A Perspective on Revising OSEP Indicator 14

Extending the Indicator

According to recent OSEP data, approximately 75% of students with disabilities leave high school at ages 17 or 18 (U.S. Department of Education OSEP, 2010). ¹ Under current Indicator 14 guidelines, this obligates states to track students until age 18 or 19. In effect, transition services intended to prepare students for adult living are based on data gathered from late-stage adolescents. ² Services based on data gathered from former students who have reached adulthood are likely more relevant and effective.

This proposed shift is buttressed by recent neuroscientific research, which has revealed important and fundamental distinctions between adolescents and adults. While human beings develop during adolescence many of the traits and characteristics they carry into adulthood, the differences between these two stages are numerous and significant, particularly with regard to transition services. From a neurological perspective, adolescents are not yet adults; faculties such as behavior regulation, planning, and decision making are still works in progress.

Broadening the Indicator

Indicator 14 has the potential to offer a more comprehensive picture of transition services that is better aligned with the federal law. As noted earlier, the IDEA indicates that such services should improve the academic and functional achievement of students with disabilities and help prepare them for postschool adult living. The act specifically refers to education, employment, independent living, and community participation. Although Indicator 14 captures some important data on education and employment outcomes, it neither gauges whether youth with disabilities successfully complete postsecondary education programs nor provides details indicating the quality or type of employment in which youth with disabilities are engaged. Furthermore, it does not provide information regarding independent living or community participation. An Indicator 14 that addresses these outcomes would provide policy makers and transition service providers a more accurate, and useful, gauge of their services in the context of the IDEA. Data that are culled from a bolstered Indicator 14 can shape programming that is more responsive to the postschool realities, challenges, and opportunities that await youth with disabilities.

Recent research suggests that broadening the indicator is an important endeavor, given the shifts in various areas of life (e.g., education, employment, living arrangements, marriage, children) that youth with disabilities experience as they move further from their high school years, from adolescence to adulthood. Data on these changes can provide further relevant information on their postschool adult lives. New research from National Longitudinal Transition Study-2 (NLTS2) that provides illuminating data on these outcomes will be discussed.

Adolescents Are Not Adults

Taken together, findings from recent research on adolescents—and specifically youth with disabilities—affirm an important point: Adolescents are not adults. Indeed, Halpern (1992) noted that the first few years after an adolescent leaves school are typically spent on a search for adulthood. He referred to transition as “a period of floundering that occurs for at least the first several years after leaving school as adolescents attempt to assume a variety of adult roles in their communities” (p. 203). As such, data regarding their outcomes should not be the primary source of information used in crafting transition services intended to prepare students with disabilities for postschool adult lives. Such information should come from individuals who have on various levels—neurologically, behaviorally, and functionally—reached adulthood.

Pruning

The proliferation of gray matter in the prefrontal cortex found by Giedd et al. (1999) is subsequently tempered throughout the remainder of adolescence by synaptic pruning, a process in which underutilized synapses are eliminated. Although relatively little is known about its causes, pruning is considered necessary for neurological development (Toga, Thompson, & Sowell, 2006). It renders the brain and its remaining synaptic circuitry more efficient, discarding unnecessary connections and permitting the brain to “fine-tune” those that are found to be more useful (Blakemore & Choudhury, 2006).

Research indicates that the volume of gray matter in the frontal lobe peaks during early adolescence. After this point, the amount of gray matter drops precipitously through age 22 (Giedd et al., 1999). Sowell, Thompson, Tessner, and Toga (2001) and Sowell, Thompson, and Toga (2004) reported a similar pattern, in which adults (aged 23–30 years) lost gray matter at a significantly greater rate than adolescents (aged 12–16 years). A longitudinal study by Gogtay et al. (2004) found that gray matter pruning occurred in a posterior to anterior pattern, with the prefrontal cortex the last to lose gray matter, at the end of adolescence (17–19 years). After adolescence, during the early to mid-20s, pruning begins to slow as gray matter reaches typical adult levels (Giedd, 2004; Huttenlocher, 1979).

Myelination

Whereas synaptic pruning eliminates weaker, underutilized synapses, connections that are frequently engaged are strengthened through myelination, in which a lipid-based layer sheaths an axon, increasing the speed of neural communication (Blakemore & Choudhury, 2006; Sowell et al., 2001). These myelinated connections—also referred to as white matter—allow the brain to operate in a more efficient manner. As with pruning, myelination typically proceeds from the posterior of the brain to the anterior (Fields, 2005; Lenroot & Giedd, 2006). Research suggests that myelination starts prior to birth and increases in intensity throughout childhood and adolescence, reaching its peak during the early to mid-20s. At this point, the intensity of myelination levels off and continues through adulthood at a decreased rate (Benes, 1989; Benes, Turtle, Khan, & Farol, 1994; Giedd, 2004; Yakovlev & Lecours, 1967).

