sort of got this when you were talking about, you know, the suggestions you made, the use of various literary devices, 48 00:04:24,690 --> 00:04:33,390 the narrative scholars among you will be better than me at naming those to depict what I've called narrative causality. 49 00:04:34,080 --> 00:04:41,250 Some such and such happened because of such and such, and it's a narrative causality, not a statistical causality. 50 00:04:41,250 --> 00:04:49,290 And actually, those of you who come from quantitative backgrounds might have this found this aspect of qualitative research a bit. 51 00:04:49,620 --> 00:04:53,400 Can you hang on a minute? What's correlating with what? Well, it's not about correlation, is it? 52 00:04:53,640 --> 00:04:57,450 It's about a literary causality. 53 00:04:57,950 --> 00:05:03,390 The example I sometimes use is, is the dursleys kept Harry Potter in a cupboard. 54 00:05:03,660 --> 00:05:09,090 Why did they keep Harry in the cupboard? Because he was a wizard. And it's that word because I didn't like wizards, you know? 55 00:05:09,300 --> 00:05:14,610 And you put these things together using these literary devices, 56 00:05:14,730 --> 00:05:19,920 not just to depict what happened, but also to depict your characters as good or bad people. 57 00:05:20,940 --> 00:05:25,019 So that was what Aristotle called plot. And he was really keen on plot. 58 00:05:25,020 --> 00:05:35,580 You know, unless you've got a plot, you haven't got a story. Jerome Bruner, amazing guy, still alive, I understand, at the age of about 99. 59 00:05:35,820 --> 00:05:39,660 Last time I was in touch them, he was still teaching at the age of about 96. 60 00:05:39,900 --> 00:05:45,440 And Bruno worked right back with people like Jean Piaget. 61 00:05:45,450 --> 00:05:53,480 You know, he worked in the early days of psychology and he wrote a number of books about narrative. 62 00:05:53,490 --> 00:05:55,290 But you have to learn to take him from where he was. 63 00:05:55,520 --> 00:06:04,620 He came you know, he did his Ph.D. in his post-doc work at the heyday of behaviourism, where everything was stimulus response. 64 00:06:04,620 --> 00:06:08,520 That was what psychology was. And he said, no, no, no, no, psychology. 65 00:06:08,670 --> 00:06:16,920 It's about meaning. And he wrote brilliant work on the narrative structure of experience. 66 00:06:17,730 --> 00:06:25,770 Narrative is evidence, but it's not the same kind of evidence a statistical evidence narrative seeks to persuade. 67 00:06:26,850 --> 00:06:30,660 However, not all evidence is narrative. 68 00:06:31,030 --> 00:06:36,359 So if I give you an example of a narrative, you would say, well, that's that's just anecdote. 69 00:06:36,360 --> 00:06:40,709 That's very atypical. On the other hand, some narratives, you you look at it and you say, well, 70 00:06:40,710 --> 00:06:46,560 not only do I find that plausible, but it also resonates with my own experience of similar situations. 71 00:06:47,220 --> 00:06:53,790 And what Bruno said was, there's two types of evidence is logical deductive evidence, logical deductive causality. 72 00:06:54,030 --> 00:06:59,640 And this narrative of causality, this book Acts of meaning, is really very short. 73 00:06:59,790 --> 00:07:05,670 You can buy it from Amazon for about £6, you know, in a Second-hand bookshop, and it'll take, you know, more than a day to read. 74 00:07:05,880 --> 00:07:15,210 And it's really very, very well explained. Okay, let's go off and collect some stories. 75 00:07:15,780 --> 00:07:22,769 Now I've got a biased sample, actually, all the people who feel strongly enough about qualitative research to pay a large amount of money to come on. 76 00:07:22,770 --> 00:07:27,099 This course is collecting stories, research. 77 00:07:27,100 --> 00:07:31,020 Who says yes? Okay, about a third of you. 78 00:07:31,020 --> 00:07:34,349 And who says no one possesses? No. 79 00:07:34,350 --> 00:07:38,430 And who says that's a stupid question? I don't know. Or I'm on the fence. 80 00:07:39,960 --> 00:07:43,500 Yeah, a couple. Yeah, it depends. It depends. And that you're coercing. 81 00:07:43,500 --> 00:07:44,520 It depends. Sure. 82 00:07:46,710 --> 00:07:56,910 Few years ago, I got interested in this question, and I put together something called a Delphi panel, along with Thomson graph to ask this question. 83 00:07:56,910 --> 00:07:58,530 Is it research? Is it good research? 84 00:07:58,530 --> 00:08:08,760 And this piece of work began when we had each had applications to do research turned down by ethical committees, ethics committees. 85 00:08:09,270 --> 00:08:15,750 And I got one study turned down by the Ethics Committee to say, what you're asking is not research. 86 00:08:16,500 --> 00:08:20,430 You're not doing anything invasive, meaning you're not taking a blood sample or something like that. 87 00:08:20,430 --> 00:08:25,450 And it's nothing. Not a lot that's more invasive than asking someone to tell their entire life story and a tape recorder. 88 00:08:25,630 --> 00:08:33,010 But at the time, the ethics committees or some of the Ethics Committee was simply just turning this down, saying, this ain't science. 89 00:08:33,910 --> 00:08:38,830 So that's what led us to this story. Do you know what Delphi panel is? I mean, look it up. 90 00:08:38,980 --> 00:08:40,500 I spent a long time explaining. 91 00:08:40,500 --> 00:08:46,870 I mean, basically get a panel of experts of different kinds, people who are scholars in the field, people who are actually doing the work. 92 00:08:47,110 --> 00:08:51,160 And then you give them a number of statements or you ask them to help you generate statements, 93 00:08:51,370 --> 00:08:57,240 and then they vote as to whether they agree with those statements. And then you revise the statements and send them around again. 94 00:08:57,250 --> 00:09:04,330 You can do it by email and it's quite a good way of sort of reaching an expert consensus. 95 00:09:05,830 --> 00:09:12,670 And this is what we came up with after about, you know, nine months of going back and forth around this this panel of experts. 96 00:09:14,110 --> 00:09:19,390 What do you think of that? Happy with the definition of research. 97 00:09:21,730 --> 00:09:26,230 You can see it's a bit bland because we're trying to sort of keep people happy. 98 00:09:26,230 --> 00:09:31,240 We don't know. You know, all the extreme views were sort of filtered out by this Delphi process. 99 00:09:32,920 --> 00:09:39,610 So so in order to decide whether storytelling and story gathering is research, you've got to define what research is. 100 00:09:39,610 --> 00:09:43,060 So it's about contributing to new knowledge. Story. Yeah. 101 00:09:43,240 --> 00:09:46,000 Okay. That was pretty much what you defined the story as. 102 00:09:47,500 --> 00:09:53,620 Those of you who thought narrative collecting narratives was not research, was that because you thought the stories might not be true? 103 00:09:56,240 --> 00:10:01,320 I think I was the only one. And I think it's because the story is just the start. 104 00:10:01,930 --> 00:10:05,390 The story is just the story. So it's good. 105 00:10:06,240 --> 00:10:13,549 The research depends on the researcher, not the story. The research depends on the researcher, not the story. 106 00:10:13,550 --> 00:10:17,420 This is good. Come on. Okay. 107 00:10:19,100 --> 00:10:22,540 But what do you mean when you say the research depends on the researcher? 108 00:10:22,890 --> 00:10:26,650 Yeah, because the story is there. You. 109 00:10:26,690 --> 00:10:30,490 The story is the. There's an object here. 110 00:10:31,180 --> 00:10:37,030 Everyone has stories you can question about people, about started interviewing people. 111 00:10:37,390 --> 00:10:40,860 But then if that's not analysed, that's not true. 112 00:10:41,330 --> 00:10:44,560 Yeah, it's not a research. It's only the narrative. 113 00:10:44,620 --> 00:10:49,660 So it's a story in and of itself is just a story. 114 00:10:49,840 --> 00:10:58,060 Yeah, I agree with you. In order for that story to become research it, something else has to happen, is what you're saying. 115 00:10:58,210 --> 00:11:05,500 Yeah, interesting. That's absolutely right. So I'm not going to go through this in enormous detail. 116 00:11:05,530 --> 00:11:10,450 If you're interested, you can you can look up this paper is in medical education or I'll send it to you if you want. 117 00:11:12,610 --> 00:11:18,849 What does narrative research consist of then? Just collecting any old story for any purpose is not research. 118 00:11:18,850 --> 00:11:22,810 But let's just tighten it down. Story gathering. 