Compromise,Well-Being,and Action Behaviors in Young Adults in Career Transition

Abstract

The authors surveyed 186 first-year university students and assessed their level of career compromise associated with making the transition to university. Compromise was operationalized as the discrepancy between the job characteristics of ideal and expected occupations. The authors also assessed career well-being (satisfaction, distress), action behaviors (planning, exploration), and goal adjustment (disengagement, reengagement). The authors expected compromise to be negatively associated with well-being and positively associated with action behaviors, and the relationship between compromise and the outcome variables (well-being, action behaviors) to be moderated by goal adjustment. Compromise was negatively associated with well-being, but not associated with planning or exploration, although the Compromise × Goal Adjustment interaction was significant. Disengagement and reengagement were not associated with well-being, although the Disengagement × Reengagement interaction was significant. Disengagement was associated with planning and exploration, reengagement was associated with exploration, and both interaction terms were significant.

Keywords

career compromise career well-being career action behaviors goal adjustment goal disengagement goal reengagement career adaptability

The task of deciding on a career is an important aspect of transitioning from childhood and adolescent roles to being part of the adult workforce (Super, Savickas, & Super, 1996). In meeting this transitional task, young people assess their own interests, abilities, and opportunities, and accept or reject particular careers as possible options for themselves. They also become aware of constraints that may result in the need for compromise on desired career options: constraints that require them to give up more attractive, but less feasible, options, and pursue more practical and obtainable ones (Gottfredson, 2005). While discarding unattainable occupations and adopting new work goals is a normal part of settling on a career, there is limited research into the career compromise process; in particular, there is very little research that has examined the effects of career compromise on the individual, and virtually no research that has assessed what characteristics or strategies might facilitate or impede career progress after having to compromise on a desired career (Blanchard & Lichtenberg, 2003; Tsaousides & Jome, 2008). The current study sought to add to our understanding of career compromise by (a) testing whether career compromise was associated with career-related well-being (operationalized as career satisfaction and career distress), (b) testing whether career compromise was associated with career-related action behaviors (operationalized as career planning and career exploration), and (c) testing whether the capacity to adjust to a change in career goals (operationalized as the ability to disengage from a discarded career goal and reengage in a new career goal; Wrosch, Scheier, Miller, Schulz, & Carver, 2003), affected (i.e., moderated) the relationship between career compromise and career-related well-being, and moderated the relationship between career compromise and career action behaviors (see Figure 1).

Figure 1.

Proposed model: (a) career compromise negatively associated with career well-being, (b) positively associated with career action behaviors, and (c) both relationships moderated by goal adjustment (i.e., goal disengagement and reengagement).

Career Compromise

Virtually all career theories allude to, or specifically incorporate, a process of career compromise. For example, Holland’s (1997) person–environment fit theory of careers proposes that individuals develop an awareness of their own abilities, interests and needs, and seek out occupations that require their capabilities and satisfy their needs; that is, match their personality with the personality of the occupation. While individuals may be attracted to a range of occupations, they are more likely to be successful and satisfied when they select occupations that offer a good fit for their personality (i.e., they should discard options that do not provide a good person–environment fit, even if they are attractive to the individual). Second, social cognitive career theory (Lent, Brown, & Hacket, 1996) promotes the development of self-efficacy and ability/outcome contingency relationships as key drivers of career choice (i.e., holding efficacy for a particular area and believing that effort expended toward that area will bring rewards, will lead individuals to set goals in that direction), but that encountering barriers to those goals will lead individuals to reappraise their career direction (i.e., they will compromise on a particular set goal and redirect efforts elsewhere). However, the career theory that most explicitly addresses the career compromise process is that proposed by Gottfredson (2005). Gottfredson argues that individuals are attracted initially to occupations that are, in turn, consistent with their gender, values, and self-concept (i.e., individuals circumscribe or delineate occupations that are desirable), and then, when confronted with the realities of the occupational environment, compromise on their most desirable occupations and shift their orientation to more achievable ones.

Compromising on a career goal parallels the process of goal adjustment (Wrosch, Scheier, Miller, et al. 2003) in goal-setting theory (Locke & Latham, 2002). From this perspective, individual behavior is purposeful and motivated by the goals that individuals set for themselves, or are set by others (e.g., set by curriculum goals in education settings). Goals, and behaviors associated with goals, are continually monitored (consciously and unconsciously), and when discrepancies occur between where an individual wants to be (i.e., their goal) and their current situation (i.e., what they have achieved), goal adjustment strategies are likely to come into play. These goal adjustment strategies can involve an adjustment to the goal itself (e.g., raising or lowering the goal), an adjustment to the energies expended on the goal (e.g., increasing or decreasing the behaviors associated with meeting that goal), or adjustments to both means and ends (e.g., lowering the goal and reducing the effort currently expended to meet it; Lord, Diefendorff, Schmidt, & Hall, 2010).

