- Describe Piaget’s formal operational stage and the characteristics of formal operational thought
- Describe adolescent egocentrism
- Describe Information Processing research on attention and memory
- Describe the developmental changes in language
- Describe the various types of adolescent education
- Identify changes in high school drop-out rates based on gender and ethnicity
Piaget’s Formal Operational Stage During the formal operational stage, adolescents are able to understand abstract principles which have no physical reference. They can now contemplate such abstract constructs as beauty, love, freedom, and morality. The adolescent is no longer limited by what can be directly seen or heard. Additionally, while younger children solve problems through trial and error, adolescents demonstrate hypothetical-deductive reasoning, which is developing hypotheses based on what might logically occur. They are able to think about all the possibilities in a situation beforehand, and then test them systematically (Crain, 2005). Now they are able to engage in true scientific thinking.
Formal operational thinking also involves accepting hypothetical situations. Adolescents understand the concept of transitivity, which means that a relationship between two elements is carried over to other elements logically related to the first two, such as if A<B and B<C, then A<C (Thomas, 1979). For example, when asked: If Maria is shorter than Alicia and Alicia is shorter than Caitlyn, who is the shortest? Adolescents are able to answer the question correctly
as they understand the transitivity involved.
Does everyone reach formal operations? According to Piaget, most people attain some degree of formal operational thinking but use formal operations primarily in the areas of their strongest interest (Crain, 2005). In fact, most adults do not regularly demonstrate formal operational thought, and in small villages and tribal communities, it is barely used at all. A possible explanation is that an individual’s thinking has not been sufficiently challenged to demonstrate formal operational thought in all areas.
Adolescent Egocentrism: Once adolescents can understand abstract thoughts, they enter a world of hypothetical possibilities and demonstrate egocentrism or a heightened self-focus. The egocentricity comes from attributing unlimited power to their own thoughts (Crain, 2005). Piaget believed it was not until adolescents took on adult roles that they would be able to learn the limits to their own thoughts.
David Elkind (1967) expanded on the concept of Piaget’s adolescent egocentricity. Elkind theorized that the physiological changes that occur during adolescence result in adolescents being primarily concerned with themselves. Additionally, since adolescents fail to differentiate between what others are thinking and their own thoughts, they believe that others are just as fascinated with their behavior and appearance. This belief results in the adolescent anticipating the reactions of others, and consequently constructing an imaginary audience. “The imaginary audience is the adolescent’s belief that those around them are as concerned and focused on their appearance as they themselves are” (Schwartz, Maynard, & Uzelac, 2008, p. 441). Elkind thought that the imaginary audience contributed to the self-consciousness that occurs during early adolescence. The desire for privacy and reluctance to share personal information may be a further reaction to feeling under constant observation by others. Alternatively, recent research has indicated that the imaginary audience is not imaginary. Specifically, adolescents and adults feel that they are often under scrutiny by others, especially if they are active on social media (Yau & Reich, 2018).
Another important consequence of adolescent egocentrism is the personal fable or belief that one is unique, special, and invulnerable to harm. Elkind (1967) explains that because adolescents feel so important to others (imaginary audience) they regard themselves and their feelings as being special and unique. Adolescents believe that only they have experienced strong and diverse emotions, and therefore others could never understand how they feel. This uniqueness in one’s emotional experiences reinforces the adolescent’s belief of invulnerability, especially to death. Adolescents will engage in risky behaviors, such as drinking and driving or unprotected sex, and feel they will not suffer any negative consequences. Elkind believed that adolescent egocentricity emerged in early adolescence and declined in middle adolescence, however, recent research has also identified egocentricity in late adolescence (Schwartz, et al., 2008).
Consequences of Formal Operational Thought: As adolescents are now able to think abstractly and hypothetically, they exhibit many new ways of reflecting on information (Dolgin, 2011). For example, they demonstrate greater introspection or thinking about one’s thoughts and feelings. They begin to imagine how the world could be which leads them to become idealistic or insisting upon high standards of behavior. Because of their idealism, they may become critical of others, especially adults in their life. Additionally, adolescents can demonstrate hypocrisy, or pretend to be what they are not. Since they are able to recognize what others expect of them, they will conform to those expectations for their emotions and behavior seemingly hypocritical to themselves. Lastly, adolescents can exhibit pseudostupidity. This is when they approach problems at a level that is too complex, and they fail because the tasks are too simple. Their new ability to consider alternatives is not completely under control and they appear “stupid” when they are in fact bright, just not experienced.