Dopaminergic Activity

Neurotransmitters, chemicals that transmit signals between cells, impact which synapses are pruned and which axons are myelinated. Dopamine is one type of neurotransmitter that plays a critical role in neurological development during adolescence. It is necessary for proper working memory, attention, and decision-making functioning in the prefrontal cortex. Research suggests that a certain level of dopamine is required for adequate operation of these faculties. However, deviation from this level, particularly an increase in dopamine, may impair the prefrontal cortex (Murphy, Arnsten, Goldman-Rakic, & Roth, 1996; Sawaguchi & Goldman-Rakic, 1991, 1994).

Dopamine release is regulated by the nucleus accumbens, a section of the limbic system that interfaces with—and develops more rapidly than—the prefrontal cortex (Casey, Jones, & Hare, 2008). Steinberg (2008) posited that the dopaminergic pathways (which include the nucleus accumbens, amygdala, the prefrontal cortex, among other components) undergo significant remodeling during adolescence, causing a unique spike in dopaminergic activity in the prefrontal cortex and, consequently, increased sensation-seeking activity. This susceptibility toward willfully engaging in risk-taking behavior will be discussed later in the article.

Behavior Regulation

One distinct contrast between adult and adolescent behavior is the capacity to inhibit impulsivity. Casey et al. (1997) found that preadolescent and early adolescent children had more difficulty inhibiting responses, and were more likely to inaccurately respond to stimuli, than adults ages 21 through 24 years. This finding was corroborated by Williams, Ponesse, Schachar, Logan, and Tannock (1999), who reported that the accuracy of inhibitory responses increased throughout adolescence, peaking in adulthood. Results from Williams et al. and Bedard et al. (2002) suggest that inhibitory response speed follows a similar pattern (increasing through adolescence, reaching its peak in early adulthood).

Planning

Research by Barkley (1997) indicates that difficulties with behavior regulation contribute to deficiencies in working memory and, subsequently, planning ability. Luna, Garver, Urban, Lazar, and Sweeney (2004) highlighted the importance of working memory in planning, noting that the former facilitates the preparation and maintenance of plans until the optimal time for their usage. Difficulties with working memory, particularly with holding ideas in mind, are associated with poor planning abilities (Miller & Cummings, 2007).

Swanson (1999) reported that adults displayed higher levels of working memory functioning than children and adolescents. This is in line with functional magnetic resonance and diffusion tensor imaging studies by Olesen, Nagy, Westerberg, and Klingberg (2003) and Nagy, Westerberg, and Klingberg (2004), which found that working memory improved as the levels of white matter (i.e., myelinated axons) increased into adulthood.

Accordingly, research has found that planning improves throughout adolescence, into adulthood. Albert and Steinberg (2011), using the Tower of London assessment (a commonly used test of strategic planning), measured the performance of nearly 900 individuals ranging in age from 10 to 30 years. The results suggest that young adults ages 22 to 25 years were more adept than adolescents (10 to 17 years) at solving more challenging strategic problems. Although the maturation of working memory and impulse control abilities benefitted adolescents, young adults were impacted more by improvements in impulse control. These findings are similar to those of De Luca et al. (2003), who found that the abilities to strategically plan and to organize goal-directed behavior peaked during one’s 20s (ages 20 to 29 years).

Decision Making

Just as the ability to regulate behavior during adolescence impacts planning, it also plays a significant role in decision making. Numerous works discuss the presence of heightened risk-taking characteristics in adolescents. Statistics on indicators such as car accidents, sexually transmitted diseases (including HIV/AIDS), and detrimental health choices (e.g., smoking) support this finding (Reyna & Rivers, 2008; Romer, 2003; Spear, 2000). Research by Reyna et al. (2011) demonstrates that adolescents and young adults consider risk in fundamentally different ways. Adolescents are more likely to view risk on a surface level, interpreting risk-taking decisions in a literal (i.e., verbatim) manner. Adults, in contrast, are more likely to focus on the gist or the “essential meaning” of a risk. They found that verbatim-based thinking was associated with increased risky behaviors, noting that this type of thinking “promotes unhealthy risk taking because the benefits of risky behavior are often high whereas the risks are often low, producing a rational calculus of risk promotion” (Reyna et al., 2011, p. 1139).

