The Consequences of Unrealized Occupational Goals in the Transition to Adulthood

Abstract

Do unmet occupational goals have negative consequences for well-being? Several social-psychological theories posit that aspirations become standards against which individuals judge themselves, thereby decreasing well-being when unmet. Yet other evidence points to young adults’ goal flexibility and resilience, suggesting unmet aspirations may not affect well-being. This paper tests these alternatives using data from the National Longitudinal Study of Youth 1979 (N=9,016) and the National Educational Longitudinal Study of 1988 (N=10,547) to examine whether the degree of match between adolescent occupational aspirations (NLSY) and expectations (NELS) and later attainment affect job satisfaction and depression. This paper also examines gender differences in the cost to unmet goals. Findings reveal a cost to falling short of one’s occupational goals, manifested in more depressive symptoms for men in the older cohort, and lower job satisfaction for both men and women across two cohorts born approximately 14 years apart.

1. Introduction

The ethic of the American Dream is pervasive in the United States, contributing to a belief that the “good life”—including high occupational attainment and socioeconomic well-being—is both desirable and attainable (Hochschild 1995; Jahromi 2011; Turner 1960). This shared optimism may have led to a crisis of unmet expectations, however. Recent research finds that about 70% of high school sophomores expect to work in a professional occupation (Goyette 2008), but less than 15% of adults are employed in professional occupations (BLS 2009). Similar gaps between occupational aspirations and attainment have been documented in other research (Csikszentmihalyi and Schneider 2000, Reynolds et al. 2006).

Are there consequences to the American dream, and if so, for whom? Scholars have asserted potentially negative outcomes associated with failing to achieve one’s goals (Carr 1997; Markus and Nurius 1986; Merton and Rossi 1968; Runciman 1966; Schneider and Stevenson 1999; Trusty and Harris 1999), yet this relationship has rarely been tested. Two studies of unmet goals produce conflicting results. Reynolds and Baird (2010), using NLSY and Add Health data, find no evidence of increasing depressive symptoms among young adults who fall short of their earlier educational expectations, while Carr’s (1997) prospective study of middle aged women’s occupational aspirations using the Wisconsin Longitudinal Study finds a positive association between unmet occupational aspirations and depressive symptoms.

The current manuscript provides the first nationally representative, prospective study of the consequences of unmet occupational goals¹ for young adults. It offers an improvement over prior studies of unmet goals by using two cohorts born 1957–1965 and 1974–1976, two measures of well-being, and an exhaustive set of covariates, and by examining differences in the relationship between unmet goals and well-being by gender. First, I investigate the relationship between unmet aspirations and job satisfaction and depression using the National Longitudinal Study of Youth, 1979 (NLSY). Job satisfaction is expected to be directly related to unmet goals because “satisfaction implies a convergence of aspirations and achievement” that is distinct from other measures of distress and well-being (Mirowsky and Ross 2003, p. 28). Examining depressive symptoms will provide insight into whether the match between early aspirations and later attainment affects general indicators of well-being in the transition to adulthood. Second, I test whether these findings for job satisfaction are replicated using the National Educational Longitudinal Study (NELS) (but not depressive symptoms, as NELS does not include this measure). Finally, I consider gender differences in the relationship between unmet goals and emotional well-being for both cohorts. Findings contribute to the literatures on social psychological theories of goal setting and self-concept (Higgins 1987; Michalos 1985; Mirowsky and Ross 2003; Runciman 1966), adolescent and young adult development (Brandtstadter and Renner 1990; Heckhausen and Tomasik 2002; Jacobs, Karen, and McClelland 1991; Rindfuss, Cooksey, and Sutterlin 1999), and occupational aspirations and expectations (Alexander and Cook 1997, Carr 1997, Reynolds and Baird 2010).

2. Theoretical background

Occupational aspirations and expectations have become increasingly lofty over the past half a century (Csikszentmihalyi and Schneider 2000; Goyette 2008; Reynolds et al. 2006; Schneider and Stevenson 1999), and two theoretical perspectives hold very different predictions regarding the consequences of these heightened goals. On the one hand, social psychological theories of goal setting suggest that aspirations can become standards against which young adults judge their success (Markus and Nurius 1986; Merton and Rossi 1968; Runciman 1966). Falling short of these self-created measuring sticks can result in lowered well-being and satisfaction. On the other hand, some researchers posit that adolescent occupational goals are meaningless, pointing to their extreme ambitiousness (Alexander and Cook 1979; Rindfuss et al. 1999), and theories of adolescent development contend that high early goals and later adjustment is a normal—even ideal—part of growing up (Heckhausen 1999; Tomasik et al. 2009). Below, I describe these theoretical counterpoints and the evidence supporting them in greater detail.

2.1 Costs to unmet goals

Relative deprivation theory (Merton and Rossi 1968; Runciman 1966), multiple discrepancies theory (Michalos 1985), and self-discrepancy theory (Higgins 1987) suggest that well-being depends on one’s attainment relative to some standard. Relative deprivation theory posits that individuals establish comparisons to judge their own accomplishments. Prior studies have assumed that these comparisons are made to a reference group such as peers, co-workers, friends, or neighbors (e.g. Bernburg, Thorlindsson, and Sigfusdottir 2009; Yngwe et al. 2005). However, Runciman’s (1966) work suggests that dissatisfaction and stress may arise in response to a conflict between the imagined self and present circumstances. Similarly, Michalos’s (1985) multiple discrepancies theory posits that happiness and satisfaction are functions of the size of the gap between what one has and several comparisons, including what one wants, expected to have in the past, and expects to have in the future. Higgins (1987) self-discrepancy theory adds to this by considering the negative emotions (disappointment, dejection) that arise from discrepancies between one’s self-concept and ideal self. In sum, these theories suggest that goals are a key metric by which individuals may judge themselves and evaluate their own happiness and disappointment. Importantly, comparisons may be made from a position of relative success or lack of success. Though prior literature has examined the repercussions of such comparisons to those above and below oneself in economic well-being (Stewart 2006), the current study examines the implications of exceeding and falling short of one’s occupational goals.

The theory of “possible selves” elaborates the mechanisms by which goals may become standards with which to judge one’s success or failure. This theory argues that aspirations are reflections of individuals’ hopes and fears about their future selves, and that these future, or possible, selves serve as a context for motivating, implementing, and interpreting behavior (Markus and Nurius 1986; Ruvolo and Markus 1992). Future selves exist and interact along a number of domains, such as occupational and educational attainment, social life, material possessions, appearance, and family life (Markus and Nurius 1986; Yowell 2000). Therefore, occupational aspirations may shape behavior and be linked to daydreams about home ownership, vacations, leisure activities, and other material expectations. For example, a young person who aspires to be a surgeon and a young person who hopes to be a firefighter are not only fantasizing about the types of jobs they wish to hold, but also about the lifestyle, friends, and living environment they envision for themselves. Falling short of these goals means not only failing to reach a desired occupational attainment, but also failing to achieve the kind of family, social, and personal life one wished to have.