Cognitive Control: As noted in earlier chapters, executive functions, such as attention, increases in working memory, and cognitive flexibility have been steadily improving since early childhood. Studies have found that executive function is very competent in adolescence. However, self-regulation, or the ability to control impulses, may still fail. A failure in self-regulation is especially true when there is high stress or high demand on mental functions (Luciano & Collins, 2012). While high stress or demand may tax even an adult’s self-regulatory abilities, neurological changes in the adolescent brain may make teens particularly prone to more risky decision making under these conditions.
Inductive and Deductive Reasoning: Inductive reasoning emerges in childhood and occurs when specific observations, or specific comments from those in authority, may be used to draw general conclusions. This is sometimes referred to as “bottom-up-processing”. However, in inductive reasoning, the veracity of the information that created the general conclusion does not guarantee the accuracy of that conclusion. For instance, a child who has only observed thunder on summer days may conclude that it only thunders in the summer. In contrast, deductive reasoning emerges in adolescence and refers to reasoning that starts with some overarching principle and based on this proposes specific conclusions. This is sometimes referred to as “top-down-processing”. Deductive reasoning guarantees a truthful conclusion if the premises on which it is based are accurate.
Intuitive versus Analytic Thinking: Cognitive psychologists often refer to intuitive and analytic thought as the Dual-Process Model; the notion that humans have two distinct networks for processing information (Albert & Steinberg, 2011). Intuitive thought is automatic, unconscious, and fast (Kahneman, 2011), and it is more experiential and emotional. In contrast, analytic thought is deliberate, conscious, and rational. While these systems interact, they are distinct (Kuhn, 2013). Intuitive thought is easier and more commonly used in everyday life. It is also more commonly used by children and teens than by adults (Klaczynski, 2001). The quickness of adolescent thought, along with the maturation of the limbic system, may make teens more prone to emotional intuitive thinking than adults.
In early adolescence, the transition from elementary school to middle school can be difficult for many students, both academically and socially. Crosnoe and Benner (2015) found that some students became disengaged and alienated during this transition which resulted in negative longterm consequences in academic performance and mental health. This may be because middle school teachers are seen as less supportive than elementary school teachers (Brass, McKellar, North, & Ryan, 2019). Similarly, the transition to high school can be difficult. For example, high schools are larger, more bureaucratic, less personal, and there are less opportunities for teachers to get to know their students (Eccles & Roeser, 2016).
Peers: Certainly, the beliefs and expectations about academic success supported by an adolescent’s family play a significant role in the student’s achievement and school engagement. However, research has also focused on the importance of peers in an adolescent’s school experience. Specifically, having friends who are high-achieving, academically motivated and engaged promotes motivation and engagement in the adolescent, while those whose friends are unmotivated, disengaged, and low achieving promotes the same feelings (Shin & Ryan, 2014; Vaillancourt, Paiva, Véronneau, & Dishion, 2019).
Gender: Crosnoe and Benner (2015) found that female students earn better grades, try harder, and are more intrinsically motivated than male students. Further, Duchesne, Larose, and Feng (2019) described how female students were more oriented toward skill mastery, used a variety of learning strategies, and persevered more than males. However, more females exhibit worries and anxiety about school, including feeling that they must please teachers and parents. These worries can heighten their effort but lead to fears of disappointing others. In contrast, males are more confident and do not value adult feedback regarding their academic performance (Brass et al., 2019). There is a subset of female students who identify with sexualized gender stereotypes (SGS), however, and they tend to underperform academically. These female students endorse the beliefs that “girls” should be sexy and not smart. Nelson and Brown (2019) found that female students who support SGS, reported less desire to master skills and concepts, were more skeptical of the usefulness of an education, and downplayed their intelligence.
Life of a high school student: On average, high school teens spend approximately 7 hours each weekday and 1.1 hours each day on the weekend on educational activities. This includes attending classes, participating in extracurricular activities (excluding sports), and doing homework (Office of Adolescent Health, 2018). High school males and females spend about the same amount of time in class, doing homework, eating and drinking, and working. However, they do spend their time outside of these activities in different ways.
- High school males. On average, high school males spend about one more hour per day on media and communications activities than females on both weekdays (2.9 vs. 1.8 hours) and weekend days (4.8 vs. 3.8 hours). They also spend more time playing sports on both weekdays (0.9 vs. 0.5 hours) and weekend days (1.2 vs. 0.5 hours). On weekdays, high school males get an hour more sleep than females (9.2 vs. 8.2 hours, on average).
- High school females. On an average weekday, high school females spend more time than boys on both leisure activities (1.7 vs. 1.1 hours) and religious activities (0.1 vs. 0.0 hours). High school females also spend more time on grooming on both weekdays and weekend days (1.1 vs. 0.7 hours, on average for both weekdays and weekend days).
