Battling bad science - Ben Goldacre
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so<00:00:15.759> i'm<00:00:16.160> a<00:00:16.400> doctor<00:00:16.720> but<00:00:16.880> i<00:00:16.960> kind<00:00:17.039> of<00:00:17.119> slipped
so i'm a doctor but i kind of slipped
so i'm a doctor but i kind of slipped
sideways<00:00:17.840> into<00:00:18.000> research<00:00:18.400> and<00:00:18.480> now<00:00:18.720> i'm<00:00:18.880> an
sideways into research and now i'm an
sideways into research and now i'm an
epidemiologist<00:00:19.840> and<00:00:19.920> nobody<00:00:20.240> really<00:00:20.560> knows
epidemiologist and nobody really knows
epidemiologist and nobody really knows
what<00:00:21.279> epidemiology<00:00:22.000> is<00:00:22.160> epidemiology<00:00:22.880> is<00:00:22.960> the
what epidemiology is epidemiology is the
what epidemiology is epidemiology is the
science<00:00:23.680> of<00:00:23.840> how<00:00:24.000> we<00:00:24.160> know<00:00:24.640> in<00:00:24.800> the<00:00:24.880> real<00:00:25.119> world
science of how we know in the real world
science of how we know in the real world
if<00:00:25.519> something<00:00:25.760> is<00:00:25.920> good<00:00:26.160> for<00:00:26.240> you<00:00:26.640> or<00:00:26.880> bad<00:00:27.119> for
if something is good for you or bad for
if something is good for you or bad for
you<00:00:27.439> and<00:00:27.599> it's<00:00:27.760> best<00:00:28.000> understood<00:00:28.880> for<00:00:29.119> example
you and it's best understood for example
you and it's best understood for example
as<00:00:29.760> the<00:00:29.920> science<00:00:30.720> of<00:00:31.199> those<00:00:31.439> crazy<00:00:32.239> wacky
as the science of those crazy wacky
as the science of those crazy wacky
newspaper<00:00:33.440> headlines<00:00:34.239> and<00:00:34.719> these<00:00:34.960> are<00:00:35.040> just
newspaper headlines and these are just
newspaper headlines and these are just
some<00:00:35.440> of<00:00:35.520> the<00:00:35.680> examples<00:00:36.559> these<00:00:36.719> are<00:00:36.800> from<00:00:36.960> the
some of the examples these are from the
some of the examples these are from the
daily<00:00:37.280> mail<00:00:37.600> every<00:00:37.840> country<00:00:38.079> in<00:00:38.160> the<00:00:38.239> world
daily mail every country in the world
daily mail every country in the world
has<00:00:38.559> a<00:00:38.640> newspaper<00:00:39.120> like<00:00:39.360> this<00:00:39.840> it<00:00:40.000> has<00:00:40.160> this
has a newspaper like this it has this
has a newspaper like this it has this
kind<00:00:40.480> of<00:00:40.559> bizarre<00:00:40.960> ongoing<00:00:41.280> philosophical
kind of bizarre ongoing philosophical
kind of bizarre ongoing philosophical
project<00:00:42.480> of<00:00:42.640> dividing<00:00:42.960> all<00:00:43.040> the<00:00:43.120> unanimous
project of dividing all the unanimous
project of dividing all the unanimous
objects<00:00:43.760> in<00:00:43.840> the<00:00:44.000> world<00:00:44.320> really<00:00:44.559> into<00:00:44.800> the
objects in the world really into the
objects in the world really into the
ones<00:00:45.040> that<00:00:45.120> either<00:00:45.440> cause<00:00:46.000> or<00:00:46.239> prevent<00:00:46.960> cancer
ones that either cause or prevent cancer
ones that either cause or prevent cancer
so<00:00:47.840> here<00:00:48.000> are<00:00:48.079> some<00:00:48.239> of<00:00:48.239> the<00:00:48.320> things<00:00:48.480> they've
so here are some of the things they've
so here are some of the things they've
said<00:00:48.800> cause<00:00:49.039> cancer<00:00:49.360> recently<00:00:49.680> divorced
said cause cancer recently divorced
said cause cancer recently divorced
wi-fi<00:00:50.719> toiletries<00:00:51.520> and<00:00:51.680> coffee<00:00:52.160> here<00:00:52.320> are
wi-fi toiletries and coffee here are
wi-fi toiletries and coffee here are
some<00:00:52.559> of<00:00:52.559> the<00:00:52.640> things<00:00:52.800> they<00:00:52.960> say<00:00:53.199> prevent
some of the things they say prevent
some of the things they say prevent
cancer<00:00:53.920> crusts<00:00:54.239> red<00:00:54.399> pepper<00:00:54.640> licorice<00:00:55.199> and
cancer crusts red pepper licorice and
cancer crusts red pepper licorice and
coffee<00:00:55.680> so<00:00:55.840> already<00:00:56.399> you<00:00:56.480> can<00:00:56.640> see<00:00:56.719> there<00:00:56.879> are
coffee so already you can see there are
coffee so already you can see there are
contradictions<00:00:57.520> here<00:00:57.680> coffee<00:00:58.000> both<00:00:58.160> causes
contradictions here coffee both causes
contradictions here coffee both causes
and<00:00:58.879> prevents<00:00:59.359> cancer<00:00:59.920> and<00:01:00.079> as<00:01:00.160> you<00:01:00.320> start<00:01:00.480> to
and prevents cancer and as you start to
and prevents cancer and as you start to
read<00:01:00.800> on<00:01:00.879> you<00:01:01.039> can<00:01:01.120> see<00:01:01.280> that<00:01:01.359> maybe<00:01:01.600> there's
read on you can see that maybe there's
read on you can see that maybe there's
some<00:01:01.920> kind<00:01:02.000> of<00:01:02.079> political<00:01:02.640> valence<00:01:03.039> behind
some kind of political valence behind
some kind of political valence behind
some<00:01:03.520> of<00:01:03.680> this
some of this
some of this
so<00:01:04.559> for<00:01:04.720> women<00:01:05.040> housework<00:01:05.519> prevents<00:01:05.840> breast
so for women housework prevents breast
so for women housework prevents breast
cancer<00:01:06.640> but<00:01:06.799> for<00:01:07.040> men<00:01:07.680> shopping<00:01:08.080> could<00:01:08.240> make
cancer but for men shopping could make
cancer but for men shopping could make
you<00:01:09.040> impotent
you impotent
you impotent
so<00:01:10.560> we<00:01:10.799> know<00:01:11.360> that<00:01:11.520> we<00:01:11.680> need<00:01:11.920> to<00:01:12.080> start
so we know that we need to start
so we know that we need to start
unpicking<00:01:13.439> the<00:01:13.680> science<00:01:14.400> behind<00:01:14.880> this<00:01:15.360> and
unpicking the science behind this and
unpicking the science behind this and
what<00:01:15.680> i<00:01:15.760> hope<00:01:15.920> to<00:01:16.080> show<00:01:16.479> is<00:01:16.640> that
what i hope to show is that
what i hope to show is that
unpicking<00:01:18.320> dodgy<00:01:18.720> claims<00:01:19.119> i'm<00:01:19.200> picking<00:01:19.520> the
unpicking dodgy claims i'm picking the
unpicking dodgy claims i'm picking the
evidence<00:01:19.920> behind<00:01:20.159> dodgy<00:01:20.479> claims<00:01:21.040> isn't
evidence behind dodgy claims isn't
evidence behind dodgy claims isn't
a<00:01:22.000> kind<00:01:22.159> of<00:01:22.400> nasty<00:01:23.040> carping<00:01:23.920> activity<00:01:24.720> it's
a kind of nasty carping activity it's
a kind of nasty carping activity it's
socially<00:01:25.439> useful<00:01:25.759> but<00:01:25.920> it's<00:01:26.080> also<00:01:26.560> a<00:01:26.720> kind<00:01:26.880> of
socially useful but it's also a kind of
socially useful but it's also a kind of
an<00:01:27.600> extremely<00:01:28.000> valuable<00:01:28.880> explanatory<00:01:30.320> tool
an extremely valuable explanatory tool
an extremely valuable explanatory tool
because<00:01:30.880> real<00:01:31.040> science<00:01:31.439> is<00:01:31.520> all<00:01:31.680> about
because real science is all about
because real science is all about
critically<00:01:32.400> appraising<00:01:32.799> the<00:01:32.880> evidence<00:01:33.200> for
critically appraising the evidence for
critically appraising the evidence for
somebody<00:01:33.600> else's<00:01:34.159> position<00:01:34.560> that's<00:01:34.799> what
somebody else's position that's what
somebody else's position that's what
happens<00:01:35.200> in<00:01:35.280> academic<00:01:35.759> journals<00:01:36.240> that's<00:01:36.400> what
happens in academic journals that's what
happens in academic journals that's what
happens<00:01:37.280> at<00:01:37.439> academic<00:01:37.840> conferences<00:01:38.400> the<00:01:38.479> q<00:01:38.720> a
happens at academic conferences the q a
happens at academic conferences the q a
session<00:01:39.200> after<00:01:39.360> a<00:01:39.439> postdoc<00:01:39.840> presents<00:01:40.240> data<00:01:40.799> is
session after a postdoc presents data is
session after a postdoc presents data is
often<00:01:41.439> a<00:01:41.600> bloodbath<00:01:42.479> and<00:01:42.640> nobody<00:01:43.040> minds<00:01:43.360> that
often a bloodbath and nobody minds that
often a bloodbath and nobody minds that
we<00:01:43.759> actively<00:01:44.159> welcome<00:01:44.479> it<00:01:44.560> it's<00:01:44.640> like<00:01:44.799> a<00:01:44.880> kind
we actively welcome it it's like a kind
we actively welcome it it's like a kind
of<00:01:45.119> consenting<00:01:45.840> intellectual<00:01:46.720> s<00:01:46.960> m<00:01:47.200> activity
of consenting intellectual s m activity
of consenting intellectual s m activity
so<00:01:48.880> what<00:01:49.119> i'm<00:01:49.200> going<00:01:49.280> to<00:01:49.360> show<00:01:49.520> you<00:01:50.000> is<00:01:50.560> all<00:01:50.799> of
so what i'm going to show you is all of
so what i'm going to show you is all of
the<00:01:51.040> main<00:01:51.680> themes<00:01:52.000> all<00:01:52.159> of<00:01:52.240> the<00:01:52.399> main<00:01:52.640> features
the main themes all of the main features
the main themes all of the main features
of<00:01:53.200> my<00:01:53.360> discipline<00:01:53.759> evidence-based<00:01:54.399> medicine
of my discipline evidence-based medicine
of my discipline evidence-based medicine
and<00:01:55.280> i<00:01:55.360> will<00:01:55.680> talk<00:01:55.920> you<00:01:56.079> through<00:01:56.560> all<00:01:56.720> of<00:01:56.880> these
and i will talk you through all of these
and i will talk you through all of these
and<00:01:57.200> demonstrate<00:01:58.000> how<00:01:58.240> they<00:01:58.399> work
and demonstrate how they work
and demonstrate how they work
exclusively<00:01:59.840> using<00:02:00.159> examples<00:02:00.560> of<00:02:00.640> people
exclusively using examples of people
exclusively using examples of people
getting<00:02:01.200> stuff<00:02:01.759> wrong<00:02:02.560> so<00:02:03.119> we'll<00:02:03.360> start<00:02:03.600> with
getting stuff wrong so we'll start with
getting stuff wrong so we'll start with
the<00:02:03.920> absolute<00:02:04.560> weakest<00:02:05.040> form<00:02:05.280> of<00:02:05.439> evidence
the absolute weakest form of evidence
the absolute weakest form of evidence
known<00:02:05.920> to<00:02:06.000> man<00:02:06.159> and<00:02:06.320> that<00:02:06.479> is<00:02:06.960> authority<00:02:07.920> in