Previous research provides support for the hypothesis that unmet goals affect well-being. One study found that discrepancies between measures of hoped for and expected “work selves” were associated with lower life satisfaction (Pisarik and Shoffner 2009). In a study of university students, Michalos found that a discrepancy between what individuals have and wished to have significantly lowered reported happiness and life satisfaction after controlling for attainment and well-being. Positive changes in satisfaction and happiness have also been linked to periods in the life course when men and women attained expected levels of material goods and family life statuses (Plagnol and Easterlin 2008). Though these studies used slightly different measures of expectations than utilized here, they demonstrate that a discrepancy between goals and outcomes might lead to lower levels of satisfaction and well-being. One study of women in mid-life found that those who had not attained their occupational aspirations had higher levels of depressive symptoms and lower levels of life purpose than those who had met their aspirations, over and above objective measures of attainment and prior measures of depression (Carr 1997). However, this study assessed women’s aspirations in mid-life, when they were knowledgeable about their own skills and the demands of the labor market, and found these effects only for those who had fallen short of their goals by a large amount. Finally, research by Hudson (1985) showed that the size of the gap between occupational aspirations and attainment was linearly related to job satisfaction for a cohort of mostly white 1957 high school graduates.

Together, these theories and prior research suggest that future goals can become standards against which young adults judge their success. Not meeting these goals may lead to lower satisfaction and well-being. It is unclear whether this prediction holds for adolescents’ occupational goals and later attainment, however. Goals set in adolescence are more optimistic and may carry less risk of disappointment when not met. Furthermore, if there are negative consequences to unmet aspirations, does a larger gap between one’s goals and later attainment predict a larger drop in well-being? Does exceeding one’s goals produce any positive effects? This study will answer these questions using two nationally representative samples of youth.

2.2 Resiliency and adjustment in response to unmet goals

There are also reasons to predict that unmet goals will not influence well-being over time. The theoretical and empirical importance of future aspirations and expectations as motivators has been criticized by those who point to their instability and loftiness (Alexander and Cook 1979). Empirical research in the United States demonstrates that most young people change their occupational goals at least once during high school and their young adult years (Alexander, Bozick, and Entwisle 2008; Jacobs et al. 1991; Johnson 2002; Rindfuss et al. 1999), supporting the view that young people’s goals may not become a stable comparison by which they judge their future success. Despite the prevalence of unmet aspirations, most young people report steadily high or increasing well-being over the course of the transition to adulthood (Schulenberg, Bryant, and O’Malley 2004).

Adjusting one’s occupational goals may be an important part of adolescent development (Brandtstadter and Renner 1990; Heckhausen 1999; Tomasik et al. 2009). High aspirations can motivate youth investment in school and career-related activities and are associated with positive indicators of well-being, including self-esteem and fewer depressive symptoms (Massey, Gebhardt, and Garnefski 2008). Not having an occupational goal may be more detrimental for young adults than having any aspiration, even if it is unrealistic (Staff et al. 2010). As young people move closer to entering their first full-time job, they typically adjust these goals in response to feedback from teachers, self-assessments, and information about potential jobs (Brandtstadter and Renner 1990, Heckhausen and Tomasik 2002). Therefore, the developmental perspective suggests that unrealistic occupational goals will have little impact on well-being for those who re-calibrate their goals downward over time. This is supported by research showing that falling short of educational expectations is unrelated to well-being among young adults (Reynolds and Baird 2010).

Reactions to unmet goals may also differ by young adults’ coping resources. For example, having high self-esteem may alleviate disappointment regarding unmet goals. Alternatively, this trait may prolong young adults’ hopes of attaining their goals and delay any negative consequences to middle adulthood (Brandtstadter and Renner’s 1990). In either case, having confidence in one’s abilities may mitigate the negative consequences of unmet goals.

In summary, theories of adolescent and young adult development suggest that unmet goals may have little impact on young adults’ well-being, or that the ability to cope with unmet goals may vary by social-psychological factors. The current study will examine both whether unmet goals produce costs to well-being and, if found, whether adjustments to these goals in the transition to adulthood or positive social-psychological attributes lessen the impact of unmet goals on young adults.

2.3 For whom?

The relationship between unmet goals and well-being may not be the same for all young people. In recent years, young people’s goals have become increasingly lofty (Csikszentmihalyi and Schneider 2000; Goyette 2008; Schneider and Stevenson 1999). One study showed that the gap between the percentage of high school seniors aspiring to work in a professional job and the percentage of the high school graduates ages 25–34 that held such jobs increased by 30 points between 1976 and 2000 (Reynolds et al. 2006). The abundance of aspirations for college and post-graduate schooling and professional occupations may mean that even occupational expectations have become an expression of “ideal” rather than “planned” goals. In addition, an increase in high occupational aspirations and expectations without a corresponding change in occupational attainment means that unmet occupational goals may be normative for more recent cohorts of young adults. This may make unmet goals less distressing for these recent cohorts, if they find comfort in peers facing the same circumstances at this period of their lives. To investigate this possibility, the current study analyzes data from two cohorts of youth. The older cohort was born between the years of 1957 and 1965 and reported occupational aspirations in 1979. The younger cohort was born between 1974 and 1976, and reported occupational expectations in 1990. Given previous research, I expect to find that the gap between occupational goals and attainment is larger for the younger cohort. If so, the higher proportion of young adults falling short of their goals may decrease the negative impact of this condition. Differences in the data—particularly the measurement of aspirations versus expectations—preclude strong conclusions regarding cohort differences. However, evidence of a negative association between unmet expectations and job satisfaction for the younger cohort would suggest that rising aspirations and expectations have not entirely diminished the consequences of unmet goals.

There are also reasons to expect gender differences in the costs to unmet goals, particularly among the older cohort. In the 1970s, attitudinal norms supported a male breadwinner mode of family life (Brewster and Padavic 2000; Rindfuss, Brewster, and Kavee 1996). Many young women may have anticipated a contingent future in which marriage and family obligations would delay career goals until middle to older adulthood (Maines and Hardesty 1987). As a consequence, unmet occupational goals may have little bearing on the well-being of women who came of age during this period. On the other hand, men were more likely to see themselves in the family provider role in the 1970s and early 1980s than in later years (Wilkie 1993), which may heighten their distress in response to unmet goals. Attitudinal change in the 1980s and 1990s makes gender differences less likely for contemporary cohorts of youth, however. The percentage of women working also increased sharply over this period (Blau and Kahn 2007). When young women stated their occupational expectations in the early 1990s, therefore, they had reason to expect that work would be a dominant component of their future and that they would play an important role in their family’s economic security.

This paper will examine the relationship between unrealized aspirations and expectations and well-being for two cohorts of youth, and whether it differs by gender. Falling short of one’s goals is operationalized by a gap between hoped for and attained occupational status. While not a comprehensive measure of unmet goals, this necessarily rough estimate provides an important indicator of relative status and well-being. Analyses of the older cohort will demonstrate whether unmet goals predict job satisfaction and depressive symptoms. Analyses of the younger cohort will examine whether unmet goals continue to have an impact on job satisfaction. Job satisfaction measures provide an evaluation of a job based on what workers expect or want (Locke 1976), making this an ideal outcome. Number of depressive symptoms will be assessed to evaluate whether unmet goals have a broader impact on well-being.

