Can you spot the problem with these headlines Level 1 Jeff Leek Lucy McGowan

“New drug may cure cancer.”

“Aspirin may reduce risk of
heart attacks.”

“Eating breakfast can help
you lose weight.”

Health headlines like these
flood the news,

often contradicting each other.

So how can you figure out what’s a
genuine health concern

or a truly promising remedy,

and what’s less conclusive?

In medicine,

there’s often a disconnect between
news headlines

and the scientific research they cover.

That’s because a headline is designed
to catch attention—

it’s most effective when
it makes a big claim.

By contrast,

many scientific studies produce
meaningful results

when they focus on a narrow,
specific question.

The best way to bridge this gap

is to look at the original research
behind a headline.

We’ve come up with a simplified
research scenario

for each of these three headlines
to test your skills.

Keep watching for the explanation
of the first study;

then pause at the headline
to figure out the flaw.

Assume all the information you need
to spot the flaw is included.

Let’s start with this hypothetical
scenario:

a study using mice to test
a new cancer drug.

The study includes two groups of mice,

one treated with the drug,
the other with a placebo.

At the end of the trial,

the mice that receive the drug are cured,

while those that received
the placebo are not.

Can you spot the problem
with this headline:

“Study shows new drug
could cure cancer”

Since the subjects of the study were mice,

we can’t draw conclusions about
human disease based on this research.

In real life, early research on new drugs
and therapies is not conducted on humans.

If the early results are promising,

clinical trials follow to determine
if they hold up in humans.

Now that you’ve warmed up,

let’s try a trickier example:

a study about the impact of aspirin
on heart attack risk.

The study randomly divides a pool
of men into two groups.

The members of one group
take aspirin daily,

while the others take a daily placebo.

By the end of the trial,

the control group suffered significantly
more heart attacks

than the group that took aspirin.

Based on this situation, what’s wrong
with the headline:

“Aspirin may reduce risk of heart attacks”

In this case, the study shows evidence
that aspirin reduces heart attacks in men,

because all the participants were men.

But the conclusion “aspirin reduces risk
of heart attacks” is too broad;

we can’t assume that results found in
men would also apply to women.

Studies often limit participants based on
geographic location, age, gender,

or many other factors.

Before these findings can be generalized,

similar studies need to be run
on other groups.

If a headline makes a general claim,

it should draw its evidence from a diverse
body of research, not one study.

Can you take your skills from the first
two questions to the next level?

Try this example about the impact
of eating breakfast on weight loss.

Researchers recruit a group of people
who had always skipped breakfast

and ask them to start
eating breakfast everyday.

The participants include men and women
of a range of ages and backgrounds.

Over a year-long period,

participants lose an average
of five pounds.

So what’s wrong with the headline:

“Eating breakfast can help
you lose weight”

The people in the study started eating
breakfast and lost weight—

but we don’t know that they lost weight
because they started eating breakfast;

perhaps having their weight tracked

inspired them to change their eating
habits in other ways.

To rule out the possibility that
some other factor caused weight loss,

we would need to compare
these participants

to a group who didn’t eat breakfast
before the study

and continued to skip it during the study.

A headline certainly shouldn’t claim the
results of this research

are generally applicable.

And if the study itself made such
a claim without a comparison group,

then you should question its credibility.

Now that you’ve battle-tested your skills

on these hypothetical studies
and headlines,

you can test them on real-world news.

Even when full papers aren’t available
without a fee,

you can often find summaries of
experimental design and results

in freely available abstracts,

or even within the text
of a news article.

Individual studies have results

that don’t necessarily correspond
to a grabby headline.

Big conclusions for human health issues

require lots of evidence accumulated
over time.

But in the meantime,

we can keep on top of the science,
by reading past the headlines.

