Abstract
While previous research has examined the school-to-work transition of noncollege-bound youth, most have considered how a limited set of variables relate to job attainment at a single point in time. This exploratory study extended beyond the identification of constructs associated with obtaining a job to investigate how several factors, collected longitudinally in adolescence, related to employment stability and job quality with a diverse, nationally representative sample of non-college-bound youth. Logistic regression and structural equation modeling were used to determine the predictors of an adaptive school-to-work transition over time. Depression, substance use, adolescent educational attainment, and employment in adolescence were associated positively with obtaining employment. Adolescent educational attainment and employment in adolescence were associated positively with stability of employment. Depression, adolescent educational attainment, employment in adolescence, and income were positively associated with job quality. Substance use and parental education level were negatively associated with job quality.
When we think of high school students making the transition to adulthood, most of us picture students pursuing a college or university education. However, for some youth, the transition to adulthood is marked by entrance into the workforce, which may or may not include the completion of high school. In October 2009, 29.9% of the graduating class of 2009 was not enrolled in college (Bureau of Labor Statistics, 2010). Often termed the forgotten half, noncollege-bound youth represent an understudied population in the literature (Blustein et al., 2002) whose transition can be challenging as many experience employment and career difficulties (Pinquart, Juang, & Silbereisen, 2003). These youth may have difficulty finding employment, drift from one job to another, and eventually take jobs lacking advancement opportunities (Blustein, Juntunen, & Worthington, 2000). Current career development theories ignore this population and have been criticized for focusing on the needs of the most economically and educationally advantaged youth (Blustein et al., 2000; Worthington & Juntunen, 1997). In addition, most of the research examining the school-to-work transition has been atheoretical and focused on variables related to job attainment (e.g., Taylor, 2005); this study contributes to the literature by examining employment stability and job quality as important outcomes for youth who are transitioning into the workforce. Additionally, research is needed that follows diverse samples of youth at multiple points in their transition to work. This exploratory study, grounded in ecological theory (Bronfenbrenner, 1986), investigated the school-to-work transition of noncollege-bound youth using a diverse, nationally representative sample of youth followed longitudinally. The primary purpose of this study was to advance knowledge regarding the factors that contributed to an adaptive school-to-work transition among noncollege-bound youth by examining the predictors of employment stability and quality. In addition, predictors of job attainment were examined to assess whether previous findings in the literature would be replicated. The predictors in this study had been shown in the literature to relate individually to job attainment, represented the levels of the ecological model, and were available in a diverse, nationally representative longitudinal data set.
Ecological theory posits that individuals are influenced by a variety of factors from proximal to distal, organized around a nested set of subsystems (Bronfenbrenner, 1986). Previous research on the school-to-work transition typically has focused on the individual and microsystem levels of predictors. However, consistent with research calling for the inclusion of other levels of the ecological model (Worthington & Juntunen, 1997), this exploratory study examined variables at the individual (i.e., depression, substance use, adolescent educational attainment), microsystem (i.e., parent–youth relationship and employment in adolescence), mesosystem (i.e., parent education level and income), and exosystem (i.e., neighborhood physical risk) levels. Moreover, we defined an adaptive transition as consisting of three sociological–economic components (i.e., job attainment, stability of employment, and job quality) that enable individuals to be economically self-sufficient and of benefit to society (Blustein et al., 2000).
An Adaptive School-to-Work Transition
Job attainment has been used to define an adaptive school-to-work transition (e.g., Taylor, 2005). In addition to the economic returns to society of employment, finding a job has been related to many desirable outcomes (e.g., decreased depressive symptoms and increased self-esteem) and not finding a job can lead to mental health problems (Wald & Martinez, 2003).
Aside from attainment, early employment stability may have beneficial effects for those making the school-to-work transition (Zimmer-Gembeck & Mortimer, 2006). Unfortunately, finding a stable job can be challenging for youth as it takes approximately 5 years after leaving school before the average individual starts a job with a duration of 3 or more years (Yates, 2005). Moving from one low paying job to another without settling into a longer employment relationship, known as churning, may represent a nonproductive school-to-work transition because these jobs often lack adequate pay which is critical to an adaptive transition (Yates, 2005). Thus, employment stability represents an important marker for those making the school-to-work transition.