High School Dropouts: The status dropout rate refers to the percentage of 16 to 24 year-olds who are not enrolled in school and do not have high school credentials (either a diploma or an equivalency credential such as a General Educational Development [GED] certificate). The dropout rate is based on sample surveys of the civilian, noninstitutionalized population, which excludes persons in prisons, persons in the military, and other persons not living in households. The dropout rate among high school students has declined from a rate of 12% in 1990, to 6.1% in 2016 (U.S. Department of Education, 2018). The rate is lower for Whites than for Blacks, and the rates for both Whites and Blacks are lower than the rate for Hispanics. However, the gap between Whites, Blacks, and Hispanics have narrowed (see Figure 6.13).
The dropout rate for males in 1990 was 12%, where it stayed until 2000. Thereafter the rate has dropped to 7.1% in 2016. The dropout rate for females in 1990 was 12%, and it has dropped to 5.1% in 2016 (U.S. Department of Education, 2018).
Reasons for Dropping Out of School: Garcia et al. (2018) reviewed the research on why students dropped out of school and identified several major obstacles to school completion. These included: Adolescents who resided in foster care or were part of the juvenile justice system. In fact, being confined in a juvenile detention facility practically guaranteed that a student would not complete school. Having a physical or mental health condition, or the need for special educational services, adversely affected school completion. Being maltreated due to abuse or neglect and/or being homeless also contributed to dropping out of school. Additonally, adolescent-specific factors, including race, ethnicity and age, as well as family-specific characteristics, such as poverty, single parenting, large family size, and stressful transitions, all contributed to an increased likelihood of dropping-out of school. Lastly, community factors, such as unsafe neighborhoods, gang activity, and a lack of social services increased the number of school dropouts.
School Based Preparatory Experiences
According to the U. S. Department of Labor (2019), to perform at optimal levels in all education settings, all youth need to participate in educational programs grounded in standards, clear performance expectations and graduation exit options based upon meaningful, accurate, and relevant indicators of student learning and skills. These should include:
- Academic programs that are based on clear state standards
- Career and technical education programs that are based on professional and industry standards
- Curricular and program options based on universal design of school, work and communitybased learning experiences
- Learning environments that are small and safe, including extra supports such as tutoring, as necessary
- Supports from and by highly qualified staff
- Access to an assessment system that includes multiple measures, and
- Graduation standards that include options.
Teenagers and Working
Many adolescents work either summer jobs or during the school year. Holding a job may offer teenagers extra funds, the opportunity to learn new skills, ideas about future careers, and perhaps the true value of money. However, there are numerous concerns about teenagers working, especially during the school year. A long-standing concern is that that it “engenders precocious maturity of more adult-like roles and problem behaviors” (Staff, VanEseltine, Woolnough, Silver, & Burrington, 2011, p. 150).
Several studies have found that working more than 20 hours per week can lead to declines in grades, a general disengagement from school (Staff, Schulenberg, & Bachman, 2010; Lee & Staff, 2007; Marsh & Kleitman, 2005), an increase in substance abuse (Longest & Shanahan, 2007), engaging in earlier sexual behavior, and pregnancy (Staff et al., 2011). However, like many employee groups, teens have seen a drop in the number of jobs. The summer jobs of previous generations have been on a steady decline, according to the United States Department of Labor, Bureau of Labor Statistics (2016). See Figure 6.15 for recent trends.
Teenage Drivers Driving gives teens a sense of freedom and independence from their parents. It can also free up time for parents as they are not shuttling teens to and from school, activities, or work. The National Highway Traffic Safety Administration (NHTSA) reports that in 2014 young drivers (15 to 20 year-olds) accounted for 5.5% (11.7 million) of the total number of drivers (214 million) in the US (National Center for Statistics and Analysis (NCSA), 2016).
However, almost 9% of all drivers involved in fatal crashes that year were young drivers (NCSA, 2016), and according to the National Center for Health Statistics (2014), motor vehicle accidents are the leading cause of death for 15 to 20 year-olds. “In all motorized jurisdictions around the world, young, inexperienced drivers have much higher crash rates than older, more experienced drivers” (NCSA, 2016, p. 1). A teen’s risk of an accident is especially high during the first months of receiving a license (CDC, 2018a). The rate of fatal crashes is twice as high for young males as for young females (CDC, 2018a), although for both genders the rate was highest for the 15-20 years-old age group. For young males, the rate for fatal crashes was approximately 46 per 100,000 drivers, compared to 20 per 100,000 drivers for young females. The NHTSA (NCSA, 2016) reported that of the young drivers who were killed and who had alcohol in their system, 81% had a blood alcohol count past what was considered the legal limit. Fatal crashes involving alcohol use were higher among young men than young women. The NHTSA also found that teens were less likely to use seat belt restraints if they were driving under the influence of alcohol, and that restraint use decreased as the level of alcohol intoxication increased. Overall, teens have the lowest rate of seat belt use. In a 2017 CDC survey, only 59% of teens reported that they always wore a seat belt when riding as a passenger (CDC, 2018b). Crash data shows that almost half of teenage passengers who die in a car crash were not wearing a seat belt (Insurance Institute for Highway Safety, 2017).