known to man and that is authority in
known to man and that is authority in
science<00:02:08.319> we<00:02:08.479> don't<00:02:08.640> care<00:02:08.879> how<00:02:09.039> many<00:02:09.200> letters
science we don't care how many letters
science we don't care how many letters
you<00:02:09.599> have<00:02:09.920> after<00:02:10.239> your<00:02:10.319> name<00:02:10.560> in<00:02:10.720> science<00:02:11.120> we
you have after your name in science we
you have after your name in science we
want<00:02:11.440> to<00:02:11.520> know<00:02:11.840> what<00:02:12.000> your<00:02:12.239> reasons<00:02:12.720> are<00:02:12.800> for
want to know what your reasons are for
want to know what your reasons are for
believing<00:02:13.280> something<00:02:13.520> how<00:02:13.680> do<00:02:13.840> you<00:02:14.080> know<00:02:14.319> that
believing something how do you know that
believing something how do you know that
something<00:02:14.800> is<00:02:14.959> good<00:02:15.200> for<00:02:15.360> us<00:02:15.840> or<00:02:16.080> bad<00:02:16.400> for<00:02:16.640> us
something is good for us or bad for us
something is good for us or bad for us
but<00:02:17.599> we're<00:02:17.760> also<00:02:18.000> unimpressed<00:02:18.319> by<00:02:18.480> authority
but we're also unimpressed by authority
but we're also unimpressed by authority
because<00:02:19.200> it's<00:02:19.360> so<00:02:19.599> easy<00:02:20.080> to<00:02:20.480> contrive<00:02:21.599> this<00:02:21.760> is
because it's so easy to contrive this is
because it's so easy to contrive this is
somebody<00:02:22.080> called<00:02:22.239> dr<00:02:22.480> jillian<00:02:22.800> mckeith<00:02:23.120> phd
somebody called dr jillian mckeith phd
somebody called dr jillian mckeith phd
or<00:02:23.920> to<00:02:24.000> give<00:02:24.160> her<00:02:24.319> full<00:02:24.560> medical<00:02:24.879> title
or to give her full medical title
or to give her full medical title
jillian<00:02:25.840> mckeefe
jillian mckeefe
jillian mckeefe
again
every<00:02:30.319> country<00:02:30.800> has<00:02:31.040> somebody<00:02:31.520> like<00:02:31.840> this<00:02:32.160> she
every country has somebody like this she
every country has somebody like this she
is<00:02:32.480> our<00:02:32.640> tv<00:02:32.959> diet<00:02:33.200> guru<00:02:33.519> she<00:02:33.680> has<00:02:33.920> massive<00:02:34.319> kind
is our tv diet guru she has massive kind
is our tv diet guru she has massive kind
of<00:02:34.720> five<00:02:35.040> series<00:02:35.440> of<00:02:35.599> prime<00:02:35.920> time<00:02:36.160> television
of five series of prime time television
of five series of prime time television
giving<00:02:36.720> out<00:02:36.800> very<00:02:37.040> lavish<00:02:37.599> and<00:02:37.760> exotic<00:02:38.319> health
giving out very lavish and exotic health
giving out very lavish and exotic health
advice<00:02:39.120> she<00:02:39.440> uh<00:02:39.920> turns<00:02:40.239> out<00:02:40.400> has<00:02:40.560> a
advice she uh turns out has a
advice she uh turns out has a
non-accredited<00:02:41.440> correspondence<00:02:42.000> course<00:02:42.239> phd
non-accredited correspondence course phd
non-accredited correspondence course phd
from<00:02:43.040> somewhere<00:02:43.360> in<00:02:43.440> america<00:02:44.000> she<00:02:44.160> also
from somewhere in america she also
from somewhere in america she also
boasts<00:02:44.640> that<00:02:44.720> she's<00:02:44.879> a<00:02:44.959> certified
boasts that she's a certified
boasts that she's a certified
professional<00:02:45.920> member<00:02:46.080> of<00:02:46.160> the<00:02:46.239> american
professional member of the american
professional member of the american
association<00:02:47.280> of<00:02:47.360> nutritional<00:02:47.840> consultants
association of nutritional consultants
association of nutritional consultants
which<00:02:48.480> sounds<00:02:48.720> very<00:02:48.879> glamorous<00:02:49.280> and<00:02:49.360> exciting
which sounds very glamorous and exciting
which sounds very glamorous and exciting
you<00:02:50.080> get<00:02:50.239> a<00:02:50.319> certificate<00:02:50.879> and<00:02:50.959> everything
you get a certificate and everything
you get a certificate and everything
this<00:02:51.680> one<00:02:51.840> belongs<00:02:52.160> to<00:02:52.319> my<00:02:52.400> dead<00:02:52.640> cat<00:02:52.879> hetty
this one belongs to my dead cat hetty
this one belongs to my dead cat hetty
she<00:02:54.000> was<00:02:54.080> a<00:02:54.160> horrible<00:02:54.560> cat<00:02:54.879> you<00:02:54.959> just<00:02:55.120> go<00:02:55.280> to
she was a horrible cat you just go to
she was a horrible cat you just go to
the<00:02:55.440> website<00:02:55.840> fill<00:02:56.000> out<00:02:56.080> the<00:02:56.160> form<00:02:56.400> give<00:02:56.560> them
the website fill out the form give them
the website fill out the form give them
sixty<00:02:56.959> dollars<00:02:57.280> and<00:02:57.440> arrives<00:02:57.760> in<00:02:57.840> the<00:02:57.920> post
sixty dollars and arrives in the post
sixty dollars and arrives in the post
now<00:02:58.319> that's<00:02:58.560> not<00:02:58.640> the<00:02:58.720> only<00:02:58.959> reason<00:02:59.200> that<00:02:59.280> we
now that's not the only reason that we
now that's not the only reason that we
think<00:02:59.440> this<00:02:59.599> person<00:02:59.840> is<00:02:59.920> an<00:03:00.000> idiot<00:03:00.239> she<00:03:00.400> also
think this person is an idiot she also
think this person is an idiot she also
goes<00:03:00.879> on<00:03:01.120> uh<00:03:01.680> and<00:03:01.840> says<00:03:02.080> things<00:03:02.239> like<00:03:02.480> you
goes on uh and says things like you
goes on uh and says things like you
should<00:03:02.720> eat<00:03:02.800> lots<00:03:03.040> of<00:03:03.120> dark<00:03:03.360> green<00:03:03.519> leaves
should eat lots of dark green leaves
should eat lots of dark green leaves
because<00:03:03.920> they<00:03:04.080> contain<00:03:04.319> lots<00:03:04.560> of<00:03:04.640> chlorophyll
because they contain lots of chlorophyll
because they contain lots of chlorophyll
and<00:03:05.120> that<00:03:05.200> will<00:03:05.360> really<00:03:05.519> oxygenate<00:03:06.000> your
and that will really oxygenate your
and that will really oxygenate your
blood<00:03:07.040> and<00:03:07.360> anybody<00:03:07.680> who's<00:03:07.840> done<00:03:08.000> school
blood and anybody who's done school
blood and anybody who's done school
biology<00:03:08.720> remembers<00:03:09.040> that<00:03:09.200> chlorophyll<00:03:09.840> in
biology remembers that chlorophyll in
biology remembers that chlorophyll in
chloroplasts<00:03:10.720> only<00:03:10.959> makes<00:03:11.200> oxygen<00:03:11.760> in
chloroplasts only makes oxygen in
chloroplasts only makes oxygen in
sunlight<00:03:12.800> and<00:03:12.879> it's<00:03:13.040> quite<00:03:13.280> dark<00:03:13.760> in<00:03:13.920> your
sunlight and it's quite dark in your
sunlight and it's quite dark in your
bowels<00:03:14.480> after<00:03:14.720> you've<00:03:14.879> eaten<00:03:15.040> spinach<00:03:15.920> next
bowels after you've eaten spinach next
bowels after you've eaten spinach next
we<00:03:16.959> need<00:03:17.120> proper<00:03:17.440> science<00:03:17.760> proper<00:03:18.080> evidence
we need proper science proper evidence
we need proper science proper evidence
so
so
so
red<00:03:19.440> wine<00:03:19.680> can<00:03:19.840> help<00:03:20.000> prevent<00:03:20.319> breast<00:03:20.480> cancer
red wine can help prevent breast cancer
red wine can help prevent breast cancer
there's<00:03:20.959> a<00:03:21.040> headline<00:03:21.599> from<00:03:21.760> the<00:03:21.840> daily
there's a headline from the daily
there's a headline from the daily
telegraph<00:03:22.480> in<00:03:22.560> the<00:03:22.640> uk<00:03:23.200> a<00:03:23.360> glass<00:03:23.599> of<00:03:23.680> red<00:03:23.840> one<00:03:24.000> a
telegraph in the uk a glass of red one a
telegraph in the uk a glass of red one a
day<00:03:24.239> could<00:03:24.319> help<00:03:24.560> prevent<00:03:25.120> breast<00:03:25.440> cancer<00:03:25.760> so
day could help prevent breast cancer so
day could help prevent breast cancer so
you're<00:03:26.000> going<00:03:26.080> to<00:03:26.159> find<00:03:26.400> this<00:03:26.560> paper<00:03:26.800> and<00:03:26.879> what
you're going to find this paper and what
you're going to find this paper and what
you<00:03:27.200> find<00:03:27.519> is<00:03:27.760> it<00:03:27.920> is<00:03:28.000> a<00:03:28.080> real<00:03:28.239> piece<00:03:28.480> of
you find is it is a real piece of
you find is it is a real piece of
science<00:03:28.879> it's<00:03:29.040> a<00:03:29.120> description<00:03:29.840> of<00:03:30.000> the
science it's a description of the
science it's a description of the
changes<00:03:30.640> in<00:03:30.720> the<00:03:30.799> behavior<00:03:31.200> of<00:03:31.360> one<00:03:31.599> enzyme
changes in the behavior of one enzyme
changes in the behavior of one enzyme
when<00:03:32.480> you<00:03:32.640> drip<00:03:32.959> a<00:03:33.040> chemical<00:03:33.519> extracted<00:03:34.080> from
when you drip a chemical extracted from
when you drip a chemical extracted from
some<00:03:34.480> red<00:03:34.720> grape<00:03:35.280> skin<00:03:35.920> onto<00:03:36.480> some<00:03:36.640> cancer
some red grape skin onto some cancer
some red grape skin onto some cancer
cells<00:03:37.599> in<00:03:37.760> a<00:03:38.080> dish<00:03:38.640> on<00:03:38.799> a<00:03:38.959> bench<00:03:39.440> in<00:03:39.519> a
cells in a dish on a bench in a
cells in a dish on a bench in a
laboratory<00:03:40.239> somewhere<00:03:40.799> and<00:03:40.879> that's<00:03:41.280> a<00:03:41.519> really
laboratory somewhere and that's a really
laboratory somewhere and that's a really
useful<00:03:42.799> thing<00:03:43.040> to<00:03:43.200> describe<00:03:43.680> in<00:03:43.760> a<00:03:43.840> scientific
useful thing to describe in a scientific
useful thing to describe in a scientific
paper<00:03:44.799> but<00:03:45.040> on<00:03:45.120> the<00:03:45.200> question<00:03:45.519> of<00:03:45.599> your<00:03:45.920> own
paper but on the question of your own
paper but on the question of your own
personal<00:03:46.480> risk<00:03:46.720> of<00:03:46.799> getting<00:03:47.040> breast<00:03:47.280> cancer
personal risk of getting breast cancer
personal risk of getting breast cancer
if<00:03:47.760> you<00:03:47.840> drink<00:03:48.000> red<00:03:48.159> wine<00:03:48.560> it<00:03:48.720> tells<00:03:48.959> you
if you drink red wine it tells you
if you drink red wine it tells you
