Career adaptability and academic satisfaction: Examining work volition and self efficacy as mediators

Journal of Vocational Behavior 90 (2015) 46–54

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Career adaptability and academic satisfaction: Examining work volition and self efficacy as mediators Ryan D. Duffy ⁎, Richard P. Douglass, Kelsey L. Autin University of Florida, United States

a r t i c l e

i n f o

Article history: Received 8 May 2015 Received in revised form 22 July 2015 Accepted 24 July 2015 Available online 29 July 2015 Keywords: Career adaptability Academic satisfaction Work volition CDSE

a b s t r a c t The present study examined the relation between the four components of career adaptability – concern, control, curiosity, and confidence (Savickas & Porfeli, 2012) – and academic satisfaction. Drawing from a diverse sample of 412 undergraduate students, all four components moderately correlated with academic satisfaction. In an effort to explain these relations, work volition and career decision self-efficacy (CDSE) were examined as potential mediator variables. Using structural equation modeling, work volition significantly mediated the control to satisfaction relation and CDSE significantly mediated the concern, control, and confidence to satisfaction relations. After including all variables in the model, none of the career adaptability components significantly related with academic satisfaction. These results suggest that for undergraduate students, feeling adaptable in one's career may link to greater levels of academic satisfaction due, in part, to greater feelings of control and confidence in one's career decision making. © 2015 Elsevier Inc. All rights reserved.

1. Introduction Grounded in Career Construction Theory (CCT; Savickas, 1997, 2002, 2005), the career adaptability construct has seen increased empirical attention over the last five years, particularly after the development of cross-culturally valid instruments (c.f. Savickas & Porfeli, 2012 for a detailed review). Evidence is clear that feeling adaptable in one's career is linked with a host of positive vocational and well-being outcomes. Among college student populations, career adaptability has been linked with variables such as job search self-efficacy, career optimism, proactive personality, career decision self-efficacy, career calling, self-esteem, strengths use, and meaning in life (Cai et al., 2015; Douglass & Duffy, 2015; Praskova, Hood, & Creed, 2014; Tolentino et al., 2014) and has been found to promote job search self-efficacy over time (Guan et al., 2013). Among adult populations, career adaptability has been related to job performance ratings, career satisfaction, life satisfaction, hope, and general well-being (Maggiori, Johnston, Krings, Massoudi, & Rossier, 2013; Ohme & Zacher, 2015; Santilli, Nota, Ginevra, & Soresi, 2014; Tolentino, Garcia, Restubog, Bordia, & Tang, 2013; Zacher, 2014) and longitudinal research has found that those who are adaptable are more likely to be satisfied with their jobs (Zacher & Griffin, in press). However, no known research to date has examined how adaptability is related to satisfaction within the academic domain. This represents a critical gap in the literature considering the well-documented links between aspects of career maturity and academic performance, persistence, and satisfaction (e.g., Crook, Healy, & Oshea, 1984; Flouri & Buchanan, 2002; Luzzo, 1993). In the current study, we address this gap by examining how the four components of career adaptability relate to academic satisfaction and explore two empirically and theoretically supported meditators to this relation — work volition and career decision self-efficacy (CDSE).

⁎ Corresponding author at: University of Florida, Department of Psychology, Gainesville, FL 32601, United States. E-mail address: rduf@ufl.edu (R.D. Duffy).

http://dx.doi.org/10.1016/j.jvb.2015.07.007 0001-8791/© 2015 Elsevier Inc. All rights reserved.