While job attainment and stability have been well studied, few studies examining school-to-work transition have considered job quality (Staff & Uggen, 2003) and most studies have used self-report measures to assess job quality (Zimmer-Gembeck & Mortimer, 2006). Nonetheless, job quality is an important sociological–economic factor in an adaptive transition as it has been related to increased job satisfaction (Stone & Josian, 2000). In addition, neighborhoods where individuals possess jobs of higher quality have been connected to lower crime rates.
Predictors of an Adaptive School-to-Work Transition
Although employability skills are important for career success, there are many factors that influence job attainment, stability, and quality (Worthington & Juntunen, 1997). Thus, predictors were examined at each level of the ecological model.
Individual Level Predictors
Three areas of potential intervention were identified at the individual level. Depression has been linked with job status (Zimmerman, Christakis, & Vander Stoep, 2004) and difficulty with the school-to-work transition (Maatta, Nurmi, & Majava, 2002). Likewise, substance use has been found to be related to increased risk for disconnection (Hair et al., 2005b), lowered occupational expectations (Brook, Adams, Balka, & Johnson, 2002), and difficulty making the school-to-work transition (Hartnagel, 1997). Finally, adolescent educational attainment was correlated negatively with unemployment and stable employment (Miller & Porter, 2006).
Microsystem Predictors
At the microsystem level, having involved parents and work experience seem to provide the foundation for adolescents to develop the motivation, knowledge, and skills to succeed in the workforce. Parents play a key role in an adaptive school-to-work transition (Blustein et al., 2000). Parents may provide financial, emotional, or motivational support to improve a youth’s chances for success in adulthood (Settersten, 2005). In addition, work experiences in adolescence have been found to build on experiences needed in career development (Zimmer-Gembeck & Mortimer, 2006).
Mesosystem Predictors
Two variables were identified at the mesosystem level of analysis. While less malleable than other variables, parent education level related negatively to an adaptive transition to the workforce (MaCurdy, Keating, & Nagavarapu, 2006). Likewise, income below poverty level was related to undesirable employment outcomes (Blustein et al., 2002) and is the most cited barrier to making an adaptive school-to-work transition (Wentling & Waight, 2001). In short, those most at economic disadvantage are most likely to experience difficulties with the school-to-work transition (Worthington & Juntunen, 1997).
Exosystem Predictors
A final variable examined was neighborhood physical risk. Neighborhood characteristics have been connected to school-to-work training opportunities (Ainsworth & Roscigno, 2005), career aspirations (Hartung, Porfeli, & Vondracek, 2005), and an adaptive school-to-work transition (Imm, Kehres, Wandersman, & Chinman, 2006).
Hypotheses
This exploratory study sought to better understand the variables in adolescence that may be associated with an adaptive school-to-work transition for a diverse, nationally representative sample of adolescents. As a preliminary analysis, we sought to determine whether previous findings in the literature were replicated regarding predictors of job attainment. Specifically, we hypothesized that, consistent with prior research, low levels of depression, lack of substance use, high educational attainment, positive parent–youth relationships, employment in adolescence, high parent education level, high income, and low neighborhood physical risk would be predictive of job attainment.
Our primary purpose was to explore the predictors of stability of employment and job quality since these constructs are salient for healthy work functioning yet have not been the focus of school-to-work research. We hypothesized that the independent variables, gathered over time, would predict stability of employment and job quality. In particular, low levels of depression, lack of substance use, high educational attainment, a positive parent–youth relationship, employment in adolescence, high parent education level, high income, and low neighborhood physical risk were expected to relate to stability of employment and high quality jobs in a diverse sample of adolescents.