119 00:11:23,110 --> 00:11:25,870 Collecting stories that are already been told or written. 120 00:11:25,870 --> 00:11:30,759 You know, getting onto the Internet and finding people's blogs and then saying, That's my dataset. 121 00:11:30,760 --> 00:11:34,030 That could be research story eliciting. 122 00:11:34,030 --> 00:11:37,899 That's the most common going along in asking a participant to tell a story. 123 00:11:37,900 --> 00:11:40,030 And that's what they do, of course, with Health Talk Online. 124 00:11:40,780 --> 00:11:47,560 Then this story interpreting, actually drawing meaning from the stories and story collecting, 125 00:11:47,710 --> 00:11:51,460 collecting several stories and bringing them together and synthesising them. 126 00:11:51,910 --> 00:12:00,880 Okay. If that is done with the explicit intention of furthering a body of knowledge, okay, that would count as research. 127 00:12:02,530 --> 00:12:05,970 One of the people I've worked with once was the OC. 128 00:12:05,980 --> 00:12:12,010 One of my courses was the ombudsman whose job it was to collect complaints and respond to complaints. 129 00:12:12,130 --> 00:12:17,700 And yes, what he wanted to do was analyse the complaints letters and write research papers on it. 130 00:12:17,720 --> 00:12:18,670 So you can't do that. 131 00:12:18,670 --> 00:12:25,270 You know, it's not like they wrote it, they wrote the complaints, but they were they were narratives that were very powerful narratives. 132 00:12:25,540 --> 00:12:30,400 But of course, to convert those into research, you'd have to write back to people saying, would you mind, etc., etc. 133 00:12:31,600 --> 00:12:37,650 So firstly, any research has to be, you know, systematic. 134 00:12:37,660 --> 00:12:44,140 You have to have a question, you have to think about your study design, your sample size, all that kind of thing. 135 00:12:46,000 --> 00:12:51,340 And particularly this last year for this works good two days. 136 00:12:52,030 --> 00:12:59,710 G The research is awareness of the possibility of error and the steps taken to minimise or take account of this. 137 00:12:59,950 --> 00:13:07,480 So that applies for quantitative research, qualitative research, whatever, and it's really, really important. 138 00:13:07,900 --> 00:13:17,000 Are you being reflexive about the possibility of error or distortion or perspective or bias or whatever, and what are you doing to minimise that? 139 00:13:18,160 --> 00:13:22,899 There is also an issue in research and I think the example I'm going to give you will highlight this, 140 00:13:22,900 --> 00:13:30,880 that either when you go out and collect a story or when you take an existing story and turn it into research material or seek to do that, 141 00:13:31,300 --> 00:13:35,530 you take on ethical duties towards the storyteller. 142 00:13:35,920 --> 00:13:40,050 And if have you have you had to look at the health talk videos yet? 143 00:13:40,600 --> 00:13:48,100 Yes. So if you have if you haven't just put health talk into Google, you'll find lots and lots of videos of people talking about their illnesses. 144 00:13:48,220 --> 00:13:53,410 I was at a conference in London yesterday and someone showed a very powerful video of a guy who was dying of cancer and all the rest of it. 145 00:13:53,770 --> 00:13:58,870 Now, once you've heard that story, once you are collecting it, 146 00:13:58,870 --> 00:14:05,680 and once you've got it in your dataset, you have duties towards the person who told it on a stage. 147 00:14:05,740 --> 00:14:10,510 You're not going to just cherry pick quotes like the press do sometimes with the well, 148 00:14:10,510 --> 00:14:16,629 then all of us ready to do no harm to make sure that really this is a person who's told you a story. 149 00:14:16,630 --> 00:14:22,860 You know, if you're going to stick it on the Internet or published in the Journal, have you thought about the effect that will have on the person? 150 00:14:23,350 --> 00:14:27,760 All sorts of issues around consent and confidentiality. 151 00:14:27,940 --> 00:14:32,709 Of course, if the person is agreeing to have the video onto the Internet, 152 00:14:32,710 --> 00:14:38,650 that's a different kind of confidentiality from, you know, if they would like to remain anonymous. 153 00:14:38,650 --> 00:14:43,900 And so that's an ongoing negotiation. I'm sure you have you have talks on research ethics. 154 00:14:43,900 --> 00:14:49,299 Yes. Yeah. Okay. Let me tell you about this gifts program, then. 155 00:14:49,300 --> 00:14:57,880 So the principal investigator is not me. It's a diabetic allergist and geneticist called Graham Hittman, who's based at Ball's Health Trust in London. 156 00:14:58,300 --> 00:15:02,770 And it was FP7 funded. Enormous amount of money, actually. 157 00:15:02,770 --> 00:15:08,380 But then this went across, I think, eight different countries and 18 different centres. 158 00:15:08,620 --> 00:15:18,309 And the big chunk of money went to on the sort of genetics and the and the big randomised controlled trial and I got a tiny bit of money, 159 00:15:18,310 --> 00:15:24,820 I actually got £44,000 up to the €3 million to do the little qualitative side salad. 160 00:15:25,390 --> 00:15:28,780 And some of us who in qualitative research are always rather cynical about this. 161 00:15:28,870 --> 00:15:33,310 Kind of work, you know, that people come up to you and say, Can I put you on my grant application? 162 00:15:33,320 --> 00:15:39,250 Because in amongst this enormous great genetic study, we'd like to put a little bit of qualitative tinsel. 163 00:15:39,520 --> 00:15:48,100 Please, can you collect some narratives? And that'll kind of jazz up our rather boring genetics, blah, blah, blah. 164 00:15:48,130 --> 00:15:52,120 So, in fact, I normally say no to these, but but Graeme's a good bloke. 165 00:15:52,600 --> 00:15:56,379 He really does get the, the socio cultural stuff. 166 00:15:56,380 --> 00:16:03,830 And he really did want to do this, not just as a bit of tinsel. So I was work package nine storytelling. 167 00:16:06,490 --> 00:16:11,650 This is a paper from someone else. This is just the sort of a bit of background. 168 00:16:11,920 --> 00:16:15,550 Why on earth would you need storytelling and a genetic study? 169 00:16:15,870 --> 00:16:21,550 And this is what I want to talk about today. Epigenetics. 170 00:16:21,970 --> 00:16:28,200 Do you know how much did anyone know about epigenetics? Anyone you know that we got know someone's going like that. 171 00:16:28,210 --> 00:16:37,270 So, yeah. Okay. So the study of changes in organisms caused by modification of gene expression rather than the alteration of genetic code. 172 00:16:37,540 --> 00:16:47,920 So two people have got the same gene, but somehow one of them expresses it in in a more advanced way than the other, that kind of thing. 173 00:16:50,050 --> 00:16:53,470 And of course, all sorts of things affect gene expression. 174 00:16:53,470 --> 00:16:54,760 And this is not my field, 175 00:16:54,760 --> 00:17:01,750 but I've been working with these people because actually a lot of things that happen in our lives affect the expression of our genes. 176 00:17:02,140 --> 00:17:08,590 So this paper, which was in The Lancet in 2011, type two diabetes, a big pandemic. 177 00:17:08,740 --> 00:17:22,569 Now, what they say here in amongst a lot of other things is a very sort of detailed technical paper, is that in women with gestational diabetes, 178 00:17:22,570 --> 00:17:26,950 in other words, women who weren't diabetic before they got pregnant, they're now diabetic when they are pregnant. 179 00:17:26,950 --> 00:17:31,210 And then they're going to get become non-diabetic again after pregnancy. 180 00:17:31,420 --> 00:17:39,660 So in women with gestational diabetes, two things give you problems. 181 00:17:39,670 --> 00:17:41,170 One is overnutrition. 182 00:17:41,170 --> 00:17:49,750 In other words, eating more than you need to eat, and the other is under exercising, taking less exercise than would be recommended. 183 00:17:50,200 --> 00:17:53,680 That leads to what we call metabolic programming. 184 00:17:54,040 --> 00:17:59,649 Okay. The sort of you know, there's a sort of couch potato metabolism here where there's different hormones and different 185 00:17:59,650 --> 00:18:05,860 genes come out that will increase that woman's risk of subsequently developing type two diabetes. 186 00:18:06,460 --> 00:18:16,240 But it will also lead to metabolic programming in the foetus, in the environment in which that foetus is developing and its genes becoming expressed, 187 00:18:16,630 --> 00:18:21,130 that that will increase the risk of type two diabetes in the next generation. 