0:00:06.912,0:00:11.532 One simple vitamin can reduce [br]your risk of heart disease. 0:00:11.532,0:00:15.522 Eating chocolate reduces [br]stress in students. 0:00:15.522,0:00:20.222 New drug prolongs lives of [br]patients with rare disease. 0:00:20.222,0:00:23.187 Health headlines like these are published[br]every day, 0:00:23.187,0:00:26.307 sometimes making opposite claims [br]from each other. 0:00:26.307,0:00:28.427 There can be a disconnect between broad, 0:00:28.427,0:00:31.537 attention-grabbing headlines [br]and the often specific, 0:00:31.537,0:00:34.977 incremental results of the medical [br]research they cover. 0:00:34.977,0:00:39.357 So how can you avoid being [br]misled by grabby headlines? 0:00:39.357,0:00:42.467 The best way to assess a headline’s [br]credibility 0:00:42.467,0:00:45.807 is to look at the original [br]research it reports on. 0:00:45.807,0:00:48.217 We’ve come up with a hypothetical research[br]scenario 0:00:48.217,0:00:50.507 for each of these three headlines. 0:00:50.507,0:00:53.357 Keep watching for the explanation[br]of the first example; 0:00:53.357,0:00:56.447 then pause at the headline to [br]answer the question. 0:00:56.447,0:00:58.517 These are simplified scenarios. 0:00:58.517,0:01:02.827 A real study would detail many more [br]factors and how it accounted for them, 0:01:02.827,0:01:04.837 but for the purposes of this exercise, 0:01:04.837,0:01:08.837 assume all the information [br]you need is included. 0:01:11.048,0:01:14.098 Let’s start by considering the [br]cardiovascular effects 0:01:14.098,0:01:17.068 of a certain vitamin, Healthium. 0:01:17.068,0:01:19.868 The study finds that participants taking[br]Healthium 0:01:19.868,0:01:24.078 had a higher level of healthy cholesterol [br]than those taking a placebo. 0:01:24.078,0:01:28.036 Their levels became similar to those of [br]people with naturally high levels 0:01:28.036,0:01:29.936 of this kind of cholesterol. 0:01:29.936,0:01:33.326 Previous research has shown that people [br]with naturally high levels 0:01:33.326,0:01:37.486 of healthy cholesterol have lower [br]rates of heart disease. 0:01:37.486,0:01:39.991 So what makes this headline misleading: 0:01:39.991,0:01:44.311 Healthium reduces risk of heart disease. 0:01:44.311,0:01:48.791 The problem with this headline is that the[br]research didn’t actually investigate 0:01:48.791,0:01:51.561 whether Healthium reduces heart disease. 0:01:51.561,0:01:53.651 It only measured Healthium’s impact 0:01:53.651,0:01:56.791 on levels of a particular [br]kind of cholesterol. 0:01:56.791,0:01:59.931 The fact that people with naturally high[br]levels of that cholesterol 0:01:59.931,0:02:01.951 have lower risk of heart attacks 0:02:01.951,0:02:04.391 doesn’t mean that the same [br]will be true of people 0:02:04.391,0:02:07.731 who elevate their cholesterol[br]levels using Healthium. 0:02:07.731,0:02:10.141 Now that you’ve cracked the [br]case of Healthium, 0:02:10.141,0:02:13.581 try your hand at a particularly alluring [br]mystery: 0:02:13.581,0:02:17.321 the relationship between eating chocolate[br]and stress. 0:02:17.321,0:02:20.281 This hypothetical study [br]recruits ten students. 0:02:20.281,0:02:23.531 Half begin consuming a [br]daily dose of chocolate, 0:02:23.531,0:02:25.141 while half abstain. 0:02:25.141,0:02:28.691 As classmates, they all follow [br]the same schedule. 0:02:28.691,0:02:32.481 By the end of the study, the chocolate [br]eaters are less stressed 0:02:32.481,0:02:35.451 than their chocolate-free counterparts. 