3. Data and methods

3.1 NLSY Sample

The National Longitudinal Study of Youth, 1979 (NLSY) began in 1979 as a nationally representative survey of youth ages 14 to 22. Participants were re-interviewed annually until 1994 and every other year after that time through the present. The initial sample included a nationally representative sample of young men and women (N=6,111); a supplemental sample of Hispanic or Latino, Black, and economically disadvantaged non-Black/non-Hispanic youth (N = 5,295); and a nationally representative sample of youth serving in the military (N = 1,280).

The present study uses data from all available participants in the baseline survey (1979) and 1992, when participants were between the ages of 27 and 35. This year was used as an endpoint because it was the earlier of only two years in which depressive symptoms were assessed, thereby better aligning sample members’ ages to those of the NELS study participants. In 1992, 71% of the original respondents participated, for an N of 9,016. This includes an attrition rate of 7.65% and a larger percentage of cases that were dropped purposely (21.28%). Attrition and dropped cases should not bias estimates when adjusted using panel weights (MaCurdy, Mroz, and Gritz 1998). Attrition was more common among men, blacks and Hispanics, and older study sample members, although in total a higher proportion of whites were not reinterviewed over time due to purposefully dropped subsamples. I use all available respondents who had worked at least once since their last survey and were not missing responses on the dependent variables. The long-term unemployed and not employed were excluded because this status could be due to a number of factors, including disability, student status, or institutionalization. Long-term unemployment was more common among non-whites, men, and the less educated. Additionally, both occupational information and job satisfaction responses were only available for those employed at some point in the prior year. The analytic sample size for analyses of job satisfaction is 7,769 (1,183 long-term unemployed/not employed and 64 missing on job satisfaction). The analytic sample size for analyses of depressive symptomology is 7,703 (1,183 long-term unemployed/not employed and 130 missing on depression).

3.2 NLSY Measurement

3.2.1 Dependent variables

Weighted descriptive statistics for NLSY variables are listed in Table 1. In 1992 the NLSY survey included the Center for Epidemiological Studies Depression Scale (CES-D), which is used to assess the risk of developing clinical depression (Mirowsky and Ross 2002). It includes 20 items that ask respondents how often they felt sad, lonely, fearful, bothered, depressed, the blues, as good as others, everything took extra effort, hopeful, like a failure, happy, less talkative, others were unfriendly, they enjoyed life, disliked by others and could not get going and had trouble keeping their mind on tasks, a poor appetite, experienced crying spells, and a restless sleep. Responses to each question were coded from 0 (rarely) to 3 (most or all of the time). Positive items were reverse-coded, and responses were summed.² Responses ranged from 0 to 59, with an average of 8.52. This indicates a high positive skew, which was accounted for in models as described in the analytic strategy section. The Cronbach’s alpha for this scale was 0.88, indicating a high internal reliability.

Table 1.

Weighted descriptive statistics, NLSY and NELS

	NLSY				NELS
	Mean/%	Std. Error	Range	Alpha	Mean/%	Std. Error	Range	Alpha
Depression	8.52	0.11	0 to 59	0.88	----	----	----
Job satisfaction	3.33	0.01	1 to 4		83.85%	0.01	0 to 1
SEI of occupational aspiration	46.94	0.30	14 to 90		55.71	0.38	19 to 82
SEI of occupational attainment	36.45	0.25	14 to 90		38.52	0.31	19 to 82
Aspirations-attainment match					Expectations-attainment match
Exceeded	25.33%	0.00	0 to 1		14.84%	0.00	0 to 1
Matched	10.52%	0.00	0 to 1		9.35%	0.00	0 to 1
Fell short	56.66%	0.01	0 to 1		56.55%	0.01	0 to 1
Don’t know aspiration	7.48%	0.00	0 to 1		10.31%	0.01	0 to 1
Other aspiration	----	----	----		8.95%	0.01	0 to 1
Employment status
Currently working	87.02%	0.00	0 to 1		91.89%	0.00	0 to 1
Unemployed	4.80%	0.00	0 to 1		4.73%	0.00	0 to 1
Out of the labor market	8.19%	0.00	0 to 1		3.38%	0.00	0 to 1
Logged income	9.44	0.02	3 to 11.4		9.79	0.03	0.7 to 13.2
Years of schooling	13.35	0.03	0 to 20		----	----	----
Educational attainment
Less than high school graduate	----	----	----		6.29%	0.01	0 to 1
High school graduate	----	----	----		17.01%	0.01	0 to 1
Some college	----	----	----		46.67%	0.01	0 to 1
College graduate or more	----	----	----		30.03%	0.01	0 to 1
Marital status
Married	60.21%	0.01	0 to 1		39.31%	0.01	0 to 1
Never married	24.38%	0.01	0 to 1		53.57%	0.01	0 to 1
Separated/divorced/widowed	15.41%	0.00	0 to 1		7.13%	0.01	0 to 1
Number of children	1.24	0.02	0 to 9		0.67	0.02	0 to 5
Female	50.03%	0.01	0 to 1		48.73%	0.01	0 to 1
Race/ethnicity
White	65.36%	0.01	0 to 1		71.68%	0.01	0 to 1
Black	14.14%	0.01	0 to 1		12.76%	0.01	0 to 1
Latin	6.59%	0.00	0 to 1		11.93%	0.01	0 to 1
Other	13.91%	0.00	0 to 1		3.64%	0.00	0 to 1
Age	17.69	0.03	14 to 22		---	---	---
Age 14–15	----	----	----		9.55%	0.01	0 to 1
Age 16	----	----	----		66.49%	0.01	0 to 1
Age 17–19	----	----	----		23.96%	0.01	0 to 1
Two-parent family	75.52%	0.01	0 to 1		67.56%	0.01	0 to 1
Number of siblings	3.27	0.03	0 to 14		2.28	0.03	0 to 6
Parent in professional occupation	16.93%	0.01	0 to 1		21.56%	0.01	0 to 1
Parents’ education
Less than high school	23.05%	0.01	0 to 1		10.25%	0.01	0 to 1
High school graduate	43.30%	0.01	0 to 1		21.74%	0.01	0 to 1
Some college/technical school	12.99%	0.00	0 to 1		39.19%	0.01	0 to 1
Four years of college	20.66%	0.01	0 to 1		28.82%	0.01	0 to 1
Ability score	50.08	0.40	0 to 100		51.09	0.21	32 to 71
Self-esteem/self-concept	32.53	0.06	16 to 40	0.83	24.54	0.11	8 to 32	0.82
Job satisfaction in 1979
Like it very much	17.46%	0.01	0 to 1		----	----	----
Like it fairly well	25.74%	0.01	0 to 1		----	----	----
Dislike it somewhat/very much	8.22%	0.00	0 to 1		----	----	----
Not working	48.58%	0.01	0 to 1		----	----	----
Number	9,015				10,547

Job satisfaction in 1992 was measured on a four-point scale from “dislike it very much” (1) to “like it very much” (4). Those temporarily unemployed or not employed were asked to rate their satisfaction with their most recent job. Respondents averaged a value of 3.33.