absolutely<00:03:49.760> bugger<00:03:50.159> all<00:03:50.480> okay<00:03:51.040> actually
absolutely bugger all okay actually
absolutely bugger all okay actually
turns<00:03:51.599> out<00:03:51.760> that<00:03:51.840> your<00:03:52.159> risk<00:03:52.400> of<00:03:52.560> breast
turns out that your risk of breast
turns out that your risk of breast
cancer<00:03:53.200> actually<00:03:53.519> increases<00:03:54.000> slightly<00:03:54.319> with
cancer actually increases slightly with
cancer actually increases slightly with
every<00:03:54.799> amount<00:03:55.120> of<00:03:55.360> alcohol<00:03:55.680> that<00:03:55.840> you<00:03:56.159> drink
every amount of alcohol that you drink
every amount of alcohol that you drink
so
so
so
what<00:03:57.840> we<00:03:57.920> want<00:03:58.239> is<00:03:58.400> studies<00:03:58.799> in<00:03:59.040> real<00:03:59.599> human
what we want is studies in real human
what we want is studies in real human
people<00:04:00.560> and<00:04:01.120> here's<00:04:01.360> another<00:04:01.680> example<00:04:02.239> this
people and here's another example this
people and here's another example this
is<00:04:02.959> from<00:04:03.439> britain's<00:04:03.840> leading<00:04:04.319> diet
is from britain's leading diet
is from britain's leading diet
nutritionist<00:04:05.439> in<00:04:05.519> the<00:04:05.599> daily<00:04:05.840> mirror<00:04:06.159> which
nutritionist in the daily mirror which
nutritionist in the daily mirror which
is<00:04:06.400> our<00:04:06.480> second<00:04:06.720> biggest<00:04:06.959> selling<00:04:07.200> newspaper
is our second biggest selling newspaper
is our second biggest selling newspaper
an<00:04:08.000> australian<00:04:08.480> study<00:04:08.720> in<00:04:08.799> 2001<00:04:09.360> found<00:04:09.519> that
an australian study in 2001 found that
an australian study in 2001 found that
olive<00:04:09.760> oil<00:04:10.000> in<00:04:10.080> combination<00:04:10.400> with<00:04:10.560> fruits
olive oil in combination with fruits
olive oil in combination with fruits
vegetables<00:04:11.280> and<00:04:11.360> pulses<00:04:11.760> offers<00:04:12.000> measurable
vegetables and pulses offers measurable
vegetables and pulses offers measurable
protection<00:04:13.120> against<00:04:13.519> skin<00:04:13.840> wrinkling<00:04:14.239> so
protection against skin wrinkling so
protection against skin wrinkling so
then<00:04:14.560> they<00:04:14.640> give<00:04:14.799> the<00:04:14.879> advice<00:04:15.360> if<00:04:15.439> you<00:04:15.599> eat
then they give the advice if you eat
then they give the advice if you eat
olive<00:04:16.079> oil<00:04:16.239> and<00:04:16.320> vegetables<00:04:16.720> you'll<00:04:16.880> have
olive oil and vegetables you'll have
olive oil and vegetables you'll have
fewer<00:04:17.359> skin<00:04:17.600> wrinkles<00:04:18.160> and<00:04:18.239> they<00:04:18.400> very
fewer skin wrinkles and they very
fewer skin wrinkles and they very
helpfully<00:04:18.880> tell<00:04:19.040> you<00:04:19.120> how<00:04:19.199> to<00:04:19.280> find<00:04:19.440> the<00:04:19.519> paper
helpfully tell you how to find the paper
helpfully tell you how to find the paper
so<00:04:19.919> you<00:04:20.000> go<00:04:20.079> and<00:04:20.239> find<00:04:20.400> the<00:04:20.479> paper<00:04:20.959> and<00:04:21.040> what
so you go and find the paper and what
so you go and find the paper and what
you<00:04:21.280> find<00:04:21.519> is<00:04:21.600> an<00:04:21.759> observational<00:04:22.400> study<00:04:22.800> right
you find is an observational study right
you find is an observational study right
obviously<00:04:23.600> nobody<00:04:24.000> has<00:04:24.240> ever<00:04:24.400> been<00:04:24.639> able<00:04:24.880> to
obviously nobody has ever been able to
obviously nobody has ever been able to
go<00:04:25.440> back<00:04:25.600> to<00:04:25.759> like<00:04:25.919> 1930<00:04:27.040> get<00:04:27.280> all<00:04:27.440> of<00:04:27.600> the
go back to like 1930 get all of the
go back to like 1930 get all of the
people<00:04:28.000> born<00:04:28.240> in<00:04:28.400> one<00:04:28.720> maternity<00:04:29.280> unit<00:04:29.440> and
people born in one maternity unit and
people born in one maternity unit and
half<00:04:29.759> of<00:04:29.919> them<00:04:30.080> eat<00:04:30.240> lots<00:04:30.479> of<00:04:30.560> fruit<00:04:30.800> and<00:04:30.880> veg
half of them eat lots of fruit and veg
half of them eat lots of fruit and veg
and<00:04:31.280> olive<00:04:31.520> oil<00:04:31.840> and<00:04:31.919> then<00:04:32.080> half<00:04:32.320> of<00:04:32.400> them<00:04:32.639> eat
and olive oil and then half of them eat
and olive oil and then half of them eat
mcdonald's<00:04:33.520> and<00:04:33.600> then<00:04:33.759> we<00:04:33.840> see<00:04:34.000> how<00:04:34.160> many
mcdonald's and then we see how many
mcdonald's and then we see how many
wrinkles<00:04:34.720> you've<00:04:34.800> got<00:04:34.960> later<00:04:35.280> you<00:04:35.360> have<00:04:35.520> to
wrinkles you've got later you have to
wrinkles you've got later you have to
take<00:04:35.759> a<00:04:35.840> snapshot<00:04:36.400> of<00:04:36.479> how<00:04:36.639> people<00:04:36.960> are<00:04:37.360> now
take a snapshot of how people are now
take a snapshot of how people are now
and<00:04:37.759> what<00:04:37.919> you<00:04:38.000> find<00:04:38.240> is<00:04:38.400> of<00:04:38.560> course<00:04:39.120> people
and what you find is of course people
and what you find is of course people
who<00:04:39.520> eat<00:04:39.600> fruit<00:04:39.840> and<00:04:39.919> veg<00:04:40.160> and<00:04:40.240> olive<00:04:40.479> oil<00:04:40.800> have
who eat fruit and veg and olive oil have
who eat fruit and veg and olive oil have
fewer<00:04:41.360> skin<00:04:41.520> wrinkles<00:04:42.240> but<00:04:42.400> that's<00:04:42.639> because
fewer skin wrinkles but that's because
fewer skin wrinkles but that's because
people<00:04:43.280> who<00:04:43.440> eat<00:04:43.520> fruit<00:04:43.680> and<00:04:43.759> veg<00:04:43.919> and<00:04:44.000> olive
people who eat fruit and veg and olive
people who eat fruit and veg and olive
oil<00:04:44.639> they're<00:04:44.960> freaks<00:04:45.680> okay<00:04:46.240> they're<00:04:46.479> not
oil they're freaks okay they're not
oil they're freaks okay they're not
normal<00:04:47.199> they're<00:04:47.440> like<00:04:47.680> you<00:04:48.160> they<00:04:48.400> come<00:04:48.639> to
normal they're like you they come to
normal they're like you they come to
events<00:04:49.520> like<00:04:49.759> this<00:04:50.320> right<00:04:50.800> they<00:04:51.040> are<00:04:51.600> posh
events like this right they are posh
events like this right they are posh
they're<00:04:52.160> wealthy<00:04:52.560> they're<00:04:52.800> less<00:04:52.960> likely<00:04:53.199> to
they're wealthy they're less likely to
they're wealthy they're less likely to
have<00:04:53.520> outdoor<00:04:53.919> jobs<00:04:54.240> they're<00:04:54.400> less<00:04:54.560> likely<00:04:54.720> to
have outdoor jobs they're less likely to
have outdoor jobs they're less likely to
do<00:04:54.960> manual<00:04:55.280> labor<00:04:55.840> they<00:04:56.000> have<00:04:56.160> better<00:04:56.479> social
do manual labor they have better social
do manual labor they have better social
support<00:04:57.040> they're<00:04:57.199> less<00:04:57.360> likely<00:04:57.520> to<00:04:57.600> smoke<00:04:57.840> so
support they're less likely to smoke so
support they're less likely to smoke so
for<00:04:58.080> a<00:04:58.160> whole<00:04:58.400> host<00:04:58.960> of<00:04:59.120> fascinating
for a whole host of fascinating
for a whole host of fascinating
interlocking<00:05:00.160> social<00:05:00.400> political<00:05:00.800> and
interlocking social political and
interlocking social political and
cultural<00:05:01.199> reasons<00:05:01.600> they<00:05:01.759> are<00:05:01.840> less<00:05:02.000> likely<00:05:02.240> to
cultural reasons they are less likely to
cultural reasons they are less likely to
have<00:05:02.400> skin<00:05:02.560> wrinkles<00:05:02.960> that<00:05:03.120> doesn't<00:05:03.360> mean
have skin wrinkles that doesn't mean
have skin wrinkles that doesn't mean
that<00:05:04.080> it's<00:05:04.240> the<00:05:04.400> vegetables<00:05:05.120> or<00:05:05.280> the<00:05:05.440> olive
that it's the vegetables or the olive
that it's the vegetables or the olive
oil
oil
oil
so
so
so
ideally<00:05:09.280> what<00:05:09.440> you<00:05:09.520> want<00:05:09.600> to<00:05:09.680> do<00:05:09.759> is<00:05:09.919> a<00:05:10.000> trial
ideally what you want to do is a trial
ideally what you want to do is a trial
and<00:05:10.479> everybody<00:05:10.720> thinks<00:05:10.880> they're<00:05:11.039> very
and everybody thinks they're very
and everybody thinks they're very
familiar<00:05:11.520> with<00:05:11.600> the<00:05:11.680> idea<00:05:11.919> of<00:05:12.000> a<00:05:12.080> trial<00:05:12.400> trials
familiar with the idea of a trial trials
familiar with the idea of a trial trials
are<00:05:12.880> very<00:05:13.120> old<00:05:13.280> the<00:05:13.360> first<00:05:13.520> trial<00:05:13.680> was<00:05:13.840> in<00:05:13.919> the
are very old the first trial was in the
are very old the first trial was in the
bible<00:05:14.320> daniel<00:05:14.639> 112.<00:05:15.600> it's<00:05:15.759> very
bible daniel 112. it's very
bible daniel 112. it's very
straightforward<00:05:16.479> you<00:05:16.639> take<00:05:16.800> a<00:05:16.800> bunch<00:05:17.039> of
straightforward you take a bunch of
straightforward you take a bunch of
people<00:05:17.360> you<00:05:17.440> split<00:05:17.680> them<00:05:17.759> in<00:05:17.919> half<00:05:18.080> you<00:05:18.240> treat
people you split them in half you treat
people you split them in half you treat
one<00:05:18.560> group<00:05:18.720> one<00:05:18.880> way<00:05:19.039> you<00:05:19.120> treat<00:05:19.280> the<00:05:19.360> other
one group one way you treat the other
one group one way you treat the other
group<00:05:19.680> the<00:05:19.759> other<00:05:19.919> way<00:05:20.080> and<00:05:20.160> then<00:05:20.320> a<00:05:20.400> little
group the other way and then a little
group the other way and then a little
while<00:05:20.720> later<00:05:20.960> you<00:05:21.120> fold<00:05:21.280> them<00:05:21.440> up<00:05:21.520> and<00:05:21.680> see
while later you fold them up and see
while later you fold them up and see
what<00:05:22.160> happened<00:05:22.400> to<00:05:22.560> each<00:05:22.800> of<00:05:22.880> them<00:05:23.440> so<00:05:23.600> i'm
what happened to each of them so i'm
what happened to each of them so i'm
