1 00:00:01,920 --> 00:00:07,080 Speaker 1: Welcome to brain Stuff production of iHeart Radio. Hey brain Stuff, 2 00:00:07,120 --> 00:00:11,200 Speaker 1: Lauren boglebam here. Do you make better decisions in the 3 00:00:11,200 --> 00:00:14,960 Speaker 1: morning or in the evening? That might depend on whether 4 00:00:15,000 --> 00:00:18,560 Speaker 1: you want a quick decision or an accurate one. A 5 00:00:18,600 --> 00:00:21,439 Speaker 1: few years back, researchers looked at the decision making behavior 6 00:00:21,480 --> 00:00:23,319 Speaker 1: of a dred and eighty four users of the Free 7 00:00:23,320 --> 00:00:26,279 Speaker 1: Internet Chess Server to discover at what time of day 8 00:00:26,320 --> 00:00:30,040 Speaker 1: players made the best decisions. Chess players, who in this 9 00:00:30,080 --> 00:00:33,160 Speaker 1: case made around forty move decisions in games lasting from 10 00:00:33,159 --> 00:00:36,199 Speaker 1: three to fifteen minutes, are often used in experiments that 11 00:00:36,240 --> 00:00:40,360 Speaker 1: analyze complex human thinking. The Free Internet Chess Server Chess 12 00:00:40,360 --> 00:00:43,960 Speaker 1: Game Database presented itself as an optimal study tool with 13 00:00:44,040 --> 00:00:47,280 Speaker 1: its treasure trove of time stamped right and wrong decisions, 14 00:00:47,560 --> 00:00:50,320 Speaker 1: and allowed researchers to study not just the length of time, 15 00:00:50,520 --> 00:00:53,960 Speaker 1: but also the quality of real world decision making behavior 16 00:00:54,120 --> 00:00:58,040 Speaker 1: at various times of day. Study published in the journal 17 00:00:58,080 --> 00:01:01,400 Speaker 1: Cognition showed that, whether you're morning person or not, the 18 00:01:01,480 --> 00:01:04,200 Speaker 1: most accurate decision making happens on the early side of 19 00:01:04,240 --> 00:01:08,679 Speaker 1: the day, between eight am and one pm. However, even 20 00:01:08,680 --> 00:01:11,760 Speaker 1: though morning decisions were the most accurate, those also took 21 00:01:11,760 --> 00:01:14,800 Speaker 1: the longest to make, and that's a liability in time 22 00:01:14,840 --> 00:01:18,400 Speaker 1: limited activities like a chess game. As the day wore on, 23 00:01:18,600 --> 00:01:23,039 Speaker 1: the chess player's decision making sped up, but accuracy slumped. Ultimately, 24 00:01:23,080 --> 00:01:25,480 Speaker 1: the time of day had no effect on the player's scores, 25 00:01:25,800 --> 00:01:30,360 Speaker 1: as decisions, speed and accuracy canceled each other out. We 26 00:01:30,400 --> 00:01:33,560 Speaker 1: spoke with the studies lead author, Maria Juliana Leone, who 27 00:01:33,640 --> 00:01:36,520 Speaker 1: is herself a chess champion and a postdoctoral fellow at 28 00:01:36,560 --> 00:01:41,920 Speaker 1: the Integrated Neuroscience Lab at the Universidada in Buenos Aires, Argentina. 29 00:01:42,400 --> 00:01:45,640 Speaker 1: She said, in some way these two variables are compensating 30 00:01:45,680 --> 00:01:50,280 Speaker 1: to maintain the performance throughout the day. Leon suspected it 31 00:01:50,320 --> 00:01:52,880 Speaker 1: was more than growing tiredness as a day waned that 32 00:01:52,920 --> 00:01:56,280 Speaker 1: affected player's speed of decision making. Groups of players were 33 00:01:56,320 --> 00:01:59,760 Speaker 1: observed playing more games at certain times than