Method
Population and Sample
The data source for the present study was the National Longitudinal Survey of Youth, 1997 Cohort (NLSY97), an ongoing survey that tracks the transition from school to work. The NLSY97 is a nationally representative sample of 8,984 adolescents who were of age 12–16 in 1997 (with oversamples of African American and Hispanic youth). These adolescents were interviewed annually on a variety of topics related to occupational outcomes. The NLSY97 data set contained a number of items and measures that had been used in previous research. In a few cases, we constructed measures from salient items to operationalize some of the constructs of interest in this study. Additional details about the NLSY97 data set can be found in the user's guide (Bureau of Labor Statistics, 2011). The present study utilized data from several rounds of data collection to assess job attainment, stability, and quality.
Analyses focused on the sample of youth who have left school but have not gone on to attend college (i.e., noncollege-bound youth). This sample was limited to participants who were between the ages of 12 and 14 in 1997, as this was the sample of participants who completed the measures assessing the variables of interest. Specifically, this sample of participants was asked about neighborhood physical risk, parent–youth relationship, depression, personality, and some substance abuse items, whereas older participants were not. A total of 2,042 participants met these criteria. The sample was approximately 42% White, non-Hispanic, 32% Black, non-Hispanic, 24% Hispanic, and the rest were other races. The average age of the participants in the sample was 13.14 (SD = 0.79), and a little more than half were male (54.95%). To examine job stability and quality, the sample was further limited to the 1,657 participants who were employed in 2005. This subsample was comparable to the full sample with regard to age, gender, race, employment, and the independent variables.
Independent Variables
The independent variables were gathered from Rounds 1 through 9 of data collection (i.e., 1997–2005) which represent a 9-year time frame in which the participants were likely to have transitioned from school to work. At the individual level, depression was assessed using a 5-item abbreviated version of the Center for Epidemiologic Studies Depression Scale (CES-D; Radloff, 1977). Similar abbreviated versions of the CES-D have been successfully used in previous studies (e.g., Falci, 2006). Data from this scale over three waves (2000, 2002, 2004) were included as three indicators of a latent variable of depression. These waves of data captured participants who ranged in age from 15 through 21. This time frame was relevant since the depression prevalence tends to increase during this time (Weisz, Sandler, Durlak, & Anton, 2005). The reliability of the CES-D in the present study ranged from .69 to .75. Substance use was a latent construct consisting of four measures: an existing index of substance use (i.e., The Substance Use Index-Youth Report) and three individual items. The Substance Use Index-Youth Report (Child Trends & Center for Human Resources Research, 1999) was based on three youth-reported dichotomous items asking the adolescent whether they had ever smoked a cigarette, had a drink of an alcoholic beverage, and used marijuana. This index has been used in previous research to assess substance use (Paternoster, Bushway, Brame, & Apel, 2003). The reliability of the Substance Use Index was .81 in the present study.
In addition to the Substance Use Index, three questions taken from the NLSY97 were included in the substance use latent variable. These three questions asked adolescents to indicate (during the last 30 days) how many days they smoked a cigarette, had one or more drinks of an alcoholic beverage, or used marijuana. These questions have been used in previous research to measure substance use (Amuendo-Dorantes, Mach, & Clapp, 2004). Reliability estimates for these questions ranged from .74 to .91 and the measurement model indicated that these indicators were part of the same latent construct. The substance use variables were gathered in various years (i.e.,1997–2004) to reflect adolescents’ substance use behavior from ages 12 to 21. This age range is of particular importance since previous research indicated that substance use in adolescence leads to continued substance use later in life (Martin & Milot, 2007). Finally, adolescent educational attainment was defined as the highest grade of school completed as of 2005 (Round 9) and has been used to understand the school-to-work transition (Yates, 2005).
At the microsystem level, parent–youth relationship was assessed using the Parent–Youth Relationship–Youth Report (Child Trends & Center for Human Resources Research, 1999). This measure consisted of 8 items developed for the IOWA Youth and Family Project (Conger & Elder, 1994; e.g., my parent helps me with things that are important). This measure has been shown to be reliable (α = .74–.82) and have predictive validity (Hair et al., 2005a); the α for this study was .75.
Employment in adolescence consisted of two variables that assessed participants’ activity at employee-type jobs (e.g., jobs where an individual is working for an organization or another individual). The first indicator assessed the average number of hours per week an adolescent worked at an employee-type job from age 14 through 19. The second indicator assessed the total number of employee-type jobs held from age 14 through 19. These two indicators of employment in adolescence have been used by other researchers to understand the influence of employment during adolescence (Pabilonia, 2001).