going<00:05:23.759> to<00:05:23.840> tell<00:05:24.000> you<00:05:24.160> about<00:05:24.479> about<00:05:24.720> one<00:05:24.960> trial
going to tell you about about one trial
going to tell you about about one trial
which<00:05:25.520> is<00:05:25.680> probably<00:05:25.919> the<00:05:26.000> most<00:05:26.240> well<00:05:26.479> reported
which is probably the most well reported
which is probably the most well reported
trial<00:05:27.520> in<00:05:27.680> the<00:05:27.759> uk<00:05:28.160> news<00:05:28.400> media<00:05:28.720> over<00:05:28.960> the<00:05:29.039> past
trial in the uk news media over the past
trial in the uk news media over the past
decade<00:05:30.240> and<00:05:30.320> this<00:05:30.479> is<00:05:30.639> trial<00:05:30.880> official
decade and this is trial official
decade and this is trial official
appeals<00:05:31.680> and<00:05:31.759> the<00:05:31.840> claim<00:05:32.000> was<00:05:32.240> official<00:05:32.639> pills
appeals and the claim was official pills
appeals and the claim was official pills
improved<00:05:33.520> school<00:05:33.759> performance<00:05:34.240> and<00:05:34.400> behavior
improved school performance and behavior
improved school performance and behavior
in<00:05:35.120> mainstream<00:05:35.680> children<00:05:36.000> and<00:05:36.080> they<00:05:36.160> said
in mainstream children and they said
in mainstream children and they said
we've<00:05:36.479> done<00:05:36.639> a<00:05:36.800> trial<00:05:37.199> all<00:05:37.360> the<00:05:37.440> previous
we've done a trial all the previous
we've done a trial all the previous
trials<00:05:38.000> were<00:05:38.160> positive<00:05:38.479> and<00:05:38.560> we<00:05:38.639> know<00:05:38.800> this
trials were positive and we know this
trials were positive and we know this
one's<00:05:39.199> going<00:05:39.280> to<00:05:39.360> be<00:05:39.520> two<00:05:39.840> that<00:05:40.000> should<00:05:40.160> always
one's going to be two that should always
one's going to be two that should always
ring<00:05:40.479> alarm<00:05:40.800> bells<00:05:41.039> right<00:05:41.280> because<00:05:41.520> if<00:05:41.680> you
ring alarm bells right because if you
ring alarm bells right because if you
already<00:05:42.400> know<00:05:42.560> the<00:05:42.720> answer<00:05:43.039> to<00:05:43.120> your<00:05:43.280> trial
already know the answer to your trial
already know the answer to your trial
you<00:05:43.600> shouldn't<00:05:43.840> be<00:05:43.919> doing<00:05:44.160> one<00:05:44.400> either<00:05:44.880> uh
you shouldn't be doing one either uh
you shouldn't be doing one either uh
you've<00:05:45.280> rigged<00:05:45.600> it<00:05:45.759> by<00:05:45.919> design<00:05:46.560> or<00:05:47.120> uh<00:05:47.440> you've
you've rigged it by design or uh you've
you've rigged it by design or uh you've
got<00:05:47.759> enough<00:05:47.919> data<00:05:48.160> so<00:05:48.320> there's<00:05:48.479> no<00:05:48.639> need<00:05:48.800> to
got enough data so there's no need to
got enough data so there's no need to
randomize<00:05:49.360> people<00:05:49.600> anymore<00:05:50.080> so<00:05:50.240> this<00:05:50.400> is<00:05:50.479> what
randomize people anymore so this is what
randomize people anymore so this is what
they<00:05:50.720> were<00:05:50.800> going<00:05:50.880> to<00:05:50.960> do<00:05:51.360> in<00:05:51.440> their<00:05:51.600> trial
they were going to do in their trial
they were going to do in their trial
they<00:05:52.479> were<00:05:52.639> taking<00:05:52.960> 3<00:05:53.440> 000<00:05:53.919> children<00:05:54.639> they
they were taking 3 000 children they
they were taking 3 000 children they
were<00:05:54.880> going<00:05:54.960> to<00:05:55.039> give<00:05:55.199> them<00:05:55.440> all<00:05:55.840> these<00:05:56.080> huge
were going to give them all these huge
were going to give them all these huge
fish<00:05:56.560> oil<00:05:56.800> pills<00:05:57.120> six<00:05:57.360> of<00:05:57.440> them<00:05:57.600> a<00:05:57.680> day<00:05:58.400> and
fish oil pills six of them a day and
fish oil pills six of them a day and
then<00:05:58.800> a<00:05:58.960> year<00:05:59.120> later<00:05:59.360> they<00:05:59.520> were<00:05:59.600> going<00:05:59.680> to
then a year later they were going to
then a year later they were going to
measure<00:06:00.000> their<00:06:00.160> school<00:06:00.479> exam<00:06:00.720> performance
measure their school exam performance
measure their school exam performance
and<00:06:01.280> compare
and compare
and compare
their<00:06:02.560> exam<00:06:02.800> performance<00:06:03.199> against<00:06:03.440> what<00:06:03.600> they
their exam performance against what they
their exam performance against what they
predicted<00:06:04.319> their<00:06:04.479> exam<00:06:04.720> performance<00:06:05.280> would
predicted their exam performance would
predicted their exam performance would
have<00:06:05.680> been<00:06:06.080> if<00:06:06.319> they<00:06:06.479> hadn't<00:06:06.800> had<00:06:06.960> the<00:06:07.120> pills
have been if they hadn't had the pills
have been if they hadn't had the pills
now<00:06:08.880> can<00:06:09.039> anybody<00:06:09.520> spot<00:06:09.840> a<00:06:10.160> flaw<00:06:10.720> in<00:06:10.880> this
now can anybody spot a flaw in this
now can anybody spot a flaw in this
design
design
design
and<00:06:12.240> no<00:06:12.639> professors<00:06:13.120> of<00:06:13.199> clinical<00:06:13.520> trial
and no professors of clinical trial
and no professors of clinical trial
methodology<00:06:14.560> are<00:06:14.720> allowed<00:06:14.960> to<00:06:15.120> answer<00:06:15.440> this
methodology are allowed to answer this
methodology are allowed to answer this
question<00:06:16.479> so<00:06:16.639> there's<00:06:16.800> no<00:06:16.960> control<00:06:17.440> okay
question so there's no control okay
question so there's no control okay
there's<00:06:17.840> no<00:06:18.000> control<00:06:18.240> group<00:06:18.400> but<00:06:18.479> that<00:06:18.560> sounds
there's no control group but that sounds
there's no control group but that sounds
really<00:06:19.039> techy<00:06:19.440> right<00:06:19.759> that<00:06:19.919> sounds<00:06:20.160> really<00:06:20.400> no
really techy right that sounds really no
really techy right that sounds really no
that's<00:06:20.800> a<00:06:20.880> technical<00:06:21.280> term<00:06:21.840> the<00:06:22.080> the<00:06:22.240> kids<00:06:22.479> got
that's a technical term the the kids got
that's a technical term the the kids got
the<00:06:22.720> pills<00:06:22.960> and<00:06:23.039> then<00:06:23.120> their<00:06:23.280> performance
the pills and then their performance
the pills and then their performance
improved<00:06:24.160> what<00:06:24.400> else<00:06:24.560> could<00:06:24.720> it<00:06:24.800> possibly<00:06:25.199> be
improved what else could it possibly be
improved what else could it possibly be
if<00:06:25.520> it<00:06:25.600> wasn't<00:06:25.840> the<00:06:26.000> pills
if it wasn't the pills
if it wasn't the pills
they<00:06:28.080> got<00:06:28.319> older<00:06:28.560> okay<00:06:28.800> we<00:06:28.880> all<00:06:29.039> develop<00:06:29.520> over
they got older okay we all develop over
they got older okay we all develop over
time<00:06:30.240> and<00:06:30.400> of<00:06:30.479> course<00:06:30.800> also<00:06:31.039> there's<00:06:31.199> the
time and of course also there's the
time and of course also there's the
placebo<00:06:31.919> effect<00:06:32.400> the<00:06:32.479> placebo<00:06:32.800> effect<00:06:33.039> is<00:06:33.120> one
placebo effect the placebo effect is one
placebo effect the placebo effect is one
of<00:06:33.280> those<00:06:33.440> fascinating<00:06:33.919> things<00:06:34.160> in<00:06:34.240> the<00:06:34.319> whole
of those fascinating things in the whole
of those fascinating things in the whole
of<00:06:34.639> medicine<00:06:34.960> it's<00:06:35.120> not<00:06:35.280> just<00:06:35.440> about<00:06:35.600> taking<00:06:35.840> a
of medicine it's not just about taking a
of medicine it's not just about taking a
pill<00:06:36.160> and<00:06:36.319> your<00:06:36.400> performance<00:06:36.880> and<00:06:36.960> your<00:06:37.039> pain
pill and your performance and your pain
pill and your performance and your pain
getting<00:06:37.600> better<00:06:38.080> it's<00:06:38.240> about<00:06:38.479> our<00:06:38.639> beliefs
getting better it's about our beliefs
getting better it's about our beliefs
and<00:06:39.199> expectations<00:06:39.840> it's<00:06:40.000> about<00:06:40.160> the<00:06:40.240> cultural
and expectations it's about the cultural
and expectations it's about the cultural
meaning<00:06:41.120> of<00:06:41.280> a<00:06:41.360> treatment<00:06:41.680> and<00:06:41.759> this<00:06:41.919> has<00:06:42.000> been
meaning of a treatment and this has been
meaning of a treatment and this has been
demonstrated<00:06:42.880> in<00:06:42.960> a<00:06:43.039> whole<00:06:43.280> raft<00:06:43.680> of
demonstrated in a whole raft of
demonstrated in a whole raft of
fascinating<00:06:44.240> studies<00:06:44.560> comparing<00:06:45.199> one<00:06:45.520> kind
fascinating studies comparing one kind
fascinating studies comparing one kind
of<00:06:46.319> placebo<00:06:46.800> against<00:06:47.120> another<00:06:47.440> so<00:06:47.600> we<00:06:47.680> know
of placebo against another so we know
of placebo against another so we know
for<00:06:48.000> example<00:06:48.319> that<00:06:48.639> two<00:06:48.800> sugar<00:06:49.120> pills<00:06:49.360> a<00:06:49.440> day
for example that two sugar pills a day
for example that two sugar pills a day
are<00:06:49.759> a<00:06:49.840> more<00:06:50.080> effective<00:06:50.479> treatment<00:06:51.039> for
are a more effective treatment for
are a more effective treatment for
getting<00:06:51.440> rid<00:06:51.600> of<00:06:51.680> gastric<00:06:52.080> ulcers<00:06:52.720> than<00:06:53.039> one
getting rid of gastric ulcers than one
getting rid of gastric ulcers than one
sugar<00:06:53.520> pill<00:06:53.680> a<00:06:53.759> day<00:06:53.919> two<00:06:54.080> sugar<00:06:54.319> pills<00:06:54.560> a<00:06:54.639> day
sugar pill a day two sugar pills a day
sugar pill a day two sugar pills a day
beats<00:06:55.039> one<00:06:55.199> sugar<00:06:55.440> pill<00:06:55.600> a<00:06:55.680> day<00:06:55.919> and<00:06:56.000> that's<00:06:56.240> an
beats one sugar pill a day and that's an
beats one sugar pill a day and that's an
outrageous<00:06:56.960> and<00:06:57.120> ridiculous<00:06:57.520> finding<00:06:57.759> but
outrageous and ridiculous finding but
outrageous and ridiculous finding but