188 00:18:21,470 --> 00:18:31,000 Where I worked until recently in the east end of London, there are 50% of diabetes in secondary school children is now type two. 189 00:18:31,330 --> 00:18:36,220 In other words, when I was at medical school, type two diabetes was something you got when you were in your sixties. 190 00:18:36,370 --> 00:18:44,440 But if you're from an ethnic minority in the east end of London, it's something that you might well get when you're 13 or whatever. 191 00:18:44,790 --> 00:18:51,100 So this is really quite worrying in terms of sort of epidemiology and the risks and things like that. 192 00:18:51,340 --> 00:18:58,510 So it's a big problem. So of course, the geneticists say, well, we're going to have genes for diabetes, but I've got genes for diabetes. 193 00:18:58,510 --> 00:19:01,749 My father had type two diabetes, but I'm not diabetic. Why not? 194 00:19:01,750 --> 00:19:06,340 Because I try not to overeat and you know, I try not to. 195 00:19:06,340 --> 00:19:12,640 Yeah. Whatever. Do lots of exercise now. So that's the sort of epigenetics in a nutshell. 196 00:19:13,360 --> 00:19:16,299 Solutions to this problem will include, 197 00:19:16,300 --> 00:19:25,690 and this is a quote from the paper Improvements in maternal public health programs in pre transition and post transition populations. 198 00:19:25,870 --> 00:19:31,370 What do you mean by pre transition? The idea that economic transition. 199 00:19:31,420 --> 00:19:35,860 So so you know if you live in rural China that you've got a low risk of diabetes 200 00:19:35,860 --> 00:19:42,170 because everyone sort of eats quite healthily and runs around all the time. So knowing kind of what to call post transition is, you know, 201 00:19:42,190 --> 00:19:47,200 when we're all sort of driving around in our cars in cities and working in office jobs, etc. 202 00:19:48,190 --> 00:19:50,590 So that's one thing improvements in maternal public health, 203 00:19:50,710 --> 00:19:58,660 but also provision of education to relevant groups about the risks of rapidly adopting Western lifestyles could be considered. 204 00:20:00,640 --> 00:20:08,130 Are you happy with that as qualitative researchers? You know, sort of 12 pages of clever genetics and then they say, well, 205 00:20:08,140 --> 00:20:12,370 this is going to be expressed differently when women eat too much, exercise too little when they're pregnant. 206 00:20:12,670 --> 00:20:19,620 So there we go. We're going to we're going to provide them with education, you know, happy? 207 00:20:19,630 --> 00:20:28,690 Well, no, it's a first of all, the whole obesity and diabetes is a hugely complex issue. 208 00:20:28,690 --> 00:20:39,730 Yeah. And the whole subject has been hijacked with people with single issues and saying, oh, it's, it's fizzy drinks or oh yeah. 209 00:20:40,030 --> 00:20:45,070 Or we've failed to address the problem because of the lack of a holistic approach. 210 00:20:45,940 --> 00:20:51,429 And also the like, you know, and you've, you've expressed, you know, it's around walking, 211 00:20:51,430 --> 00:20:56,799 cycling, just being active and not being overweight for which there are lots of conditions. 212 00:20:56,800 --> 00:20:59,420 But the environment that we live in, you know, 213 00:20:59,440 --> 00:21:07,360 built around cars so that the element which addresses the post-transition populations is we have to be really clear, 214 00:21:07,360 --> 00:21:09,849 what is it about that first transition population? 215 00:21:09,850 --> 00:21:20,860 And so if people aspire to, you know, in the dishwasher, you know, that's in some respects we are taking away from the individual, 216 00:21:21,640 --> 00:21:27,520 you know, through normalisation of behaviours, the chance to radically change that. 217 00:21:27,520 --> 00:21:35,950 So you can tell them you should walk more. But if it's just the environment that's in the United States where everyone drives, yeah, yeah, yeah. 218 00:21:36,310 --> 00:21:44,900 That's brilliantly put. I couldn't have put it better myself. I think I would add to that the very, you know, it's it is over. 219 00:21:44,920 --> 00:21:48,580 It's overly simplistic. It's what I call the Ontological Desert. 220 00:21:49,750 --> 00:22:00,340 So the assumption here that the pedagogically and culturally naive model of behaviour change is that, you know, the learner here is the patient, 221 00:22:00,340 --> 00:22:09,820 the person is an empty bucket and you'd put in education in the top like a sort of dollop of education and then that would change that behaviour. 222 00:22:10,510 --> 00:22:14,590 It isn't going to work like that and anybody who's a clinician knows that it doesn't work like that. 223 00:22:14,770 --> 00:22:22,089 Anyone who's tried to get either their parent or their child to change their behaviour by telling them it would be a very good idea if you do next. 224 00:22:22,090 --> 00:22:27,280 It's it's just not the way any of us behave. So we submitted this paper actually. 225 00:22:27,280 --> 00:22:29,860 It's been published now. I think this isn't this no version. 226 00:22:30,850 --> 00:22:36,549 But if you look it up in BMC Medicine, it's it's actually pretty much top of the hit parade in BMC Medicine. 227 00:22:36,550 --> 00:22:39,940 It's been downloaded lots of times and think people are very excited about the paper now, 228 00:22:39,940 --> 00:22:42,880 which is good because when I wrote the lecture, I wasn't sure whether they were going to like it. 229 00:22:43,960 --> 00:22:51,370 So we used narrative to try and unpack what was going on in South Asian women with diabetes in pregnancy. 230 00:22:52,120 --> 00:22:58,449 And this is a it's a great picture, but it's a bit complicated to get your head around. 231 00:22:58,450 --> 00:22:59,860 I'm going to talk you through it. 232 00:23:01,000 --> 00:23:11,590 The the horizontal axis, you know, starts here when you're born and you go along here and then this is when you're old and presume you die about here. 233 00:23:11,620 --> 00:23:19,390 So this is your your life. And then down here is the smallest unit, which is your genes. 234 00:23:19,990 --> 00:23:23,410 And I know there's probably people who go under and further below that and mind. 235 00:23:23,680 --> 00:23:31,479 Then you've got your molecules, you've got your cells, you've got your, your systems, and then here you've got what you do. 236 00:23:31,480 --> 00:23:36,700 This is human behaviour. And then up here is your family, your social networks, your groups. 237 00:23:36,700 --> 00:23:41,259 Then you've got your workplace in your school, then you've got national, then you've got the global level. 238 00:23:41,260 --> 00:23:47,820 That's things like, I don't know, the Grexit or whatever, you know, all the things that are going to affect, for example, 239 00:23:47,830 --> 00:23:53,410 the, you know, the global economic situation, which might affect whether you can afford to buy food, all that kind of thing. 240 00:23:53,650 --> 00:23:59,500 So it's actually very easy because it's saying this is how you live, you know, this is your life. 241 00:23:59,500 --> 00:24:03,280 And then this is the level at which we're analysing it. 242 00:24:04,060 --> 00:24:08,080 And this is a lot of sociological gobbledegook. 243 00:24:08,080 --> 00:24:11,290 But what it's saying. All these things are interrelated. 244 00:24:11,920 --> 00:24:15,489 And the thing to really note is that there's a bit in it. 245 00:24:15,490 --> 00:24:20,139 It's really simple, which is it's all about human behaviour. 246 00:24:20,140 --> 00:24:26,350 In the end, it's how we behave, it's how we learn that the reason why different groups, different age groups, 247 00:24:26,350 --> 00:24:31,299 genders, ethnic groups have different outcomes is largely because we behave differently, 248 00:24:31,300 --> 00:24:37,900 but we behave differently for all sorts of reasons, partly because, you know, the genes are firing things, 249 00:24:37,900 --> 00:24:44,040 but also because all these social things and particularly they look to opportunities and constraints. 250 00:24:44,050 --> 00:24:49,390 To what extent, for example, does the built environment create opportunities for exercise or whatever? 251 00:24:51,040 --> 00:24:55,090 So things are embodied at the level of human behaviour. 252 00:24:56,500 --> 00:25:04,810 Okay, so what were we doing? First of all, we're trying to understand these multiple influences on behaviour, 253 00:25:05,140 --> 00:25:10,660 which in turn all the risks to the metabolic health of a South Asian woman and her unborn child. 