At the mesosystem level, parent education level was defined as the highest grade achieved by a residential parent in Round 1 (1997). This definition has been found to relate to disconnection in previous research (Ling, Hair, & Moore, 2011). Income was assessed by a variable indicating the ratio of household income to poverty level in the previous year, taking into account household size. This method is used by the Census Bureau to report income level and poverty status, and previous research has used this measure to assess poverty status (Hair, Moore, Ling, Cleveland, & McPhee, 2006).
Finally, at the exosystem level, neighborhood physical risk was assessed with The Physical Environment Risk Index (Child Trends & Center for Human Resources Research, 1999). Questions on this index asked the adolescent to report on two environmental characteristics and the interviewers to report on three aspects of the home/neighborhood (e.g., how many days they heard gunshots in their neighborhood in a typical week). This index has been used in previous research to assess neighborhood quality (e.g., Manlove, Terry-Humen, Ikramullah, & Moore, 2006).
Dependent Variables
The dependent variables were gathered in 2005 (Round 9). Respondents ranged from age 20 through 22 in 2005 (M = 21.14, SD = 0.79). Job attainment was measured using a single dichotomous variable. Participants were classified as having attained employment if they worked at least 1 week of the year in 2005 (Round 9). Participants who had not worked any of the weeks of the year in 2005 were classified as not having attained employment. Stability of employment consisted of two indicators. The first indicator was the average annual length of employment in weeks since leaving school, with longer job tenure indicating greater employment stability. The second indicator was the average annual number of employee-type jobs (not self-employment) held since the adolescent left school; this item was reverse scored with more jobs held indicating lower employment stability. Both the indicators of job tenure and movement between different jobs have been used to assess employment stability in previous research (Yates, 2005).
Finally, since research has found that job quality tends to increase as adolescents make the transition to the workforce, data for the most recent job was used in measuring job quality (Yates, 2005). Job quality was operationalized with two measures. The first was a latent construct (titled job quality) consisting of three indicators describing the most recent job the respondent reported having in 2005 (Round 9). First, respondents were asked to indicate how many (using a predetermined list of 10) fringe benefits were offered by their work setting. These fringe benefits included medical, surgical, or hospitalization insurance, life insurance, dental benefits, paid maternity or paternity leave, unpaid maternity or paternity leave, a retirement plan other than Social Security, a flexible work schedule, tuition reimbursement, company provided or subsidized child care, and employee stock ownership plans. For the second indicator of the job quality latent variable, respondents were asked to indicate the number of paid vacation days they received each year. The final indicator of the job quality latent variable asked respondents to indicate the number of paid sick days they were entitled to during the year. With all three of these indicators, high scores indicated high job quality. An examination of the measurement model confirmed that these three indicators were part of the same latent construct.
In addition to the latent construct of job quality, job quality also was assessed with an observed variable measuring hourly pay. Respondents were asked to report on the hourly rate of pay for their most recent job. High scores indicated high job quality. In combination, these two measures allowed for the creation of an operational definition that captured multiple dimensions of job quality. This is important since research has yet to clearly define job quality for those engaged in the school-to-work transition.
Results
Missing Data
Since the NLSY97 contains missing data at the variable level, a full information maximum likelihood (FIML) procedure was used for cases with incomplete data using a statistical modeling program (Mplus). FIML is a theory-based maximum likelihood method of accounting for missing data that makes use of all available data points, even for cases with some missing responses (Enders, 2001). FIML does not impute missing values but rather computes the likelihood for the observed portion of each case's data which is then accumulated and maximized. FIML has been demonstrated to be superior to other methods of accounting for missing data including listwise deletion and pairwise deletion (Enders & Bandalos, 2001).
At the index and scale level, missing data were handled by examining the amount of missing data in a scale or index. For cases where 75% or more of data were present, missing values were imputed by applying the average value of the nonmissing variables in the scale or index to the missing value. For cases where less than 75% of the values within the scale or index were present, the scale or index was coded as missing.
