Self-regulation has been defined as an individual’s ability to control and regulate his/her own actions, cognitions, and emotions as well as the ability to begin and end activities based on situational demands, and to modulate their behavior in social and educational settings (Bronson, 2000). Self-regulation is believed to develop during adolescence and by the age of 13 or 14, adolescents generally develop the ability to be planful with regard to their short- and long-term goals and thus able to regulate their behavior to increase the likelihood that these goals will be attained (Demetriou, 2000). Research suggests that students who engage in self-regulatory behavior do better in school (Pintrich, 2000) and that students who observe and evaluate their performance accurately can react appropriately by keeping or changing their study strategies to achieve optimal results (Hartman, 2001). Bakracevic Vukman and Licardo (2010) examined the relationship between self-regulation and school achievement. Results indicated that metacognitive self-regulation was found to be an important predictor of school achievement in both primary and secondary school students, with self-regulation explaining 21 % of the variance of school performance their secondary school sample.

The process of self-regulation includes three subprocesses: self-monitoring, self-evaluation, and behavioral adjustment (Singer & Bashir, 1999). The question then arises: can self-regulation skills be improved via directed interventions? Research has consistently demonstrated that direct instruction, modeling, and practice and feedback have all been found effective in teaching students self-monitoring and self-regulation procedures which have subsequently been found to improve both academic performance and classroom behavior (Coleman & Webber, 2002; Zimmerman, 1996).

Two psychological disorders which can have a major impact on both academic achievement and graduation are depression and conduct disorder. An increase in adjustment problems, such as depression, is not uncommon during adolescent development (Graber, 2004). The rate of depression increases throughout the adolescent years, with a rate of 3.9 % for 12-year-olds, 11.6 % for 16-year-olds, and 10.6 % for 17-year-olds with the rate among girls being three times that for boys (National Institute for Mental Health, 2010). By later adolescence, the prevalence of major depression is very similar to prevalence for adults (Hankin, 2006) with 18–24-years-olds having the highest rate of overall depression of any age group (Centers for Disease Control and Prevention, 2011).

Depression in adolescence has been found to be related to academic performance and high school graduation (Humensky et al., 2010). For example, Wilcox-Gok, Marcotte, Farahati, and Borkoski (2004) found that men who retrospectively recalled onset of depression prior to age 16 were less likely to graduate from high school. Similarly, Fletcher (2008) found that adolescent girls diagnosed with depression were less likely to graduate from high school or enroll in college. In addition, Ding, Lehrer, Rosenquist, and Audrain-McGovern (2009) found that female adolescents with depression had greater decreases in school performance than males.

Humensky and colleagues (2010) examined school performance among adolescents at risk for major depression. Results indicated that the relationship between depressive symptoms and actual school performance was not statistically significant; however, adolescent perception of functioning and school performance was related to depressive symptoms. They found that depressive symptoms affected adolescents’ perception of their ability to perform in school, do their homework, concentrate, and engage in other adaptive academic behaviors.

Fröjda et al. (2008) found, in a large sample of Finnish 7th through 9th graders, that when participants reported a lower GPA or when their academic performance had decreased from the previous term, they were more likely to self-report depressive symptoms at a level consistent with moderate to severe depression. A relationship was also found between depression and other factors such as concentration and social relationships. The study concluded that the lower a student’s GPA, the higher the likelihood of them being depressed.

Conduct-disordered (CD) youth are at an even greater risk of failure to achieve academically. That is because, by definition, children and adolescents diagnosed with CD are likely to eventually come into contact with the criminal justice system. Virtually every one of the 15 criteria listed in the DSM-IV for CD involves a behavior that, if manifested to a sufficient magnitude and chronicity, will eventually lead to arrest and possible incarceration. This generally necessitates dismissal from school or low attendance which can negatively affect both grades and graduation rate. Grisso (1998) reviewed the epidemiological research with regard to the prevalence of childhood mental disorders in delinquent populations and found that CD is the most prevalent diagnosis with a rate probably about 50–60 %.

In terms of prevalence, conduct disorder is diagnosed more frequently in males than females. A study by Keenan, Wroblewski, Hipwell, Loeber, and Stouthamer-Loeber (2010) indicated 2–16 % of boys and 1–9 % of girls may be diagnosed. Age of onset is an additional important consideration. However, presently, data are somewhat sparse regarding developmental patterns particularly for females. Some authors have suggested a need to consider differing criteria for girls in terms of overt versus covert aggression in the diagnosis of CD (Delligatti, Akin-Little, & Little, 2003).

Kazdin (1998) and Sholevar and Sholevar (1995) both discuss the correlation between school-related factors and CD. These factors include attending school where little emphases is placed on academic work, the poor physical condition of the school building(s), infrequent use of teacher praise, low teacher expectancy, and teacher unavailability to deal with students’ problems. Given the lack of promise to both scholastic achievement and graduation for students diagnosed with CD (Boden, Fergusson, & Horwood, 2010), all studies emphasize the critical nature of early, wraparound (i.e., inclusion of school and familial environment), efficacious intervention (e.g., Murray & Farrington, 2010).

Finally, Crick and Dodge (1994) present a reformulated social information-processing (SIP) model that can help explain the development of aggressive and antisocial behavior in school-age children. They proposed that children process social information in six steps: (1) encoding cues, (2) interpreting cues, (3) clarifying goals, (4) accessing or constructing responses, (5) deciding on responses, and (6) enacting behaviors. Research has consistently supported links between this model and overt aggressive behavior, particularly in boys (Crick & Dodge, 1996; Dodge et al., 2003). In addition, social rejection, as predicted from this model, has been found to reduce inhibit classroom participation (Ladd, 2008) and increase antisocial behavior (Martens & Witt, 2004).