it's<00:06:58.080> true<00:06:58.639> we<00:06:58.800> know<00:06:58.960> from<00:06:59.120> three<00:06:59.280> different
it's true we know from three different
it's true we know from three different
studies<00:06:59.840> on<00:06:59.919> three<00:07:00.080> different<00:07:00.319> types<00:07:00.560> of<00:07:00.720> pain
studies on three different types of pain
studies on three different types of pain
that<00:07:01.039> a<00:07:01.120> saltwater<00:07:01.599> injection<00:07:01.919> is<00:07:02.000> a<00:07:02.080> more
that a saltwater injection is a more
that a saltwater injection is a more
effective<00:07:02.720> treatment<00:07:03.120> for<00:07:03.280> pain
effective treatment for pain
effective treatment for pain
than<00:07:04.400> taking<00:07:04.720> a<00:07:04.800> sugar<00:07:05.120> pill<00:07:05.360> taking<00:07:05.520> a<00:07:05.680> dummy
than taking a sugar pill taking a dummy
than taking a sugar pill taking a dummy
pill<00:07:06.080> that<00:07:06.240> has<00:07:06.400> no<00:07:06.560> medicine<00:07:06.960> in<00:07:07.039> it<00:07:07.360> not
pill that has no medicine in it not
pill that has no medicine in it not
because<00:07:07.759> the<00:07:07.919> injection<00:07:08.319> or<00:07:08.400> the<00:07:08.479> pill<00:07:08.639> do
because the injection or the pill do
because the injection or the pill do
anything<00:07:09.120> physically<00:07:09.520> to<00:07:09.599> the<00:07:09.680> body<00:07:10.160> but
anything physically to the body but
anything physically to the body but
because<00:07:10.560> an<00:07:10.639> injection<00:07:11.039> feels<00:07:11.280> like<00:07:11.440> a<00:07:11.520> much
because an injection feels like a much
because an injection feels like a much
more<00:07:12.000> dramatic<00:07:12.880> intervention<00:07:13.520> so<00:07:13.680> we<00:07:13.919> know
more dramatic intervention so we know
more dramatic intervention so we know
that<00:07:14.800> our<00:07:14.880> beliefs<00:07:15.280> and<00:07:15.440> expectations<00:07:16.080> can<00:07:16.240> be
that our beliefs and expectations can be
that our beliefs and expectations can be
manipulated<00:07:17.039> which<00:07:17.199> is<00:07:17.360> why<00:07:17.599> we<00:07:17.759> do<00:07:18.160> trials
manipulated which is why we do trials
manipulated which is why we do trials
where<00:07:18.639> we<00:07:18.800> control
where we control
where we control
against<00:07:20.400> a<00:07:20.560> placebo<00:07:21.039> where<00:07:21.280> one<00:07:21.520> half<00:07:21.759> of<00:07:21.840> the
against a placebo where one half of the
against a placebo where one half of the
people<00:07:22.400> get<00:07:22.560> the<00:07:22.639> real<00:07:22.800> treatment<00:07:23.199> and<00:07:23.280> the
people get the real treatment and the
people get the real treatment and the
other<00:07:23.520> half<00:07:23.840> get<00:07:24.240> placebo
other half get placebo
other half get placebo
but<00:07:25.759> that's<00:07:26.160> not<00:07:26.800> enough
but that's not enough
but that's not enough
what<00:07:28.560> i've<00:07:28.639> just<00:07:28.800> shown<00:07:29.039> you<00:07:29.280> are<00:07:29.440> examples<00:07:29.840> of
what i've just shown you are examples of
what i've just shown you are examples of
the<00:07:30.000> very<00:07:30.240> simple<00:07:30.479> and<00:07:30.560> straightforward<00:07:31.360> ways
the very simple and straightforward ways
the very simple and straightforward ways
that<00:07:31.919> journalists<00:07:32.560> and<00:07:32.720> food<00:07:32.880> supplement
that journalists and food supplement
that journalists and food supplement
pill<00:07:33.599> peddlers<00:07:34.160> and<00:07:34.560> naturopaths<00:07:35.360> can
pill peddlers and naturopaths can
pill peddlers and naturopaths can
distort<00:07:36.000> evidence<00:07:36.319> for<00:07:36.479> their<00:07:36.720> own<00:07:37.199> purposes
distort evidence for their own purposes
distort evidence for their own purposes
what<00:07:38.319> i<00:07:38.479> find<00:07:38.800> really<00:07:39.199> fascinating<00:07:40.319> is<00:07:40.479> that
what i find really fascinating is that
what i find really fascinating is that
the<00:07:40.720> pharmaceutical<00:07:41.440> industry<00:07:42.000> use<00:07:42.319> exactly
the pharmaceutical industry use exactly
the pharmaceutical industry use exactly
the<00:07:42.800> same<00:07:43.120> kinds<00:07:43.440> of<00:07:43.520> tricks<00:07:44.080> and<00:07:44.240> devices<00:07:45.120> but
the same kinds of tricks and devices but
the same kinds of tricks and devices but
slightly<00:07:45.680> more<00:07:45.840> sophisticated<00:07:46.639> versions<00:07:47.120> of
slightly more sophisticated versions of
slightly more sophisticated versions of
them<00:07:47.840> in<00:07:48.000> order<00:07:48.240> to<00:07:48.400> distort<00:07:48.720> the<00:07:48.880> evidence
them in order to distort the evidence
them in order to distort the evidence
that<00:07:49.440> they<00:07:49.599> give<00:07:49.840> to<00:07:50.000> doctors<00:07:50.560> and<00:07:50.639> patients
that they give to doctors and patients
that they give to doctors and patients
in<00:07:51.120> which<00:07:51.280> we<00:07:51.440> use<00:07:51.599> to<00:07:51.759> make<00:07:51.919> vitally
in which we use to make vitally
in which we use to make vitally
important<00:07:52.639> decisions<00:07:53.520> so<00:07:54.000> firstly<00:07:54.720> trials
important decisions so firstly trials
important decisions so firstly trials
against<00:07:55.440> placebo<00:07:56.240> everybody<00:07:56.560> thinks<00:07:56.800> they
against placebo everybody thinks they
against placebo everybody thinks they
know<00:07:57.120> that<00:07:57.280> a<00:07:57.360> trial<00:07:57.599> should<00:07:57.759> be<00:07:57.919> a<00:07:58.000> comparison
know that a trial should be a comparison
know that a trial should be a comparison
of<00:07:58.639> your<00:07:58.800> new<00:07:58.960> drug<00:07:59.199> against<00:07:59.440> placebo<00:07:59.840> but
of your new drug against placebo but
of your new drug against placebo but
actually<00:08:00.400> in<00:08:00.560> a<00:08:00.560> lot<00:08:00.720> of<00:08:00.800> situations<00:08:01.280> that's
actually in a lot of situations that's
actually in a lot of situations that's
wrong<00:08:01.759> because<00:08:02.000> often<00:08:02.400> we<00:08:02.560> already<00:08:02.800> have<00:08:03.039> a
wrong because often we already have a
wrong because often we already have a
very<00:08:03.360> good<00:08:03.520> treatment<00:08:03.840> that<00:08:04.080> is<00:08:04.160> currently
very good treatment that is currently
very good treatment that is currently
available<00:08:05.039> so<00:08:05.199> we<00:08:05.360> don't<00:08:05.440> want<00:08:05.520> to<00:08:05.599> know<00:08:05.759> that
available so we don't want to know that
available so we don't want to know that
your<00:08:06.160> alternative<00:08:06.720> new<00:08:06.879> treatment<00:08:07.440> is<00:08:07.599> better
your alternative new treatment is better
your alternative new treatment is better
than<00:08:08.080> nothing<00:08:08.639> we<00:08:08.800> want<00:08:08.879> to<00:08:08.960> know<00:08:09.120> that<00:08:09.199> it's
than nothing we want to know that it's
than nothing we want to know that it's
better<00:08:09.520> than<00:08:09.599> the<00:08:09.680> best<00:08:10.000> currently<00:08:10.319> available
better than the best currently available
better than the best currently available
treatment<00:08:11.039> that<00:08:11.199> we<00:08:11.360> have<00:08:11.840> and<00:08:12.080> yet
treatment that we have and yet
treatment that we have and yet
repeatedly<00:08:13.280> you<00:08:13.440> consistently<00:08:14.000> see<00:08:14.240> people
repeatedly you consistently see people
repeatedly you consistently see people
doing<00:08:14.720> trials<00:08:15.120> still<00:08:15.440> against<00:08:15.759> placebo<00:08:16.400> and
doing trials still against placebo and
doing trials still against placebo and
you<00:08:16.560> can<00:08:16.720> get<00:08:16.879> licensed<00:08:17.360> to<00:08:17.440> bring<00:08:17.599> your<00:08:17.759> drug
you can get licensed to bring your drug
you can get licensed to bring your drug
to<00:08:18.080> market<00:08:18.400> with<00:08:18.639> only<00:08:18.879> data<00:08:19.199> showing<00:08:19.520> that
to market with only data showing that
to market with only data showing that
it's<00:08:19.840> better<00:08:20.160> than<00:08:20.560> nothing<00:08:20.960> which<00:08:21.199> is
it's better than nothing which is
it's better than nothing which is
useless<00:08:21.759> for<00:08:21.919> a<00:08:22.000> doctor<00:08:22.319> like<00:08:22.560> me<00:08:22.879> trying<00:08:23.039> to
useless for a doctor like me trying to
useless for a doctor like me trying to
make<00:08:23.280> a<00:08:23.360> decision<00:08:24.080> but<00:08:24.240> that's<00:08:24.479> not<00:08:24.560> the<00:08:24.720> only
make a decision but that's not the only
make a decision but that's not the only
way<00:08:25.039> that<00:08:25.199> you<00:08:25.280> can<00:08:25.440> rig<00:08:25.599> your<00:08:25.840> data<00:08:26.160> you<00:08:26.319> can
way that you can rig your data you can
way that you can rig your data you can
also<00:08:26.639> rig<00:08:26.879> your<00:08:27.039> data<00:08:27.759> by<00:08:28.080> making<00:08:28.319> the<00:08:28.479> thing
also rig your data by making the thing
also rig your data by making the thing
that<00:08:28.720> you<00:08:28.879> compare<00:08:29.360> your<00:08:29.520> new<00:08:29.759> drug<00:08:29.919> against
that you compare your new drug against
that you compare your new drug against
really<00:08:30.800> rubbish<00:08:31.520> you<00:08:31.680> can<00:08:31.919> give<00:08:32.080> the
really rubbish you can give the
really rubbish you can give the
competing<00:08:32.719> drug<00:08:33.120> in<00:08:33.360> too<00:08:33.599> lower<00:08:33.839> dose<00:08:34.240> so<00:08:34.399> that
competing drug in too lower dose so that
competing drug in too lower dose so that
people<00:08:34.719> aren't<00:08:34.880> properly<00:08:35.279> treated<00:08:35.839> you<00:08:36.000> can
people aren't properly treated you can
people aren't properly treated you can
give<00:08:36.320> the<00:08:36.399> competing<00:08:36.719> drug<00:08:36.959> in<00:08:37.039> two<00:08:37.279> higher
give the competing drug in two higher
give the competing drug in two higher
dose<00:08:38.080> so<00:08:38.240> that<00:08:38.399> people<00:08:38.640> get<00:08:38.880> side<00:08:39.120> effects<00:08:39.440> and
dose so that people get side effects and
dose so that people get side effects and
