Introduction
Neural network activated in parenting: Parts of the brain involved in paternal attachment, love, and responsiveness include: anterior cingulate cortex; anterior insula; mesial prefrontal cortex; right orbitofrontal cortex; periaqueductal gray; hypothalamus; thalamus; caudate nucleus; nucleus accumbens; and putamen. Bartels and Zeki (2004); Lorberbaum et al. (2002); Noriuchi et al. (2008); and Swain et al. (2007).
Prose throughout is our mutual collaboration: From start to finish, the book has been a joint effort, from the research to the writing. However, at times in the text when recalling personal experiences, we needed to identify ourselves individually. Therefore, when the pronoun “I” is used, it refers to Po’s personal experiences; when “Ashley” is employed, this refers to her personal experiences. These passages of text, though, are jointly composed and edited.
Chapter 1, The Inverse Power of Praise
Categorization of gifted students: The exact requirements for gifted programs vary, but most start calling children gifted based on scores on an intelligence test or achievement test at the 90th percentile.
Advanced students’ poor self-assessment of competence: That gifted students frequently underestimate their abilities has been reported in a number of studies, including: Cole et al. (1999); Phillips (1984); and Wagner and Phillips (1992). Note that in these studies, a common method of assessment is to ask students to describe their proficiency in a school subject and then compare the students’ self-reports to their actual achievement scores.
Columbia University survey: Dweck (1999).
Brightest girls collapse after failure round: One of the things that Dweck’s research suggests is that there is nothing inherently fragile or dramatic about being blessed with an advanced brain, but it’s the praise that makes intelligent children more vulnerable.
Interestingly, in one of her studies, Dweck found that after the failure round of tests, all the girls were collapsing, but the higher their IQ, the more they collapsed—to the remarkable point where girls who had the highest IQs in the first round of tests performed even worse than the low IQ girls in the last round. Explaining this, Dweck conjectured: “Girls are used to being perfect. Girls feel other people’s opinions and feedback are valid ways to learn about their abilities. Boys always call each other morons. Nobody else is going to give you the final verdict on your abilities.”
This may explain findings by Henderlong: she has seen age and gender differences in her own renditions of praise experiments, indicating that boys may respond differently to person-oriented praise such as “You’re smart.” Henderlong Corpus and Lepper (2007).
Baumeister’s assessment of self-esteem findings: Baumeister’s expressed disappointment at the results of his findings was originally reported by Ahuja (2005).
Higher self-esteem leads to higher aggression: Since Baumeister’s review, the relationship between high self-esteem and aggression has been expressly seen in the study of children. In 2008, scholars reported on a study where children were to play computer games—believing that they were playing against other children, but in reality playing only against the computer—with a predetermined, losing outcome. After studying how the children attacked their believed opponents, the researchers concluded that there was no empirical support for a claim that children with low self-esteem were aggressive, but there was support that those with high self-esteem were more aggressive and more narcissistic. They even suggested that efforts to boost self-esteem “are likely to increase (rather than to decrease) the aggressive behavior of youth at risk.” Thomaes et al. (2008).
Review of 150 praise studies: Henderlong and Lepper (2002).
Cloninger’s location of the persistence circuit in the brain: Cloninger put people inside an fMRI scanner to measure their brain activity while they looked through a series of 360 photographs, like car accidents and people holding children. He asked them to rate the photographs as pleasant, neutral, or unpleasant. Those who were most persistent (scored on a seven-factor personality test) had the highest activity in their lateral orbital and medial prefrontal cortex, as well as their ventral striatum. Interestingly, they also rated more neutral photographs as pleasant, and unpleasant photographs as neutral. In other words, persistent individuals actually experience the world as more pleasant—less bothers them.
Chapter 2, The Lost Hour
Parents’ poor accuracy in assessing the sufficiency of their children’s sleep: Several scholars have tried to figure out how accurate parents are at assessing their children’s amount of sleep, comparing parental reports with kids’ reports and scientific measures (actigraphy). Parents frequently overestimate the time their kids are asleep by at least a half-hour—even as much as an hour and a half. See, for example, National Sleep Foundation (2006a) and Werner et al. (2008).