Career Compromise and Well-Being

Adjusting goals downward (i.e., compromising on a desired goal) is typically associated with reduced satisfaction and well-being and associated with a change in behaviors around the compromised goal and any new goals (Lord et al., 2010). In relation to well-being, giving up on a cherished goal can be appraised as threatening, and thus stressful to the individual, which can result in negative feelings such as dissatisfaction, sadness, and distress (Carver & Connor-Smith, 2010). This proposition is supported by the general goal-disruption literature (MacGeorge, Samter, Feng, Gillihan, & Graves, 2007; Roseman & Smith, 2001), and consistent with reports in the career area. Carr (1997), for example, asked women who were in their mid-career to reflect on their past occupational goals, and found that those who were dissatisfied with their level of achievement, vis-à-vis their original expectations, were more likely to report symptoms of depression and to have less purpose in life. Hesketh and McLachlan (1991) compared two groups of employees in the banking sector, one group who saw their job as a compromise on what they really wanted, and a second group who were not compromisers. Those who viewed their job as a compromise were less satisfied and reported more negative attitudes about their career. Using an experimental design, where students were assigned to one of the four compromise conditions (none, minor, moderate, major), Tsaousides and Jome (2008) found negative associations between compromise and measures of well-being. Based on the above, our first prediction (Hypothesis 1) was that career compromise would be negatively associated with well-being (See Figure 1).

Career Compromise and Behavior

Compromising on a desired goal is likely to be associated also with a change in behaviors around the compromised goal (e.g., a student withdrawing from a desired course) and around any new goals (e.g., exploring the best educational pathways to achieve the new goals; Lord et al., 2010). These relationships are reflected in the general perspective that goals are powerful motivators of behaviors (Covington, 2000; Locke & Latham, 1990), and specifically delineated in much of the career literature. The social cognitive career theory (Lent et al., 1996), for example, explicitly states that the three key motivators of career-related behaviors are self-efficacy, outcome expectations, and career goals. The same authors describe these three variables as the “building blocks” of career development, as they are considered the most important variables driving the individual’s career behaviors. Thus, compromising on an unattainable career goal and establishing new goals also has the effect of driving new behaviors for the individual. Hesketh and McLachlan (1991) found this when they compared compromisers and noncompromising graduate students in the banking industry. Compromisers reported greater turnover intentions, indicating that they did not believe they would be working in the banking sector in the future. Turnover intentions are strong predictors of actual turnover and are associated with a range of behaviors, such as job seeking, applying for jobs, and job withdrawal behaviors, such as reduced effort (Griffeth, Hom, & Gaertner, 2000).

We examined the two important career behaviors of planning and exploration, which are regarded as action behaviors in the social cognitive career theory as they underpin the mechanism for career-related agency (Lent et al., 1996). Career planning is an ongoing activity that becomes more salient at times of vocational crisis or transition. It involves marshalling the information one has to formulate a course of action. This might include setting subgoals, identifying strategies, and deciding on tasks and timelines that will be required to progress one’s vocational development (Zikic & Klehe, 2006). Career planning is associated positively with career success (Hall, 2002). Career exploration is also a lifelong process, and it too is especially important when the individual is in transition. Exploration involves the gathering of relevant information required to progress a career goal, and can include examining oneself (e.g., one’s interests and values) and examining one’s environment (e.g., finding out information about education and training, occupations and employers; Zikic & Klehe, 2006). Career exploration is viewed as an antecedent to career success (Blustein, 1997) and integral to sound career decision making (Hartung & Blustein, 2002). Thus, we considered that having compromised on a particular career would drive rethinking, exploration, and the planning processes associated with establishing and preparing for a new career; that is (Hypothesis 2), that career compromise would be positively associated with career exploration and planning (see Figure 1).

Intervening Variables

Important intervening variables that might affect the relationships between career compromise and well-being and between career compromise and behavior are the individual’s capacities, first, to disengage from a previously held goal, and, second, to reengage in a new goal (Wrosch, Scheier, Miller, et al. 2003). Goal disengagement reflects the capacity to withdraw effort and commitment from a goal that has been identified as unattainable, rather than continuing to persevere with it when it is not achievable. The advantages of being able to disengage from unachievable goals are that repeated failures and disappointments are avoided and personal and other resources are freed up to address the revised and/or newly set goals. Reengagement strategies, on the other hand, involve goal revision and/or identifying new goals, becoming committed to the new goals, and marshalling the required personal and support resources in an effort to move toward achieving them. Reengaging in new goals maintains a sense of purpose in life (Wrosch, Miller, Scheier, & Brun de Pontet, 2007).

The two processes of goal disengagement and reengagement are considered to be somewhat trait-like, but influenced by context, and to be somewhat independent constructs, meaning that an individual can disengage from one goal while not having an alternate goal in mind, and reengage in new goals without having discarded currently valued, but unachievable, goals (Wrosch, Scheier, Miller, et al. 2003). As goal disengagement and reengagement are somewhat separate constructs, it is thus possible that the two constructs will interact with one another and generate different outcomes for individuals with different levels of each, compared to the outcomes based on examining the two constructs separately. In support of this proposition, Wrosch, Scheier, and colleagues found that university students who were low on both disengagement and reengagement also reported the lowest levels of personal mastery and the poorest well-being.