3.2.2 Key explanatory variables

The key explanatory variable for this study is a measure of the gap between occupational aspirations and attainment. This variable was constructed from two measures: occupational aspirations at the first survey and occupational attainment in 1992. In 1979, respondents were asked what they would like to be doing at age 35: working, raising a family, or something else. They were then funneled into an occupational aspiration question (“What kind of work would you like to be doing at age 35?”) with wording specific to their general plans (e.g., those who indicated they wished to raise a family were asked, if they were to work, what kind of job they would like to hold). This strategy ensured that even respondents who did not plan to work reported an aspiration. Despite this, 637 respondents reported that they did not know what they wanted to being doing at age 35. Occupational attainment was reported in 1992. Temporarily unemployed respondents reported occupational information for their most recent job.

Occupational aspirations and attainment were converted from 1970 census codes into the Stevens and Featherman socioeconomic index³ of occupational status (1981). This measure was derived by regressing occupational prestige on the percentage of occupational incumbents who earned incomes of $10,000 or more and the percentage who had attended college for at least one year. Respondents’ occupational attainment SEI score was subtracted from their occupational aspiration SEI score, to obtain a linear measure of the gap between goals and outcome, ranging from −65 to 76, with higher (positive) numbers indicating greater shortfalls. This linear measure was converted into three dichotomous indicators of aspiration-attainment match: exceeded aspirations, met occupational aspiration SEI score, and fell short of occupational aspiration SEI score. An indicator of “do not know future plan” was also included as a fourth category. As a final step, survey respondents who had aspired to stay home and raise a family and achieved this goal were coded as matched on desired and obtained occupational prestige.

There is a mismatch in the age of the predicted occupational outcome (35) and the ages at which job satisfaction and depression were measured (27–35). There are two reasons to believe that this should not inhibit the validity of these results. First, adolescents asked about their occupational aspirations are unlikely to distinguish between adult ages accurately. Previous studies have demonstrated that most young people expect to start their careers in their early to mid-20s (Barker and Galambos 2005, Crockett and Bingham 2000, Greene 1990). Second, sensitivity tests performed on these analyses revealed that there was no significant difference in the relationship between unmet aspirations and job satisfaction or depression by age.

3.2.3 Control variables

Occupational attainment is controlled using an indicator of the respondent’s current or most recent job’s Stevens-Featherman SEI score.⁴ Current employment status is controlled with dichotomous indicators of unemployed and out of the labor force, with currently employed as the reference category. The respondents’ reported logged yearly earnings from the previous year are also controlled for, after setting the minimum value to 2. Next, a linear measure of years of schooling completed is included in all models. Finally, controls for current family status are included in all models, including indicators of never married and separated, divorced, or widowed status compared to being married, and number of children.

Demographic controls and ability are included in all models. A dummy variable indicates whether the respondent is female. Race/ethnicity is measured using dichotomous indicators of Black, Latino, or other, with White as the reference category. Age is measured by a single variable indicating age in the baseline year. I include two measures of family structure: an indicator of whether the respondent was living with two biological or adoptive parents at age 14 and a variable indicating the number of siblings in the home. Two measures of socioeconomic status are included: parental educational attainment and a dichotomous indicator of whether at least one of the respondent’s parents held a job in a professional occupation. The Armed Forces Qualifying Test (AFQT) provides an indicator of ability.

A scaled indicator of self-esteem in 1980 serves as the closest available proxy of mental health at baseline. The Rosenberg (1965) self-esteem inventory is a 10-item scale measuring individual’s degree of approval or disapproval toward themselves. Respondents selected strongly agree, agree, disagree, or strongly disagree with whether they felt useless, no good, satisfied with themselves, they did not have much to be proud of, like a failure, and capable and thought of themselves as a person of worth, had a number of good qualities, had a positive attitude, and wished they had more self-respect. Items were coded so that higher numbers indicated more positive views. Responses were summed to create a scale with a range of 16 to 40 and average of 32.5. The Cronbach’s alpha for this item is .83.

A categorical measure of job satisfaction in 1979 was included in models predicting job satisfaction in 1992. Four dichotomous indicators were constructed: 1) Like very much (reference), 2) Like fairly well, 3) Dislike somewhat/very much, and 4) Not employed in 1979.

3.3 NELS Sample

The National Educational Longitudinal Study (NELS) began as a nationally representative survey of eighth graders in 1988. Approximately 24 eighth graders were sampled from each of 1,000 public and private schools for an N of 24,599. This sample was re-interviewed in 1990, 1992, 1994, and 2000. I use data from participants who completed the first follow-up in 1990 through the final follow-up in 2000, when respondents were approximately age 26 (N=11,422). This includes 94% of all participants in the final follow-up survey, and allows me to use panel weights to estimate longitudinal parameters that describe the population of 10th graders in 1990. Young men and non-whites were more likely to attrit between the two survey years employed. I further constrain my sample to respondents who were employed at some point during 1999 or 2000 (excluded=564) and who have valid responses on job satisfaction (missing=311), for an analytic sample size of 10,547. No depression indicators were available in the NELS dataset. Weighted descriptive data is presented in Table 1.

3.4 NELS Measurement

3.4.1 Dependent variable

The measure of job satisfaction employed for the NELS dataset is a question asking respondents whether they were satisfied (1) or dissatisfied (0) with their current or most recent job overall.

3.4.2 Key explanatory variables

Occupational expectations in the NELS dataset (“Which of the categories below comes closest to describing the job or occupation that you expect to have when you are 30 years old?”) came from the second wave of the survey, when most respondents were sophomores in high school. Possible responses were: clerical, craftsman, farmer, homemaker, laborer, manager/administrator, military, operative, “low” professional (e.g., nurse), high professional (e.g., lawyer), proprietor, protective services, sales, school teacher, service, technical, not planning to work, other, and don’t know. These responses were converted into 13 occupational categories by eliminating homemaker, not planning to work, other, and don’t know responses, and combining proprietor and manager/administrator into a single group and military and protective service into another group. Next, I computed average SEI values for each category.⁵ Occupational attainment in 2000 was converted into the same average SEI values.

Using the average SEI values, occupational attainment was subtracted from expectations, and the gap between these values was converted into the same categories used for the NLSY analyses: exceeded aspirations, matched on desired and obtained occupational SEI (reference), and fell short. Additional categories indicated that the respondent did not know what occupation they wished to hold or held another occupational aspiration. This latter category included those who selected “other”, did not wish to work, or wished to take care of home and family.

