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