In a AAA study of non-fatal, but moderate to severe motor vehicle accidents in 2014, more than half involved young male drivers 16 to 19 years of age (Carney, McGehee, Harland, Weiss, & Raby, 2015). In 36% of rear-end collisions, teen drivers were following cars too closely to be able to stop in time, and in single-vehicle accidents, driving too fast for weather and road conditions was a factor in 79% of crashes involving teens. Distraction was also a factor in nearly 60% of the accidents involving teen drivers. Fellow passengers, often also teenagers (84% of the time), and cell phones were the top two sources of distraction, respectively. This data suggested that having another teenager in the car increased the risk of an accident by 44% (Carney et al., 2015). According to the NHTSA, 10% of drivers aged 15 to 19 years involved in fatal crashes were reported to be distracted at the time of the crash; the highest figure for any age group (NCSA, 2016). Distraction coupled with inexperience has been found to greatly increase the risk of an accident (Klauer et al., 2014). Finally, despite all the public service announcements warning of the dangers of texting while driving, four out of ten teens report having engaged in this within the past 12 months (CDC, 2018b).
The NHTSA did find that the number of accidents has been on a decline since 2005. They attribute this to greater driver training, more social awareness to the challenges of driving for teenagers, and to changes in laws restricting the drinking age. The NHTSA estimates that the raising of the legal drinking age to 21 in all 50 states and the District of Columbia has saved 30,323 lives since 1975. The CDC also credits graduated driver licenses (GDL) for reducing the number of accidents. While GDL programs vary widely, a comprehensive program has a long practice period, requires greater parental participation, and limits newly licensed drivers from driving under certain high-risk conditions (CDC, 2018a).
Albert, D., & Steinberg, L. (2011). Adolescent judgment and decision making. Journal of Research on Adolescence, 21, 211– 224.
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (Fifth Edition). Washington, D. C.: Author.
Arcelus, J., Mitchell, A. J., Wales, J., & Nielsen, S. (2011). Mortality rates in patients with anorexia nervosa and other eating disorders. Archives of General Psychiatry, 68(7), 724-731.
Birkeland, M. S., Melkivik, O., Holsen, I., & Wold, B. (2012). Trajectories of global self-esteem during adolescence. Journal of Adolescence, 35, 43-54.
Bosson, J. K., Vandello, J., & Buckner, C. (2019). The psychology of sex and gender. Thousand Oaks, CA: Sage.
Brass, N., McKellar, North, E., & Ryan, A. (2019). Early adolescents’ adjustment at school: A fresh look at grade and gender differences. Journal of Early Adolescence, 39(5), 689-716.
Brown, B. B., & Larson, J. (2009). Peer relationships in adolescence. In R. M. Lerner & L. Steinberg (Eds.), Handbook of adolescent psychology (pp. 74–103). New York, NY: Wiley.
Carney, C., McGehee, D., Harland, K., Weiss, M., & Raby, M. (2015, March). Using naturalistic driving data to assess the prevalence of environmental factors and driver behaviors in teen driver crashes. AAA Foundation for Traffic Safety. Retrieved from https://www.aaafoundation.org/sites/default/files/2015TeenCrashCausationReport.pdf
Carroll, J. L. (2016). Sexuality now: Embracing diversity (5th ed.). Boston, MA: Cengage Learning.
Caspi, A., Lynam, D., Moffitt, T. E., & Silva, P. A. (1993). Unraveling girls’ delinquency: Biological, dispositional, and contextual contributions to adolescent misbehavior. Developmental Psychology, 29(1), 19-30.
Center for Disease Control. (2004). Trends in the prevalence of sexual behaviors, 1991-2003. Bethesda, MD: Author.