“新药可能治愈癌症。”

“阿司匹林可以降低
心脏病发作的风险。”

“吃早餐可以帮助
你减肥。”

像这样的健康头条新闻
充斥着新闻,

经常相互矛盾。

那么,您如何才能弄清楚什么是
真正的健康问题

或真正有希望的补救措施,

而什么是不确定的呢?

在医学领域,

新闻标题

和它们所涵盖的科学研究之间经常存在脱节。

那是因为标题
旨在吸引注意力——


它提出一个大的要求时,它是最有效的。

相比之下,

许多科学研究

在关注一个狭窄的
具体问题时会产生有意义的结果。

弥合这一差距的最佳方法

是查看
标题背后的原始研究。

我们为这三个标题中的每一个都提出了一个简化的
研究方案

来测试你的技能。

继续关注
第一个研究的解释;

然后在标题处暂停
以找出缺陷。

假设包含了发现缺陷所需的所有信息

让我们从这个假设
场景开始:

一项使用小鼠
测试新抗癌药物的研究。

该研究包括两组小鼠,

一组接受药物治疗
,另一组接受安慰剂治疗。

试验结束时

,接受药物治疗的小鼠痊愈,


接受安慰剂的小鼠则没有。

你能发现
这个标题的问题吗:

“研究表明新药
可以治愈癌症”

由于研究对象是老鼠,

我们不能
根据这项研究得出关于人类疾病的结论。

在现实生活中,新药
和疗法的早期研究并不是针对人类进行的。

如果早期结果很有希望,

接下来的临床试验将
确定它们是否适用于人类。

现在你已经热身了,

让我们尝试一个更棘手的例子:

一项关于阿司匹林
对心脏病发作风险影响的研究。

该研究将一
组男性随机分为两组。

一组的成员
每天服用阿司匹林,

而其他人每天服用安慰剂。

到试验结束时

,对照组比服用阿司匹林的组患
心脏病的次数

要多得多。

基于这种情况
,标题有什么问题:

“阿司匹林可能会降低心脏病发作的风险”

在这种情况下,研究
显示阿司匹林可以减少男性心脏病发作的证据,

因为所有参与者都是男性。

但“阿司匹林
降低心脏病发作风险”的结论过于宽泛。

我们不能假设在男性中发现的结果
也适用于女性。

研究经常根据
地理位置、年龄、性别

或许多其他因素限制参与者。

在推广这些发现之前,

需要对其他群体进行类似的研究

如果标题做出笼统的声明,

它应该从
多元化的研究中获取证据,而不是从一项研究中获取证据。

你能把你的技能从前
两个问题提升到一个新的水平吗?

试试这个关于
吃早餐对减肥的影响的例子。

研究人员招募了一组
一直不吃早餐的人

,让他们开始
每天吃早餐。

参与者包括
不同年龄和背景的男性和女性。

在长达一年的时间里,

参与者平均减掉
5 磅。

那么标题有什么问题:

“吃早餐可以帮助
你减肥”

研究中的人开始吃
早餐并减肥 -

但我们不知道他们减肥
是因为他们开始吃早餐;

也许跟踪他们的体重会

激发他们
以其他方式改变饮食习惯。

为了排除
其他因素导致体重减轻的可能性,

我们需要将
这些参与者

与研究前不吃早餐并在研究期间继续不吃早餐的一组进行比较

标题当然不应该声称
这项研究的

结果普遍适用。

如果研究本身在
没有对照组的情况下提出这样的主张,

那么你应该质疑它的可信度。

既然您已经

在这些假设性研究
和头条新闻中对自己的技能进行

了实战测试,您就可以在现实世界的新闻中对其进行测试。

即使无法免费获得完整的论文

您也经常可以在免费提供的摘要中找到
实验设计和结果的

摘要,

甚至可以在
新闻文章的文本中找到。

个别研究的

结果不一定
与抢眼的标题相对应。

关于人类健康问题的重大结论

需要
随着时间的推移积累大量证据。

但与此同时,

我们可以
通过阅读过去的头条新闻来保持科学的领先地位。