Recent research has demonstrated the value of understanding goal disengagement and/or reengagement strategies in situations where the individual’s goals become unattainable. For example, Duke, Leventhal, Brownlee, and Leventhal (2002) found improved psychological well-being in older adults who were able to replace activities that were lost as a result of health problems. Wrosch, Scheier, Carver, and Schulz (2003) found better subjective well-being in students who used these goal adjustment strategies to manage the compromises and challenges of transitioning to university, and Wrosch et al. (2007) found fewer physical health symptoms in college students with more adaptive goal adjustment strategies. Thus, we considered that having the capacity to disengage from goals judged to be unattainable and reengage in new or revised goals would be beneficial when revising career pathways.

We expected (Hypothesis 3a) that the capacity to disengage from unobtainable goals and reengage in new goals would be positively associated with well-being. This hypothesis is consistent with previous studies (e.g., Wrosch, Scheier, Miller, et al. 2003), which found positive associations with well-being, although our study is the first to test the association in the career well-being domain. Second, we expected (Hypothesis 3b) that disengagement and reengagement would be positively associated with career-related activities. This hypothesis is also consistent with previous studies. Wrosch, Scheier, et al. found positive associations between goal adjustment and mastery behaviors. Again, our study is the first to test the association in the career area. Third, as those with higher levels of goal disengagement and reengagement are likely to be advantaged in situations where goals have to be adjusted, we expected (Hypothesis 4a) higher levels of goal disengagement and goal reengagement to buffer the relationship between career compromise and declines in well-being, and expected (Hypothesis 4b) higher levels of disengagement and reengagement to energize career action behaviors following compromise (see Figure 1). These hypotheses are consistent with viewing self-regulatory variables as intervening between goals and the individual’s well-being and behavior around those goals (Lord et al., 2010). There is evidence for this in the occupational area, where, for example, the (self-regulatory) capacity to seek feedback moderates the relationship between goal setting and performance (Neubert, 1998).

Consistent with previous literature regarding the interaction between disengagement and reengagement where it has been shown that some people have an easier time disengaging and reengaging than others (Wrosch, Scheier, Miller, et al. 2003), we also explored the interaction effects between these two variables, first, on well-being and career action behaviors, and, second, as moderators between compromise and well-being, and between compromise and career action behaviors, as particular profiles may be associated with the outcome variables and/or play buffering roles. These latter examinations are somewhat exploratory as no research has tested goal disengagement and goal reengagement as moderating variables between compromise and well-being and between compromise and behavior.

We tested all hypotheses using a sample of first-year university students. Using this sample is appropriate as the transition to university can involve many compromises to ideal career options. When commencing university, students confront many barriers and changes in person and personal circumstances, such as not getting an offer to a desired course, not liking a desired course when offered, and the developmental changes to values and preferences driven by this life stage (Albion, 2000).

Method

Participants

Participants were 186 first-year university students enrolled in a social science degree. There were 143 female (76.9%) and 43 male students (23.1%), whose average age was 19.72 years (SD = 2.29; range = 17–25). We asked students to indicate their typical high school grade (or equivalent): 18.3% indicated very high achievement, 62.4% indicated high achievement, and 18.3% indicated sound achievement (two students [1.1%] did not provide an answer to this question). On a 5-point scale of self-reported socioeconomic status, 9.7% reported being much better off in comparison to other students, 21% a little better off, 48.4% about the same, 15.1% a little worse off, and 2.7% much worse off (six students did not answer this question). Finally, 70.4% of the students reported working part-time as well as studying; 29.6% were not working.

Materials

Career compromise

Previous studies that assessed career compromise used single item questions (e.g., Hesketh & McLachlan, 1991), discrepancy scores between previously and currently held occupations (e.g., Carr, 1997), and simulated occupational discrepancy scores induced experimentally (e.g., Tsaousides & Jome, 2008). Some studies have assessed discrepancies between ideal and expected occupations and treated these as aspirational discrepancies (e.g., Rojewski, 2005), although they parallel the measures and intent used in the compromise research.

We sought to assess a broader construct of compromise by operationalizing it as the discrepancy between the job characteristics of the students’ ideal and expected occupations. Job characteristics are features inherent in all occupations, and include dimensions such as how much autonomy there is in the job and how much social contact is involved (Hackman & Oldham, 1980; Warr, 2008). Warr (2008) summarized nine job characteristics that are supported in the literature. These are the opportunities for control, skill use, externally generated goals, variety, environmental clarity, availability of money, physical security, interpersonal contact, and social position. Job characteristics act as motivators/demotivators and are related to occupational satisfaction, work attitudes, and achievement (Fried, & Ferris, 2006). An assessment of an individual’s perceived job characteristics can be considered a measure of person–job fit (Verquer, Beehr, & Wagner, 2003), and a measure of the discrepancy between the ideal and expected job characteristics can be considered a measure of compromise on the perceived fit with a desired occupation. Assessing compromise using job characteristics in this way provides a multidimensional measure of ideal and expected occupational goals and addresses criticism in the literature that using single occupational ratings generates too narrow a measure (Rojewski, 2005). To our knowledge, this is the first time that compromise has been operationalized and assessed in this manner.