254 00:25:11,290 --> 00:25:21,580 We wanted to theorise that is, generate potential explanations using this nested hierarchy model of how these different 255 00:25:21,670 --> 00:25:26,530 influences interact and build over time is exactly what my colleague was suggesting we do. 256 00:25:27,370 --> 00:25:36,700 I didn't brief him before, by the way, and then we wanted to inform the design of interventions because the interventions are far too simplistic. 257 00:25:36,970 --> 00:25:45,280 They're all predicated on this empty bucket thing, you know, or that what's that behaviour change, you know. 258 00:25:45,460 --> 00:25:51,790 Are you and are you? What's the one where you when you're giving up smoking or trying to persuade someone to give it a go on. 259 00:25:52,750 --> 00:25:56,830 It's not the cycle of change. Yeah. Motivational interviewing, you know. 260 00:25:57,070 --> 00:26:01,479 Yeah, that sometimes works a bit. But when you using it, don't you think I'm going to mean it? 261 00:26:01,480 --> 00:26:04,990 There's all sorts of things happening with this person on in this model. 262 00:26:05,860 --> 00:26:11,170 So I'm not saying the model is, you know, completely useless, but we wanted to kind of get underneath that. 263 00:26:11,920 --> 00:26:21,969 So what do we do? Well, our sample was 45 women who had currently or previously diabetes in pregnancy. 264 00:26:21,970 --> 00:26:25,240 And we decided that could be either gestational or pre-existing. 265 00:26:25,240 --> 00:26:30,940 And the reason is that all the risk factors for gestational diabetes are pretty much the same as the risk factors for type two diabetes, 266 00:26:31,720 --> 00:26:35,170 which is a sort of AB, you know, B energy balance that isn't right. 267 00:26:36,400 --> 00:26:40,990 They either join the story sharing group where they, you know, 268 00:26:40,990 --> 00:26:48,399 they came to a group and told stories in the group and we recorded those or we went and interviewed them at home. 269 00:26:48,400 --> 00:26:51,700 So the original design was they would all come and join in story sharing groups, 270 00:26:51,700 --> 00:26:55,899 which we'd run very successfully for last 15 years with middle aged people with diabetes. 271 00:26:55,900 --> 00:26:57,700 They love coming to stories, sharing groups. 272 00:26:58,180 --> 00:27:06,130 You try doing that with sort of 21 year old who's got one child is pregnant with another and he's kind of doing all sorts of things around the house. 273 00:27:06,350 --> 00:27:10,600 They actually very few they wanted to come to the group, but they couldn't. 274 00:27:11,590 --> 00:27:13,840 And so we went to the houses and interviewed them. 275 00:27:14,140 --> 00:27:22,900 And it turned in, I think about in the end, almost two thirds of the women were interviewed at home and we just started to tell the story. 276 00:27:23,380 --> 00:27:27,130 Tell me the story. We use narrative prompts. 277 00:27:27,160 --> 00:27:32,469 Now, you've probably done semi-structured interviewing. You should go home. 278 00:27:32,470 --> 00:27:37,330 And when you of talking to your partner about what they did instead of saying, what do you do today? 279 00:27:37,540 --> 00:27:40,540 They're doing the semi-structured interview. 280 00:27:40,540 --> 00:27:50,150 Go to some lists and start asking them. You can have a pretty funny conversation on a narrative interview is why you just go in and say, Well, 281 00:27:50,170 --> 00:27:58,680 tell me about your diabetes and you use your own curiosity to prompt the next stage, you know, Oh, why? 282 00:27:58,690 --> 00:28:03,940 Why were you so upset at that point or Oh, tell me more, or what happened next? 283 00:28:03,940 --> 00:28:11,650 You know, those kind of the kind of questions you would have just in the normal conversation, a little bit more systematic than that. 284 00:28:11,680 --> 00:28:15,280 And then we, of course, we translated and transcribed them some of the asking questions. 285 00:28:15,280 --> 00:28:21,400 Yeah. Give you a couple of questions. Yeah, definitely. Is this approach likely to be far more fact based? 286 00:28:21,790 --> 00:28:27,640 Because it seems to me, for example, in sustainability and behaviour change there's what's called a values action gap. 287 00:28:27,940 --> 00:28:33,550 So is environment involved? Yes, it's very important to I believe an environment is really important to me, but they don't actually do it. 288 00:28:33,940 --> 00:28:37,390 So actually there's a gap between what they believe and what they do. 289 00:28:37,450 --> 00:28:43,790 Yet I think it's a latent opportunity, not necessarily a problem, but then anti and then you don't get it. 290 00:28:43,810 --> 00:28:49,540 So if you're saying do you recycle? Yes, I recycle. But if you look at observed behaviour yeah there's a gap. 291 00:28:49,570 --> 00:28:57,160 Yeah, yeah. You have to ask somebody through your process, you get away from telling what you actually did, tell me the story you get. 292 00:28:57,340 --> 00:29:07,090 You really you might be getting closer to the real, but I don't think you'll get facts because facts are something else. 293 00:29:07,150 --> 00:29:16,250 You know, facts. You get something. That the person you'd get something in the person genuine unless they're trying to deceive you. 294 00:29:16,250 --> 00:29:23,450 But assuming they're not, you'd get their version of events just like you do when you are you to kids who've been fighting, who started it. 295 00:29:23,640 --> 00:29:26,209 Know each of them genuinely believes that the other one started it. 296 00:29:26,210 --> 00:29:36,740 And they will tell you a story that will, you know, justify that, but in a way that neither of them facts and they're both interpretations. 297 00:29:37,040 --> 00:29:40,339 Let me go on. So how do we analyse this narrative data? 298 00:29:40,340 --> 00:29:44,480 Because what you get with any qualitative data, it doesn't look messy. 299 00:29:44,570 --> 00:29:47,660 It doesn't really look like data at all until you've done something with it. 300 00:29:48,350 --> 00:29:51,020 Well, the first thing and this is this is quite important. 301 00:29:51,020 --> 00:29:59,389 If you ever want to do narrative research, the first thing to do with stories is read them and read them again and again. 302 00:29:59,390 --> 00:30:06,870 Read them three or four times. Go through them, mark things in the margin, put exclamation marks of the interesting bits until you are familiar. 303 00:30:07,160 --> 00:30:17,910 That's called immersion. Then this description where you're really pulling out what's going on in this story, telling to say, Well, what? 304 00:30:17,960 --> 00:30:21,380 What's the beginning, what's the model, what's the end, that kind of thing. 305 00:30:22,190 --> 00:30:27,370 And then this theorise zation and I'm going to illustrate fear ization, which is give us an explanation, 306 00:30:27,410 --> 00:30:32,150 try and get all that kind of nested hierarchy stuff to map to the stories or 307 00:30:32,210 --> 00:30:36,650 the stories to map to the theoretical approach which I've introduced you to. 308 00:30:37,460 --> 00:30:42,560 Then this illustration, which is either pick a particular narrative, 309 00:30:44,630 --> 00:30:52,730 a real narrative from your dataset that illustrates the really the points you're trying to make or make one up, in other words, 310 00:30:52,730 --> 00:31:02,059 generate another narrative which is kind of representative of all the narratives, but which is a bit of this one, a bit of that one, 311 00:31:02,060 --> 00:31:09,840 and I'll show you that because, you know, people have commented that, hang on a minute, are you really allowed to make one up when you know? 312 00:31:10,490 --> 00:31:18,020 Because of course, you if you take a real narrative, you've then got the confidentiality problem, know when you're publishing and then validation, 313 00:31:18,020 --> 00:31:27,380 which is to go back to the people who gave you their stories and the advocates and the workers who are working with with these women, 314 00:31:28,100 --> 00:31:32,929 some of whom are quite poor, some of the people illiterate, etc., feedback to them. 315 00:31:32,930 --> 00:31:38,809 This is what we think your stories were telling is that, you know, does that resonate with you? 316 00:31:38,810 --> 00:31:45,320 And the sort of respondent validation again, is a very important aspect of qualitative research. 