this<00:08:39.760> is<00:08:39.839> exactly<00:08:40.240> what<00:08:40.399> happened<00:08:40.880> with
this is exactly what happened with
this is exactly what happened with
antipsychotic<00:08:41.839> medication<00:08:42.320> for
antipsychotic medication for
antipsychotic medication for
schizophrenia
schizophrenia
schizophrenia
20<00:08:44.320> years<00:08:44.480> ago<00:08:44.880> a<00:08:45.120> new<00:08:45.279> generation<00:08:45.680> of
20 years ago a new generation of
20 years ago a new generation of
antipsychotic<00:08:46.560> drugs<00:08:46.800> were<00:08:46.880> brought<00:08:47.200> in<00:08:47.360> and
antipsychotic drugs were brought in and
antipsychotic drugs were brought in and
the<00:08:47.519> promise<00:08:47.920> was<00:08:48.399> that<00:08:48.560> they<00:08:48.720> would<00:08:48.880> have
the promise was that they would have
the promise was that they would have
fewer<00:08:49.360> side<00:08:49.600> effects<00:08:49.920> so<00:08:50.080> people<00:08:50.320> set<00:08:50.480> about
fewer side effects so people set about
fewer side effects so people set about
doing<00:08:50.959> trials<00:08:51.279> of<00:08:51.360> these<00:08:51.519> new<00:08:51.680> drugs<00:08:52.160> against
doing trials of these new drugs against
doing trials of these new drugs against
the<00:08:52.640> old<00:08:52.800> drugs<00:08:53.279> but<00:08:53.440> they<00:08:53.600> gave<00:08:53.760> the<00:08:53.920> old
the old drugs but they gave the old
the old drugs but they gave the old
drugs<00:08:54.399> in<00:08:54.560> ridiculously<00:08:55.360> high<00:08:55.519> doses<00:08:56.000> 20
drugs in ridiculously high doses 20
drugs in ridiculously high doses 20
milligrams<00:08:56.720> a<00:08:56.800> day<00:08:56.959> of<00:08:57.040> haloperidol<00:08:58.000> and<00:08:58.160> it's
milligrams a day of haloperidol and it's
milligrams a day of haloperidol and it's
a<00:08:58.480> foregone<00:08:58.880> conclusion<00:08:59.360> if<00:08:59.440> you<00:08:59.600> give<00:08:59.760> a<00:09:00.000> drug
a foregone conclusion if you give a drug
a foregone conclusion if you give a drug
at<00:09:00.640> that<00:09:00.880> higher<00:09:01.120> dose<00:09:01.600> that<00:09:01.760> it<00:09:01.839> will<00:09:02.000> have
at that higher dose that it will have
at that higher dose that it will have
more<00:09:02.320> side<00:09:02.480> effects<00:09:02.800> and<00:09:02.959> that<00:09:03.040> your<00:09:03.200> new<00:09:03.360> drug
more side effects and that your new drug
more side effects and that your new drug
will<00:09:03.680> look<00:09:03.920> better<00:09:04.399> ten<00:09:04.560> years<00:09:04.720> ago<00:09:04.959> history
will look better ten years ago history
will look better ten years ago history
repeated<00:09:05.680> itself<00:09:06.000> interestingly<00:09:06.640> when
repeated itself interestingly when
repeated itself interestingly when
risperidone<00:09:07.519> which<00:09:07.680> was<00:09:07.839> the<00:09:07.920> first<00:09:08.160> of<00:09:08.240> the
risperidone which was the first of the
risperidone which was the first of the
new<00:09:08.560> generation<00:09:08.959> antipsychotic<00:09:09.680> drugs<00:09:10.080> came
new generation antipsychotic drugs came
new generation antipsychotic drugs came
off<00:09:10.560> copyright<00:09:11.120> so<00:09:11.279> anybody<00:09:11.600> could<00:09:11.680> make
off copyright so anybody could make
off copyright so anybody could make
copies<00:09:12.399> everybody<00:09:12.720> wanted<00:09:12.880> to<00:09:12.959> show<00:09:13.120> that
copies everybody wanted to show that
copies everybody wanted to show that
their<00:09:13.440> drug<00:09:13.600> was<00:09:13.760> better<00:09:14.000> than<00:09:14.080> risperidone
their drug was better than risperidone
their drug was better than risperidone
so<00:09:14.880> you<00:09:14.959> see<00:09:15.120> a<00:09:15.200> bunch<00:09:15.440> of<00:09:15.519> trials<00:09:15.839> comparing
so you see a bunch of trials comparing
so you see a bunch of trials comparing
new<00:09:16.560> antipsychotic<00:09:17.200> drugs<00:09:17.519> against
new antipsychotic drugs against
new antipsychotic drugs against
risperidone<00:09:18.399> at<00:09:18.560> eight<00:09:18.720> milligrams<00:09:19.200> a<00:09:19.279> day
risperidone at eight milligrams a day
risperidone at eight milligrams a day
again<00:09:20.160> not<00:09:20.320> an<00:09:20.480> insane<00:09:20.959> dose<00:09:21.200> not<00:09:21.360> an<00:09:21.440> illegal
again not an insane dose not an illegal
again not an insane dose not an illegal
dose<00:09:22.160> but<00:09:22.399> very<00:09:22.640> much<00:09:22.800> at<00:09:22.959> the<00:09:23.040> high<00:09:23.120> end<00:09:23.279> of
dose but very much at the high end of
dose but very much at the high end of
normal<00:09:23.600> until<00:09:23.839> you're<00:09:24.160> bound<00:09:24.480> to<00:09:24.640> make<00:09:24.800> your
normal until you're bound to make your
normal until you're bound to make your
new<00:09:25.200> drug<00:09:25.680> look<00:09:26.240> better<00:09:27.040> and<00:09:27.120> so<00:09:27.279> it's<00:09:27.440> no
new drug look better and so it's no
new drug look better and so it's no
surprise<00:09:28.560> that<00:09:28.720> overall<00:09:29.760> industry-funded
surprise that overall industry-funded
surprise that overall industry-funded
trials<00:09:31.040> are<00:09:31.200> four<00:09:31.440> times<00:09:31.839> more<00:09:32.000> likely<00:09:32.480> to
trials are four times more likely to
trials are four times more likely to
give<00:09:32.800> a<00:09:32.880> positive<00:09:33.200> result<00:09:33.839> than
give a positive result than
give a positive result than
independently<00:09:34.720> sponsored<00:09:35.200> trials
independently sponsored trials
independently sponsored trials
but
but
but
and<00:09:38.800> it's<00:09:38.959> a<00:09:39.040> big<00:09:39.200> but
it<00:09:42.480> turns<00:09:42.880> out<00:09:43.279> when<00:09:43.440> you<00:09:43.680> look<00:09:44.000> at<00:09:44.080> the
it turns out when you look at the
it turns out when you look at the
methods<00:09:44.800> used<00:09:45.440> by<00:09:45.680> industry<00:09:46.080> funded<00:09:46.480> trials
methods used by industry funded trials
methods used by industry funded trials
that<00:09:47.200> they're<00:09:47.440> actually<00:09:48.000> better<00:09:48.800> than
that they're actually better than
that they're actually better than
independently<00:09:49.680> sponsored<00:09:50.080> trials<00:09:50.800> and<00:09:51.040> yet
independently sponsored trials and yet
independently sponsored trials and yet
they<00:09:51.440> always<00:09:51.760> manage<00:09:52.000> to<00:09:52.160> get<00:09:52.320> the<00:09:52.399> result
they always manage to get the result
they always manage to get the result
that<00:09:52.880> they<00:09:53.040> want<00:09:53.600> so<00:09:53.839> how<00:09:54.000> does<00:09:54.160> this<00:09:54.399> work
that they want so how does this work
that they want so how does this work
how<00:09:55.920> can<00:09:56.080> we<00:09:56.320> explain<00:09:56.720> this<00:09:57.040> strange
how can we explain this strange
how can we explain this strange
phenomenon
phenomenon
phenomenon
well<00:09:58.880> it<00:09:58.959> turns<00:09:59.279> out<00:09:59.680> that<00:09:59.839> what<00:10:00.080> happens<00:10:00.480> is
well it turns out that what happens is
well it turns out that what happens is
the<00:10:01.120> negative<00:10:01.519> data<00:10:01.839> goes<00:10:02.080> missing<00:10:02.320> in<00:10:02.399> action
the negative data goes missing in action
the negative data goes missing in action
it's<00:10:02.800> withheld<00:10:03.200> from<00:10:03.360> doctors<00:10:03.600> and<00:10:03.680> patients
it's withheld from doctors and patients
it's withheld from doctors and patients
and<00:10:04.240> this<00:10:04.560> is<00:10:04.720> the<00:10:04.800> most<00:10:05.040> important<00:10:05.600> aspect<00:10:06.160> of
and this is the most important aspect of
and this is the most important aspect of
the<00:10:06.320> whole<00:10:06.560> story<00:10:06.880> it's<00:10:07.040> at<00:10:07.120> the<00:10:07.279> top<00:10:07.519> of<00:10:07.680> the
the whole story it's at the top of the
the whole story it's at the top of the
pyramid<00:10:08.160> of<00:10:08.240> evidence<00:10:08.640> we<00:10:08.720> need<00:10:08.880> to<00:10:08.959> have<00:10:09.440> all
pyramid of evidence we need to have all
pyramid of evidence we need to have all
of<00:10:09.680> the<00:10:09.839> data<00:10:10.399> on<00:10:10.560> a<00:10:10.640> particular<00:10:11.120> treatment<00:10:11.680> to
of the data on a particular treatment to
of the data on a particular treatment to
know<00:10:12.080> whether<00:10:12.399> or<00:10:12.480> not<00:10:12.880> it<00:10:13.040> really<00:10:13.279> is
know whether or not it really is
know whether or not it really is
effective<00:10:14.079> and<00:10:14.240> there<00:10:14.399> are<00:10:14.480> two<00:10:14.720> different
effective and there are two different
effective and there are two different
ways<00:10:15.200> that<00:10:15.279> you<00:10:15.360> can<00:10:15.519> spot<00:10:15.760> whether<00:10:16.079> some<00:10:16.240> data
ways that you can spot whether some data
ways that you can spot whether some data
has<00:10:16.720> gone<00:10:16.959> missing<00:10:17.279> in<00:10:17.440> action<00:10:17.920> you<00:10:18.079> can<00:10:18.160> use
has gone missing in action you can use
has gone missing in action you can use
statistics<00:10:19.040> or<00:10:19.200> you<00:10:19.279> can<00:10:19.360> use<00:10:19.600> stories<00:10:20.000> i
statistics or you can use stories i
statistics or you can use stories i
personally<00:10:20.480> prefer<00:10:20.720> statistics<00:10:21.200> so<00:10:21.279> that's
personally prefer statistics so that's
personally prefer statistics so that's
what<00:10:21.519> i'm<00:10:21.680> going<00:10:21.760> to<00:10:21.839> do<00:10:22.000> first<00:10:22.480> this<00:10:22.720> is
what i'm going to do first this is
what i'm going to do first this is
something<00:10:23.040> called<00:10:23.200> a<00:10:23.360> funnel<00:10:23.680> plot<00:10:24.000> and<00:10:24.160> a
something called a funnel plot and a
something called a funnel plot and a
funnel<00:10:24.480> plot<00:10:24.640> is<00:10:24.720> a<00:10:24.800> very<00:10:24.959> clever<00:10:25.200> way<00:10:25.279> of
funnel plot is a very clever way of
funnel plot is a very clever way of
spotting<00:10:26.000> if<00:10:26.240> small<00:10:26.959> negative<00:10:27.440> trials<00:10:27.839> have
spotting if small negative trials have