First, we asked students (a) to think about the occupation they would “most like to have in the future”; that is, the occupation they would have if there were no barriers to achieving that position (This question is similar to that devised by Looft [1971] and used widely in the career literature [Rojewski, 2005]), and then (b) to rate a list of job characteristics, based on the job characteristics identified by Warr (2008), as being salient to all work settings. The students responded to 10 items (e.g., This job would require me to use a number of complex or high level skills, This job would let me use my personal initiative and judgment, and, This job would give me the opportunity to meet people), using a 6-point Likert-type format with end points of strongly disagree (1) and strongly agree (6).

Second, we repeated the above procedure for the students’ expected occupation. We asked students (a) to think about the job they “really expect to have in the future”; that is, taking into consideration the barriers that may stop them achieving their most desired job (cf. Looft, 1971), and then (b) to rate this occupation on the same 10 job characteristics (cf. Warr, 2008), using the same response format used for the ideal occupation.

Third, we created job characteristic discrepancy scores by subtracting the job characteristic scores for the expected occupation from the job characteristic scores for the ideal occupation. This was done separately for each individual pair of scores (e.g., the expected occupation independence job characteristic score was subtracted from the ideal independence job characteristic score, and so on). Fourth, we converted these individual job characteristic discrepancy scores to absolute discrepancy scores (i.e., we removed the negative signs). This is appropriate as career compromise may involve accepting a career pathway that offers less of a job characteristic than is desired (e.g., too little people contact) as well as one that offers too much of a job characteristic than is desired (e.g., too much people contact).

We conducted an exploratory factor analysis on the 10 individual absolute discrepancy scores. This analysis supported a single-factor structure, with factor loadings ranging from .48 to .65. We used the sum of this single factor as our measure of career compromise, where higher scores indicated more career compromise. The internal reliability coefficient for the 10 items was .81.

Goal adjustment

We used slightly modified versions of the 4-item Goal Disengagement scale and 6-item Goal Reengagement scale that were devised by (Wrosch, Scheier, Miller, et al. 2003). First, we revised the original items so that students were responding in the context of having compromised on career goals. For example, the question, “It was easy for me to stop thinking about that goal and let it go” was changed to “It was easy for me to stop thinking about that career and let it go” (goal disengagement), and the question, “I put effort towards other meaningful goals” was changed to “I put effort towards other meaningful careers” (goal reengagement). Second, as the Goal Disengagement scale contained 4 items only, we added a 5th item (I kept thinking about how much I really wanted that career) to broaden the domain coverage. Students responded to the items using a 6-point Likert-type format with end points of strongly disagree (1) and strongly agree (6). Wrosch, Scheier, et al. reported internal reliability coefficients of .84 and .86 for the two subscales, respectively, and provided support for validity by testing the factor structure and examining the association of the two scales with other constructs. We conducted a confirmatory factor analysis (CFA; AMOS Version 17) on the 11 items, which supported a two-factor model, χ²(29) = 60.22, p = .009, Goodness-of-Fit Index (GFI) = .94, Comparative Fit Index (CFI) = .98, root mean square error of approximation (RMSEA) = .06, with item loading ranging from .33 to .78 (goal disengagement) and .58 to .89 (goal reengagement). The internal reliability coefficients were .74 and .89, respectively.

Career-related well-being

We assessed two domains of career well-being: career satisfaction and career distress. Students responded to both scales using a 6-point Likert-type format with end points of strongly disagree (1) and strongly agree (6). Career satisfaction was measured using the 5-item Career Satisfaction scale (Richardson, Lounsbury, Bhaskar, Gibson, & Drost, 2009). This scale measures global satisfaction with one’s career path, career progress, and future career prospects. Sample items were, “I am satisfied with the way my career has progressed so far,” and “I am satisfied with the future career opportunities that are open to me.” Higher scores represent more satisfaction. Richardson et al. reported an internal reliability of .81 for the scale and addressed issues of convergent validity by correlating the scale with measures of general satisfaction with life.

Career distress was measured using the 13-item subjective career distress subscale from the Coping with Career Indecision scale (Larson, Toulouse, Ngumba, Fitzpatrick, & Heppner, 1994). This subscale was designed to assess students’ degree of subjective distress in relation to their career decision making and avoidance of career thought or goal setting. Sample items were “I often feel down or depressed about selecting a career,” and “I tend to smooth over any career problem I have and pretend it doesn’t exist.” Higher scores represent more distress. Larson et al. reported internal reliability coefficients of .90 for the Subjective Career Distress subscale and .90 for the full measure, and addressed validity by demonstrating correlations with standard well-being scales.