317 00:31:46,520 --> 00:31:48,259 We did use an Excel spreadsheet, 318 00:31:48,260 --> 00:31:55,370 we did use a little bit of a framework analysis which you probably lean towards just to sort of organise the data and become familiar with it. 319 00:31:57,500 --> 00:32:06,800 Yeah. Are you focus on responding to limitations because what can you do if you participant disagrees with your interpretation of the story? 320 00:32:07,730 --> 00:32:11,780 What do you do if your participant disagrees with your interpretation of their story? 321 00:32:13,130 --> 00:32:15,500 Have you got an example of when that happened? No, 322 00:32:15,500 --> 00:32:23,480 but I've always so I've I've never really used respondent because with the rationale that I am interpreting 323 00:32:25,640 --> 00:32:31,190 and at that point you stepping away from the story with as the storyteller whose story it is, 324 00:32:31,850 --> 00:32:37,800 is your version of your accounts. Mm hmm. Well, first of all, yes. 325 00:32:38,320 --> 00:32:47,330 Story. So what I've done in terms of this one in validation, I've taken back the sort of, you know, my my interpretation of all the stories. 326 00:32:47,480 --> 00:32:52,660 Yeah, yeah. That's what we did. We didn't go back and respond and interpret a single story. 327 00:32:52,910 --> 00:33:00,139 No, no, no, exactly. That's that we we I think precisely for that reason is that we go back and that's another 328 00:33:00,140 --> 00:33:06,530 reason for actually creating a new story to say this is the kind of data we've been getting, 329 00:33:06,530 --> 00:33:12,740 these are the kind of interpretations we're getting, and these are the kind of emotions that are coming through. 330 00:33:13,070 --> 00:33:18,469 Does this resonate? And people are actually very good looking at that, saying, yeah, that's pretty good. 331 00:33:18,470 --> 00:33:21,800 Actually, she was more upset than I would have been, but I can see that. 332 00:33:22,160 --> 00:33:27,050 And so yeah, but yes, the whole business of respondent validation is a bit difficult. 333 00:33:27,080 --> 00:33:30,170 The other reason it's difficult is that if anyone's ever done this, 334 00:33:30,500 --> 00:33:35,250 usually your research participants are not that interested in looking at what you've done anyway, you know? 335 00:33:35,330 --> 00:33:37,969 So we think it's a very worthy thing we think is ethical, 336 00:33:37,970 --> 00:33:43,010 but in the end they've usually disappeared or they don't reply to your email or they know when you visit them, etc. 337 00:33:43,340 --> 00:33:49,730 Okay, so let me give you some results. First result is well, what were the stories about? 338 00:33:50,420 --> 00:33:56,130 Um, so one of the things we found was the stories had different time courses. 339 00:33:56,150 --> 00:34:00,050 There was some short term stories, some medium term and some very long term. 340 00:34:00,350 --> 00:34:05,929 And the short term stories, of course, were about their pregnancy and they depicted the pregnancy. 341 00:34:05,930 --> 00:34:08,990 Most of these women depicted the pregnancy as absolutely ghastly. 342 00:34:09,150 --> 00:34:13,620 So you go onto the NCT website or something and women would say, Oh no, it's wonderful. 343 00:34:13,620 --> 00:34:18,930 I felt like a fantastic thing. I did my yoga and it's great and I had a massage and all that. 344 00:34:19,200 --> 00:34:23,700 We didn't get that at all. You know, we got this horrible experience of pregnancy very, 345 00:34:23,700 --> 00:34:33,299 very stressful and out of control and really difficult trying to find, you know, trying to keep the diabetes controlled. 346 00:34:33,300 --> 00:34:43,050 And the second thing that came out was the idea that exercising made them ill, made them tired. 347 00:34:43,050 --> 00:34:47,010 It made them it made their feet swell. It made them breathless. 348 00:34:47,010 --> 00:34:52,050 Someone's nodding. Why, you know, is this effort that's going to work? 349 00:34:52,260 --> 00:34:57,860 Go. All right. Okay. So, I mean, one of the things that came up in my research and time study. 350 00:35:00,150 --> 00:35:04,770 Sweating. Sweating, lots of sweating yet makes them sweat totally. 351 00:35:06,060 --> 00:35:10,170 And actually, we cited other research, much cited. 352 00:35:10,530 --> 00:35:17,309 I'll talk to you afterwards. The idea that the very things people were recommending were making these women feel ill. 353 00:35:17,310 --> 00:35:21,570 And so they might do a little bit of exercise, but then they'd have to go to bed because they felt so awful. 354 00:35:22,140 --> 00:35:27,600 And the idea that they felt much better when they ate for two. I mean, I mean, some of them use this expression eating for two. 355 00:35:27,600 --> 00:35:31,770 But, you know, the idea that eating to eating rice made them feel better. 356 00:35:32,310 --> 00:35:36,510 And accounts of advice and other women would say to them, go to bed. 357 00:35:37,050 --> 00:35:45,180 People write that thing. But if you look and if you've done the sort of discourse nurses a lot of people advise me to eat this week, 358 00:35:45,180 --> 00:35:52,380 that this is absolutely part of the culture. You know, advising women what to eat, you know, is also part of white British culture. 359 00:35:52,410 --> 00:35:58,979 Frankly, when you're pregnant, everyone chips in with a bit of advice. So I followed their orders rather than just the doctors. 360 00:35:58,980 --> 00:36:07,710 And it's a brilliant hierarchy here, but also orders, you know, the community, 361 00:36:08,070 --> 00:36:13,050 the peer group, the female peer group is allowed to order you, you know, what you eat. 362 00:36:13,440 --> 00:36:20,130 So the medium term stories were about what goes on in our family, in our community. 363 00:36:20,490 --> 00:36:25,130 And this the recurring storyline of a woman's work is never done. 364 00:36:25,140 --> 00:36:33,629 That's my metaphor. But what there wasn't in in the women we interviewed was any sense of what I've 365 00:36:33,630 --> 00:36:37,860 called or what other people have called the Taylor ization of domestic time. 366 00:36:38,280 --> 00:36:43,139 So, you know, many of you go back home and then you'll say to your partner and look here, 367 00:36:43,140 --> 00:36:47,250 I've taken the rubbish out and you know, you've cooked supper because I was at a lecture. 368 00:36:47,550 --> 00:36:49,860 So it's probably my turn to do this. 369 00:36:49,860 --> 00:36:57,990 And so you're all the time, you've got the taxi metre ticking as to how much work you've done to either bath the kids or cook the dinner or whatever. 370 00:36:58,530 --> 00:37:02,489 That didn't happen in I'm not saying it never happened in Asian communities. 371 00:37:02,490 --> 00:37:09,059 I'm saying that the women we interviewed who are mostly quite poor, East End, Bangladeshi, 372 00:37:09,060 --> 00:37:16,980 Gujarat women, that there was this continuing expectation on them to be domestically active. 373 00:37:17,190 --> 00:37:23,840 It was never finished. And that was why they couldn't come to the group's stories of progressive weight gain over years. 374 00:37:23,850 --> 00:37:28,080 You know, in my first example in a bit, wait a second, to put in a bit more blah, blah, blah, blah, blah. 375 00:37:28,410 --> 00:37:30,270 And that was completely normalised. 376 00:37:30,840 --> 00:37:37,889 And then there was past experiences with the health service, a very common one, because people get very upset about this. 377 00:37:37,890 --> 00:37:42,090 Is that sign on the wall in the GP surgery, one appointment, one problem. 378 00:37:42,390 --> 00:37:47,100 You go in there and say, I've got sort of foot, that's it. If you've got a cough as well, you've got make another appointment. 379 00:37:47,430 --> 00:37:54,569 And so that was the end of the GP. So are not saying all the time in the world, phew, you want to come along and tell me about your planned pregnancy? 380 00:37:54,570 --> 00:37:57,180 I'd be happy to listen. It was the opposite to that. 381 00:37:58,710 --> 00:38:03,690 So actually they had much better experiences with the hospital services than with the GP's and that is 382 00:38:03,690 --> 00:38:14,370 probably something to do with the work load that the GP's have a lot of stuff about finishing stuff up. 383 00:38:14,850 --> 00:38:23,820 All they've become is a waste and this sort of idea that this inexorable gain in weight was somehow expected and normalised. 384 00:38:24,090 --> 00:38:32,190 And then the long term stories about the distant past, about genetic heritage, about everyone in our community is at high risk. 385 00:38:32,490 --> 00:38:38,370 My grandmother had it, you know, back in Bangladesh, so and so had it all, that kind of thing. 