0:02:35.451,0:02:37.301 What’s wrong with this headline: 0:02:37.301,0:02:41.371 Eating chocolate reduces [br]stress in students 0:02:43.408,0:02:48.638 It’s a stretch to draw a conclusion about [br]students in general from a sample of ten. 0:02:48.638,0:02:52.024 That’s because the fewer participants are[br]in a random sample, 0:02:52.024,0:02:54.884 the less likely it is that the sample will[br]closely represent 0:02:54.884,0:02:57.934 the target population as a whole. 0:02:57.934,0:03:02.734 For example, if the broader population of [br]students is half male and half female, 0:03:02.734,0:03:04.784 the chance of drawing a sample of 10 0:03:04.784,0:03:10.144 that’s skewed 70% male and [br]30% is about 12%. 0:03:10.144,0:03:15.693 In a sample of 100 that would be less than[br]a .0025% chance, 0:03:15.693,0:03:17.525 and for a sample of 1000, 0:03:17.525,0:03:22.795 the odds are less than 6 x 10^-36. 0:03:22.795,0:03:25.137 Similarly, with fewer participants, 0:03:25.137,0:03:29.340 each individual’s outcome has a larger [br]impact on the overall results— 0:03:29.340,0:03:32.550 and can therefore skew big-picture trends. 0:03:32.550,0:03:37.490 Still, there are a lot of good reasons for[br]scientists to run small studies. 0:03:37.490,0:03:39.269 By starting with a small sample, 0:03:39.269,0:03:42.039 they can evaluate whether the results are [br]promising enough 0:03:42.039,0:03:45.139 to run a more comprehensive, [br]expensive study. 0:03:45.139,0:03:48.609 And some research requires very specific[br]participants 0:03:48.609,0:03:51.999 that may be impossible to [br]recruit in large numbers. 0:03:51.999,0:03:54.329 The key is reproducibility— 0:03:54.329,0:03:57.629 if an article draws a conclusion [br]from one small study, 0:03:57.629,0:03:59.649 that conclusion may be suspect— 0:03:59.649,0:04:03.099 but if it’s based on many studies [br]that have found similar results, 0:04:03.099,0:04:04.699 it’s more credible. 0:04:04.699,0:04:06.919 We’ve still got one more puzzle. 0:04:06.919,0:04:11.899 In this scenario, a study tests a new drug[br]for a rare, fatal disease. 0:04:11.899,0:04:14.156 In a sample of 2,000 patients, 0:04:14.156,0:04:17.636 the ones who start taking the drug upon [br]diagnosis 0:04:17.636,0:04:21.052 live longer than those who [br]take the placebo. 0:04:21.052,0:04:23.642 This time, the question [br]is slightly different. 0:04:23.642,0:04:28.012 What’s one more thing you’d like to know [br]before deciding if the headline, 0:04:28.012,0:04:33.619 New drug prolongs lives of patients[br]with rare disease, is justified? 0:04:34.902,0:04:36.472 Before making this call, 0:04:36.472,0:04:40.792 you’d want to know how much the drug [br]prolonged the patients’ lives. 0:04:40.792,0:04:43.163 Sometimes, a study can have results that, 0:04:43.163,0:04:48.243 while scientifically valid, don’t have [br]much bearing on real world outcomes. 0:04:48.243,0:04:52.941 For example, one real-life clinical trial [br]of a pancreatic cancer drug 0:04:52.941,0:04:57.457 found an increase in life expectancy—[br]of ten days. 0:04:57.457,0:05:00.277 The next time you see a surprising medical[br]headline, 0:05:00.277,0:05:04.027 take a look at the science [br]it’s reporting on. 0:05:04.027,0:05:06.957 Even when full papers aren’t [br]available without a fee, 0:05:06.957,0:05:09.987 you can often find summaries of [br]experimental design 0:05:09.987,0:05:13.177 and results in freely available abstracts, 0:05:13.177,0:05:16.361 or even within the text [br]of a news article. 0:05:16.361,0:05:19.671 It’s exciting to see scientific research [br]covered in the news, 0:05:19.671,0:05:23.951 and important to understand [br]the studies’ findings.