spotting if small negative trials have
disappeared<00:10:28.399> have<00:10:28.480> gone<00:10:28.720> missing<00:10:28.959> in<00:10:29.120> action
disappeared have gone missing in action
disappeared have gone missing in action
so<00:10:29.680> this<00:10:29.839> is<00:10:29.920> a<00:10:30.000> graph<00:10:30.320> of<00:10:30.480> all<00:10:30.640> of<00:10:30.720> the<00:10:30.880> trials
so this is a graph of all of the trials
so this is a graph of all of the trials
that<00:10:31.360> have<00:10:31.519> been<00:10:31.600> done<00:10:31.839> on<00:10:31.920> a<00:10:32.079> particular
that have been done on a particular
that have been done on a particular
treatment<00:10:33.200> and<00:10:33.440> as<00:10:33.600> you<00:10:33.760> go<00:10:33.920> up<00:10:34.160> towards<00:10:34.480> the
treatment and as you go up towards the
treatment and as you go up towards the
top<00:10:34.720> of<00:10:34.800> the<00:10:34.880> graph<00:10:35.440> what<00:10:35.600> you<00:10:35.760> see<00:10:35.920> is<00:10:36.160> each
top of the graph what you see is each
top of the graph what you see is each
dot<00:10:36.640> is<00:10:36.720> a<00:10:36.880> trial<00:10:37.440> and<00:10:37.600> as<00:10:37.760> you<00:10:37.839> go<00:10:38.000> to<00:10:38.079> the<00:10:38.160> top
dot is a trial and as you go to the top
dot is a trial and as you go to the top
those<00:10:38.480> are<00:10:38.560> the<00:10:38.640> bigger<00:10:38.880> child<00:10:39.040> so<00:10:39.200> they've
those are the bigger child so they've
those are the bigger child so they've
got<00:10:39.519> less<00:10:39.760> error<00:10:40.079> in<00:10:40.160> them<00:10:40.320> so<00:10:40.399> they're<00:10:40.560> less
got less error in them so they're less
got less error in them so they're less
likely<00:10:40.959> to<00:10:41.040> be<00:10:41.120> randomly<00:10:41.600> false<00:10:41.920> positives
likely to be randomly false positives
likely to be randomly false positives
randomly<00:10:42.720> false<00:10:43.040> negatives<00:10:43.600> so<00:10:43.760> they<00:10:43.920> all
randomly false negatives so they all
randomly false negatives so they all
cluster<00:10:44.480> together<00:10:44.800> the<00:10:44.880> big<00:10:45.279> trials<00:10:45.680> are
cluster together the big trials are
cluster together the big trials are
closer<00:10:46.160> to<00:10:46.320> the<00:10:46.480> true<00:10:46.880> answer<00:10:47.680> then<00:10:48.000> as<00:10:48.160> you<00:10:48.240> go
closer to the true answer then as you go
closer to the true answer then as you go
further<00:10:48.720> down<00:10:48.959> at<00:10:49.040> the<00:10:49.120> bottom<00:10:49.440> what<00:10:49.600> you<00:10:49.680> can
further down at the bottom what you can
further down at the bottom what you can
see<00:10:50.079> is<00:10:50.399> over<00:10:50.640> on<00:10:50.720> this<00:10:50.880> side<00:10:51.200> spurious<00:10:51.600> false
see is over on this side spurious false
see is over on this side spurious false
negatives<00:10:52.240> and<00:10:52.320> over<00:10:52.480> on<00:10:52.560> this<00:10:52.720> side<00:10:52.959> the
negatives and over on this side the
negatives and over on this side the
spurious<00:10:53.519> false<00:10:54.000> positives<00:10:55.040> if<00:10:55.519> there<00:10:55.680> is
spurious false positives if there is
spurious false positives if there is
publication<00:10:56.480> bias<00:10:56.880> if<00:10:57.279> small<00:10:57.760> negative
publication bias if small negative
publication bias if small negative
trials<00:10:58.399> have<00:10:58.480> gone<00:10:58.640> missing<00:10:58.959> in<00:10:59.040> action<00:10:59.600> you
trials have gone missing in action you
trials have gone missing in action you
can<00:10:59.920> see<00:11:00.079> it<00:11:00.240> on<00:11:00.320> one<00:11:00.399> of<00:11:00.480> these<00:11:00.640> graphs<00:11:00.959> so<00:11:01.120> you
can see it on one of these graphs so you
can see it on one of these graphs so you
can<00:11:01.360> see<00:11:01.600> here<00:11:02.000> that<00:11:02.160> the<00:11:02.320> small<00:11:02.720> negative
can see here that the small negative
can see here that the small negative
trials<00:11:03.440> that<00:11:03.600> should<00:11:03.760> be<00:11:03.839> on<00:11:03.920> the<00:11:04.000> bottom<00:11:04.320> left
trials that should be on the bottom left
trials that should be on the bottom left
have<00:11:04.880> disappeared<00:11:05.760> this<00:11:06.000> is<00:11:06.079> a<00:11:06.160> graph
have disappeared this is a graph
have disappeared this is a graph
demonstrating<00:11:06.959> the<00:11:07.040> presence<00:11:07.440> of
demonstrating the presence of
demonstrating the presence of
publication<00:11:08.160> bias<00:11:08.720> in<00:11:08.880> studies<00:11:09.600> of
publication bias in studies of
publication bias in studies of
publication<00:11:10.560> bias<00:11:10.959> and<00:11:11.120> i<00:11:11.200> think<00:11:11.360> that's<00:11:11.519> the
publication bias and i think that's the
publication bias and i think that's the
funniest<00:11:12.000> epidemiology<00:11:12.640> joke<00:11:12.880> that<00:11:12.959> you<00:11:13.120> will
funniest epidemiology joke that you will
funniest epidemiology joke that you will
ever<00:11:13.760> hear
ever hear
ever hear
that's<00:11:15.200> how<00:11:15.360> you<00:11:15.440> can<00:11:15.519> prove<00:11:15.760> it
that's how you can prove it
that's how you can prove it
statistically<00:11:16.959> but<00:11:17.120> what<00:11:17.360> about<00:11:17.600> stories
statistically but what about stories
statistically but what about stories
well<00:11:18.480> they're<00:11:18.640> heinous<00:11:19.200> they<00:11:19.360> really<00:11:19.680> are
well they're heinous they really are
well they're heinous they really are
this<00:11:20.480> is<00:11:20.640> a<00:11:20.720> drug<00:11:21.040> called<00:11:21.200> roboxetine<00:11:21.839> and
this is a drug called roboxetine and
this is a drug called roboxetine and
this<00:11:22.000> is<00:11:22.079> a<00:11:22.160> drug<00:11:22.399> which<00:11:22.560> i<00:11:22.720> myself<00:11:23.360> have
this is a drug which i myself have
this is a drug which i myself have
prescribed<00:11:24.399> to<00:11:24.560> patients<00:11:25.040> and<00:11:25.120> i'm<00:11:25.200> a<00:11:25.279> very
prescribed to patients and i'm a very
prescribed to patients and i'm a very
nerdy<00:11:25.839> doctor<00:11:26.240> i<00:11:26.320> hope<00:11:26.560> i<00:11:26.640> go<00:11:26.800> out<00:11:26.959> of<00:11:27.040> my<00:11:27.120> way
nerdy doctor i hope i go out of my way
nerdy doctor i hope i go out of my way
to<00:11:27.440> try<00:11:27.600> and<00:11:27.680> read<00:11:28.079> and<00:11:28.240> understand<00:11:28.640> all<00:11:28.800> the
to try and read and understand all the
to try and read and understand all the
literature<00:11:29.360> i<00:11:29.519> read<00:11:29.920> the<00:11:30.079> trials<00:11:30.399> on<00:11:30.480> this
literature i read the trials on this
literature i read the trials on this
they<00:11:30.880> were<00:11:30.959> all<00:11:31.120> positive<00:11:31.600> they<00:11:31.680> were<00:11:31.839> all
they were all positive they were all
they were all positive they were all
well<00:11:32.320> conducted<00:11:32.800> i<00:11:32.959> found<00:11:33.519> no<00:11:33.839> flaw
well conducted i found no flaw
well conducted i found no flaw
unfortunately<00:11:35.760> it<00:11:35.839> turned<00:11:36.160> out
unfortunately it turned out
unfortunately it turned out
that<00:11:37.200> many<00:11:37.440> of<00:11:37.519> these<00:11:37.760> trials<00:11:38.000> were<00:11:38.079> withheld
that many of these trials were withheld
that many of these trials were withheld
in<00:11:38.640> fact<00:11:39.279> 76
in fact 76
in fact 76
of<00:11:41.040> all<00:11:41.200> of<00:11:41.279> the<00:11:41.360> trials<00:11:41.680> that<00:11:41.760> were<00:11:41.920> done<00:11:42.399> on
of all of the trials that were done on
of all of the trials that were done on
this<00:11:42.720> drug<00:11:43.120> were<00:11:43.279> withheld<00:11:43.680> from<00:11:43.839> doctors<00:11:44.160> and
this drug were withheld from doctors and
this drug were withheld from doctors and
patients<00:11:44.720> now<00:11:44.880> if<00:11:45.040> you<00:11:45.200> think<00:11:45.360> about<00:11:45.680> it<00:11:46.000> if<00:11:46.160> i
patients now if you think about it if i
patients now if you think about it if i
toss<00:11:46.720> a<00:11:46.880> coin<00:11:47.440> a<00:11:47.600> hundred<00:11:48.000> times<00:11:48.640> and<00:11:48.800> i'm
toss a coin a hundred times and i'm
toss a coin a hundred times and i'm
allowed<00:11:49.200> to<00:11:49.360> withhold<00:11:49.760> from<00:11:50.000> you<00:11:50.160> the<00:11:50.320> answers
allowed to withhold from you the answers
allowed to withhold from you the answers
half<00:11:51.440> the<00:11:51.680> times<00:11:52.160> then<00:11:52.399> i<00:11:52.560> can<00:11:52.720> convince<00:11:53.200> you
half the times then i can convince you
half the times then i can convince you
that<00:11:53.760> i<00:11:53.920> have<00:11:54.079> a<00:11:54.160> coin<00:11:54.480> with<00:11:54.720> two<00:11:54.959> heads<00:11:55.600> okay
that i have a coin with two heads okay
that i have a coin with two heads okay
if<00:11:56.560> we<00:11:56.800> remove<00:11:57.279> half<00:11:57.519> of<00:11:57.680> the<00:11:57.760> data<00:11:58.320> we<00:11:58.480> can
if we remove half of the data we can
if we remove half of the data we can
never<00:11:58.959> know<00:11:59.120> what<00:11:59.279> the<00:11:59.440> true<00:11:59.760> effect<00:12:00.160> size<00:12:00.640> of
never know what the true effect size of
never know what the true effect size of
these<00:12:00.959> medicines<00:12:01.519> is<00:12:01.920> and<00:12:02.000> this<00:12:02.240> is<00:12:02.320> not<00:12:02.560> an
these medicines is and this is not an
these medicines is and this is not an
isolated<00:12:03.760> story<00:12:04.240> around<00:12:04.560> half<00:12:04.880> of<00:12:04.959> all<00:12:05.120> of<00:12:05.279> the
isolated story around half of all of the
isolated story around half of all of the
trial<00:12:05.920> data<00:12:06.240> on<00:12:06.399> antidepressants<00:12:07.120> has<00:12:07.200> been
trial data on antidepressants has been
trial data on antidepressants has been
withheld<00:12:07.920> but<00:12:08.079> it<00:12:08.160> goes<00:12:08.480> way<00:12:08.880> beyond<00:12:09.200> that<00:12:09.440> the
withheld but it goes way beyond that the
withheld but it goes way beyond that the
nordic<00:12:09.920> cochrane<00:12:10.399> group<00:12:10.639> we're<00:12:10.800> trying<00:12:10.959> to