386 00:38:39,330 --> 00:38:45,930 But also about cultural heritage, about the you know, this is these are collective societies. 387 00:38:45,930 --> 00:38:52,890 They're not they're not you're Californian. Let's have some me. Time and material, heritage, food insecurity, 388 00:38:53,880 --> 00:39:03,000 memories of the Bangladesh famine from people who weren't even born when the Bangladesh famine happened, that it was part of the collective memory. 389 00:39:03,240 --> 00:39:06,209 And if you know anything, you know the literature on food insecurity, 390 00:39:06,210 --> 00:39:15,570 you'll know that a community memory of famine is going to make people more likely to eat a lot when they've got it, 391 00:39:15,870 --> 00:39:19,080 because subconsciously you think, well, at some point you may not have it, okay? 392 00:39:20,520 --> 00:39:27,330 And of course, this stuff about back home, back home, even though you've never been to Bangladesh, it's still known as back home. 393 00:39:27,480 --> 00:39:31,290 And everybody's healthier and they didn't get diabetes. This was this isn't a myth. 394 00:39:31,290 --> 00:39:37,140 This is true, except that if you're in Dhaka now, it's not true anymore, etc. 395 00:39:37,590 --> 00:39:42,780 Okay, so let me link these up because now I've got a timeline, 396 00:39:43,080 --> 00:39:48,810 the present here and then this is the ancestral past, the distant past, the recent past. 397 00:39:48,840 --> 00:39:54,480 Got it. And you've got the short term stories. The medium term stories and the long term stories. 398 00:39:54,780 --> 00:39:59,330 And these are all nested in. So if you look at the data, they don't say, I'm not going to tell. 399 00:39:59,390 --> 00:40:05,540 You a long term story. It's the sort of little fragments that you have to tease out analytically. 400 00:40:05,870 --> 00:40:09,440 That here we've got a very short term story. This happened three months ago. 401 00:40:09,590 --> 00:40:17,749 Here we've got one of ten years ago. And here we've got one. You know, back home was actually when my grandparents lived in Bangladesh sort of thing. 402 00:40:17,750 --> 00:40:21,140 So we drew that out and that was that was quite fun unpacking that. 403 00:40:21,920 --> 00:40:27,200 I'm going to give you a fictionalised narrative now, now that you read that. 404 00:40:28,520 --> 00:40:36,560 So everything in this is something that's that reflects the stories that we got. 405 00:40:36,590 --> 00:40:43,340 So, for example, the stillbirth, you know, I was asked by a previous school, I got a minute, how can you say there was a stillbirth? 406 00:40:43,340 --> 00:40:50,719 But actually, in our group of 45 women, there were quite a few stillbirths that women talked about. 407 00:40:50,720 --> 00:41:01,820 And yet statistically, you wouldn't expect that many. But a few years ago I was working with a group who were working on the competition 408 00:41:01,820 --> 00:41:06,320 inquiry on stillbirth and deaths in infancy and maternal diabetes is a very, 409 00:41:06,320 --> 00:41:10,760 very common link with stillbirth. 410 00:41:10,760 --> 00:41:16,520 So, you know, this is this is not do you see so although I'm not saying this is statistically representative, 411 00:41:16,520 --> 00:41:21,979 I'm bringing out themes that are quite important. So this, I think, is quite important. 412 00:41:21,980 --> 00:41:25,880 She, you know, she was getting advice, she was getting education, if you like. 413 00:41:25,950 --> 00:41:31,190 She was trying. But, you know, this is there's a lot of things here that are going against this. 414 00:41:31,460 --> 00:41:43,340 Let me give you the next page of this narrative. Can you see how the narrative weaves together these different layers of influence? 415 00:41:43,580 --> 00:41:48,260 So you've got some physiological influences. This is something I'm quite interested in as a clinician. 416 00:41:48,260 --> 00:41:55,650 I originally trained as a diver to suggest that actually it's not very nice being hungry and it's not very nice feeling tired. 417 00:41:55,670 --> 00:41:59,330 You know, when you're hungry you get this urge to eat, especially if you're on insulin. 418 00:42:02,540 --> 00:42:08,690 When you exercise and it makes you feel exhausted, those symptoms will stop you exercising. 419 00:42:08,700 --> 00:42:15,320 So it's not just the sociocultural things, it's also the physiological influences here that I'm quite interested in. 420 00:42:15,650 --> 00:42:24,200 And you go right up to the sort of macro level of these women didn't feel safe going out of doors, their husbands wouldn't let them go out. 421 00:42:24,200 --> 00:42:27,200 So then my husband let me go out and exercise, you know, 422 00:42:27,200 --> 00:42:36,700 after dinner in the east end of London and sometimes in the state between the advice people being given about calorie balance, 423 00:42:36,710 --> 00:42:39,980 you know, the difference between exercise. 424 00:42:40,310 --> 00:42:45,200 I didn't go, man, you didn't do running the way you would do. 425 00:42:45,200 --> 00:42:50,120 And the alternative to be active, which you might find far easier to do. 426 00:42:50,390 --> 00:43:02,540 Yeah, absolutely. And so the exercise advice that comes totally disembodied from all everything else that's going on in fat time as life. 427 00:43:03,050 --> 00:43:06,440 She's not going to be able to it's not operationalise it. 428 00:43:06,650 --> 00:43:14,360 It's not tailored to her. Absolutely. Another thing that this story illustrates that the game is very common is, oh, 429 00:43:14,360 --> 00:43:21,320 she had the blood test and it showed that the diabetes had gone away completely staggered two years later and she gets diabetes, 430 00:43:21,590 --> 00:43:24,950 whereas actually she was heading for diabetes. 431 00:43:24,950 --> 00:43:31,280 Either you could see it, you know, in the story, but completely it was complete surprise. 432 00:43:31,290 --> 00:43:38,209 All right. So this is the model that we developed based on those narratives. 433 00:43:38,210 --> 00:43:43,370 And I'm giving you a very superficial version of the narratives. 434 00:43:44,150 --> 00:43:50,150 And you can see how we've adapted the diagram, which I took from Tom Glass's work, 435 00:43:52,220 --> 00:43:59,210 where we've still got maternal behaviours in the middle and we've got this energy inputs and energy expenditure. 436 00:43:59,780 --> 00:44:05,479 But here what happens is these two things that happen, baby people focus on weight gain. 437 00:44:05,480 --> 00:44:10,070 But I think there's also a big issue around loss of physical fitness. 438 00:44:10,310 --> 00:44:14,270 It's like in the elderly, you know, a lot, not in half. 439 00:44:14,480 --> 00:44:23,719 They're just out of shape. So what you have here is this weight gain and loss of fitness becomes the baseline for the next pregnancy. 440 00:44:23,720 --> 00:44:34,100 And so it all just gets worse and worse and worse. But in addition, you've got foetal programming here from this adverse micro environment in utero. 441 00:44:34,100 --> 00:44:43,580 So this foetus comes here and then when he or she is born, you know, they may have a high birth weight if they if they're, 442 00:44:43,760 --> 00:44:50,210 you know actually macros so make but they they're actually starting off life on day one when they're born. 443 00:44:50,420 --> 00:44:55,040 They already pre-programmed to have problems and then they're born into this 444 00:44:55,040 --> 00:44:59,300 environment here so that by the time this person is 18 and having a first. 445 00:44:59,380 --> 00:45:04,870 Pregnancy. Do you see what I mean? This is a vicious cycle, so you could pick that apart. 446 00:45:05,020 --> 00:45:09,060 I'm sure you know people will. Although I haven't yet. 447 00:45:09,070 --> 00:45:12,140 But I know this isn't the answer. 448 00:45:12,250 --> 00:45:16,000 This is this is getting us a little bit hopefully it's getting us a little bit 449 00:45:16,000 --> 00:45:22,720 further on that sort of epigenetics track than the quote I gave you earlier on. 450 00:45:24,040 --> 00:45:28,750 I love this quote from Glasson, McCarty, who's whose diagram I showed you initially? 451 00:45:28,930 --> 00:45:34,240 Human behaviour is sandwiched inextricably between ecology and biology. 452 00:45:34,720 --> 00:45:40,299 That's a good one. So this number writes the rising prevalence, 453 00:45:40,300 --> 00:45:48,730 the astronomically rising prevalence in poor South Asians in particular is mediated by patterns of behaviour in pregnant women, 454 00:45:48,730 --> 00:45:52,870 what they eat, how much exercise they take that are very poorly matched to their metabolic needs. 