High school students reporting sleep deprivation: Teens’ lack of sleep is a problem that by no means is limited to American youth: teens around the world are exhausted. In a study of Singaporean high-schoolers, 96.9% said they weren’t getting enough sleep. And only 0.5% of them had discussed their sleep difficulties with a physician. Lim et al. (2008).
Basis of “lost hour” of kids’ sleep: There seems to be universal agreement as to the fact that kids are getting less sleep today than in years past. However, there’s less agreement in just how much sleep kids have lost. We base our “one lost hour” on research we did in sleep studies and general time use studies: our determination is probably a conservative assessment.
According to one report, in 1997, children age 3 to 5 were found to be getting just over 10.8 hours of sleep per night, while children 6 to 8 years old were getting 10.1 hours of sleep. In 2004, the National Sleep Foundation found that the 3- to 5-year-olds were down to 10.4 hours of sleep, and the 6- to 8-year-olds were down to 9.5 hours. (Compare Hofferth and Sandberg [2001] to the National Sleep Foundation’s 2004 Sleep in America Poll.)
Over the same time period, Brown University found that, in 1997, nine- to twelve-year-olds were getting about 9.6 hours of sleep, but in 2004, sixth graders were getting 8.3 of sleep—a difference of 1.3 hours. Carskadon (2004) and Sleep in America poll (2006).
Further support for the hour loss of sleep can be found in an influential and widely cited study of Swiss children. In that study, throughout the 1990s, sleep duration for children fell across all ages—meaning that a two-year-old slept less in 1986 than he would have in 1974, and a fourteen-year-old slept less in 1986 than he did in 1974. The youngest children actually saw the most severe drop in sleep duration. Six-month-old infants born in 1993 were sleeping 2.5 hours less than those born in 1978, while there was a 1.0 hour difference for sixteen-year-olds. Iglowstein et al. (2003).
In 2005, the American Academy of Pediatrics’ Working Group on Sleepiness in Adolescents/Young Adults and the AAP Committee on Adolescence issued a technical report that opined that the Iglowstein study was an “impressive work” and a valuable guideline as to trends in youth sleep in the United States; if anything, the American scholars believed that the US results would be more “extreme” than the Swiss results. Millman et al. (2005). And Landhuis et al. believe that a two-hour drop in the past two decades is also a supportable claim. Landhuis et al. (2008).
Other studies addressing the international downward trend in sleep duration include: Van Cauter et al. (2008) and Taheri (2006).
Rhode Island study on teens setting bedtimes: Wolfson and Carskadon (1998).
Sleep deprivation and its effects on emotional stability and development: For ADHD, authors’ interviews with Ronald Chervin and Louise O’Brien; Chervin et al. (2005); Chervin et al. (2002); and Chervin et al. (1998). For emotional stability of adolescents, authors’ interviews with Ronald Dahl, David Dinges, and Frederick Danner, as well as Dahl (1999); Danner and Phillips (2008).
Experimental manipulation of children’s sleep duration and test performance: Since Sadeh’s experiment, Tzischinsky et al. (2008) essentially replicated his findings—having eighth
graders sleep an hour more than normal. The students who slept the extra time scored significantly higher on math tests and attention measures.
Effects of sleep loss akin to lead exposure: McKenna (2007).
Studies reporting a sleep/grade correlation: See, e.g., Danner and Gilman (2008); Warner et al. (2008); Bachmann and Ax (2007); and Fredriksen et al. (2004).
Sleep deprivation’s interference with brain mechanisms: Durmer and Dinges (2005).
Slow-wave sleep and kids’ learning vocabulary: Backhaus et al. (2008).
Edina, Minn. SAT scores: The New York Times previously reported on Edina’s SAT gains; however, the article reported incorrect scores. The Times reported lower figures than the students had actually achieved. Wahlstrom had requested a correction at the time; however, no one responded to her query. Per our request to Wahlstrom, Wahlstrom retrieved the information that she had previously provided the Times, and then re-analyzed the data to confirm the accuracy of the increase.