others. She 34 00:02:00,000 --> 00:02:03,400 Speaker 1: thought the gamers chronotypes might be playing a role. Your 35 00:02:03,480 --> 00:02:06,240 Speaker 1: chronotype is a classification based on which of a day's 36 00:02:06,240 --> 00:02:09,839 Speaker 1: twenty four hours you choose for sleep. Subjects were asked 37 00:02:09,880 --> 00:02:12,880 Speaker 1: to complete a morning this evening miss questionnaire to determine 38 00:02:12,880 --> 00:02:15,160 Speaker 1: whether they tended to be larks who preferred to rise 39 00:02:15,160 --> 00:02:19,560 Speaker 1: early or owls who like to sleep late. Leon's research 40 00:02:19,600 --> 00:02:22,200 Speaker 1: showed that both larks and owls played the most chess 41 00:02:22,200 --> 00:02:25,480 Speaker 1: games at about the same hours since awakening. Even though 42 00:02:25,480 --> 00:02:28,040 Speaker 1: owls would get started later than larks, the number of 43 00:02:28,080 --> 00:02:31,720 Speaker 1: games would end up being about the same. Surprisingly, the 44 00:02:31,760 --> 00:02:34,720 Speaker 1: decision making pattern was the same for both groups. It 45 00:02:34,840 --> 00:02:38,519 Speaker 1: got slower as the day progressed. However, the larks slowed 46 00:02:38,560 --> 00:02:42,160 Speaker 1: down the most. So how can we put the findings 47 00:02:42,200 --> 00:02:46,200 Speaker 1: of the study to concrete use, Leon said, If we 48 00:02:46,320 --> 00:02:48,400 Speaker 1: know that during the morning we are slower, but our 49 00:02:48,440 --> 00:02:51,040 Speaker 1: decisions are more accurate, and during the afternoon we know 50 00:02:51,080 --> 00:02:53,640 Speaker 1: that our decisions will be faster but less accurate, we 51 00:02:53,680 --> 00:02:56,360 Speaker 1: can decide when to make some important decisions according to 52 00:02:56,400 --> 00:02:59,520 Speaker 1: what's important for that decision. In particular, maybe we need 53 00:02:59,560 --> 00:03:02,280 Speaker 1: to prior has the time or the quality. If we 54 00:03:02,320 --> 00:03:04,720 Speaker 1: need to make a decision faster, maybe it's better to 55 00:03:04,720 --> 00:03:08,720 Speaker 1: make that decision in the afternoon. Leon took the chronotype 56 00:03:08,800 --> 00:03:11,840 Speaker 1: questionnaire and found she was halfway between the morning larks 57 00:03:11,840 --> 00:03:15,320 Speaker 1: and the night owls. She therefore tries to schedule intense 58 00:03:15,320 --> 00:03:18,040 Speaker 1: work tasks closer to the middle of the day, but 59 00:03:18,200 --> 00:03:20,480 Speaker 1: with all the daily demands of the work. She hasn't 60 00:03:20,520 --> 00:03:23,080 Speaker 1: yet managed to divide and schedule her decision making for 61 00:03:23,240 --> 00:03:26,760 Speaker 1: optimal results. She said, it's not easy for me either. 62 00:03:32,000 --> 00:03:34,560 Speaker 1: Today's episode was written by Michelle Edelman and produced by 63 00:03:34,560 --> 00:03:36,760 Speaker 1: Tyler Clay. For more on this and lots of other 64 00:03:36,800 --> 00:03:39,840 Speaker 1: curious topics, visit how stuff works dot com. Brain Stuff 65 00:03:39,880 --> 00:03:42,200 Speaker 1: is a production of iHeart Radio. For more podcasts, for 66 00:03:42,240 --> 00:03:45,040 Speaker 1: my heart Radio is the I heart Radio app, Apple Podcasts, 67 00:03:45,080 --> 00:03:46,720 Speaker 1: or where ever you listen to your favorite shows.