3.4.3 Control variables

Control variables were matched to the NLSY data when possible. Occupational attainment was included as a linear measure of average SEI score for the category. Income, employment status, marital status, and number of children were coded identically to these measures in the NLSY data. Respondent educational attainment was measured categorically. Due to the young age of this sample, a dummy variable for school enrollment was included in all models. Other controls included sex, race/ethnicity, family structure, and parental attainment. Age was measured in categories of ages 14–15, 16, and 17–19. A standardized reading score controls for prior ability. Lastly, the NELS survey collected responses to a self-concept indicator at baseline. Respondents indicated (strongly agree to strongly disagree) whether they felt good about themselves, they were a person of worth, able to do things as well as others, satisfied with themselves, useless, no good at all, they did not have much to be proud of, and emotionally empty. These variables were recoded so that higher numbers indicated more positive self-concept, and summed. The Cronbach’s alpha for this scale is 0.83, indicating a high internal consistency. Unfortunately, no early measure of job satisfaction was available in the NELS data.

3.5 Missing data and weighting

Missing data was imputed for all analyses by replacing missing values with predictions based on observed information in the sample (Rubin 1987). Prediction models used all variables used within the primary analysis, but dependent variables are not imputed (Allison 2002). Data was imputed using the “ICE” program in Stata 12, and results were obtained by averaging results across five imputed datasets.

Sample weights were used for analyses of the NLSY and NELS data. Descriptive statistics for the NLSY data are weighted to provide population estimates using the 1979 cross-sectional weight for demographic and family background control variables and 1992 panel weights for outcome and attainment variables measured in those years. Multivariate analyses are weighted using the 1992 panel weight. Panel weights incorporate adjustments for the base year sample design and differential probabilities of inclusion and make adjustments for sample attrition at each wave (MaCurdy, Mroz, and Gritz 1998). NELS descriptive statistics and multivariate analyses are weighted to adjust for unequal probabilities of sampling in 1990 and non-response in each subsequent year to yield population estimates of 10^th graders in 1990.

3.6 Comparing across NLSY and NELS cohorts

Using data for the NLSY (older) cohort, I examine the costs of unmet aspirations for job satisfaction and depression. I follow with an analysis of the impact of unmet expectations on job satisfaction in the NELS (younger) cohort. The coefficients for the relationship between failed goals and well-being are not comparable across datasets. Rather, the NLSY provides detailed data with which to examine the influence of unmet aspirations on well-being, while NELS data shows that the conclusions drawn from the first cohort are robust across time. These datasets are unique in containing measures of occupational goals at adolescence and attainment in adulthood. Longitudinal data on adolescence through early adulthood remains scarce, and several surveys of youth collect data on educational goals, but not occupational goals (e.g. Add Health, NLSY97).

One difference between the cohorts deserves special mention. The NLSY asks respondents to provide their occupational aspirations, whereas the NELS survey asks for respondents’ expectations. To adjust for this, I conducted additional analyses for the NLSY cohort, limiting the sample to those who said their expected ability to achieve their goals was either “excellent” or “good.” Results were consistent using this criterion.

3.7 Analytic Strategy

Models of job satisfaction using the NLSY dataset employ an ordinal logit model. The CES-D scale is essentially a positively skewed count variable, making ordinary least squares regression an inappropriate means of analysis. Furthermore, the variance of this measure (86.6) was much higher than the mean (9.8). This distribution is best suited to a negative binomial regression, which is appropriate for count variables in which the variance exceeds the mean. After employing this method, chi-square and Wald chi-square tests confirmed that the negative binomial regression outperformed a Poisson regression in predicting depression.

Logistic regression was employed to predict the log-odds of reporting overall satisfaction with one’s current job using NELS data. Standard errors are reported in parentheses in all tables. For both cohorts, I tested whether results differed by gender by interacting indicators of unmet goals and all control variables with respondent sex. I found significant differences by gender in the relationship between unmet goals and depression for the NLSY cohort. I report results separately for men and women for this outcome.

4.0 Results

4.1 NLSY

Table 2 presents results from regressing job satisfaction and depressive symptoms on failure to attain one’s aspirations and other background factors for the NLSY cohort. The first column displays coefficients for an ordinal logistic regression predicting job satisfaction. Coefficients in this model are equivalent to the expected change in the log-odds of job satisfaction for a one unit increase in the explanatory variable. Odds ratio output is also provided, for ease of interpretation. They represent the cumulative probability of being in one category versus all lower or higher categories. Results from this model show that falling short of one’s occupational aspiration is associated with an odds ratio of 0.77, suggesting that those who fell short of their aspirations by a small amount have 23% lower odds of reporting that they liked their job very much compared to all lower categories. Not knowing one’s aspiration in adolescence was unrelated to later job satisfaction. Higher SEI scores and being currently employed are also related to an increase in job satisfaction, such that every one-point increase in attained SEI was associated with a 1% increase in the odds of reporting satisfaction with one’s job, holding other factors constant. Being unemployed or not in the labor force decreased the odds of reporting high satisfaction with one’s previous job (by 30% and 28%, respectively) compared to those currently working. Never married respondents had 0.87 times the odds of reporting high job satisfaction than unmarried respondents, and divorced or separated young adults had .85 times the odds of reporting satisfaction. Black respondents had 17% lower odds than whites of saying they liked their jobs very much compared to all lower response categories, while Latino respondents had 20% higher odds than whites of reporting liking their jobs very much. Respondents who exhibited higher cognitive ability in adolescence reported lower job satisfaction on average. The coefficient for this predictor is −0.04, suggesting that for every additional 10 points on the AFQT test, the odds of reporting high satisfaction drops by 3.92%. Self-esteem was positively related to job satisfaction, with each point increasing the odds of reported high job satisfaction by 4%. Early levels of job satisfaction were strongly associated with job satisfaction in 1992.

Table 2.

Weighted analyses of job satisfaction and depression in 1992 on failure to attain aspirations (NLSY)