This pattern of risk assessment is consistent with research by Galvan et al. (2006), which suggests that suboptimal decision making in adolescents, driven by immediate, reward-seeking behavior and a bias toward short-term (vs. long-term) gain, may be caused by the nucleus accumbens and the related elevated levels of dopaminergic activity during adolescence. They posited that, in conjunction with a slowly developing prefrontal cortex (in which activity levels in adolescents more closely resemble those of children rather than adults), activity from a more rapidly maturing nucleus accumbens may be at the root of the poor decision making that increases adolescents’ vulnerability to drug use and addiction. Findings from research by Eshel, Nelson, Blair, Pine, and Ernst (2007) also note adolescents’ limited use of the prefrontal cortex, compared with adults. In making financial decisions involving significant amounts of risk, they found that adolescents tend to rely less on the regulatory components (e.g., orbitofrontal cortex, ventrolateral prefrontal cortex) of the prefrontal cortex than their adult counterparts.

Steinberg (2008) stated that risk-taking behaviors typically decline during the mid-20s due to improvements in cognitive control, the ability to willingly regulate one’s own behavior. This is consistent with results from testing on go/no-go tasks, which suggest that adults, due to advanced maturation of frontostriatal connectivity, are more likely to display a capacity for cognitive control than children and adolescents (Liston et al., 2006).

Atypical Development

The course of development described thus far is a part of the typical neurological and behavioral maturation processes that occur in youth. Pruning, myelination, and dopaminergic activity impact how each individual’s brain functions, and the skills, abilities, and temperament they acquire. Whereas many individuals with disabilities experience such developmental patterns at the specified benchmarks, others may not. For these students, development may be delayed or absent. For example, research indicates that youth with reading difficulties may experience atypical neurological development, as evidenced by the reduced size of certain areas of the cerebral cortex (e.g., the insula, planum temporale) and by the underactivation of the areas of the brain related to word recognition (e.g., the left fusiform gyrus; Hynd, Semrud-Clikeman, Lorys, Novey, & Eliopulos, 1990; Semrud-Clikeman, n.d.; Shaywitz, 2005). These deficits, however, can be remediated by intensive training that focuses on phonological awareness. Recent studies indicate that students undergoing such interventions experience significant improvements in their reading abilities, while demonstrating brain activity similar to that of children without reading difficulties (Meyler, Keller, Cherkassky, Gabrieli, & Just, 2008; Noble, Tottenham, & Casey, 2005). Such delays in development—and the potential remediation of them—further underscore the importance of extending the scope of Indicator 14 beyond 1 year.

Works in Progress

Many of the executive functioning capacities that evolve during adolescence are housed in the prefrontal cortex. It is this area of the brain that is typically the last to reach maturity, typically during one’s 20s, as indicated by pruning, myelination, and dopaminergic activities (Giedd, 2004; Lenroot & Giedd, 2006; Steinberg et al., 2008). These patterns of neurological and behavioral development lend credence to the words of Weinberger, Elvevåg, and Giedd (2005):

Teens are full of promise, often energetic and caring, capable of making many contributions to their communities, and able to make remarkable spurts in intellectual development and learning. But neurologically, they are not adults. They are . . . a work in progress. (p. 3)

Education

As indicated in the NLTS2 and other studies, the differences are readily apparent in the domain of postsecondary education. Many individuals with disabilities seek to further their education after the first couple of years out of high school. In 2005, 30% of students who were out of high school for 2 years or less had engaged in a postsecondary education program (Wagner, Newman, Cameto, Garza, & Levine, 2005). In 2011, this figure rose dramatically: 60% of students out of school for up to 8 years were in such programs (Newman et al., 2011). Furthermore, students with disabilities who are in a postsecondary education program are typically beyond adolescence. According to a 2009 U.S. Government Accountability Office report, postsecondary students with a disability are, on average, 26 years of age. Nearly half of all undergraduate students with disabilities are 24 years or older; more than half of all graduate students with disabilities are 30 years of age or older (Snyder & Dillow, 2011).

As such, given its 1-year time frame, Indicator 14 provides little useful data about how individuals with disabilities pursue postsecondary education. Extending the tracking of student enrollment, as well as completion rates, would yield valuable data for transition programs at the secondary level. ⁴ It would also likely bring attention to the barriers that prevent program completion. Compared with their nondisabled peers, students with disabilities are much less likely to graduate from a postsecondary education program (52% vs. 41%). The disparity is magnified in the 4-year college graduation rate: 34% of students with disabilities in this setting complete their degrees, compared with 51% of nondisabled students (Newman et al., 2011). Furthermore, students with disabilities who do graduate tend to take longer to complete their studies than students without disabilities (National Council on Disability, 2003; U.S. Government Accountability Office, 2009). Such barriers are critically important, given the impact education attainment has on many life outcomes. Students with disabilities who complete a postsecondary education program are more likely than non-completers to be employed, to earn more compensation, to live independently, to use financial tools (e.g., checking accounts, credit cards), to have a driver’s license or a learner’s permit, and to engage in social and civic activities (e.g., communicate with friends, register to vote; Newman et al., 2011).