A CFA on the combined satisfaction and distress scores confirmed a two-factor solution, χ²(121) = 173.08, p = .001, GFI = .91, CFI = .97, RMSEA = .05, indicating structural independence of the two scales. Item loadings ranged from .33 to .78 (satisfaction) and .46 to .79 (career distress). The internal reliability coefficients were .74 and .89, respectively.

Career action behaviors

We measured the two career action behaviors of career planning and career exploration, which Lent et al. (1996) described as the key behaviors associated with career development. Students responded to both scales using a 6-point Likert-type format with end points of strongly disagree (1) and strongly agree (6).

Career planning was assessed using the 8-item career thinking and planning subscale of Greenhaus’ (1971) Career Salience scale. This subscale was designed to assess an individual’s level of career relevant thoughts and planning. Sample items were “Planning for and succeeding in a career is my primary concern” and “I enjoy thinking about and making plans about my future career.” Higher scores indicate more career planning. Internal reliability coefficients have been reported in the .70–.80 range (Zikic & Klehe, 2006). Support for construct validity has been demonstrated by showing associations between the subscale and the full scale and between the subscale and job searching and career exploration behaviors (Zikic & Klehe).

Career exploration was assessed using the 6-item environmental exploration subscale of the career exploration survey (Stumpf, Colarelli, & Hartman, 1983). Sample items were “I have been investigating career possibilities” and “I have sought information on specific areas of my career interest.” Higher scores indicate more career exploration. The authors reported a sound internal reliability coefficient for the subscale (.88) and demonstrated validity by testing associations with other dimensions of the full scale.

We conducted a CFA on the combined planning and exploration scales. This supported a two-factor solution after we removed 1 item from the Career Planning scale, χ²(32) = 100.03, p = .001, GFI = .92, CFI = .96, RMSEA = .06, suggesting the two scales were independent. Item loadings ranged from .43 to .72 (planning) and .57 to .81 (exploration). The internal reliability coefficients were .78 for the 7-item Planning scale and .88 for the 6-item Exploration scale.

Procedure

The study was cross-sectional and survey based. Students were recruited from first-year university classes during the final third of their first university semester. Volunteers were able to take the survey with them, complete it at their leisure, and return it to the researchers. We distributed approximately 250 surveys and received 186 completed responses (return rate = 74%). Students received course credit for their research participation. The study was conducted under the auspices of the university ethics committee.

Results

Predicting Career-Related Well-Being

We used two hierarchical regression analyses to test (a) if career compromise was associated with career-related well-being (career satisfaction, career distress), (b) if goal adjustment (goal disengagement, goal reengagement, the interaction between goal disengagement and goal reengagement) was associated with well-being, and (c) if goal adjustment moderated the relationship between career compromise and well-being. We created the interaction terms (e.g., Goal Disengagement × Goal Reengagement) by first standardizing the variables and then finding the products of the standardized variables. This procedure was recommended by Aiken and West (1991) to avoid multicollinearity between the interaction terms and the main effect variables. Age, gender, and educational achievement had no consistent associations with any of the outcome variables thus were not included in the analyses.

For career satisfaction, career compromise at Step 1 accounted for 7.1% of the variance, F(1, 184) = 15.05, p < .001. At Step 2, goal disengagement and goal reengagement did not explain significant, additional variance, F _chg(2, 182) = 1.41, p = .25. At Step 3, the Goal Disengagement × Goal Reengagement interaction term accounted for an additional 2.5% of variance, F _chg(1, 181) = 5.18, p = .024, whereas the Compromise × Goal Adjustment interaction terms included at Step 4 were not significant, F _chg(3, 178) = .54, p = .66. At Step 3, the most parsimonious model, 11.5% of the variance was accounted for in career satisfaction, F(4, 181) = 5.88, p < .001, with career compromise (β = −.27, p < .001, sr² = 7.35%) and the Goal Disengagement × Goal Reengagement interaction (β = −.16, p = .024, sr² = 2.53%) explaining unique variance.

For career distress, career compromise accounted for 7% of the variance at Step 1, F(1, 184) = 13.76, p < .001. Goal disengagement and goal reengagement were not significant at Step 2, F _chg(2, 182) = .04, p = .96. The Goal Disengagement × Goal Reengagement interaction term accounted for 2.7% of the variance at Step 3, F _chg(1, 181) = 5.47, p = .02, and the Compromise × Goal Adjustment interaction terms were not significant at Step 4, F _chg(3, 178) = .28, p = .84. At Step 3, 9.7% of the variance was accounted for in career distress, F(4, 181) = 4.88, p = .001, with career compromise (β = .26, p < .001, sr² = 6.71%) and the Goal Disengagement × Goal Reengagement interaction (β = .17, p = .02, sr² = 2.72%) both significant. See Table 1 for summary data and bivariate correlations. See Table 2 for summary of the hierarchical regression analyses.