	All		Meng		Womeng
	Job Satisfaction	Odds ratio	Depression	IRR	Depression	IRR
Aspiration-Attainment matcha
Exceeded	−0.15 (0.11)	0.86	0.17 (0.08)	1.19	−0.02 (0.07)	0.98
Fell short	−0.26* (0.10)	0.77	0.22** (0.07)	1.25	−0.01 (0.07)	0.99
Did not know aspiration	−0.15 (0.14)	0.86	0.20* (0.10)	1.22	−0.00 (0.09)	1.00
Occupational SEI score	0.01*** (0.00)	1.01	−0.00 (0.00)	1.00	0.00 (0.00)	1.00
Logged income	0.01 (0.03)	1.01	−0.03 (0.02)	0.97	−0.01 (0.02)	0.99
Employment statusb
Unemployed	−0.36* (0.15)	0.70	0.18* (0.08)	1.20	0.30*** (0.08)	1.35
Not in labor force	−0.32* (0.14)	0.72	0.41*** (0.11)	1.50	0.10 (0.07)	1.11
Years of schooling	0.01 (0.02)	1.01	−0.00 (0.01)	1.00	−0.03* (0.01)	0.97
Marital statusc
Never married	−0.14* (0.07)	0.87	0.23*** (0.05)	1.26	0.16** (0.05)	1.17
Separated/divorced/widowed	−0.16* (0.08)	0.85	0.33*** (0.06)	1.39	0.28*** (0.05)	1.32
Number of children	0.05 (0.03)	1.05	0.06*** (0.02)	1.06	−0.02 (0.02)	0.98
Female	0.04 (0.06)	1.04	---		---
Race/ethnicityd
Black	−0.19* (0.08)	0.83	0.05 (0.05)	1.06	−0.02 (0.05)	0.98
Latin	0.18* (0.08)	1.20	0.04 (0.06)	1.04	−0.01 (0.06)	0.99
Other	0.01 (0.08)	1.01	−0.05 (0.05)	0.95	−0.01 (0.06)	0.99
Age	−0.01 (0.01)	0.99	0.00 (0.01)	1.00	0.02* (0.01)	1.02
Two-parent family	0.02 (0.06)	1.02	−0.02 (0.04)	0.98	−0.08 (0.04)	0.92
Number of siblings	−0.01 (0.01)	0.99	−0.01 (0.01)	0.99	0.01 (0.01)	1.01
Parent in professional occupation	−0.03 (0.09)	0.97	−0.07 (0.06)	0.93	0.02 (0.07)	1.02
Parent’s educatione
Less than high school	−0.10 (0.07)	0.90	0.03 (0.05)	1.03	−0.01 (0.05)	0.99
Some college/technical school	−0.02 (0.09)	0.98	0.04 (0.06)	1.04	−0.04 (0.06)	0.96
Four years of college	−0.12 (0.09)	0.89	0.11 (0.07)	1.12	0.14* (0.07)	1.15
AFQT score	−0.00** (0.00)	1.00	−0.00*** (0.00)	1.00	−0.00*** (0.00)	1.00
1980 Self-esteem	0.04*** (0.01)	1.04	−0.04*** (0.00)	0.96	−0.04*** (0.01)	0.97
1979 Job satisfactionf
Like fairly well	−0.45*** (0.08)	0.64	---		---
Dislike somewhat/very much	−0.71*** (0.12)	0.49	---		---
Not working	−0.32*** (0.08)	0.72	---		---
Constant	----		3.41***		3.67***
N	7,769		4,103		3,600
Cragg-Uhler R-squared	----		0.12		0.09
Log-likelihood	−7712.79		----

^*p < 0.05,

^**p < 0.01,

^***p < 0.001, Standard errors in parentheses

^aReference category is “Matched aspiration and attainment”

^bReference category is “Employed”

^cReference category is “Married”

^dReference category is “White”

^eReference category is “Completed HS”

^fReference category is “Like very much”

^gSignificant differences between men and women in the fully interacted model (p<.05) are bolded for ease of interpretation.

Next, I employed a negative binomial regression to predict depressive symptomology from the same set of predictors. Interactive models indicated that the relationship between unmet aspirations and depression differed by gender, so I present separate models for men and women. Bolded numbers indicate a significant difference in the relationship between these variables and depression by gender. Coefficients are equivalent to the expected change in the log of the outcome variable for a one-unit increase in the explanatory variable. These coefficients can also be expressed as incidence rate ratios (IRR), which show the expected change in the rate of the outcome variable for a one-unit increase in the explanatory variable.

For men, I find that falling short of one’s occupational aspirations is associated with a .22 increase in the log of depressive symptoms, or a rate of depressive symptoms that is approximately 1.25 greater than those whose aspirations in adolescence matched their attainment in 1992. Although not knowing one’s aspirations also appear related to depressive symptoms for men, the coefficient for this variable was insignificant in the combined model and interactions indicated no significant difference in results by gender. For women, falling short of one’s occupational aspirations was unrelated to number of depressive symptoms.

Several other predictors were significantly related to men’s and women’s depressive symptoms. Being unemployed was significantly associated with higher levels of depressive symptoms for both men and women, by a logged value of about 0.24 in the combined model. For men, being out of the labor force (not working or looking for work) was related to a 1.50 increase in the rate of depressive symptoms compared to those who were employed. For both men and women, being unmarried increased the log of depressive symptoms. The rate of depressive symptoms was 1.26 times higher for never married men and 1.39 for separated or divorced men than for married men, and 1.17 and 1.32 times higher for never married and separated or divorced women, respectively, than for married women. Each additional child increased the rate of depressive symptoms by 1.06 for men, but not for women. Family background factors were unrelated to depressive symptoms. AFQT and self-esteem measures were both negatively related to depressive symptoms. For each one point increase in the AFQT score, the rate of depressive symptoms decreases by a factor of 0.996 for both men and women, holding all other factors constant. For each one point increase in self-esteem, the rate of depressive symptoms decreases by a factor of 0.96 for men and 0.97 for women.

Theories of human development suggest that young people may adjust their aspirations downward over time, cushioning the disappointment they experience in response to unmet aspirations (Heckhausen 1999; Tomasik et al. 2009). Alternatively, social psychological factors such as resilience may moderate responses to these unmet goals (Brandtstadter and Renner 1990). To test the first proposal, a measure of occupational aspirations in 1982 was used to create an indicator of whether the respondent adjusted his or her occupational aspiration downward between 1979 and 1982,⁶ and dummy variables indicating of adjustment/non-adjustment and the aspirations-attainment match were also constructed (results available upon request). Neither approach changed the results. The index of self-esteem was interacted with indicators of the aspirations-attainment match, but no significant interactions were found. Two alternative measures that might alter young adults’ reactions to failed aspirations were interacted with aspirations-attainment match indicators: mastery (the extent to which individuals feel they are in control) and a dummy variable indicating whether the respondent thought discrimination on the basis of race, sex, nationality, or age had interfered with their ability to obtain a job. Neither set of interactions was significant.

4.1.1 Robustness checks for NLSY analyses

Supplemental analyses (available upon request) point to the robustness of the preceding findings. I tested several alternative measures of the aspirations-attainment gap, including a linear measure of the distance between one’s occupational aspiration and attainment SEI; a squared term and linear term; a logged term; and a six-category measure dividing the exceeding and falling short categories into relatively small and large gaps. Coefficients for the linear, squared, and logged terms were statistically insignificant. The six-category term and tests of coefficient differences suggested that there was no significant difference between large and small gaps between one’s aspirations and expectations. I also tested whether excluding respondents who had aspired to stay home and raise a family changed the results, which they did not. Next, I considered whether including the long-term unemployed in models of depression alter the results (job satisfaction was not available for this group). Long-term unemployment was, surprisingly, unrelated to depression, and inclusion of this category did not change the association between falling short of and exceeding one’s occupational goals.

Finally, I tested whether social class background (operationalized as whether one or more parents worked in a professional occupation) and race/ethnicity moderated the association between unmet aspirations and either outcome. There were no significant interaction effects for social class. Hispanic respondents’ depressive symptoms were more strongly associated with either exceeding or falling short of their goals than Whites in the full sample, and both relationships were positive. No other differences were evident.