Employment

Like education, tracking the employment outcomes of adolescents for 1 year will likely provide an incomplete picture of their career paths as adults. Following students for an extended period will paint a more complete picture of how their paths unfold—particularly, what opportunities and barriers await them—and of what educational approaches will best prepare them during adolescence.

Age is a significant factor in the employment patterns of youth with disabilities. Indeed, Cameto (2005) noted that “the employment picture in the early transition years for all youth often is characterized by holding several jobs for brief periods. Similarly, long-term employment is fairly rare among youth with disabilities out of school for up to 2 years” (pp. 5–9). According to the American Community Survey, adolescents aged 16 through 20 with disabilities are much less likely be employed than their adult counterparts, ages 21 through 64 (21.2% vs. 36%; Erickson et al., 2010a). Newman et al. (2011) found that individuals with disabilities out of school for less than 3 years were noticeably less likely to have reported working since leaving school than were individuals out of school for three or more years.

Differences in employment characteristics extend to job duration and compensation. The average tenure of employment for youth with disabilities out of school for up to 2 years is 8 months (Cameto, 2005). For individuals out of school for 5 to 8 years, this figure triples, to 27 months (Newman et al., 2011). Correspondingly, this latter group earns a significantly higher average wage (US$11.10 per hour) than those out of school for 5 years or less (US$9.60). Workers with disabilities out of school for 3 years or longer are also much more likely to receive paid vacation or sick leave, health insurance, and retirement benefits than those out of school for 3 years or less (Newman et al., 2011).

Based on employment rates, compensation, and the average duration of employment, it appears that those individuals with disabilities who have been out of school for longer periods of time (5 years or more) are much more likely to be engaged in a career path than those who have been out of school for 2 years or less, who are more likely to be working in a job. The distinctions between a job and a career are significant. Whereas a job is a specific position, a career is a longer endeavor, into which one invests time and effort to acquire the skills and abilities necessary to attain positions of increasing knowledge and importance (U.S. Department of Labor, 2011). The distinction is captured well by former Congressman Tom Delay (2004):

The difference may seem small, but it could not be more important. A job is for survival in the here and now. It is something you do for a paycheck to make ends meet. A career, on the other hand, is for the future. It is long-term security for you and your family. It pushes you to get out of bed in the morning and inspires you with a sense of purpose and the feeling that you are making a contribution, and it is something that stays with you your entire life, not just until you punch out at the end of the day. (p. 11227)

By basing educational programming on employment data gathered from adults, instead of adolescents, with disabilities, schools may be able to better prepare their students to find career fields in which they can develop professionally, as opposed to finding jobs that offer temporary solutions and less room for vocational growth.

Personal Lives: Independent Living, Marriage, and Children

The differences between adolescents and adults with disabilities extend into the more personal domains of living arrangements, marital status, and children. According to recent NLTS2 research, individuals who have been out of high school for longer periods of time are more likely to be living independently, to be married, and to have had or have fathered a child. For example, Newman et al. (2011) found that 3% of individuals out of school for less than 3 years were married. For those who were out of school between 5 and 8 years, this figure rose significantly, to 17%. Likewise, individuals in the latter group were nearly twice as likely as those in the former to live independently or to have children. This pattern of personal development is consistent with patterns found in other NLTS2 reports (Newman et al., 2010; Sanford et al., 2011; Wagner et al., 2005).

What to Follow and for How Long?

Incorporating the tracking of postschool outcomes noted in this article, including postsecondary program completion, employment duration and compensation, independent living, marriage, and having or fathering children, would help bring Indicator 14 into closer alignment with the federal definition of transition services, permitting a more comprehensive and informative view of the adult lives of individuals with disabilities. Completion rates from postsecondary programs are critical harbingers for economic and social success; knowing more about postsecondary experiences may help students with disabilities better navigate the difficult barriers to completion that may await them. Job duration and compensation data may help inform instruction on how to obtain and maintain employment, and highlight for students the importance of finding a career path. Statistics on marriage, children, and independent living could help transition personnel better understand—and address—some of the challenges their students are likely to encounter in the years after high school.