Center for Disease Control. (2016). Birth rates (live births) per 1,000 females aged 15–19 years, by race and Hispanic ethnicity, select years. Retrieved from http://www.cdc.gov/teenpregnancy/about/birth-rates-chart-2000-2011-text.htm
Centers for Disease Control. (2018a). Teen drivers: Get the facts. Retrieved from https://www.cdc.gov/motorvehiclesafety/teen_drivers/teendrivers_factsheet.html
Centers for Disease Control. (2018b). Trends in the behaviors that contribute to unintentional injury: National Youth Risk Behavioral Survey. Retrieved from https://www.cdc.gov/healthyyouth/data/yrbs/pdf/trends/2017_unintentional_injury_trend_yrbs.pdf
Chein, J., Albert, D., O’Brien, L., Uckert, K., & Steinberg, L. (2011). Peers increase adolescent risk taking by enhancing activity in the brain’s reward circuitry. Developmental Science, 14(2), F1-F10. doi: 10.1111/j.1467-7687.2010.01035.x
Chen, B., Vansteenkiste, M., Beyers, W., Soensens, B., & Van Petegem, S. (2013). Autonomy in family decision making for Chinese adolescents: Disentangling the dual meaning of autonomy. Journal of Cross-Cultural Psychology, 44, 1184- 1209.
Connolly, J., Craig, W., Goldberg, A., & Pepler, D. (2004). Mixed-gender groups, dating, and romantic relationships in early adolescence. Journal of Research on Adolescence, 14, 185-207.
Connolly, J., Furman, W., & Konarski, R. (2000). The role of peers in the emergence of heterosexual romantic relationships in adolescence. Child Development, 71, 1395–1408.
Costigan, C. L., Cauce, A. M., & Etchinson, K. (2007). Changes in African American mother-daughter relationships during adolescence: Conflict, autonomy, and warmth. In B. J. R. Leadbeater & N. Way (Eds.), Urban girls revisited: Building strengths (pp. 177-201). New York NY: New York University Press.
Côtè, J. E. (2006). Emerging adulthood as an institutionalized moratorium: Risks and benefits to identity formation. In J. J. Arnett & J. T. Tanner (Eds.), Emerging adults in America: Coming of age in the 21st century, (pp. 85-116). Washington D.C.: American Psychological Association Press.
Crain, W. (2005). Theories of development concepts and applications (5th ed.). New Jersey: Pearson.
Crooks, K. L., & Baur, K. (2007). Our sexuality (10th ed.). Belmont, CA: Wadsworth.
Crosnoe, R., & Benner, A. D. (2015). Children at school. In M. H. Bornstein, T. Leventhal, & R. M. Lerner (Eds.). Handbook of child psychology and developmental science: Ecological settings and processes (pp. 268-304). Hoboken, NJ: John Wiley & Sons Inc.
De Wit, D. J., Karioja, K., Rye, B. J., & Shain, M. (2011). Perceptions of declining classmate and teacher support following the transition to high school: Potential correlates of increasing student mental health difficulties. Psychology in the Schools, 48, 556-572.
Dishion, T. J., & Tipsord, J. M. (2011). Peer contagion in child and adolescent social and emotional development. Annual Review of Psychology, 62, 189–214.
Dobbs, D. (2012). Beautiful brains. National Geographic, 220(4), 36. Dolgin, K. G. (2011). The adolescent: Development, relationships, and culture (13th ed.). Boston, MA: Pearson.
Duchesne, S., Larose, S., & Feng, B. (2019). Achievement goals and engagement with academic work in early high school: Does seeking help from teachers matter? Journal of Early Adolescence, 39(2), 222-252.
Dudovitz, R.N., Chung, P.J., Elliott, M.N., Davies, S.L., Tortolero, S,… Baumler, E. (2015). Relationship of age for grade and pubertal stage to early initiation of substance use. Preventing Chronic Disease, 12, 150234. doi:10.5888/pcd12.150234.
Eccles, J. S., & Rosner, R. W. (2015). School and community influences on human development. In M. H. Bornstein & M. E. Lamb (Eds.), Developmental science (7th ed.). NY: Psychology Press.
Elkind, D. (1967). Egocentrism in adolescence. Child Development, 38, 1025-1034.
Euling, S. Y., Herman-Giddens, M.E., Lee, P.A., Selevan, S. G., Juul, A., Sorensen, T. I., Dunkel, L., Himes, J.H., Teilmann, G., & Swan, S.H. (2008). Examination of US puberty-timing data from 1940 to 1994 for secular trends: panel findings. Pediatrics, 121, S172-91. doi: 10.1542/peds.2007-1813D.
Eveleth, P. & Tanner, J. (1990). Worldwide variation in human growth (2nd edition). New York: Cambridge University Press.