4.2 NELS

Table 3 presents results from analyses of the relationship between failed expectations and job satisfaction for the NELS cohort. Interestingly, both exceeding and falling short of one’s occupational expectations is significantly and negatively related to job satisfaction. The odds of reporting job satisfaction for those who exceeded their expectations was 0.66 times as high as for those who met their goals. Falling short of occupational expectations lowered the odds of reporting job satisfaction by 49%. Those who said they did not know what they wanted to do had 0.57 times the odds of reporting job satisfaction compared to those who matched their goals.

Table 3.

Weighted estimates of job satisfaction on failure to obtain expectations (NELS)

	Job Satisfaction	Odds
Expectation-Attainment matcha
Exceeded	−0.42* (0.21)	0.66
Fell short	−0.67*** (0.17)	0.51
Did not know aspiration	−0.57** (0.22)	0.57
Other aspiration	−0.27 (0.21)	0.76
Occupational SEI score	0.02*** (0.00)	1.02
Logged income	0.05 (0.04)	1.05
Employment statusb
Unemployed	−1.33*** (0.19)	0.26
Not in labor force	−0.93*** (0.21)	0.39
Educational attainmentc
High school graduate	0.39 (0.33)	1.48
Some college	0.15 (0.34)	1.16
College graduate or more	0.44 (0.36)	1.55
Marital statusd
Never married	0.45** (0.14)	1.57
Separated/divorced/widowed	0.16 (0.28)	1.17
Number of children	0.03 (0.07)	1.03
Enrolled in school	−0.57*** (0.12)	0.57
Female	−0.24* (0.12)	0.79
Race/ethnicitye
Black	−0.80*** (0.20)	0.45
Latin	−0.17 (0.19)	0.84
Other	0.06 (0.28)	1.06
Agef
Age 14–15	−0.19 (0.21)	0.83
Age 17–19	−0.02 (0.16)	0.98
Two-parent family	0.21 (0.14)	1.23
Number of siblings	−0.01 (0.04)	0.99
Parent in professional occupation	0.16 (0.17)	1.17
Parent’s educationc
High school graduate	−0.11 (0.30)	0.90
Some college/technical school	0.02 (0.25)	1.02
Four years of college’	−0.24 (0.27)	0.79
Reading test score	−0.02* (0.01)	0.98
Self-concept	0.05** (0.02)	1.05
Constant	1.10
N	10,571
Log-likelihood	−4304.70

^*p < 0.05,

^**p < 0.01,

^***p < 0.001, Standard errors in parentheses

^aReference category is “Matched aspiration and attainment”

^bReference category is “Employed”

^cReference category is “Completed HS”

^dReference category is “Married”

^eReference category is “White”

^fReference category is “Age 16”

Several control variables were associated with job satisfaction. Each additional 10 SEI points on the index is related to a 22% increase in the odds of reporting job satisfaction. Respondents who were unemployed or not in the labor market had lower odds of saying they were satisfied with their job (for their most recent job prior to leaving the labor market) than employed respondents, by a factor of 0.26 and 0.39, respectively. The odds of reporting that they were satisfied with their jobs was 1.57 times as high for never married respondents compared to married respondents. Those enrolled in school were 0.57 times as likely to say they were satisfied as those not enrolled. Black respondents had 55% lower odds of reporting job satisfaction compared to whites. Finally, higher ability was associated with lowered job satisfaction, while those with higher self-concept report greater job satisfaction. Each additional point on a reading aptitude test was associated with 2% lower odds of job satisfaction in young adulthood, and each additional point on the self-concept index was associated with 5% higher odds of reporting job satisfaction in adulthood.

A final step in the analyses (results available upon request) investigated whether adjusting one’s occupational expectations between 1990 and 1994 (when respondents were approximately age 20) mediated or moderated the relationship between unmet expectations and job satisfaction or whether self-concept moderated the association between the expectations-attainment gap and job satisfaction. There was no evidence for a relationship between adjusted expectations and job satisfaction.

4.2.1 Robustness checks for NELS analyses

There were no significant differences in the relationship between expectations-attainment match and job satisfaction by gender, race/ethnicity, or social class in the fully interacted model. I also tested models controlling for other aspirations and wished not to work separately and using alternative linear and categorical measures of expectations-attainment match. Findings were robust across all measures, and findings did not differ by relative size of the expectations-attainment gap. I also tested whether including the long-term unemployed and not employed but controlling for an indicator of this status would change my results. The coefficient for falling short of one’s goals remained significant and negative, although the coefficient for exceeding one’s goals became insignificant in the larger group analysis. Long-term unemployment/non-employment was unrelated to reported job satisfaction of the last held job. Finally, I used an alternative measure of job satisfaction, which added indicators of respondents’ satisfaction with their jobs along seven dimensions (pay, benefits, importance of work, opportunities for advancement, opportunities to use past training/education, job security, and opportunities for further training/education). I regressed the total value onto all independent and control variables. Results were congruent with the findings for overall satisfaction.

5.0 Discussion

Research has long claimed that happiness is based not only on absolute measures of well-being, but also on relative measures (e.g. Blanchflower and Oswald 2004, Diener 1984, Easterlin 1995). This paper demonstrates the importance of early goals as a standard against which young adults compare later accomplishments, and offers qualified support for social-psychological theories of goal setting and well-being.

First, job satisfaction is strongly related to the gap between young adults’ occupational goals and outcomes. This is important, because employed Americans spend nearly one-quarter of their time in work-related activities (Frazis and Stewart 2004). Being dissatisfied with one’s job has been found to increase stress, anxiety, and other markers of poor mental health (Faragher, Cass, and Cooper 2005; Heslop et al. 2002). Across two cohorts, gender, social class, and race/ethnicity, young adults expressed less satisfaction with their work if they fell short of their prior goals. This is remarkable given the increasing number of people who fell short of their goals in the younger cohort.

Failing to achieve one’s early occupational aspirations is also related to more depressive symptoms among men in the older cohort. Although the relationship between unmet aspirations and depressive symptoms is moderate, the results are robust to several specifications of the model and including controls for occupational and educational attainment, income, and employment status. This is notable both for the seriousness of the outcome and the gendered nature of this association. Unmet aspirations were not related to women’s depressive symptoms in the older cohort. For this generation of men and women, differences in attitudes toward work and family life and expectations regarding careers (Lopata 1993; Rindfuss, Brewster, and Kavee 1996) may have tempered women’s reactions to falling short of their goals. However, a similar study by Carr (1997) found that unmet occupational aspirations lowered middle-aged women’s well-being. Therefore, it may be that women in their mid-20s in the early 1990s anticipated that their careers might be delayed by marriage and childbearing (Maines and Hardesty 1987). Later in the lifecourse, unmet aspirations may have more serious repercussions for women.

Two other findings deserve attention. First, not having an occupational goals is related to lower job satisfaction in adulthood among the younger cohort and more depressive symptoms among the older cohort. This finding supports prior research suggesting that uncertain career ambitions have negative consequences for young adults (Staff et al. 2010). It also demonstrates support for developmental theories of adolescence which characterize aspiration formation as an important component to successful development (Heckhausen 1999; Heckhausen and Tomasik 2002; Tomasik et al. 2009). Second, exceeding one’s aspirations appears to be associated with costs to well-being among the younger cohort. More research is needed to understand this outcome. It may be that for at least some young adults, relative deprivation is an even more markedly comparative stance than prior work assumes, making the definition of “failure” about personal goals and outcomes as well as social ranking and occupational benefits. This finding speaks to the literature arguing that deprivation is a fully situated experience, although in contrast to such work (Stewart 2006), I find that rather than improving one’s outcomes, relative success may still be experienced by the individual as failure.