Control Variables
Consistent with previous research using this data set (e.g., Hair et al., 2005a; Ling et al., 2011; Manlove et al., 2006) and to control for the potentially confounding effect of demographic and socioeconomic influences as well as cohort effects, the analyses controlled for race–ethnicity, gender, and age. Also consistent with previous research, due to the relatively large number of variables examined, a conservative significance level of p < .001 was used in the present study to reduce potential Type 1 errors (Tabachnik & Fidell, 1996).
Logistic Regression Results
To examine the contribution of the independent variables to the prediction of job attainment, a logistic regression within a latent variable framework was conducted with the full sample of noncollege-bound participants who were of age 12–14 in 1997 and were interviewed in 2005 (Round 9). Specifically, a logistic regression within a latent variable framework was used to predict employment in 2005 (Round 9) from the independent variables. The model was significant (χ2 = 452.61, df = 59, p <.001) and accounted for 23% of the variance in the dependent variable (R 2 = .23), after controlling for age, race, and gender. In this sample, there were 1,657 participants who were employed and 385 participants who were not employed in 2005. In other words, 20% of the sample did not obtain employment in 2005.
Depression, substance use, adolescent educational attainment, employment in adolescence: jobs held, and employment in adolescence: hours worked were predictors of employment in 2005. Odds ratios were calculated for the predictors in the logistic regression; these are presented in Table 1. For every unit increase in depression measure, the probability of being employed increased by a factor of 1.13, likewise for every unit of increase in substance use, the odds of employment increased by a factor of 1.19. Similarly, an increase in the grade of schooling attained by the participants increased the chances of being employed increased by a factor of 1.11. An increase in the number of jobs held between the ages of 14 and 19 increased the likelihood of employment by 1.15. Finally, for every hour increase in average hours worked per week between the ages of 14 and 19, the likelihood of employment in 2005 increased by 1.01. Parent–youth relationship and the mesosystem and exosystem variables were not related to job attainment in 2005.
Logistic Regression Results.
Structural Equation Model (SEM) Results
SEM was used to explore the relationship between the independent variables and job stability and quality. To evaluate the model fit of the SEM, the Root Mean Square Error of Approximation (RMSEA; a value of less than 0.05 indicates an adequately fitting model), the Comparative Fit Index (CFI), and the Tucker–Lewis Index (TLI) were used. For the CFI and TLI, a value between 0.90 and 0.95 indicated an adequate fit of the specified model (Kenny & McCoach, 2003).
The fit of the SEM, χ2 (90, n = 1,657) = 504.63, p < .001, RMSEA = 0.05, CFI = 0.93, TLI = 0.92, indicated that the proposed model described the relationships adequately. Adolescent educational attainment and employment in adolescence were associated with stability of employment. Depression, substance use, adolescent educational attainment, employment in adolescence: hours worked, parental education level, and income were associated with job quality (see Table 2 and Figure 1). However, parent–youth relationship and neighborhood physical risk were not associated with the stability and quality variables.
Standardized and Unstandardized Path Coefficients From the Structural Equation Model.
Note. *p < .001.
Structural equation model for the adolescent predictor variables on job characteristics. All path coefficients are completely standardized (only significant paths presented).
For the individual level variables, most relationships were in the expected directions and relatively small. Substance use had a negative relationship with job quality (β = −.116, p <.001). Adolescent educational attainment had a positive relationship with the stability of employment job tenure (β = .320, p <.001), latent variable of job quality (β = .193, p <.001), and hourly pay (β = .162, p <.001). However, unexpectedly, depression had a small positive relationship with the latent variable of job quality (β = .105, p <.001) and hourly pay (β = .104, p <.001).
The relationships between microsystem variables and outcome variables also were in expected directions. Employment in adolescence: jobs held had a positive relationship with the stability of employment job tenure (β = .219, p < .001). Also consistent with theory, there was a negative relationship between the employment in adolescence: jobs held and the stability of employment movement between jobs (β = −.532, p < .001). The employment in adolescence: hours worked was related positively with stability of employment job tenure (β = .381, p < .001), the latent job quality variable (β = .127, p < .001), and hourly pay (β = .080, p < .001).