455 00:45:53,650 --> 00:45:58,930 Narrative research can begin to unpack these multiple interacting influences. 456 00:46:01,000 --> 00:46:09,430 Speaking now, wearing my sociology hat, these behaviours, which are very much prompted by peer groups and the community pressure, 457 00:46:10,990 --> 00:46:15,729 were intimate in that they were deeply personal, they were familiar. 458 00:46:15,730 --> 00:46:22,810 That is, they were grounded in the richness of family relationships and traditions and they were morally resonant. 459 00:46:23,050 --> 00:46:33,400 They were viewed as the right thing to do. And that is why these pregnancy related behaviours that, you know, I as a GP think are not quite right. 460 00:46:33,910 --> 00:46:40,660 That is why they are so entrenched, they're so resistant to change, they're intimate, they're familiar and they're morally resonant. 461 00:46:41,440 --> 00:46:46,030 The kind of education that we tend to offer South Asian women before, 462 00:46:46,030 --> 00:46:53,800 during and after pregnancy is not going to work because it's not familiar and it's not morally resonant. 463 00:46:53,950 --> 00:46:59,050 We have to make health advice more culturally meaningful and more morally resonant, 464 00:46:59,260 --> 00:47:02,830 and the way we might do that is by paying attention to the narratives. 465 00:47:03,850 --> 00:47:09,100 We need more imaginative interventions which are co-designed by families and 466 00:47:09,100 --> 00:47:16,270 communities to actually resonate more strongly with these nested narratives. 467 00:47:16,690 --> 00:47:19,780 So that's I think it's all I've got to say. 468 00:47:19,900 --> 00:47:23,200 Yes, I think we've got a couple of questions. 469 00:47:24,510 --> 00:47:28,320 Yes. But this description of the sort of feedback. Hmm. 470 00:47:29,700 --> 00:47:35,730 Is there any evidence that second or third or fourth children are more likely to die? 471 00:47:37,050 --> 00:47:40,830 It's a very interesting question. I don't know. 472 00:47:41,610 --> 00:47:45,659 Someone is has probably addressed that question. 473 00:47:45,660 --> 00:47:47,640 But you would have expected, wouldn't you? 474 00:47:48,120 --> 00:47:56,460 I mean, certainly in subsequent generations, the offspring of South Asian mothers are getting it younger and younger. 475 00:47:56,490 --> 00:48:03,629 I do know that. But you're right that it we we should be focussed on this. 476 00:48:03,630 --> 00:48:12,810 There are many contributing studies. I'm from Pakistan with the guy with his decision and this is quite evident that there 477 00:48:12,810 --> 00:48:16,860 are a couple of people from my own department who we have a vending machine expert, 478 00:48:17,070 --> 00:48:28,890 a couple of people who have diabetes, and including three people who are after five or six time that use that for more risk of developing diabetes. 479 00:48:29,280 --> 00:48:34,950 But that's that's the mother. That's the mother. But has anyone followed up all those children? 480 00:48:35,260 --> 00:48:40,890 The follow up. Yeah. It's interesting that these children would want to visit you and. 481 00:48:41,370 --> 00:48:44,730 Yeah, it is a dysfunction. And that would be the future. 482 00:48:45,010 --> 00:48:48,330 Yeah. Yeah, absolutely. Thank you. 483 00:48:48,360 --> 00:48:59,250 Thank you for that. I mean, it's I should say that the gift study has partners in both Pakistan and Bangladesh and actually not most of the feel. 484 00:48:59,490 --> 00:49:03,390 The big trials are being done in South Asia. 485 00:49:03,750 --> 00:49:07,080 But this qualitative study we did in the east end of London, 486 00:49:08,490 --> 00:49:15,600 partly because I didn't fancy living in Bangladesh to actually I quite like to live among the cities, but it didn't happen to me. 487 00:49:16,810 --> 00:49:20,580 Yeah. Who else had a hand up? Yeah. 488 00:49:22,170 --> 00:49:28,110 Oh, sorry, you cherry. Yeah, well, I. You can see I talked about this. 489 00:49:28,110 --> 00:49:37,230 This is about establishing what wasn't already known and the long, complicated words that I need to go into as well. 490 00:49:38,460 --> 00:49:45,030 What is what do you feel will be the next stage in advancing this towards something that people can look at, applying them? 491 00:49:45,900 --> 00:49:47,850 Oh, I think yeah, great question. 492 00:49:48,090 --> 00:49:56,940 I I'm very interested in co-design as an approach which is getting people to design the interventions that would work for them. 493 00:49:57,660 --> 00:50:04,920 So I've got a real problem with the MRC framework for developing complex interventions and I can say that into a podcast we are on the internet. 494 00:50:05,250 --> 00:50:10,020 I think the idea that these experts are going to rigorously develop this perfect intervention and, 495 00:50:10,110 --> 00:50:13,080 you know, test it in these clever trials, that's going to work. 496 00:50:13,980 --> 00:50:19,680 You know, I need to go to Tower Hamlets, get groups of people together saying, come on, what is going to work for you? 497 00:50:20,400 --> 00:50:29,850 And unless you know, because only then will we really embed these socio cultural narratives into the intervention. 498 00:50:30,120 --> 00:50:33,749 Some of the most successful work that I did and I didn't do very much of it, sadly, 499 00:50:33,750 --> 00:50:38,819 so got distracted to other things with working with the mosque, the local mosque in eastern London, 500 00:50:38,820 --> 00:50:43,290 working with the imams, working with the also the women who work in the mosque, 501 00:50:43,740 --> 00:50:49,170 the female religious scholars who really understand, you know, the Koran. 502 00:50:49,170 --> 00:50:53,069 They understand the lives of the people that are trying to help. 503 00:50:53,070 --> 00:50:56,670 And that's one of the imams said to me the words imam means teacher. 504 00:50:57,360 --> 00:51:02,790 They said, we are the ones that should be doing the teaching and doing the behavioural interventions. 505 00:51:03,240 --> 00:51:11,490 You are the doctors, you can bring some science to it. And I think if we could actually take the lead from communities and from, you know, 506 00:51:11,490 --> 00:51:16,980 the wise individuals in those communities, you know, from what we do about that, what's going to work and what doesn't. 507 00:51:18,270 --> 00:51:28,540 So that's where I would want to take this next. Obviously when you have a narrative, it's an intensely personal. 508 00:51:30,070 --> 00:51:36,940 But even though you might aggregate individuals narratives towards some commonality, you are completely, you know. 509 00:51:37,240 --> 00:51:38,350 Yeah, yeah, yeah. Totally. 510 00:51:38,740 --> 00:51:47,559 So I thought your conclusion was very powerful, but much of the public debate that say, on obesity and diabetes is right up here. 511 00:51:47,560 --> 00:51:51,639 And The Daily Mail's going to say about that well-known scientific journal. 512 00:51:51,640 --> 00:51:57,100 Yeah. So tell us about that, because I thought what you were saying is that separate it from the individual, 513 00:51:57,100 --> 00:51:59,860 their community and their environment and their genetics. Mm hmm. 514 00:51:59,920 --> 00:52:04,750 What does it mean for public policy and where the debate at and where the debate needs to change? 515 00:52:06,040 --> 00:52:13,019 Well, I think actually you can grow public policy from the community. 516 00:52:13,020 --> 00:52:19,599 Yeah. From the bottom up. I think if you have a more enabling approach and actually some examples in 517 00:52:19,600 --> 00:52:26,620 America of obesity schemes where they've taken a whole town and really yeah, 518 00:52:26,620 --> 00:52:33,880 probably France as well, you know and then what happens is someone will say, gosh, look what they're doing in such and such a locality. 519 00:52:34,750 --> 00:52:38,079 And of course you can't take that model and just replicate it everywhere. 520 00:52:38,080 --> 00:52:45,460 You still have to grow it from the ground up wherever you are. But people can come along and take a look and say, Oh, this is how it all works, 521 00:52:45,730 --> 00:52:49,690 and then go along and say, Now, how might we adapt to that to work here? 522 00:52:50,080 --> 00:52:54,370 And it's it's a very different I'm going to write a module on co-design. 