Furman, W., & Shaffer, L. (2003). The role of romantic relationships in adolescent development. In P. Florsheim (Ed.), Adolescent romantic relations and sexual behavior: Theory, research, and practical implications (pp. 3–22). Mahwah, NJ: Erlbaum.
Garcia, A. R., Metraux, S., Chen, C., Park, J., Culhane, D., & Furstenberg, F. (2018). Patterns of multisystem service use and school dropout among seventh-, eighth-, and ninth-grade students. Journal of Early Adolescence, 38(8), 1041-1073.
Giedd, J. N. (2015). The amazing teen brain. Scientific American, 312(6), 32-37. Goodman, G. (2006). Acne and acne scarring: The case for active and early intervention. Australia Family Physicians, 35, 503- 504.
Graber, J. A. (2013). Pubertal timing and the development of psychopathology in adolescence and beyond. Hormones and Behavior, 64, 262-289.
Grotevant, H. (1987). Toward a process model of identity formation. Journal of Adolescent Research, 2, 203-222
Harter, S. (2006). The self. In N. Eisenberg (Ed.), Handbook of child psychology: Vol. 3 Social, emotional, and personality development (6th ed., pp. 505-570). Hoboken, NJ: Wiley.
Harter, S. (2012). Emerging self-processes during childhood and adolescence. In M. R. Leary & J. P. Tangney, (Eds.), Handbook of self and identity (2nd ed., pp. 680-715). New York: Guilford.
Hihara, S., Umemura, T., & Sigimura, K. (2019). Considering the negatively formed identity: Relationships between negative identity and problematic psychosocial beliefs. Journal of Adolescence, 70, 24-32.
Hudson, J. I., Hiripi, E., Pope, H. G., & Kessler, R. C. (2007). The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication. Biological Psychiatry, 61(3), 348-358.
Insurance Institute for Highway Safety. (2017). Fatality facts: Teenagers 2016. Retrieved from http://www.iihs.org/iihs/topics/t/teenagers/fatalityfacts/teenagersExternal
Kahneman, D. (2011). Thinking, fast and slow. New York NY: Farrar, Straus and Giroux.
Kim-Spoon, J., Longo, G.S., & McCullough, M.E. (2012). Parent-adolescent relationship quality as moderator for the influences of parents’ religiousness on adolescents’ religiousness and adjustment. Journal or Youth & Adolescence, 41 (12), 1576-1578.
King’s College London. (2019). Genetic study revelas metabolic origins of anorexia. Retrieved from www.sciencedaily.com/releases/2019/07/190715164655.htm
Klaczynski, P. (2001). Analytic and heuristic processing influences on adolescent reasoning and decision-making. Child Development, 72 (3), 844-861.
Klauer, S. G., Gun, F., Simons-Morton, B. G., Ouimet, M. C., Lee, S. E., & Dingus, T. A. (2014). Distracted driving a risk of road crashes among novice and experienced drivers. New England Journal of Medicine, 370, 54-59. doi: 10.1056/NEJMsa1204142
Kuhn, D. (2013). Reasoning. In. P.D. Zelazo (Ed.), The Oxford handbook of developmental psychology. (Vol. 1, pp. 744-764). New York NY: Oxford University Press.
Lee, J. C., & Staff, J. (2007). When work matters: The varying impact of work intensity on high school dropout. Sociology of Education, 80(2), 158–178.
Longest, K. C., & Shanahan, M. J. (2007). Adolescent work intensity and substance use: The mediational and moderational roles of parenting. Journal of Family and Marriage, 69(3), 703-720.
Luciano, M., & Collins, P. F. (2012). Incentive motivation, cognitive control, and the adolescent brain: Is it time for a paradigm shift. Child Development Perspectives, 6 (4), 394-399.
March of Dimes. (2012). Teenage pregnancy. Retrieved from http://www.marchofdimes.org/materials/teenage-pregnancy.pdf
Marcia, J. (2010). Life transitions and stress in the context of psychosocial development. In T.W. Miller (Ed.), Handbook of stressful transitions across the lifespan (Part 1, pp. 19-34). New York, NY: Springer Science & Business Media.
Marsh, H. W., & Kleitman, S. (2005). Consequences of employment during high school: Character building, subversion of academic goals, or a threshold? American Educational Research Journal, 42, 331–369.
McAdams, D. P. (2013). Self and Identity. In R. Biswas-Diener & E. Diener (Eds), Noba textbook series: Psychology. Champaign, IL: DEF publishers. Retrieved from: nobaproject.com.
McClintock, M. & Herdt, G. (1996). Rethinking puberty: The development of sexual attraction. Current Directions in Psychological Science, 5, 178-183.