The relationships between mesosystem and exosystem variables with the outcome variables were not all in the expected directions. Parent education level was related negatively to hourly pay (β = −.111, p < .001). However, income, as expected, was associated positively with the job quality latent variable (β = .091, p < .001) and hourly pay (β = .112, p < .001).
Discussion
This exploratory study sought to advance our understanding of the factors that contributed to an adaptive school-to-work transition among noncollege-bound youth using a diverse and nationally representative sample of youth followed longitudinally. With regard to the predictors of stability of employment and job quality, partial support emerged for the hypotheses as depression, substance use, adolescent educational attainment, employment in adolescence: hours worked, parental education level, and income were related to job quality; parent–youth relationship, employment in adolescence: jobs held, and neighborhood physical risk were not. Also, adolescent educational attainment and employment in adolescence were related to employment stability. However, depressive symptoms, substance use, parent–youth relationship, parental education level, income, and neighborhood physical risk were not related to stability of employment. Most of these variables accounted for less than 5% of the variance in the outcome variables. Moreover, several of the findings were counterintuitive. Specifically, the relationships between depression, parent education, and job quality were the opposite of the expected relationships. It is possible that while these findings were statistically significant, they did not have practical significance; small effect sizes combined with a large sample size may have contributed to these results.
Only three of the relationships in the SEM predicted more than 10% of the variance in the outcome variables: adolescent educational attainment, the number of jobs held in adolescence, and the number of hours worked in adolescence. Adolescent educational attainment was associated positively with the number of hours worked since leaving school indicating that higher levels of education were related to working more hours upon transitioning to the workforce. This was consistent with the finding that youth who had a high level of education were more likely to hold more stable employment and be employed longer (Yates, 2005). Interestingly, adolescent educational attainment was not associated with job tenure since leaving school. This may have reflected the phenomenon in the school-to-work literature known as churning (Yates, 2005); the participants may have been trying to find a stable job as it may take several years for youth to find stable employment (Yates, 2005).
The more jobs held in adolescence was related to a fewer number of jobs obtained after transitioning to the workforce. In addition, the number of hours worked in adolescence was positively related with the number of hours worked since leaving school. This was consistent with previous research that has found employment in adolescence is related to an adaptive transition to the workforce (Mortimer & Staff, 2004). Counselors and high school teachers may want to encourage adolescent employment and develop interventions to assist adolescents in obtaining decent work experiences and processing what is learned from being employed. Future research could investigate the efficacy of such programs.
Overall, there were few practically significant paths in the SEM. First, since stronger associations were found with stability of employment compared with job quality, it may have been that employment stability is the more important construct in the school-to-work transition than job quality. Another theory is that these variables may have been working differently than anticipated. For instance, stability of employment may have acted as a mediator between the independent variables and job quality variables. In other words, stable employment may be a path to a high-quality job.
With regard to the hypotheses on job attainment, partial support emerged; only four of the independent variables were related to job attainment. Specifically, high levels of depression, the presence of substance use, greater academic attainment, and more employment in adolescence were related to job attainment. However, it is important to note that with most of these variables, the variance explained was relatively small and only one of the independent variables explained more than 10% of the variance (i.e., substance use, 20.2%). Parent–youth relationship, parent education level, income, and neighborhood physical risk had no relationship with job attainment. The findings that both employment in adolescence and educational attainment were predictive of job attainment were consistent with previous research which found that work experiences and levels of education in adolescence were related to later employment outcomes (Pinquart et al., 2003). Individuals who complete more school and who have work experiences are likely to be employed in the future. Continued efforts to keep struggling students in school and expose them to positive work experiences are needed.
As with job quality and stability of employment, several of the relationships were unexpected. Specifically, the presence of depressive symptoms and use of substances were associated with job attainment. Perhaps individuals who left school and obtained jobs were more likely to feel sadness or loss regarding their lives. Depressive symptoms may be associated with youth who have entered the workforce due to academic difficulty. Moreover, youth who are employed may take on characteristics of adults in the working world (who may use substances). Alternatively, these findings may reflect the combination of small effect sizes and a large sample size, yielding statistically significant but practically insignificant results.