O’Reilly of the College Board explained to us in an interview that the increase is even more extraordinary on two points. First, the scores we include in the text were based on the 1600-point test: a 212-point increase would essentially account for 14% of a total score. Second, most Minnesota students take the ACT: only the most competitive students take the SAT. Accordingly, O’Reilly says that students in the top 10% of an Edina SAT class would be in the top 1% nationally. We also note that the increase in scores after the later start time is roughly equivalent to the increase promised by professional SAT prep courses.
Later school start times result in improved quality of life: Htwe et al. (2008); Danner and Phillips (2008) and Wahlstrom interviews.
Prevalence of early morning high school start times: Wolfson and Carskadon (2005).
McMaster review of obesity prevention programs: Thomas (2006). British officials completed a similar large-scale review of obesity prevention programs and also concluded that there was “scant” evidence that such programs were effective. See “Obesity ‘Not Individuals’ Fault” (2007). Stice et al. (2006) also considered the efficacy of most programs to be “trivial.”
Kids’ TV watching and other sedentary activity: Vandewater isn’t the only scholar who disputes the premise that kids limit their physical activity because they are watching television. Taveras et al. (2007) concluded that if a kid watched an hour less of television each week, there would be no increase in his physical activity. And other researchers have measured the time spent on homework, computer use, reading, hobbies, hanging out with friends, even sitting in a car on the way to school. When those are considered, television is as little as one-third of a teen’s sedentary activity. Biddle et al. (2009); Biddle (2007); and Utter et al. (2003).
Studies showing relationships between sleep deprivation and children’s obesity: In addition to the American, Australian, Canadian, and Japanese studies finding a connection between children’s shortened sleep and obesity, this same relationship has now also been found by scholars in France, Germany, Portugal, Tunisia, China, Hong Kong, Taiwan, Brazil, and New Zealand—where scholars found that shortened sleep in elementary school children predicted obesity at age 32. Studies reporting a connection include: Landhuis et al. (2008); Nixon et al. (2008); Taveras et al. (2008); Lumeng et al. (2007); Eisenmann et al. (2006); Chaput et al. (2006); Gupta et al. (2002); and Sekine et al. (2002).
Two meta-analyses also have found a relationship between children’s sleep and obesity: Cappuccio et al. (2008) and Chen et al. (2008).
While some scholars—e.g., Hassan et al. (2008) and Horne (2008)—are still unsure about the relationship between sleep and kids’ obesity, Pediatrics has determined that enough data supports short-sleep’s relationship to overweight in children, that sleep should be considered in assessing an individual child’s weight issues. Krebs et al. (2007). And other scholars believe that the data is now persuasive enough that kids’ sleep and obesity should be considered a public health issue. Young (2008).
CDC/USDA positions on kids and sleep: Park (2008); Schoenborn and Adams (2008); Redding (2007); and Hensley (2007).
Chapter 3, Why White Parents Don’t Talk About Race
Infants’ perception of racial differences: Kelly et al. (2007) have determined that infants begin to notice the visually apparent aspects of racial differences somewhere between the third and sixth months.
Experiment with cross-race groups: Rooney-Rebeck and Jason (1986).
Subgroupism in Japanese schools: Based in part on authors’ interview and correspondence with David Crystal and Crystal et al. (2000).
Shushing kids’ discussion of race: In one case we learned about, a kindergarten teacher began her lecture on Martin Luther King Jr. only to have one of the children cut her off with: “Mommy says we shouldn’t talk about color.” Polite and Saenger (2003).
Study of Detroit high school students: Oyserman et al. (2006).
Black Santa and White Santa: Account is based on authors’ interviews, correspondence with Coperhaven-Johnson, and her report, Coperhaven-Johnson (2007).
Chapter 4, Why Kids Lie
100,000 children testifying: Following Talwar’s discoveries about children’s understanding of lying, and under what circumstance they are more likely to lie, the Canadian legislature revised its procedure to determine if children should be allowed to testify. Talwar et al. (2002) and Bill C-2 (2004).