Table 1.

Summary Data and Intercorrelations Among all Variables; N = 186.

Variables	M	SD	2	3	4	5	6	7	8	9	10
1. Career compromise	5.75	5.13	−.28***	.26***	.09	−.10	−.10	.08	.00	.03	−.09
2. Career satisfaction	22.28	4.16	1	−.38***	.07	.21**	.08	.06	.05	−.04	.04
3. Career distress	36.38	12.14		1	−.07	−.05	−.04	.04	−.03	.00	−.02
4. Career planning	31.31	5.48			1	.39***	.27***	−.05	.05	.11	.27***
5. Career exploration	24.00	6.06				1	.17*	.10	−.05	.11	.12
6. Goal disengagement	20.07	4.48					1	−.35***	.06	.00	.05
7. Goal reengagement	24.61	5.97						1	.04	−.01	−.04
8. Age	19.72	2.29							1	−.27***	−.19**
9. School achievement	3.96	.72								1	.114
10. Gender	—	—									1

Note. *p < .05. **p < .01. ***p < .001.

Table 2.

Summary of Hierarchical Multiple Regression Analyses Predicting Career Satisfaction and Career Distress; N = 186.

Variables	Career satisfaction				Career distress
Variables	ΔR ²	B	SEB	β	ΔR ²	B	SEB	β
Step 1	.08***				.07***
Career compromise (CC)		−.22	.06	−.28***		.62	.17	.26***
Step 2	.01				.00
Goal disengagement (GD)		.08	.07	.09		−.01	.21	−.01
Goal reengagement (GR)		.08	.05	.12		.04	.16	.02
Step 3	.03*				.03*
GD × GR		−.70	.31	−.16*		2.12	.90	.17*
Step 4	.01				.00
CC × GD		.04	.32	.01		.32	.96	.03
CC × GR		.03	.34	.01		.89	.99	.07
CC × GD × GR		.36	.29	.10		.10	.86	.01

Note. *p < .05. **p < .01. ***p < .001; SEB = standard error of B.

In line with the recommendations by Aiken and West (1991), we graphed the significant interaction effects to aid interpretation. We used the computation tool provided by Dawson (2011), which generates simple regression lines for the moderator variable one standard deviation above and below the mean and plots them in relation to the predictor and outcome variables. For the significant Goal Disengagement × Goal Reengagement interaction term predicting career satisfaction, there was little variation in career satisfaction for the high goal reengagement group when goal disengagement was high or low. For the low goal reengagement group, career satisfaction levels were similar to the high reengagement group when goal disengagement was high, but as goal disengagement reduced so did career satisfaction. Those with the lowest levels of disengagement together with the lowest levels of reengagement reported the lowest levels of career satisfaction. For the significant Goal Disengagement × Goal Reengagement interaction term predicting career distress, when goal disengagement was low, career distress was higher for those who also had low goal reengagement, but as goal disengagement increased, distress increased for those with high goal reengagement, and decreased for those with low goal reengagement. Career distress was high when goal disengagement and goal reengagement were both low, and high when goal disengagement and goal reengagement were both high (see Figure 2).

Figure 2.

Effects of Goal Disengagement × Goal reengagement on (a) career satisfaction and (b) career distress.

Predicting Career Action Behaviors

In a similar manner, we used two hierarchical regression analyses to test the same variables as predictors of career planning and career exploration. For career planning, career compromise at Step 1 was not significant, F(1, 184) = 1.63, p = .20. At Step 2, goal disengagement and goal reengagement accounted for 8.2% of the variance, F _chg(2, 182) = 8.19, p < .001, with goal disengagement alone contributing unique variance. At Step 3, the Goal Disengagement × Goal Reengagement interaction term accounted for an additional 2.6% of variance, F _chg(1, 181) = 5.31, p = .022. The Compromise × Goal Adjustment interaction terms included at Step 4 were not significant, F _chg(3, 178) = .19, p = .90. At Step 3, 11.7% of the variance was accounted for in career planning, F(4, 181) = 5.97, p < .001, with goal disengagement (β = .29, p < .001, sr² = 7.56%) and the Goal Disengagement × Goal Reengagement interaction term (β = −.16, p = .022, sr² = 2.60%) explaining unique variance. For the significant Goal Disengagement × Goal Reengagement interaction term predicting career planning, when goal disengagement was high there was little difference in career planning between those low and those high in goal reengagement. As the capacity to goal disengage decreased, however, career planning decreased for both groups, but decreased disproportionately more for the low goal reengagement group. Career planning was lowest when goal disengagement and goal reengagement were both low (see Figure 3).

Figure 3.

Effects of Goal Disengagement × Goal reengagement on (a) career planning and (b) career exploration.