523 00:52:54,760 --> 00:52:56,649 I'm not sure anyone's coming to SAP c next week. 524 00:52:56,650 --> 00:53:04,060 I'm running a workshop on co-design of interventions actually with Claire Jackson, who's doing this in Australia. 525 00:53:06,970 --> 00:53:14,320 I want to ask my colleague here about your work on South Asian women, about how this was similar or different. 526 00:53:15,150 --> 00:53:19,090 I mean, I didn't feel graphic, so I spent about six. 527 00:53:22,560 --> 00:53:25,889 Uh huh. Uh huh. Uh huh. And. 528 00:53:25,890 --> 00:53:31,110 And we didn't know anything. It's mainly first generation. 529 00:53:31,320 --> 00:53:35,250 Mhm. And so I it and not necessarily. 530 00:53:36,270 --> 00:53:40,210 And we've been having diabetes the first generation. 531 00:53:42,930 --> 00:53:46,520 Hmm. Absolutely. I mean, I had the privilege of listening to the. 532 00:53:50,310 --> 00:53:54,730 Spending time? Yes. Shops and homes. 533 00:53:56,100 --> 00:53:59,280 Yeah. And definitely the context. 534 00:54:01,110 --> 00:54:07,979 Yeah. It's and I think in a way, anybody who's even vaguely sympathetic to qualitative research knows it's the context. 535 00:54:07,980 --> 00:54:11,969 But how do you unpack all that? And how do you get from saying, look, 536 00:54:11,970 --> 00:54:19,020 it's far more complicated than this behaviour is the stuff of educating women not to kind of succumb to their genes. 537 00:54:19,650 --> 00:54:22,080 How do you get from that to an intervention that's going to work? 538 00:54:22,380 --> 00:54:28,870 And you know, that is that is complex, but then it's not impossible and we should be doing it anyway. 539 00:54:31,620 --> 00:54:35,010 So in the sense of the individual, it's different. 540 00:54:35,400 --> 00:54:45,060 So there is a lot of emphasis on the person functioning in relation to the family rather than the person doing something for themselves. 541 00:54:45,210 --> 00:54:53,010 Yeah, I totally agree. And actually we could go back and analyse our narrative. 542 00:54:54,030 --> 00:54:57,269 A colleague of mine, one of our researchers, was taking it, 543 00:54:57,270 --> 00:55:02,760 was taking one of these narrative interviews and she sort of halfway through it in the woman's flat, 544 00:55:03,150 --> 00:55:06,030 and there was a knock at the door and a group of friends arrived. 545 00:55:06,330 --> 00:55:11,819 So then immediately stopped the interview, cooked a beautiful, lovely, delicious meal. 546 00:55:11,820 --> 00:55:14,880 Everybody ate it and they still cleared up. And then she carried on the interview. 547 00:55:15,630 --> 00:55:22,170 Now, the idea that you might say to people, actually, I've got someone here who's interviewing me, could you come back a bit later? 548 00:55:22,170 --> 00:55:25,570 It just doesn't work like that. Someone's arrived. Guests have arrived, right? 549 00:55:25,590 --> 00:55:29,280 That's it. You have to be hospitable. It wasn't. Do you want a cup of tea? 550 00:55:29,280 --> 00:55:33,690 It was alright, you know, sit down. The dutiful curry and that, you know, I mean, 551 00:55:36,330 --> 00:55:43,979 we have to remember the huge cultural expectations and nothing brings that across more efficiently than narrative. 552 00:55:43,980 --> 00:55:50,450 I suppose that's the that's the argument. She you had a question, I think you'd like to ask that and then that will happen. 553 00:55:50,460 --> 00:55:56,210 Mm. Okay. Well I really enjoyed your tough love and your flair for the narrative. 554 00:55:56,310 --> 00:55:59,340 I think what's coming next is hierarchy. Well, that's what I've called it. Yeah. 555 00:55:59,370 --> 00:56:08,819 To be very evocative and it seemed to me and I could be very wrong about this term, it's the most superficial look at your work. 556 00:56:08,820 --> 00:56:15,110 But there was a real emphasis on the individual and individual behaviour. 557 00:56:15,450 --> 00:56:24,530 Mm hmm. Hierarchy. So that in the end, the. The advice was, you know, should be educational interventions were culturally relevant, morally over. 558 00:56:25,080 --> 00:56:30,420 Um, but there seemed to be some element of sort of inevitability to the structure. 559 00:56:30,870 --> 00:56:36,540 So I mean, even in the language of pre transition and post transition, it's sort of there's kind of this evolution. 560 00:56:36,540 --> 00:56:43,590 The structure is just transition, you know, as it is and that, that, you know, the, the structure, the cultural structure of the rest. 561 00:56:44,670 --> 00:56:48,510 It's it's hard to change. It's hard to change, isn't it? 562 00:56:49,710 --> 00:56:54,210 But it's not impossible to change. I'm not saying. But is it part of the project? 563 00:56:54,210 --> 00:57:00,030 Is it part of what you look at when you sort of say, well, what could we do with we haven't started the co-design work yet, 564 00:57:01,830 --> 00:57:06,330 but certainly we've got another project going in the East End actually, which is much more quantitative, 565 00:57:06,330 --> 00:57:14,309 where we're looking at prediabetes and actually using individual patient data from GP records to identify people who are very high risk of diabetes. 566 00:57:14,310 --> 00:57:19,260 And I'm working with geographers who are drawing maps and things, so it's very interesting quantitative project. 567 00:57:19,260 --> 00:57:20,930 But now we're saying, well alright, 568 00:57:20,940 --> 00:57:29,010 having identified 27,000 people in one borough of London who are very high risk of developing diabetes and they're all still quite young, 569 00:57:29,700 --> 00:57:35,640 what on earth are we going to do with them? So you could say, Oh, bring them in and send them to a dietician on on the strength of this. 570 00:57:35,700 --> 00:57:38,830 So that's not going to work. So what will you do then? 571 00:57:40,080 --> 00:57:43,370 Well, we could make these then safer to exercise it. 572 00:57:43,380 --> 00:57:47,400 We could close down all those ghastly fried chicken shops. 573 00:57:47,400 --> 00:57:54,930 So in the end, the reason why and Harry Rutter is very good on this, the reason why we do individual interventions, at least you can try. 574 00:57:55,320 --> 00:57:59,970 Whereas what you can't do is, you know, change the way the East End is. 575 00:58:00,900 --> 00:58:05,220 Having said that, this is another project we're doing on the Olympic legacy in Newham. 576 00:58:06,120 --> 00:58:11,640 Well, we did change the East and hugely we built the Olympic stadium swimming pool, running track, cycling track. 577 00:58:13,140 --> 00:58:17,220 And the youngsters in Newham schools do not use those facilities. 578 00:58:17,670 --> 00:58:26,219 We've got a paper in the press at the moment on that. So it's hard, even, for example, about Newham and Tower Hamlets after the Olympics. 579 00:58:26,220 --> 00:58:31,140 They wanted people to exercise and the London Cycle campaign in particular came and more people did. 580 00:58:31,140 --> 00:58:36,240 So yeah. And they really struggled to get ethnic minority people to get on the bicycle. 581 00:58:36,240 --> 00:58:41,700 And so the one intervention which has worked really well is the buddy system where a friend 582 00:58:41,700 --> 00:58:46,469 or colleague or somebody they know will take them and show them the route on a bicycle. 583 00:58:46,470 --> 00:58:52,200 And they do it together. The one you can tell somebody that's interesting will be in the cycle. 584 00:58:52,200 --> 00:58:56,999 They won't go with somebody they know and trust and they should do it together. 585 00:58:57,000 --> 00:59:00,299 And you de-risk it for them. Well, that's yeah. 586 00:59:00,300 --> 00:59:05,880 And actually we have been for, I mean, a good 15 years, we've been doing group work for older. 587 00:59:06,270 --> 00:59:09,960 It's mainly women who come, but it's actually for both genders and any ethnic group. 588 00:59:11,070 --> 00:59:18,360 And they've set up things like walking groups in parks, but it's got to emerge from what goes on in the groups. 589 00:59:18,510 --> 00:59:24,600 What you can't do is set up groups in the park, I would say, and then expect people to turn up. 590 00:59:24,600 --> 00:59:27,720 It's it's got to be grown. It's got to evolve. It's my view. 591 00:59:29,040 --> 00:59:32,489 And when it does evolve, it can be quite good and quite powerful and enduring, 592 00:59:32,490 --> 00:59:37,170 which is what some of the American examples funded by Robert Wood Johnson Foundation have shown. 593 00:59:37,590 --> 00:59:41,850 But no, this is this is tough stuff. Thank you so much, Trish. 594 00:59:41,850 --> 00:59:44,030 Thank you very, very much for that. Just.