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2. Career construction 2.1. Theoretical framework Career Construction Theory (CCT; Savickas, 1997, 2002, 2005) is a lens on vocational development that is concerned with a contexualistic worldview of vocational development across the life-span. Proponents of CCT are largely interested in studying how people use their self-regulatory strengths to deal with current and future vocational tasks (Savickas & Porfeli, 2012). In CCT, career adaptability – defined as a person's resources for coping with current and anticipated vocational tasks (Savickas & Porfeli, 2012) – is emphasized as a central variable, representing a set of strengths that individuals can acquire which theoretically affect how they make their way through the world of work. Career adaptability is broken down into four components: concern, control, curiosity, and confidence (Savickas, 1997). Concern addresses how able a person is to prepare for the vocational future. Control refers to the degree of responsibility people feel they possess in shaping their future careers. Curiosity is concerned with the self-exploration people engage in regarding future occupational choices. Finally, confidence identifies the degree to which people feel able to overcome potential vocational barriers (Savickas & Porfeli, 2012). 2.2. Career adaptability among undergraduate students Given the vocational context of CCT (Savickas, 1997, 2002, 2005), a majority of studies on career adaptability among undergraduates have examined the relation between career adaptability and vocational outcomes. One study followed a sample of Chinese students pre and post-graduation and found career adaptability was positively related to job search self-efficacy pre-graduation and to employment status post-graduation (Guan et al., 2013). In other words, students who felt highly adaptable in their careers not only felt more confident while searching for jobs, but were also more likely to be employed post-graduation. Another study among Chinese undergraduates found all four components of career adaptability to have moderate positive relations with professional competence (Guo et al., 2014). Among a sample of U.S. undergraduates, Douglass and Duffy (2015) found career adaptability was positively related to career decision self-efficacy, such that students higher in career adaptability felt more efficacious in making career decisions. Other studies have found similar positive relations between career adaptability and vocational outcomes such as job search self-efficacy, career optimism, career planning, skill development, and work effort (Cai et al., 2015; Praskova et al., 2014; Taber & Blankemeyer, 2015; Tolentino et al., 2014). In sum, undergraduates with high levels of career adaptability are more likely to be employed post-graduation, feel more able to search for jobs, are more efficacious in making career decisions, and overall tend to be more competent and optimistic regarding their careers. Although the construct of career adaptability largely references vocational contexts, Savickas (2005) highlighted the relevance of career adaptability outside the workplace by suggesting that career adaptability can help with the struggles of daily life. Savickas (2002) provided a case example demonstrating the applicability of CCT (Savickas, 1997) to a student struggling with academic underachievement. Although the example was more broadly related to CCT as a whole, it took into consideration the client's sense of career control – one component of career adaptability – when informing the counselor's future directions for counseling. In another example, the client's levels of confidence, control, and concern help the counselor to identify the client's academic and vocational ambitions (Savickas, 2002). These narratives highlight the potential role of adaptability in promoting non-career outcomes. Although no known studies have examined the relation of career adaptability to academic satisfaction, one study found career adaptability to have a positive link with GPA (Ӧncel, 2014) and another study, framed in CCT, found the adapt-ability resource of optimism predicted academic adaption among undergraduates over time (Perera & McIlveen, 2014). Building from the theoretical links presented above, along with quantitative evidence that positions adaptability as a predictor variable of outcomes among undergraduates, we suggest that career adaptability may predict a student's level of satisfaction within the academic domain. Specifically, we hypothesize that the four components of adaptability – concern, control, curiosity, confidence – will each positively relate with academic satisfaction (Hypotheses 1–4). 3. Mediator variables Along with hypothesizing direct relations between career adaptability and academic satisfaction, we also explore mediators that may explain why feeing adaptable links with satisfaction. Specifically, we hypothesize that career adaptability promotes a sense of control and confidence around one's career decision making (the key task in college student career development) that in turn promotes satisfaction within the academic domain. 3.1. Work volition Work volition is defined as one's perceived freedom of future work choice despite constraints (Duffy, Diemer, & Jadidian, 2012; Duffy, Diemer, Perry, Laurenzi, & Torrey, 2012). The construct is distinct from the related adaptability construct of control because it explicitly measures the perception of control in career decision making, versus overall career development. Previous studies among undergraduate students have been linked work volition to a host of positive vocational outcomes. For example, in the instrument development study, Duffy, Diemer, & Jadidian (2012) found student work volition scores positively correlated with career decision self-efficacy (CDSE) and negatively correlated with career barriers. Other studies have found work volition to correlate with social cognitive constructs (domain self-efficacy, outcome expectations, interests, and goals; Duffy, Bott, Allan, & Autin, 2014), a