For career exploration, career compromise at Step 1 was not significant, F(1, 184) = 2.02, p = .16. Goal disengagement and goal reengagement at Step 2 accounted for 5.7% of the variance, F _chg(2, 182) = 5.34, p = .005, with goal disengagement and goal reengagement both contributing unique variance. The Goal Disengagement × Goal Reengagement interaction term at Step 3 accounted for an additional 4.0%, F _chg(1, 181) = 8.19, p = .005, and the Compromise × Goal Adjustment interaction terms at Step 4 explained an additional 4.3% of the variance, F _chg(3, 178) = 3.00, p = .032. When these interaction terms were tested separately, Career Compromise × Goal Disengagement and Career Compromise × Goal Reengagement (but not the three-way interaction term) explained unique variance. At Step 4, 15.1% of the variance was accounted for in career exploration, F(7, 178) = 4.52, p < .001, with goal disengagement (β = .24, p = .002, sr² = 4.80%), goal reengagement (β = .21, p = .007, sr² = 3.53%), the Goal Disengagement × Goal Reengagement interaction term (β = −.15, p = .045, sr² = 1.96%), the Career Compromise × Goal Disengagement interaction term (β = −.16, p = .031, sr² = 2.28%), and the Career Compromise × Goal Reengagement interaction term (β = .17, p = .019, sr² = 2.69%) accounting for unique variance. See Table 3 for summary data for these hierarchical regression analyses.

Table 3.

Summary of Hierarchical Multiple Regression Analyses Predicting Career Planning and Career Exploration; N = 186.

Variables	Career planning				Career exploration
Variables	ΔR ²	B	SEB	β	ΔR ²	B	SEB	β
Step 1	.01				.01
Career compromise (CC)		.10	.08	.09		−.12	.09	−.10
Step 2	.08***				.06**
Goal disengagement (GD)		.37	.09	.30***		.31	.10	.23**
Goal reengagement (GR)		.04	.07	.04		.19	.08	.19*
Step 3	.03*				.04**
GD × GR		−.93	.40	−.16*		−1.28	.45	−.20**
Step 4	.00				.04*
CC × GD		−.31	.43	−.05		−.97	.44	−.16*
CC × GR		−.04	.44	−.01		1.09	.46	.17*
CC × GD × GR		.05	.38	.01		−.18	.42	−.03

Note. *p < .05. **p < .01. ***p < .001; SEB = standard error of B.

For the significant Goal Disengagement × Goal Reengagement interaction term predicting career exploration, there was little variation in career exploration when goal reengagement was high. Career exploration for the low goal reengagement group was similar to exploration of the high reengagement group when goal disengagement was high, but career exploration decreased as goal disengagement decreased. Career exploration was lowest when goal disengagement and goal reengagement were both low (see Figure 3). For the significant Career Compromise × Goal Disengagement interaction term predicting career exploration, there was little variation in the (low) levels of career exploration for the low goal disengagement group when compromise was high or low. When goal disengagement was high, levels of exploration were similar for the low disengagement group when compromise was high, but with lower levels of compromise career exploration increased. Career exploration was highest when disengagement was high and compromise was low. For the significant Career Compromise × Goal Reengagement interaction, there was no difference between the low and the high goal reengagement groups on career exploration when compromise was low, but with higher levels of compromise, career exploration was lower for the low, but not the high, goal reengagement group. Exploration was highest when goal reengagement was high and career compromise was high. Exploration was lowest when goal reengagement was low and compromise was high (see Figure 4).

Figure 4.

Effects of (a) Career Compromise × Goal Disengagement and (b) Career Compromise × Goal Reengagement, on career exploration.

Discussion

First, supporting Hypothesis 1, career compromise was negatively associated with career-related well-being: specifically, career compromise was negatively associated with career satisfaction (i.e., satisfaction with career direction, progress, and future prospects) and positively associated with career distress (i.e., distress about the difficulty or inability to settle on a career path). These results are consistent with the general goal adjustment literature, which has shown that having to compromise on valued goals is associated with reduced satisfaction (Lord et al., 2010), and is consistent with research conducted in the career area with adults (Carr, 1997; Hesketh & McLachlan, 1991) and experimentally with adolescents (Tsaousides & Jome, 2008). Social cognitive career theory (Lent et al., 1996), which can be considered a goal-directed theory, predicts reduced satisfaction when goals are not achieved, but has yet to specifically address compromise in this process.

These results are important as they add to the small body of research that shows that disruption to career development can be associated with poorer psychological health and adjustment. While deciding upon and abandoning careers and specific occupations may be part of the normal vocational development process, these results suggest that this compromise might be associated with poorer adjustment. Many career theories stress that social adjustment and well-being in young people are dependent on them making smooth career transitions (e.g., Super, 1990). However, the focus of career theories is largely on how young people might forestall foreclosure, overcome barriers, and reduce the need for compromise (Gottfredson, 2005). By and large, career theories do not address the emotional maturity and personal coping strategies required to navigate the ups and downs of the transition to adult employment. Additionally, there has been little empirical research examining the consequences when career development does go astray (Skorikov, 2007).