Obesity is usually defined as having a body mass index (BMI) of 30 or greater (Centers for Disease Control and Prevention, 2010). Further the CDC has identified obesity rates in the United States ranging from a low of 18.6 % of the population in Colorado to a high of 34.4 % of the population in Mississippi with African Americans and Hispanics both having a higher rate of obesity than Whites (51 % and 21 % higher, respectively) with similar patterns found in children and adolescents (Ogden, Carroll, Curtin, Lamb, & Flegal, 2010). Sabia (2007) found a consistent negative relationship between BMI and grade point average (GPA) for white adolescent females. In a review of research on the association between obesity and academic performance in school-age children, Taras and Potts-Datema (2005) concluded being overweight or obese was associated with lower academic achievement; however, the directionality of this relationship is not clear.

Studies have shown that there is also a relationship between obesity and low self-esteem and mental health conditions such as anxiety and depression (Zametkin, Zoon, Klein, & Munson, 2004). It is entirely possible that it is these conditions that predispose children and adolescents to both obesity and poor school performance (Datar, Sturm, & Magnabosso, 2004). However, in a study of Korean adolescents, Cho, Lambert, Kim, and Kim (2009) concluded from their data that obesity and poor academic performance are simultaneously determined.

Chronic medical conditions are defined as those having debilitating symptoms or which last for more than 3 months a year (Thompson & Gustafson, 1996) and include developmental illnesses (e.g., cerebral palsy) and chronic diseases (e.g., diabetes, epilepsy). About 10.3 million children and adolescents in the United States have chronic medical conditions or illnesses, which involve limitations in cognitive, physical, or psychosocial development (Algozzine & Ysseldyke, 2006; Valletutti, 2004; Walsh & Murphy, 2003). In addition, about 4.4 million children with chronic conditions face problems hindering their participation in school (Kaffenberger, 2006; Thies & McAllister, 2001) which may interfere with their school performance (Nabors, Little, Akin-Little, & Iobst, 2008).

It is not uncommon for factors related to the chronic illness and not the illness itself to contribute to poor academic performance. Smith, Taylor, Newbould, and Keady (2008) suggested that the adverse effects of medication may be related to school performance. Calsbeek, Rijken, Bekkers, Dekker, and van Berge Henegouwen (2006) examined adolescents and young adults with chronic digestive disorders and found a relationship between the disease and academic performance. Their conclusions, however, was that it was depression associated with the disease that led to the academic difficulties and not the disease itself. McNelis, Johnson, Huberty, and Austin (2005) examined the relationship between chronic epilepsy and academic performance. While their results indicated that most students with chronic seizures perform in the average range, teachers rate 25 % as at or below one standard deviation of the mean. Similarly, Nabors and colleagues’ (2008) results indicated that relatively few teachers in their survey indicated having high knowledge of chronic illnesses or confidence in working with students with all but the most common chronic illnesses (e.g., asthma). Spilkin and Ballantyne (2007) found that while children with cystinosis, a genetic disorder characterized by the abnormal accumulation of the amino acid cystine, may have real academic limitations related to their disease, teachers do not always recognize this and misattribute it to laziness. Finally, in discussing children with cancer and academic performance, Armstrong and Horn (1995) noted that school performance may be affected by the cancer but the type and severity of the performance deficit is dependent on the type and location of the tumor. Further, cancer treatments (e.g., radiation, chemotherapy) may interfere with a child or adolescent’s ability to attend school or result in long-term cognitive deficits (e.g., processing speed) which may affect school performance.

Approximately 750,000 girls and women age 15–19 become pregnant each year in the United States, with 59 % of these pregnancies resulting in birth (Guttmacher Institute, 2010), a rate nearly twice that of Canada (McKay & Barrett, 2010). Teenage childbearing has been found to have unfavorable outcomes for both mother and child (Meade, Kershaw, & Ickovics, 2008), including lower educational attainment (Coley & Chase-Lansdale, 1998). For example, Jones, Astone, Keyl, Kim, and Alexander (1999) found that teen childbearing reduces the probability of completing high school by 8–10 %.

Unfortunately, it is not uncommon for adolescents to be exposed to traumatic events (Little, Akin-Little & Somerville, in press). Children and adolescents may experience a number of different types of trauma. These can include abuse (e.g., sexual, physical), grief, exposure to domestic and community violence, natural disasters, or a combination of the above (Little, Akin-Little, & Gutierrez, 2009). Felitti and colleagues (1998) conducted a retrospective study of over 17,000 adults and found that more than one half of their sample reported experiencing at least one adverse event in childhood with approximately one quarter reporting having experienced two or more.

While not every child exposed to a traumatic event experiences negative outcomes, trauma symptoms are not uncommon and have been categorized into four domains: affective, behavioral, cognitive, and physical (Cohen, Mannarino, & Deblinger, 2006). Common affective symptoms include fear, depression, anger, and frequent mood changes; behavioral symptoms usually center on avoiding reminders of the trauma; cognitive symptoms usually involve distorted cognitions about themselves, others, the event, or the world (e.g., “the event is my fault”); and physical symptoms include stress related responses such as elevated heart rates and blood pressure, increased muscle tension, and hypervigilance. It has also been found that prolonged exposure to trauma and maltreatment can decrease brain size and functioning (De Bellis et al., 1999). With regard to school performance, few studies exist that directly relate trauma exposure to decreases in school performance. The trauma symptoms described by Cohen and colleagues above all are likely to have an impact on school performance however. In one of the few empirical studies comparing trauma exposure to a no trauma control group, Green et al. (2001) found that a traumatic loss group had higher rates of impaired school performance compared to the no trauma control group. Similarly, in a more recent study from the UK, Abdelnoor and Hollins (2004) found significant underachievement in secondary school performance for adolescents who lost a parent to death.