Meeus, W., Branje, S., & Overbeek, G. J. (2004). Parents and partners in crime: A six-year longitudinal study on changes in supportive relationships and delinquency in adolescence and young adulthood. Journal of Child Psychology & Psychiatry, 45(7), 1288-1298. doi:10.1111/j.1469-7610.2004.00312.x
Mendle, J., Harden, K. P., Brooks-Gunn, J., & Graber, J. A. (2010). Development’s tortoise and hare: Pubertal timing, pubertal tempo, and depressive symptoms in boys and girls. Developmental Psychology, 46,1341–1353. doi:10.1037/a0020205
Mendle, J., Harden, K. P., Brooks-Gunn, J., & Graber, J. A. (2012). Peer relationships and depressive symptomatology in boys at puberty. Developmental Psychology, 48(2), 429–435. doi: 10.1037/a0026425
Miller, B. C., Benson, B., & Galbraith, K. A. (2001). Family relationships and adolescent pregnancy risk: A research synthesis. Developmental Review, 21(1), 1-38. doi:10.1006/drev.2000.0513
National Center for Health Statistics. (2014). Leading causes of death. Retrieved from: http://webappa.cdc.gov/sasweb/ncipc/leadcaus10_us.html
National Center for Statistics and Analysis. (2016, May). Young drivers: 2014 data. (Traffic Safety Facts. Report No. DOT HS 812 278). Washington, DC: National Highway Traffic Safety Administration. Retrieved from: http://wwwnrd.nhtsa.dot.gov/Pubs/812278.pdf
National Eating Disorders Association. (2016). Health consequences of eating disorders. Retrieved from https://www.nationaleatingdisorders.org/health-consequences-eating-disorders
National Institutes of Mental Health. (2016). Eating disorders. Retrieved from https://www.nimh.nih.gov/health/topics/eating-disorders/index.shtml
National Sleep Foundation. (2016). Teens and sleep. Retrieved from https://sleepfoundation.org/sleep topics/teens-and-sleep
Nelson, A., & Spears Brown, C. (2019). Too pretty for homework: Sexualized gender stereotypes predict academic attitudes for gener-typical early adolescent girls. Journal of Early Adolescence, 39(4), 603-617.
Office of Adolescent Health. (2018). A day in the life. Retrieved from https://www.hhs.gov/ash/oah/facts-and-stats/day-in-thelife/index.html
Pew Research Center. (2015). College-educated men taking their time becoming dads. Retrieved from http://www.pewresearch.org/fact-tank/2015/06/19/college-educated-men-take-their-time-becoming-dads/
Phinney, J. S. (1989). Stages of ethnic identity development in minority group adolescents. Journal of Early Adolescence, 9, 34- 49.
Phinney, J. S. (1990). Ethnic identity in adolescents and adults: Review of research. Psychological Bulletin, 108(3), 499-514. doi:10.1037/0033-2909.108.3.499
Phinney, J. S. (2006). Ethnic identity exploration. In J. J. Arnett & J. L. Tanner (Eds.) Emerging adults in America: Coming of age in the 21st Century. (pp. 117-134) Washington DC: American Psychological Association.
Rawatlal, N., Kliewer, W., & Pillay, B. J. (2015). Adolescent attachment, family functioning and depressive symptoms. South African Journal of Psychiatry, 21(3), 80-85. doi:10.7196/SAJP.8252
Rosenbaum, J. (2006). Reborn a virgin: Adolescents’ retracting of virginity pledges and sexual histories. American Journal of Public Health, 96(6), 1098-1103.
Ryan, A. M., Shim, S. S., & Makara, K. A. (2013). Changes in academic adjustment and relational self-worth across the transition to middle school. Journal of Youth and Adolescence, 42, 1372-1384.
Russell, S. T., Clarke, T. J., & Clary, J. (2009). Are teens “post-gay”? Contemporary adolescents’ sexual identity labels. Journal of Youth and Adolescence, 38, 884–890.
Sadker, M. (2004). Gender equity in the classroom: The unfinished agenda. In M. Kimmel (Ed.), The gendered society reader, 2nd edition. New York: Oxford University Press.
Schwartz, P. D., Maynard, A. M., & Uzelac, S. M. (2008). Adolescent egocentrism: A contemporary view. Adolescence, 43, 441- 447.
Seifert, K. (2012). Educational psychology. Retrieved from http://cnx.org/content/col11302/1.2
Shin, H., & Ryan, A. M. (2014). Early adolescent friendships and academic adjustment: Examining selection and influence processes with longitudinal social network analysis. Developmental Psychology, 50(11), 2462-2472.