While the current study was cross-sectional, and thus, cannot tease out causal relationships between compromise and well-being, the results should alert practitioners to possible downsides for adolescents who have to give up on their ideal careers, particularly in times of transition, and should encourage researchers to give more attention to career development and adjustment connections. We examined the period around the transition to university, but young people face many other transitions where they will encounter career and life barriers as they move to and through high school and university and then enter the labor force.

Second, career compromise was not associated directly with career planning or exploration, which does not support Hypothesis 2. However, the effect of career compromise on career exploration (but not planning) was moderated by both goal disengagement and goal reengagement, indicating that, for some students, career compromise might be associated with exploratory behaviors (Figure 4). For Compromise × Goal Disengagement, career exploration was higher when goal disengagement was higher, but only when compromise was lower (in all other conditions, exploration was lower). This result supports the notion that career compromise might be considered as a stressor, which is associated with reduced career exploration, and moderated (i.e., stimulated) by having high levels of goal disengagement. A similar interpretation can be made for the Compromise × Goal Reengagement interaction result. Exploration was higher for those with a higher capacity to reengage, no matter what the level of compromise. Exploration was higher also for those with lower goal reengagement when compromise was lower, but with higher levels of compromise the level of exploration decreased for the poor reengagers. In the case of reengagement, those with lower levels of reengagement were disadvantaged when compromise was higher; that is, participants with a lower capacity to reengage with new goals reported lower levels of career exploration when (the stressor of) compromise was higher. Career theories that include a notion of compromise on career directions (cf. Gottfredson, 2005) do not articulate mechanisms that account for the compromise process. Goal disengagement and reengagement capacities, or their corollary of goal persistence, suggest means by which compromise is enacted, and indicates one example of how such means might affect subsequent behavior.

Third, goal disengagement and reengagement were not directly associated with career-related well-being. This was not consistent with our expectations (Hypothesis 3a) and is inconsistent with other studies that have shown positive relationships between the two goal adjustment strategies and general well-being. However, it was the case that the Disengagement × Reengagement interaction term was associated with both career satisfaction and career distress (Figure 2). Career satisfaction was lowest when goal disengagement and goal reengagement were both low. For career distress, distress was highest for those who had the lowest levels of goal disengagement and goal reengagement, which is consistent with the career satisfaction result. It was also the case here that distress was higher for those higher on goal reengagement and higher also on goal disengagement. This latter result might indicate that being too ready to drop old goals and reengage in new ones is also distressing. This interpretation is consistent with the impulsivity literature, which suggests that this trait is associated with poorer well-being (e.g., Vittersø, & Nilsen, 2002). Thus, while no direct effects were found for disengagement and reengagement on well-being, there was a small group of participants whose poor well-being (satisfaction and distress) was associated with lower disengagement and lower reengagement, and whose well-being (distress) was associated with higher disengagement and reengagement.

Fourth, while disengagement and reengagement were not directly associated with well-being, they were positively associated with the career action behaviors. Goal disengagement was positively associated with career planning, and goal reengagement was positively associated with both career planning and career exploration; these results partially support Hypothesis 3b. As far as we can determine, this is the first time that the capacity for goal adjustment in this manner has been found to be associated with career-related behaviors, and suggests that planning or exploring for a career might be facilitated by such capacities. At an applied level, this opens the possibility for including goal management strategies in career interventions for young people. At the theoretical level, these relationships indicate mechanisms that might drive these career behaviors. The Goal Disengagement × Reengagement interaction term was a significant predictor for both career planning and career exploration (Figure 3). Planning and exploration were at their lowest when goal disengagement and goal reengagement were at their lowest, suggesting that a small proportion of participants, whose goal adjustment capacities were both low, may be disadvantaged in their career development generally, not specifically related to when they have to compromise.

Our study demonstrated associations between career compromise and well-being (direct) and between career compromise and exploration (moderated). It also demonstrated associations between goal adjustment and well-being (moderated) and between goal adjustment and career action behaviors (direct and moderated). These results are consistent with goal-setting approaches (Locke & Latham, 1990) and add to the growing literature on career adaptability/self-regulation in the careers area (Creed, Fallon, & Hood, 2009; Hirschi, 2009); that is, adds to the literature on how individuals manage both predictable and unpredictable challenges associated with the preparation for work (Savickas, 1997). However, the results need to be viewed in the context of the limitations of the study. First, the study was cross-sectional, and while we tested plausible, causative relationships, these need to be confirmed with longitudinal studies. Second, we tested the relationships with a narrow sample of university students, and replications need to be made with more heterogeneous samples. Third, our sample contained a disproportionate number of women (77%). Gender is an important consideration in the career development area (Patton & Creed, 2001) and future studies need to consider samples with a more equal gender balance. Fourth, we tested the associations at a particular point in time for university students, and testing the associations at other transition points would add to the career development literature. Finally, as career development is ongoing and developmental, studies need to look at how the compromise process develops and is managed over time.

Footnotes

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

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