Career Goal Setting and Goal Pursuit in Young Adults: The Role of Financial Distress

Career-Related Indecision

Unclear career goals have been conceptualized as an underdeveloped career calling (Hirschi, 2011), imprecise career aspirations (Caza et al., 2015), and immature vocational identity (Hirschi, 2012). Consistent with Stringer et al. (2011), we operationalized unclear goals as career indecision, which refers to the individual’s inability to settle on a career direction. Indecision reflects perceived discrepancies between abilities and desired direction (Lord et al., 2010), lack of preparation, engagement, and support for the career decision-making process, conflict with others about a career direction, or personality traits (e.g., perfectionism) that sabotage decision-making (Brown et al., 2012).

As career indecision is considered potentially maladaptive (Lent & Brown, 2013), the consequences can be considerable, both in the short term (e.g., choosing a course) and long term (e.g., finding a satisfying job). For example, career indecision can disrupt the development of career maturity (i.e., capacity to manage age relevant, career tasks; Jun, 2018) and vocational identity (i.e., self-perceptions of career goals, interests, and abilities; Stringer et al., 2011) and can affect educational engagement and achievement (Germeijs & Verschueren, 2007), labor force entry (Sabates et al., 2011), and later person–job fit (Fort & Murariu, 2018). It has also been associated with career-related stress (Vignoli, 2015; Walker & Peterson, 2012) and perceived employability (Huang, 2015; Praskova, Creed, & Hood, 2014), which we included in our model.

Career Stress and Perceived Employability

Career stress refers to the negative feelings (e.g., frustration, disappointment) that are generated when individuals encounter adverse experiences in their career goal setting and pursuit (Creed, Hood, et al., 2016). It is one of the most common reasons why students attend college counseling services (Benton et al., 2003) and also acts as an impediment to other career-related actions such as career exploration and commitment (Skorikov, 2007). From a goal-setting/self-regulatory perspective (Bandura, 1991; Latham & Locke, 1991), career stress is the result of appraising a discrepancy between a goal or standard set by the individual and the individual’s progress toward that goal or meeting the standard. Career indecision has been shown to be related to career stress in both high school students (Vignoli, 2015) and undergraduates (Walker & Peterson, 2012). It is also related to poorer well-being generally (Viola et al., 2017).

Hypothesis 1: Career indecision is related positively to career stress.

Perceived employability is the individual’s appraisal of their chances of obtaining and maintaining employment that matches their skills and abilities (Vanhercke et al., 2014). For young people not yet in the adult labor force, it reflects how employable they perceive themselves to be when they complete their formal education (Gunawan et al., 2018). In this way, perceived employability represents one’s future occupational self (Cross & Markus, 1991), which drives goal setting and striving activities (Creed & Klisch, 2005). Consistent with this, perceived employability is related to career choice satisfaction (Jackson & Wilton, 2017), having a strong career calling (Praskova, Creed, & Hood, 2014), study commitment (Rothwell et al., 2009), and committing energies and focus to career-related activities (Praskova, Creed, & Hood, 2014). Specific to the current study, career indecision has been shown to be related to lower perceived employability, whether measured with specific indecision scales (e.g., Huang, 2015; Praskova, Creed, & Hood, 2014) or assessed via its component parts (e.g., McIlveen et al., 2013).

Hypothesis 2: Career indecision is related negatively to perceived employability.

Career-Related Effort

Effort, expressed as the investment of energy and resources (Lord et al., 2010), is key to goal management, as it underpins motivational systems that focus attention, allocate time and energy, and deal with setbacks (Hall & Chandler, 2005). Goals drive achievement-related effort, and when goals are clear, commitment and effort are higher, and performance is better (Latham & Locke, 2007). Clearer career goals, expressed as higher career calling, are related to greater current and later career effort (Praskova et al., 2015). More broadly, active goal engagement is related to increased career effort (Creed, Kjoelaas, & Hood, 2016), while clarifying goal progress via feedback is related to greater individual and team effort (London, 2008). Career ambiguity is related to lower career goals and goal disengagement (Hu et al., 2017). We were unable to identify any studies that directly tested the relationship between career indecision and career-related effort; however, these studies provide indirect evidence to support a relationship between these two variables.

Thus, we expected (Hypothesis 3) career indecision to be related negatively to career effort.