Shomaker, L. B., & Furman, W. (2009). Parent-adolescent relationship qualities, internal working models, and attachment styles as predictors of adolescents’ interactions with friends. Journal or Social and Personal Relationships, 2, 579-603.
Sinclair, S., & Carlsson, R. (2013). What will I be when I grow up? The impact of gender identity threat on adolescents’ occupational preferences. Journal of Adolescence, 36(3), 465-474.
Smetana, J. G. (2011). Adolescents, families, and social development. Chichester, UK: Wiley-Blackwell. Soller, B. (2014). Caught in a bad romance: Adolescent romantic relationships and mental health. Journal of Health and Social Behavior, 55(1), 56-72.
Staff, J., Schulenberg, J. E., & Bachman, J. G. (2010). Adolescent work intensity, school performance, and academic engagement. Sociology of Education, 83, p. 183–200.
Staff, J., Van Eseltine, M., Woolnough, A., Silver, E., & Burrington, L. (2011). Adolescent work experiences and family formation behavior. Journal of Research on Adolescence, 22(1), 150-164. doi:10.1111/j.1532-7795.2011.00755.x
Steinberg, L., Icenogle, G., Shulman, E.P., et al. (2018). Around the world, adolescence is a time of heightened sensation seeking and immature self-regulation. Developmental Science, 21, e12532. https://doi.org/10.1111/desc.12532
Syed, M., & Azmitia, M. (2009). Longitudinal trajectories of ethnic identity during the college years. Journal of Research on Adolescence, 19, 601-624. doi:10.1111/j.1532-7795.2009.00609.x
Syed, M., & Juang, L. P. (2014). Ethnic identity, identity coherence, and psychological functioning: Testing basic assumptions of the developmental model. Cultural Diversity and Ethnic Minority Psychology, 20(2), 176-190. doi:10.1037/a0035330
Tartamella, L., Herscher, E., Woolston, C. (2004). Generation extra large: Rescuing our children from the obesity epidemic. New York: Basic Books.
Taylor, J. & Gilligan, C., & Sullivan, A. (1995). Between voice and silence: Women and girls, race and relationship. Cambridge, MA: Harvard University Press.
Thomas, R. M. (1979). Comparing theories of child development. Santa Barbara, CA: Wadsworth.
Troxel, W. M., Rodriquez, A., Seelam, R., Tucker, J. Shih, R., & D’Amico. (2019). Associations of longitudinal sleep trajectories with risky sexual behavior during late adolescence. Health Psychology. Retrieved from https://psycnet.apa.org/doiLanding?doi=10.1037%2Fhea0000753
Umana-Taylor, A. (2003). Ethnic identity and self-esteem. Examining the roles of social context. Journal of Adolescence, 27, 139-146.
United States Census. (2012). 2000-2010 Intercensal estimates. Retrieved from http://www.census.gov/popest/data/index.html
United States Department of Education. (2018). Trends in high school dropout and completion rates in the United States: 2018. Retrieved from https://nces.ed.gov/pubs2019/2019117.pdf
United States Department of Labor, Bureau of Labor Statistics (2016). Employment projections. Retrieved from http://www.bls.gov/emp/ep_chart_001.htm
United States Department of Labor, Office of Disability Employment Policy. (2019). School based prepatory experiences. Retrieved from: https://www.dol.gov/odep/categories/youth/school.htm
University of California at Los Angeles Medical Center. (2000). Acne. Retrieved from http://www.mednet.ucla.edu
Vaillancourt, M. C., Paiva, A. O., Véronneau, M., & Dishion, T. (2019). How do individual predispositions and family dynamics contribute to academic adjustment through the middle school years? The mediating role of friends’ characteristics. Journal of Early Adolescence, 39(4), 576-602.
Wade, T. D., Keski‐Rahkonen, A., & Hudson, J. I. (2011). Epidemiology of eating disorders. Textbook of Psychiatric Epidemiology, Third Edition, 343-360.
Weintraub, K. (2016). Young and sleep deprived. Monitor on Psychology, 47(2), 46-50. Weir, K. (2015). Marijuana and the developing brain. Monitor on Psychology, 46(10), 49-52.
Weir, K. (2016). The risks of earlier puberty. Monitor on Psychology, 47(3), 41-44.
Yau, J. C., & Reich, S. M. (2018). “It’s just a lot of work”: Adolescents’ self-presentation norms and practices on Facebook and Instagram. Journal of Research on Adolescence, 29(1), 196-209.
Adapted from Chapter 6 from Lifespan Development: A Psychological Perspective Second Edition by Martha Lally and Suzanne Valentine-French under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 unported license.