These findings differ from conclusions reached by Reynolds and Baird (2010), who found that unmet educational expectations did not predict depression among two cohorts of youth. Given the similarities of these studies, the explanation likely lies in the difference between educational and occupational goals. Recent research shows that young people’s educational and occupational goals are increasingly disconnected from one another (Goyette 2008, Schneider and Stevenson 1999). In fact, many young people hope to complete more education than is necessary for the jobs they wish to hold, possibly due to the increasingly common assumption that getting a college degree is a normative part of the transition to adulthood (Goyette 2008). Therefore, falling short of one’s educational goals may not always coincide with unmet occupational goals. Additionally, young people who do meet their educational expectations may find themselves overeducated for the jobs they hold, leading to frustration with these jobs (Vaisey 2006). More research is needed to understand the interactions between adolescent goals and outcomes within the educational and occupational spheres.

These findings have implications for theories of goal setting and adolescent and young adult development. According to multiple discrepancies theory, well-being is conditional on the standards one sets for oneself (Michalos 1985, see also Higgins 1987). Previous research has demonstrated that this may include a reference group, such as peers or co-workers (Bernburg, Thorlindsson, and Sigfusdottir 2009; Yngwe et al. 2005). The current study shows that individuals’ own goals may become standards against which they judge themselves. Not meeting these goals has implications for well-being, particularly within work settings. Possible selves theory suggests that one kind of plan, such as an occupational goal, may be linked to daydreams about lifestyle, home ownership, vacations, leisure activities, and other material expectations that signal the good life. As this paper demonstrates, failing to achieve this occupational success—and, perhaps, the accompanying lifestyle—has consequences for job satisfaction and depression in young adulthood. While the size of these effects are modest, it is important to note that unrealized goals were consistently linked to lower job satisfaction and emotional well-being while controlling for ability, educational and occupational attainment, income, employment status, and family status, all of which have independent effects on these outcomes.

Theories of adolescent development suggest that starting with ambitious aspirations and readjusting them over time is the best strategy for maintaining well-being (Heckhausen 1999; Tomasik et al. 2009). Findings from the current study did not support this contention. Young people who lowered their occupational goals in late adolescence did not respond any better than those who hold consistently high goals. However, this test was rough, given the data available, and therefore the conclusions are preliminary. Additional literature suggests that social-psychological factors may moderate responses to unmet goals (Brandtstadter and Renner 1990), yet findings for both cohorts showed no discrepancy in response by prior measures of self-esteem or self-concept, mastery, or attribution of failure to discrimination.

5.1 Limitations

There are several limitations to the current study. One important limitation is the inability to directly compare results across datasets. The two datasets differ in whether they ask about aspirations (NLSY79) or expectations (NELS), which may explain the relatively larger association between unmet goals and job satisfaction for the younger cohort; these young people are falling short of something they thought they could achieve, perhaps making failure more disappointing. Supplemental analyses support this supposition, showing larger associations between unmet aspirations and job satisfaction in the NLSY79 dataset when restricting the analyses to those who felt they had a good or better chance of attaining their goals. Other differences between the datasets remain. NELS data does not provide an outcome measure of depression or similar measures of well-being, and does not provide an early measure of job satisfaction against which to compare later reports.

Another limitation is the exclusion of those who are unemployed for a long period. This group of people have not met their occupational goals, and therefore their exclusion may weaken the findings. The choice to exclude them was made both for theoretical reasons (long term unemployment may be due to a number of different factors that are not identifiable within these datasets) and practical (job satisfaction was not obtained for this group in the NLSY79, controls for the reason of unemployment/non-employment were not available in NELS, and recall regarding job satisfaction in a job held years ago could bias findings). Supplemental analyses including the long-term unemployed/not employed in both datasets do not change the results, but more could be done in future studies to understand how this group might react to failed goals.

6.0 Conclusion

The foregoing analysis and discussion suggest that unmet occupational goals have negative consequences for two cohorts of young adults. Given growing optimism among adolescents (Goyette 2008; Csikszentmihalyi and Schneider 2000; Reynolds et al. 2006; Pew Report 2011), the implications of this research are worrying. One solution may be to simply dampen young people’s goals, yet previous research demonstrates that high aspirations are positively associated with school and career investment and outcomes (Massey, Gebhardt, and Garnefski 2008; Vuolo, Mortimer, and Staff 2011; Yowell 2000). It is therefore inadvisable to discourage lofty goals completely. Instead, policy aims must balance the value of high aspirations with the means to accomplish them. An ideal scenario for adolescents would be to work toward specific occupational goals that are ambitious but reachable. Specificity would encompass both the identification of a particular job or job type one wishes to hold (ie, “registered nurse working in a hospital environment” instead of “nurse”) and knowledge of that occupation’s employment qualifications, typical remunerations, and working environment. Knowledge of the path to accomplishing one’s goals has been touted as an important resource in achieving them (Schneider and Stevenson 1999). Simultaneously, efforts must be placed toward strengthening connections between educational and work pathways and stable careers. Together, these efforts would encourage ambition while improving the odds that young people’s goals will be reached.

More research is needed on this topic. The conclusions reached here are limited to young adults, yet it is also important to ask how failing to meet one’s occupational goals will influence individuals across the life course. If these goals are never met, do adults’ disappointment and dissatisfaction continue and deepen? Or do men and women adjust to current circumstances over time? Additional research using panel data is needed to follow workers over time and evaluate the costs of unmet goals over the lifespan. In addition, more attention to differences in response to unmet goals by gender, social class, race/ethnicity is warranted. The current study found that the relationship between unmet goals and depression in the older cohort differed by gender and among Hispanics compared to whites, but more could be done to investigate these differences over time and with alternative outcomes.

Conceptualizations of occupation measures, additional outcomes, and the functional form of the goals-attainment match are also important avenues of future inquiry. For example, it is important to look at differences by industry, in addition to occupational status. It may be that dampening one’s goals from being a doctor to a nurse would be less consequential than moving both downward in occupational status and across industries. Additional analysis is also needed to investigate health outcomes that might be influenced by unmet goals, as well as how health might be a precursor to such gaps. Finally, it is important to consider the functional forms that the relationship between the goals-attainment gap and well-being outcomes may take. Although I test some alternative relationships using this data, more research is needed to understand variation in responses to smaller and larger gaps between goals and outcomes.

Highlights.

• Occupational aspirations are predictive of future attainment.

• This study tests psychosocial costs of not meeting occupational aspirations.

• Two cohorts of youth are studied.

• Unmet goals associated with higher depressive symptoms among men in older cohort.

• Unmet goals associated with lower job satisfaction among for all in both cohorts.