Exerting effort typically is associated with greater personal satisfaction (Meyer et al., 2002). Specific to the career domain, effort, expressed as career commitment (Wang et al., 2016), time at work (Wrzesniewski, 2002), and goal-directed energy and persistence (Wiese et al., 2002), is related to greater job satisfaction and higher perceived career success. Additionally, career effort is related to a greater sense of life purpose (Praskova, Hood, & Creed, 2014) and higher life satisfaction (Praskova et al., 2015).

Similarly, goal-directed effort is associated with more positive attitudes about the future (Hall & Chandler, 2005). For example, career commitment is related to more psychological capital (i.e., hope, resilience; Singhal & Rastogi, 2018), career optimism (Haratsis et al., 2015), and subjective career success (Chang et al., 2017), and career engagement is related to greater career optimism (Haratsis et al., 2015). For young adults, career effort is related to current (Praskova et al., 2015) and future perceived employability (Gunawan et al., 2018).

While no studies have tested the direct relationships between career effort and career stress and perceived employability, there is considerable indirect evidence to support these relationships. Thus, we expected: Career-related effort to be related negatively to career stress (Hypothesis 4) and positively to perceived employability (Hypothesis 5).

As effort is an important self-regulatory mechanism, which is mobilized when individuals select and commit to a goal (Hall & Chandler, 2005), we considered it as an intervening variable between career indecision and the outcome variables. This is consistent with goal-setting/self-regulatory models of human behavior (e.g., Bandura, 1991; Latham & Locke, 1991) and agentic career development models (e.g., Hall & Chandler, 2005; Lent et al., 1994) and supported in the literature. Chan (2017), for example, found that proactive career behaviors mediated between goal clarity and optimism for the future, Praskova et al. (2015) found that effort and strategy engagement mediated between career calling and life satisfaction and perceived employability, and Ollo-López et al. (2016) found that effort mediated between work goals and work outcomes, including job satisfaction.

Thus, we expected that career effort would mediate between career indecision and career stress (Hypothesis 6) and perceived employability (Hypothesis 7), with greater indecision related to less effort, and less effort, in turn, related to more distress and lower perceived employability.

Financial Distress as a Contextual Moderator

When economic support is inadequate, young adults experience financial distress, which is the “subjective sense of having more needs than resources” (Mullainathan & Shafir, 2013, p. 86). From a goal-setting perspective, financial distress results from an unfavorable discrepancy between needs and resources (Lord et al., 2010). Worries about money (e.g., financing study and living expenses, managing loans, and credit card debt) is the second most important stressor reported by university students after study issues, with two thirds reporting struggling to manage on the money they have (National Survey of Student Engagement, 2015). Financial difficulties for students are related to poorer grades (Joo et al., 2008), dropout (Serido et al., 2014), taking fewer courses (Mukherjee et al., 2017), and poorer mental health (Mulder & Cashin, 2015).

The reason financial distress is important is that people think and act differently when resources are scarce compared to when they are adequate (Morton, 2017). When resources are scarce, individuals focus on pursuing short-term goals to meet current needs; when resources are adequate, they give priority to longer term goals and factor these into their thinking and decision-making. Under conditions of scarcity, survival strategies are activated, and attention is focused disproportionately on making ends meet at the expense of other needs and responsibilities; for young adults in education and training, these other responsibilities relate to study and preparing for the future (Mani et al., 2013).

Recent research suggests that financial scarcity leads to a scarcity mind-set, which reflects a pattern of thinking and prioritizing that produces a “tunnel vision” to focus on current problems at the expense of other issues and longer term outcomes (Mani et al., 2013). As financial distress becomes more pressing, it affects decision-making, increases psychological distress, and, more broadly, interferes with everyday thinking (Mullainathan & Shafir, 2013). In contrast, individuals with adequate finances feel more in control and do not need to prioritize short-term goals over long-term considerations (Destin et al., 2017). These different mind-sets result in different behavioral responses, as experience conditions individuals to generate different adaptive responses to economic pressures, which generalizes to somewhat different responses and approaches to life (Griskevicius et al., 2013).

Financial hardship affects career development. High school students from more disadvantaged backgrounds have lower occupational aspirations (Eshelman & Rottinghaus, 2015), are less clear about their career goals and the means of achieving them, express less career-related agency (Thompson et al., 2017), do less well academically, and are more likely to dropout (McCarron & Inkelas, 2006). Undergraduate students in financial hardship perceive a more restricted range of occupational choices (Allan et al., 2019), and, on graduation, while they put more effort into job searching, accept lower paid and poorer fitting jobs (Hausdorf, 2007).