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general sense of control (Duffy, Douglass, Autin, & Allan, in press), and work hope and optimism (Brown, 2015). Finally, Jadidian and Duffy (2012) found work volition to moderately correlate with academic satisfaction, the dependent variable in the present study. Work volition concerns a perception of control in one's future career decision making and as such is theorized to predict positive academic outcomes in the present — the more students feel they will be able to choose their career in the future, the more likely they will feel satisfied while meeting the academic requirements to eventually secure that career. As such, we hypothesize that work volition will serve as a bridge between career adaptability and academic satisfaction, as students who are more adaptable will feel more satisfied because they feel greater career decision making control. Specifically, work volition is hypothesized to mediate the relation of the four career adaptability components to academic satisfaction (Hypothesis 5). 3.2. Career decision self-efficacy Akin to work volition, CDSE concerns how confident students feel implementing career decisions, but in this case it is about confidence versus control. Dozens of studies have demonstrated that, for undergraduate students, feeling confident about implementing one's career decisions is linked with a host of positive vocational outcomes, including career decidedness, career commitment, perceptions of barriers, a more established vocational identity, occupational aspirations, and work hope (Chung, 2002; Guay, Senécal, Gauthier, & Fernet, 2003; Gushue, Clarke, Pantzer, & Scanlan, 2006; Juntunen & Wettersten, 2006; Patton & Creed, 2007). Additionally, CDSE has been linked with academic/major satisfaction (Dahling & Thompson, 2013; Duffy, Allan, & Dik, 2011; Jadidian & Duffy, 2012; Komarraju, Swanson, & Nadler, 2014; Nauta, 2007), major incongruence (Shin, Steger, & Lee, 2014), and all four components of career adaptability (Douglass & Duffy, 2015; Hou, Wu, & Liu, 2014). Like work volition, we propose that confidence in one's career decision making will predict positive academic outcomes in the present — the more students feel confident about implementing their career choices, the more likely they will be satisfied when meeting academic requirements for that career. Accordingly, we hypothesize that CDSE will serve as a mediating variable linking adaptability with academic satisfaction, such that students who are more adaptable will endorse higher levels of satisfaction because they have greater confidence in their career decision making. Specifically, CDSE is hypothesized to mediate the relation between the four components of adaptability to academic satisfaction (Hypothesis 6). 4. The present study The goal of the present study is to examine how the four components of career adaptability – concern, control, curiosity, and confidence – link with satisfaction within the academic domain among college students and the degree to which these links are mediated by work volition and CDSE. To address this goal, a large and diverse group of undergraduate students were surveyed and structural equation modeling (SEM) was used to examine our hypotheses, allowing for an analysis of how well career adaptability and the mediator variables link with academic satisfaction after accounting for other model variables. 5. Method 5.1. Participants The participants in the present study were 412 undergraduate students with a mean age of 18.9 years (SD = 1.5 years) and – of those who responded – 119 self-identified as male (28.9%), 290 as female (70.4%), and 1 as other (.2%). Students who responded to the ethnicity item identified as Caucasian (57%), Hispanic/Latino/a American (18.2%), Asian/Asian American (10.9%), African/AfricanAmerican (5.6%), Asian Indian (4.1%), Middle Eastern (1.2%), Native American (.2%), and Other (2.4%). Lastly, participants selfreported their current social class as lower class (n = 16, 3.9%), working class (n = 73, 17.8%), middle class (n = 195, 47.7%), upper middle class (n = 109, 26.7%), and upper class (n = 16, 3.9%). 5.2. Instruments 5.2.1. Career adaptability We administered the 24-item Career Adapt-Abilities Scale (CAAS; Savickas & Porfeli, 2012) to measure levels of career adaptability among students. There are four subscales that measure concern, control, curiosity, and confidence, each of which are six items and combine to form the CAAS. We provided students with the following directions: “Please rate how strongly you have developed each of the following abilities.” Students then responded to statements such as “Concerned about my career,” (concern), “Making decisions by myself,” (control), “Probing deeply into questions I have,” (curiosity), and “Solving problems” (confidence) using a 5-point Likert scale ranging from 1 (not strong) to 5 (strongest). The CAAS has been found to be a reliable and valid measures across 13 different countries (Savickas & Porfeli, 2012), and internal consistency reliabilities for subscale scale scores have been found to range from α = .75 to α = .85, with and α = .92 for the total CAAS scale scores. Specifically, Porfeli and Savickas (2012) found the United States version of the CAAS to correlate in the expected direction with career-related constructs such as career commitment making and career commitment identification, and the internal consistency reliability for each subscale score of the U.S. CAAS was as follows: concern (α = .85), control (α = .89), curiosity (α = .85), and confidence (α = .91). In the present study the estimated internal consistency reliability was α = .94 for the total scale and the following for each subscales: concern (α = .86), control (α = .86), curiosity (α = .84), and confidence (α = .90).