nordic cochrane group we're trying to
nordic cochrane group we're trying to
get<00:12:11.200> hold<00:12:11.440> of<00:12:11.519> the<00:12:11.600> data<00:12:11.920> on<00:12:12.000> that<00:12:12.160> to<00:12:12.320> bring<00:12:12.480> it
get hold of the data on that to bring it
get hold of the data on that to bring it
all<00:12:12.720> together<00:12:12.959> the<00:12:13.120> cochrane<00:12:13.440> groups<00:12:13.680> are<00:12:13.760> an
all together the cochrane groups are an
all together the cochrane groups are an
international<00:12:14.800> non-profit<00:12:15.440> collaboration
international non-profit collaboration
international non-profit collaboration
that<00:12:16.639> produce<00:12:17.040> systematic<00:12:17.600> reviews<00:12:17.920> of<00:12:18.160> all
that produce systematic reviews of all
that produce systematic reviews of all
of<00:12:18.480> the<00:12:18.560> data<00:12:18.800> that<00:12:18.959> has<00:12:19.120> ever<00:12:19.279> been<00:12:19.360> shown<00:12:19.680> and
of the data that has ever been shown and
of the data that has ever been shown and
they<00:12:19.839> need<00:12:20.000> to<00:12:20.079> have<00:12:20.240> access<00:12:20.800> to<00:12:21.040> all<00:12:21.200> of<00:12:21.279> the
they need to have access to all of the
they need to have access to all of the
trial<00:12:21.760> data
trial data
trial data
but<00:12:22.959> the<00:12:23.120> companies<00:12:24.000> withheld<00:12:24.480> that<00:12:24.639> data
but the companies withheld that data
but the companies withheld that data
from<00:12:25.120> them<00:12:25.760> and<00:12:26.000> so<00:12:26.160> did<00:12:26.320> the<00:12:26.399> european
from them and so did the european
from them and so did the european
medicines<00:12:27.279> agency<00:12:27.760> for<00:12:28.000> three<00:12:28.880> years<00:12:29.360> this<00:12:29.519> is
medicines agency for three years this is
medicines agency for three years this is
a<00:12:29.760> problem<00:12:30.079> that<00:12:30.320> is<00:12:30.399> currently<00:12:31.120> lacking<00:12:31.680> a
a problem that is currently lacking a
a problem that is currently lacking a
solution<00:12:32.560> and<00:12:32.720> to<00:12:32.880> show<00:12:33.120> how<00:12:33.360> big<00:12:33.600> it<00:12:33.680> goes
solution and to show how big it goes
solution and to show how big it goes
this<00:12:34.240> is<00:12:34.399> a<00:12:34.480> drug<00:12:34.720> called<00:12:34.880> tamiflu<00:12:35.360> which
this is a drug called tamiflu which
this is a drug called tamiflu which
governments<00:12:36.000> around<00:12:36.320> the<00:12:36.399> world<00:12:36.639> have<00:12:36.720> spent
governments around the world have spent
governments around the world have spent
billions<00:12:38.079> and<00:12:38.240> billions<00:12:38.959> of<00:12:39.120> dollars<00:12:39.519> on<00:12:40.079> and
billions and billions of dollars on and
billions and billions of dollars on and
they<00:12:40.399> spend<00:12:40.560> that<00:12:40.720> money<00:12:40.959> on<00:12:41.120> the<00:12:41.200> promise
they spend that money on the promise
they spend that money on the promise
that<00:12:41.920> this<00:12:42.160> is<00:12:42.320> a<00:12:42.399> drug<00:12:42.880> which<00:12:43.120> will<00:12:43.279> reduce
that this is a drug which will reduce
that this is a drug which will reduce
the<00:12:43.839> rate<00:12:44.079> of<00:12:44.240> complications<00:12:45.200> with<00:12:45.440> flu<00:12:46.000> we
the rate of complications with flu we
the rate of complications with flu we
already<00:12:46.399> have<00:12:46.560> the<00:12:46.639> data<00:12:46.959> showing<00:12:47.200> that<00:12:47.279> it
already have the data showing that it
already have the data showing that it
reduces<00:12:47.760> the<00:12:47.839> duration<00:12:48.320> of<00:12:48.399> your<00:12:48.560> flu<00:12:48.800> by<00:12:48.959> a
reduces the duration of your flu by a
reduces the duration of your flu by a
few<00:12:49.360> hours<00:12:49.760> but<00:12:49.920> i<00:12:50.000> don't<00:12:50.160> really<00:12:50.320> care<00:12:50.480> about
few hours but i don't really care about
few hours but i don't really care about
that<00:12:50.800> governments<00:12:51.120> don't<00:12:51.279> care<00:12:51.440> about<00:12:51.600> that
that governments don't care about that
that governments don't care about that
i'm<00:12:52.000> very<00:12:52.240> sorry<00:12:52.639> if<00:12:52.720> you<00:12:52.800> have<00:12:52.959> the<00:12:53.120> flu<00:12:53.440> i
i'm very sorry if you have the flu i
i'm very sorry if you have the flu i
know<00:12:53.760> it's<00:12:53.920> horrible<00:12:54.399> but<00:12:54.560> we're<00:12:54.720> not<00:12:54.880> going
know it's horrible but we're not going
know it's horrible but we're not going
to<00:12:55.040> spend<00:12:55.360> billions<00:12:55.760> of<00:12:55.920> dollars<00:12:56.560> trying<00:12:56.720> to
to spend billions of dollars trying to
to spend billions of dollars trying to
reduce<00:12:57.200> the<00:12:57.279> duration<00:12:57.760> of<00:12:57.839> your<00:12:58.000> flu<00:12:58.160> symptoms
reduce the duration of your flu symptoms
reduce the duration of your flu symptoms
by<00:12:58.800> half<00:12:59.120> a<00:12:59.200> day
by half a day
by half a day
we<00:13:00.320> prescribe<00:13:00.800> these<00:13:01.040> drugs<00:13:01.600> we<00:13:01.760> stockpile
we prescribe these drugs we stockpile
we prescribe these drugs we stockpile
them<00:13:02.480> for<00:13:02.639> emergencies<00:13:03.200> on<00:13:03.279> the
them for emergencies on the
them for emergencies on the
understanding<00:13:03.839> they<00:13:03.920> will<00:13:04.000> reduce<00:13:04.320> the
understanding they will reduce the
understanding they will reduce the
number<00:13:04.639> of<00:13:04.720> complications<00:13:05.279> which<00:13:05.440> means
number of complications which means
number of complications which means
pneumonia<00:13:06.480> and<00:13:06.639> which<00:13:06.880> means<00:13:07.200> death<00:13:07.839> the
pneumonia and which means death the
pneumonia and which means death the
infectious<00:13:08.480> diseases<00:13:08.880> cochrane<00:13:09.440> group<00:13:09.760> which
infectious diseases cochrane group which
infectious diseases cochrane group which
are<00:13:10.079> based<00:13:10.320> in<00:13:10.560> italy<00:13:11.040> have<00:13:11.200> been<00:13:11.440> trying<00:13:11.680> to
are based in italy have been trying to
are based in italy have been trying to
get<00:13:12.320> the<00:13:12.480> full<00:13:12.720> data<00:13:13.120> in<00:13:13.200> a<00:13:13.360> usable<00:13:13.839> form
get the full data in a usable form
get the full data in a usable form
out<00:13:15.120> of<00:13:15.200> the<00:13:15.360> drug<00:13:15.600> company<00:13:15.920> so<00:13:16.160> that<00:13:16.240> they<00:13:16.399> can
out of the drug company so that they can
out of the drug company so that they can
make<00:13:16.720> a<00:13:16.959> full<00:13:17.680> decision<00:13:18.240> about<00:13:18.480> whether<00:13:18.720> this
make a full decision about whether this
make a full decision about whether this
drug<00:13:19.200> is<00:13:19.279> effective<00:13:19.680> or<00:13:19.760> not<00:13:20.240> and<00:13:20.320> they've<00:13:20.560> not
drug is effective or not and they've not
drug is effective or not and they've not
been<00:13:21.040> able<00:13:21.200> to<00:13:21.360> get<00:13:21.600> that<00:13:22.160> information
been able to get that information
been able to get that information
this<00:13:24.160> is<00:13:24.399> undoubtedly<00:13:25.120> the<00:13:25.360> single
this is undoubtedly the single
this is undoubtedly the single
biggest<00:13:27.279> ethical<00:13:27.920> problem<00:13:28.639> facing<00:13:29.279> medicine
biggest ethical problem facing medicine
biggest ethical problem facing medicine
today
today
today
we<00:13:31.360> cannot<00:13:31.839> make<00:13:32.399> decisions<00:13:33.440> in<00:13:33.600> the<00:13:33.760> absence
we cannot make decisions in the absence
we cannot make decisions in the absence
of<00:13:34.959> all<00:13:35.200> of<00:13:35.279> the<00:13:35.440> information
of all of the information
of all of the information
so<00:13:37.760> it's<00:13:37.839> a<00:13:37.920> little<00:13:38.079> bit<00:13:38.240> difficult
so it's a little bit difficult
so it's a little bit difficult
from<00:13:39.680> there
from there
from there
to<00:13:40.880> spin<00:13:41.279> in<00:13:41.920> some<00:13:42.160> kind<00:13:42.320> of<00:13:42.480> positive
to spin in some kind of positive
to spin in some kind of positive
conclusion
conclusion
conclusion
but<00:13:45.200> i<00:13:45.279> would<00:13:45.519> say<00:13:45.920> this
but i would say this
but i would say this
i<00:13:49.120> think
i think
i think
that<00:13:50.240> sunlight
that sunlight
that sunlight
is<00:13:51.920> the<00:13:52.000> best<00:13:52.399> disinfectant
is the best disinfectant
is the best disinfectant
all<00:13:54.240> of<00:13:54.320> these<00:13:54.480> things<00:13:54.800> are<00:13:54.880> happening<00:13:55.279> in
all of these things are happening in
all of these things are happening in
plain<00:13:55.839> sight<00:13:56.720> and<00:13:56.800> they're<00:13:57.040> all<00:13:57.199> protected<00:13:57.760> by
plain sight and they're all protected by
plain sight and they're all protected by
a<00:13:58.000> kind<00:13:58.160> of<00:13:58.320> force<00:13:58.720> field<00:13:59.279> of<00:13:59.920> of<00:14:00.160> tediousness
a kind of force field of of tediousness
a kind of force field of of tediousness
and<00:14:01.680> i<00:14:01.760> think<00:14:01.920> with<00:14:02.160> all<00:14:02.320> of<00:14:02.399> the<00:14:02.480> problems<00:14:03.199> in
and i think with all of the problems in
and i think with all of the problems in
science<00:14:03.680> one<00:14:03.839> of<00:14:03.920> the<00:14:04.000> best<00:14:04.240> things<00:14:04.480> that<00:14:04.560> we
science one of the best things that we
science one of the best things that we
can<00:14:04.880> do<00:14:05.440> is<00:14:05.519> to<00:14:05.680> lift<00:14:06.000> up<00:14:06.079> the<00:14:06.240> lid<00:14:06.959> finger
can do is to lift up the lid finger
can do is to lift up the lid finger
around<00:14:07.600> at<00:14:07.680> the<00:14:07.760> mechanics<00:14:08.560> and<00:14:08.800> peer<00:14:09.120> in
around at the mechanics and peer in
around at the mechanics and peer in
thank<00:14:10.079> you<00:14:10.240> very<00:14:10.399> much
you
Ben Goldacre, bad, science, heatlh, advice, nutrition, TED-Ed, TED, Ed’, TEDEducation, TED