However, while studies have tested economic hardship as a correlate of career-related variables (Baker, 2019; White & Perrone-McGovern, 2017), we could find no research examining it as a boundary condition (i.e., moderator) for the underlying mechanisms of career goal setting and goal pursuit, which restricts our understanding of how the relationships in these models might differ for more and less financially distressed individuals. The current study contributes to this understanding by assessing financial distress as a moderating variable in the proposed relationships in Figure 1.

As more financially pressured young people will be disproportionately more concerned about their situation, have a greater focus on meeting basic needs, and will be distracted from focusing on future goals and attainment, we expected: The relationships between career indecision and perceived employability and career stress will be stronger for those reporting higher financial distress compared to those less financially distressed (Hypotheses 8 and 9, respectively).

As more financially distressed young people are less likely to be focused on future goals, and, thus, future goal achievement processes, we expected: The relationship between career indecision and effort will be stronger for those reporting higher financial distress (Hypothesis 10).

Last, as the relationships between indecision and effort, and effort and stress and perceived employability will be stronger for those reporting higher financial distress, we expected: The mediated pathway via effort between career indecision and career stress (Hypothesis 11) and perceived employability (Hypothesis 12) will be conditional on the level of financial distress.

We tested these hypotheses using a sample of undergraduate students, which is an appropriate population to examine as students are exposed to financial and study pressures from the beginning of their university life. In Australia, most tertiary students experience financial pressures associated with funding their education and living expenses and so must work as well as study (Australian Bureau of Statistics, 2013).

Method

Results

Analyses were conducted using AMOS Version 24. The latent variables for indecision, effort, and employability (each >6 items) were each represented by three parcels (Landis et al., 2000) and the latent variable for stress (5 items) by individual items. There also was one observed variable (financial distress) and one interaction term (Indecision × Financial Distress). Item parcels reduce the parameters to be estimated, provide more stable estimates, reduce risk of violating normality assumptions, and provide more parsimonious models to be interpreted (Hau & Marsh, 2004). To create the interaction term, the products of the Financial Distress Indicator × Three Indecision Parcels were each regressed onto financial distress and the three indecision indicators, and the residuals from these analyses were used as indicators for the interaction latent variable (see Steinmetz et al., 2011).

We tested a measurement model and then tested the mediation and moderation effects by assessing separate structural models for the two outcomes. We calculated 95% bias-corrected confidence intervals (CIs; 1,000 bootstrap samples) to assess mediation (i.e., assumed present if 95% CIs for the indirect effect do not contain zero; Preacher & Hayes, 2008). A significant path from the interaction term to an outcome indicates moderation (Steinmetz et al., 2011). Model fit was assessed using χ² (with 16 observed variables and sample <250, a significant χ² is expected), standardized χ² (χ²/df; <3.0 for a good fit), comparative fit index (CFI; ≥.95), Tucker–Lewis index (TLI; ≥.95), and the root mean square error of approximation (RMSEA; <.08; Hair et al., 2010).

The measurement model fit the data well, χ²(78) = 121.56, p = .001, χ²/df = 1.56, CFI = .98, TLI = .97, RMSEA = .05 [.03, .07]. All factor loadings were >.75 (p < .001; range .75–.96) and correlations among latent variables paralleled those for the observed variables (see Table 1). As age was related to stress (r = –.25, p = .001), this was controlled in all analyses.

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Table 1.

Summary Data, Correlations (Latent Variables Above Diagonal, Scale Variables Below), and Cronbach’s α Reliability Coefficients (Along Diagonal).

Variables	M	SD	1	2	3	4	5
1. Career indecision	22.78	5.95	.94	−.52***	.82***	−.41***	−.16*
2. Career effort	33.96	5.38	−.43***	.94	−.54***	.59***	.34***
3. Career stress	16.19	6.51	.75***	−.48***	.93	−.34***	−.05
4. Employability	25.29	4.66	−.34***	.52***	−.32***	.83	.32***
5. Financial distress	2.98	0.84	−.15*	.26***	−.05	.31***	—
6. Age	19.84	3.30	−.13	.01	−.25**	.11	−.04
7. Education	2.11	0.69	−.03	−.11	−.05	.03	−.17*
8. Gender	—	—	−.09	.05	−.14*	.18**	.05

Note. N = 214.