Lie-detection systems: In an extensive review of 150 studies on lie detection, University of Portsmouth professor Aldert Vrij concluded: “[T]here is not a single verbal, nonverbal or physiological cue uniquely related to deception. In other words, nothing similar to Pinocchio’s growing nose actually exists.” Vrij (2004). Perhaps the most common belief about lie detection is that people avert their gaze when telling a lie. However, study after study show that gaze aversion has little if any relation to a person’s lying. Gaze aversion is even less of a signal for children: they frequently look away from a conversation partner when they are concentrating. See, e.g., Talwar and Lee (2002a) and Vrij et al. (2004).
Fascinatingly, in a 2006 study of over 11,000 survey responses from 57 countries, 64% of respondents said that gaze aversion signaled lying. Scholars hypothesize that the myth of gaze aversion comes from a different emotional state altogether: around the world, people look down at the ground as an indication of shame. Therefore, the scholars suggest there’s an (errant) assumption that liars are ashamed of their falsehood and thus look away. Global Deception Research Team (2006).
Parents’ inability to detect children’s lies: Talwar has been regularly studying parents’ failure to identify children’s lying, first publishing results in 2002. She isn’t alone in her findings, either: scholars Angela M. Crossman and Michael Lewis found similar results, with parents again performing at levels lower than chance in identifying children’s lying in their study. Crossman and Lewis (2006).
In Talwar’s newest study, she’s been looking to see if some people are just better at lie detection than others. She’s found that only 4% were repeatedly significantly better at lie detection. Leach et al. (2009).
Prevalence of children who peek and lie: The percentages of children who will cheat and lie during the peeking game we’ve reported come from Talwar’s first 2002 study. Talwar and Lee (2002a). However, Talwar has since replicated this pattern in many subsequent studies: the percentage of children who peek and those who lie remain amazingly consistent. Additionally, other scholars have since replicated her work in their own versions of the peeking game.
Lying’s connection with intelligence: Talwar has found that children with more advanced executive functioning and working memory are better liars. She’s also seen relationships between children’s lying and “theory of mind”—the ability to understand and keep track of multiple people’s points of view.
Children’s lying to make a parent happy: Along with Talwar’s research, Bussey’s work fleshes out this insight. When Bussey has presented children with anecdotes, and as
ked them to predict if the protagonist would be truthful or not, the children’s responses were in part determined by whether or not the story had said if the protagonist would be punished for a misdeed or its admission. Bussey has also shown that it isn’t until children are eight years old that they begin to believe that truth telling may make the truth teller himself feel better. Bussey (1999) and Wagland and Bussey (2005).
Additionally, a 2007 University of Texas, El Paso, study offers an intriguing twist for both Talwar’s conclusion that children lie to make an adult happy and Dweck’s praise-addicted children. In the UT study, young children were asked if they’d seen anyone take an examiner’s toy. Some children were told, “Thank you, you’ve been a big help,” every time they answered “Yes” to any of the examiner’s questions. Within four minutes, half of the children who had heard that praise had begun making false confessions. They actually lied about wrongs they weren’t a part of, so that the praise could continue. Billings et al. (2007).
Frequency of children’s lies: Wilson et al. (2003) and Wilson et al. (2004).
Tattling: The primary work on children’s tattling comes from den Bak and Ross (1996) and Ross and den Bak-Lammers (1998). Friman et al. (2004) is also informative, particularly on his point that fourth-graders consider tattling an aggressive act on par with stealing or destruction of another’s property.
Frequency of adult lies: There are popularized claims that the average adult lies at least three times in a ten-minute conversation. However, that statistic is based on an experiment in a highly manipulated situation—where two strangers were told to sit in a room and at least one had been instructed to say things that would make the other like him. Even in that artificial environment, 40% of the test subjects never lied at all. The data from DePaulo and Hancock on the frequency of lies is based not on an experimental manipulation, but on diary studies—where people kept track, on a daily basis, of every lie that they told. In the DePaulo and Hancock studies, people in the general population lied only about once a day—college students twice a day. DePaulo et al. (1996) and Hancock et al. (2004).
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