Implications
While each of the independent variables explained a small amount of variance in the outcome variables, when considering the practical implications of small findings on a population as large as those who are making the school-to-work transition, even small significant relationships can have some utility in informing practice. In particular, the findings suggest a pattern of variables whereby practitioners might be able to prevent the chances of a nonadaptive transition by encouraging youth to continue with their education and gain work experience in adolescence. In the present study, these two variables predicted an adaptive school-to-work transition and these findings were in line with previous research (Zimmer-Gembeck & Mortimer, 2006). Psychologists and counselors can develop (or refer students to) interventions focused on retention. High school counselors can organize job or internship fairs where employers and social service agencies advertise work and volunteer opportunities. Also, counselors can arrange for students to receive course credits for internship experience. On a national level, psychologists and counselors could advocate for work experiences for all high school students to aid in their career development and retention.
Moreover, career counselors should be mindful that an adaptive transition includes multiple sociological–economic components. Instead of limiting career interventions to job attainment, psychologists, counselors, high school teachers, and employers might be educated to understand that an adaptive transition includes job stability and quality in addition to attainment. This is particularly important for those who left school because of poor academic achievement since academic attainment was found to be a stronger predictor of an adaptive transition. Finally, career counselors should design interventions that include targeting malleable variables at several levels of the ecological model. Although each of the variables in the present study accounted for a relatively small amount of variance in the outcome variables, taken together they might constitute a multidimensional intervention program that career counselors could use with this population. In short, there is potential for practitioners to ensure the career success of all youth making the transition to the workforce, not just college-bound youth. However, future research is needed to develop and test innovative interventions.
Limitations
As with all studies, the present study had several limitations. First, while employment stability and job quality may vary from job to job, the present study examined the most recent job. As a result, it was not possible to determine whether there was a pattern of improvement over time with regard to making an adaptive transition. Furthermore, due to the nature of the NLSY97, time was a confound in the present study. Since this study included high school dropouts as well as high school completers, it is possible that the employment in adolescence variables were capturing the same information as the outcome variables. Consequently, the relationship between employment in adolescence variables and stability of employment variables may not have been independent. In other words, some youth may have dropped out of school before the age of 19, therefore the data on outcome variables for these youth may have overlapped with their employment in adolescence. This confound reflects a difficulty in studying the school-to-work transition in that the exact time of transition can often be unclear.
There also were some measurement issues. Given the nature of the NLSY97, some measures were not available for other constructs that may have been of interest. For example, previous research has indicated that personality variables contributed up to 10% of the variance in job quality measures (Furnham, Petrides, Jackson, & Cotter, 2002). Unfortunately, there was not an adequate measure of personality available in the NLSY97. In addition, some of the measures combined data from multiple respondents or across different time points. While these measures were consistent with prior studies, the complexity of adolescent lives was not studied. Finally, complete psychometric information was not available for all measures in the study. For example, while the measurement of neighborhood physical risk was used in previous research, reliability information was not available. These limitations often occur when using an established data set to study a diverse and nationally representative sample.
Future Research
Clearly an adaptive school-to-work transition is complex and future studies should continue to examine multiple predictors of job stability and quality in addition to job attainment. In addition, future research could consider time as a variable. Since noncollege-bound youth include both high school dropouts and youth who complete high school, an examination of the timing of leaving school and the timing of other predictors may provide unique insight into this population. For example, those who drop out of high school receive less education but have more time to make an adaptive transition. Finally, future studies should improve on existing measures of predictors.
Conclusion
While previous research has addressed individual aspects of the school-to-work transition, we have yet to achieve a more complete picture which will allow counselors and policy makers to assist noncollege-bound youth in navigating their transition to the workforce. In this exploratory study, individual and microsystem variables were predictive of job attainment and stability of employment, whereas individual, microsystem, and mesosystem variables were predictive of job quality. The challenge remains to clarify the complexity of this transition to develop successful interventions. By doing so, we will offer this “forgotten half,” noncollege-bound youth, the best chance of succeeding in their transition to the world of work.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.