Data from the NLTS2 reveal other factors that could also provide illuminating information. There are some noticeable shifts in area of employment, between individuals out of school for less than 3 years and those out of school longer than 5 years. For example, a member of the former group is more likely to work in food preparation, and much less likely work in education, than an individual in the latter group. Tracking financial independence would also likely yield useful information. NLTS2 data show little difference in measures of financial independence (e.g., having a checking account or a credit card) between youth out of school for shorter periods of time and those out of school for longer periods (Newman et al., 2011). Although financial situations may come as a result of many factors, this lack of growth in financial independence warrants further investigation.

Challenges to Reshaping Indicator 14

If we hope to use Indicator 14 data to shape transition programs to prepare students with disabilities for adult living, such data should come from periods when individuals are firmly ensconced in their adult lives. Based on the research discussed within, a follow-along approach to tracking students, for at least 5 years after high school, would yield useful and relevant information for transition programming. Similar extended time frames have been suggested elsewhere in transition services literature (e.g., Brown et al., 1994).

The extension and broadening of Indicator 14 at the state and local levels will undoubtedly have associated logistical challenges, particularly with regard to financial, personnel, and student tracking issues. However, such challenges are not reasons to stop pursuit of these changes. Several states have already successfully conducted follow-along studies that have yielded valuable data (two notable examples, as detailed in Rabren & Johnson, 2010, are Alabama and Washington). Furthermore, initiatives such as the Statewide Longitudinal Data Systems (SLDS) program hold the promise of more efficient ways by which states can track student outcomes (for further information, see Alverson, Naranjo, Yamamoto, & Unruh, 2010, or the National Center for Education Statistics’ SLDS website nces.ed.gov/programs/slds).

Given the current difficult economic climate, the cost of such changes may be the most difficult barrier to navigate. However, strong arguments exist for bolstered funding for Indicator 14 and for transition services in general. One such justification is based on drop-out prevention. Students with disabilities tend to drop out of school at a higher rate than those without disabilities; in some studies, the rate is nearly twice as often (Reschly & Christenson, 2006). The provision of social services for individuals who drop out comes at a burdensome cost to the public. Levin, Belfield, Muennig, and Rouse (2007) found that, by halving the number of high school dropouts, American taxpayers would save US$45 billion annually in extra tax revenues and in decreased spending on welfare, health care, and criminal justice expenditures. Furthermore, they found that even after providing would-be high school dropouts with additional education interventions, the economic benefit to preventing dropouts totals US$127,000 per student. Programming that is aligned with the transition provisions of the IDEA can play an important role in drop-out prevention efforts for students with disabilities. Information culled from a more comprehensive Indicator 14 can help transition providers shape relevant and purposeful programming that can guide their students away from the lurking pitfalls that frequently cause premature departures from the school system, including academic failure, disinterest in school, and problematic behaviors (Princiotta & Reyna, 2009).

Drop-out prevention efforts for students with disabilities could be further supported through the reinstatement by the federal government of recently cut funding intended to prepare transition service providers, under the Personnel Preparation in Special Education, Early Intervention, and Related Services grant program in the U.S. Department of Education. ⁵ These providers can effectively use data from a bolstered Indicator 14 to craft programming and interventions that are responsive to the strengths, preferences, and interests of students with disabilities, thereby potentially increasing their engagement and investment in the school environment.

Potential Next Steps

The assembly of a technical review board might be helpful in reconsidering the parameters of Indicator 14. Participants should include, at a minimum, the federal government (e.g., OSEP, Office of Elementary and Secondary Education), the National Post-School Outcomes Center, the National Secondary Transition Technical Assistance Center, state and local education agencies, transition coordinators, teachers and administrators, students and families, and researchers from the transition and neuroscientific communities. Such a panel should review not only current follow-up and follow-along studies but also prior research, including the Secondary and Transition Services Follow-Up and Following-Along Projects funded by OSEP in the late 1980s. A review of the products (e.g., replication manuals, annual reports) of these programs, and consultation with the personnel who worked in them, may be instructive to any revision efforts. The panel should also review the methodological recommendations outlined by Halpern (1990) in his review of studies that tracked students with disabilities transitioning from school. In it, he presents several important guidelines for studies that seek to examine the postschool outcomes of these students. Among them are recommendations that researchers, whenever practicable, opt for follow-along studies instead of follow-up studies and that they include a wider, more balanced array of transition-related outcomes (including items such as employment, education, community integration, and personal/social adjustment) rather than solely focusing on readily quantifiable characteristics such as employment.

Indicator 14 is an important part of providing a free and appropriate public education to students with disabilities, particularly with regard to the provision of transition services, as defined by the IDEA. With corresponding supports, the changes described herein can help school personnel maximize the potential of Indicator 14, fostering improved transition programming and outcomes for students with disabilities.