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5.2.2. Academic satisfaction We used a 7-item measure of academic satisfaction (Lent, Singley, Sheu, Schmidt, & Schmidt, 2007) to assess the degree to which students were satisfied with their academic life. Students responded to items on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree), and example items included, “I am generally satisfied with my academic life” and “For the most part, I am enjoying my coursework.” In the instrument development study, Lent et al. found the measure of academic satisfaction to correlate in the expected directions with measures of goal progress and self-efficacy; moreover, they found the scale scores to have a strong internal consistency reliability. In the present study, the estimated internal consistency reliability of scales scores was α = .91.

5.2.3. Work volition We assessed work volition using the Volition subscale of the Work Volition Scale-Student Version (WVS-SV; Duffy, Diemer, & Jadidian, 2012). The WVS-SV is comprised of a 7-item Volition subscale and a 9-item Constraint subscale. Students responded to each item on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). For the Volition subscale example items include “I will be able to choose the jobs that I want” and “I feel total control over my future job choices.” In the instrument development study Duffy, Diemer, and Jadidian found scores on the Volition subscale to correlate in the expected directions with measures of career decision self-efficacy, personality traits, and career locus of control, and found the subscale to be adequately reliable, α = .70. The Constraint subscale contains negatively worded items (e.g., “Due to my financial situation, I will need to take any job I can find”) and was not used in the current study as we were specifically focused on positive attitudes relating to one's career. In the present study, the estimated internal consistency reliability of the Volition subscale scores was α = .81.

5.2.4. Career decision self-efficacy We evaluated levels of career decision self-efficacy among students using the 25-item short form of the Career Decision SelfEfficacy Scale (CDSE-SF; Betz, Hammond, & Multon, 2005). We provided the following scale prompt “How much confidence do you have that you could:” and students responded to statements such as “Decide what you value most in an occupation” and “Determine what your ideal job would be.” Students responded to items on a 5-point Likert scale ranging from 1 (no confidence at all) to 5 (complete confidence). Betz et al. (2005) found the scale to correlate in the expected directions with measures of vocational identity and career decision and found the internal consistency reliability to be α = .94. Numerous other recent studies have found the scale to be reliable and cross culturally valid (e.g. Buyukgoze-Kavas, 2014; Metheny & McWhirter, 2013; Presti et al., 2013). In the present study, the estimated internal consistency reliability of scales scores was α = .93.

5.3. Procedure After obtaining approval from the University Institutional Review Board, we proceeded to recruit students from the undergraduate psychology research pool at our university throughout the fall 2014 semester. Students had the option to participate in this study along with other research studies or alternative assignments to receive course credit. A total of 473 completed the entire survey. We inserted two attention checks throughout the survey (e.g., “Please select neutral to show you are paying attention”) and removed 61 students who failed to answer at least one of these items correctly. Of the remaining 412 students, 298 had complete data. The majority of remaining students were missing one item (n = 82), and 17 students were missing two items, eight missing three items, two missing four items, three missing five items, and two missing seven items. In order to address these missing data we followed the recommendations of Parent (2013) and used mean imputation to generate values for these 114 students. For each student missing data, we calculated the scale point closest to the mean score on the overall scale and used that value to replace missing data. Parent (2013) demonstrated that this method can be used in place of more advanced data imputation methods when there is a small amount of missing data (e.g., b10%). In the present study there were 177 (.69%) missing items out of a possible 25,554 items.

Table 1 Descriptive statistics and correlations (N = 412).

1. CA — concern 2. CA — control 3. CA — curiosity 4. CA — confidence 5. CA — total scale 6. Work volition 7. CDSE 8. Academic satisfaction M SD

1

2

3

4

5

6

7

8

– .58 .54 .59 .80 .30 .53 .36 22.00 4.68

– .64 .73 .87 .40 .57 .38 21.50 4.64

– .68 .84 .27 .50 .32 20.60 4.66

– .88 .36 .59 .42 21.80 4.70

– .39 .65 .44 85.86 15.84

– .51 .47 34.73 6.80

– .60 90.24 14.54

– 27.06 5.18

Note. All correlations are significant at p b .01 level. CA = career adaptability, CDSE = career decision self-efficacy.