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

Testing Mediation

First, a direct effects model (indecision → effort, stress, and employability), χ²(91) = 130.36, p = .004, χ²/df = 1.43, CFI = .98, TLI = .98, RMSEA = .05 [.03, .06], confirmed that indecision was related to stress (β = .81, p < .001; Hypothesis 1), employability (β = −.37, p < .001; Hypothesis 2), and effort (β = −.49, p < .001; Hypothesis 3). For the direct and indirect effects model (i.e., mediation paths included), χ²(91) = 132.46, p = .003, χ²/df = 1.45, CFI = .98, TLI = .98, RMSEA = .05 [.03, .07], indecision → stress remained significant (β = .72, p < .001), but the path to employability became nonsignificant (β = −.11, p = .16). Effort was related to both stress (β = −.17, p = .009; Hypothesis 4) and employability (β = .47, p < .001; Hypothesis 5), and the mediated pathways from indecision → effort → stress (95% CI [.03, .15]) and employability (95% CI [−.36, −.15]) were significant (partial mediation for indecision to stress [Hypothesis 6] and full mediation to employability; Hypothesis 7; see Figure 2). Variance explained was 31% (effort), 72% (stress), and 39% (employability). The standardized indirect effect of indecision on stress was .09 and on employability was −.24.

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Figure 2.

Standardized β weights for model with effort mediating between indecision and stress and employability.

Testing Effects of Financial Distress as Moderator

The interaction term was added to the mediation models, with links to effort, stress, and employability. In the direct effects model for stress, χ²(89) = 133.31, p = .002, χ²/df = 1.50, CFI = .98, TLI = .97, RMSEA = .05 [.03, .07], there were significant paths from the interaction to effort (β = .18, p = .007) and stress (β = −.13, p = .013), indicating that financial distress moderated the direct relationships between indecision and effort (Hypothesis 10) and stress (Hypothesis 8). As indecision increased, the decrease in effort and increase in stress were greater for the higher than the lower distressed group (Figure 3). In the direct and indirect effects model, there was an indirect effect for the interaction on stress via effort (95% CI [−.08, −.01; Hypothesis 11): as indecision increased, stress mediated via effort increased more so for the higher financially distressed group than for the lower (standardized indirect effect = −.09).

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Figure 3.

As indecision increased: (A) career effort decreased disproportionately more for those higher on financial distress than for those lower, (B) career stress increased disproportionately more for those higher on financial distress than for those lower, and (C) employability reduced disproportionately more for those high on financial distress than those lower.

For the direct effects model for employability, χ²(63) = 86.76, p = .025, χ²/df = 1.38, CFI = .99, TLI = .98, RMSEA = .04 [.02, .06], financial distress moderated the direct relationships between indecision and effort (β = .17, p = .016; Hypothesis 10) and employability (β = .22, p = .003; Hypothesis 9; Figure 3). Thus, as indecision increased, employability reduced more so for the higher financially distressed group than for the lower. The direct and indirect effects model also indicated that financial distress moderated the indirect relationship between indecision and employability (95% CI [.01, .16]; Hypothesis 12; standardized indirect effect = −.06): as indecision increased, employability, mediated via effort, reduced more so for those more financially distressed.

Discussion

Informed by goal-setting/self-regulatory theories (Bandura, 1991; Latham & Locke, 1991), we examined the mediating role of career effort (i.e., goal striving) in the relationship between career indecision (i.e., poor goal clarity) and career-related stress (i.e., affect) and perceived employability (i.e., attitude). Additionally, we tested the effect of financial distress as a moderator in these direct and indirect relationships.

Conclusion

This study confirmed and extended previously identified relationships among career indecision, career-related effort, career stress, and perceived employability, and having embedded these relationships in a goal-setting/goal-pursuit clarity perspective, we were able to confirm the mediated associations between career indecision and stress and employability via career-related effort. Last, we assessed the influence of financial distress on these direct and indirect relationships. We found financial distress effects indicating that more financially distressed and career-undecided young people exerted less effort and had lower perceived employability compared to those less financially distressed, whereas less financially distressed young people experienced more stress with career indecision. The study contributes by proposing a mechanism for how career indecision relates to important career process and outcome variables and by demonstrating the effects of financial distress on this underlying mechanism.