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6. Results Prior to testing the structural equation model, a number of analyses were conducted. First, we assessed all variables for skewness and kurtosis, and none had values that exceeded 1.0. Thus, all data were kept in the original form. Second, correlations were run to determine the relation of the four components of career adaptability to academic satisfaction. As seen in Table 1, supporting our hypotheses, each component of career adaptability was significantly, moderately correlated with academic satisfaction. Each adaptability component also significantly correlated with the two mediator variables (work volition and CDSE) and the two mediator variables significantly correlated with academic satisfaction. These relations suggest it is appropriate to test for mediation (Frazier, Tix, & Barron, 2004), which we did using structural equation modeling. 6.1. Measurement model Using EQS 6.2 (Bentler, 2006), a measurement model was constructed to examine the factor structure of the 7-factor model. First, we created observed indicators for each of the seven latent constructs. Since CDSE was composed of five subscales, these were used as observed indictors. However, for the other six constructs, item parcels were created to represent three parcels as observed indictors, respectively, for control (6 items), concern (6 items), curiosity (6 items), confidence (6 items), work volition (7 items), and academic satisfaction (7 items). For each of these six scales, parcels were created by conducting an exploratory factor analysis using principal axis factoring and then rank ordering the items in terms of strength of loading. Items were then grouped together to maximize the equality of factor loadings for each parcel within the scale (Velez & Moradi, 2012). The correlation/estimated internal consistency for each parcel was as follows: control (parcel 1 = .33, parcel 2 = .55, parcel 3 = .44), concern (parcel 1 = .38, parcel 2 = .58, parcel 3 = .48), curiosity (parcel 1 = .40, parcel 2 = .38, parcel 3 = .38), confidence (parcel 1 = .65, parcel 2 = .60, parcel 3 = .57), work volition (parcel 1 = .35, parcel 2 = .49, parcel 3 = .62 (α)), and academic satisfaction (parcel 1 = .52, parcel 2 = .66, parcel 3 = .85 (α)). Using these observed indicators, the following fit indices were used to judge this model: chi-square (χ2), the Comparative Fit Index (CFI), and the Root Mean Square Error of Approximation (RMSEA). The CFI and RMSEA were used as our primary indicators of fit as the χ2 is almost always significant with larger sample sizes (Tabachnick & Fidell, 2013). For the CFI, values greater than .95 represent good fitting models and values greater than .90 represent adequate fitting models (Hu & Bentler, 1999). For the RMSEA, values equal to or less than .06 suggest good fit and values less than .10 suggest adequate fit (Hu & Bentler, 1999). The measurement model was a good fit to the data: χ2 (209, N = 412) = 500.39, p b .001, CFI = .96, RMSEA = .06. 6.2. Structural models Next, we tested the structural model. Specifically, we examined how the four adaptability components related to academic satisfaction as mediated by work volition and CDSE. The four components were also allowed to covary in the analysis. This model was also

Fig. 1. Structural equations model. Paths in bold are significant at the p b .05 level.

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a good fit with the data: χ2 (210, N = 412) = 553.56, p b .001, CFI = .95, RMSEA = .06. Both work volition and CDSE were significant predictors of academic satisfaction. Additionally, work volition was significantly predicted by control and CDSE was significantly predicted by concern, control, and confidence. After including the two mediator variables, no significant relations existed between any of the career adaptability components and academic satisfaction, indicating mediation (see Fig. 1). In order to examine these mediation effects we used bootstrap analyses to determine the significance of the paths, focusing specifically on model paths that met Frazier et al.'s (2004) criteria for mediation (A is related to B and B is related to C). In our model, this was four sets of variables: control to academic satisfaction as mediated by work volition, concern to academic satisfaction as mediated by CDSE, control to academic satisfaction as mediated by CDSE, and confidence to academic satisfaction as mediated by CDSE. We created 1000 bootstrapped samples from the data, calculated the mean parameter estimates of all 1000 samples, and then multiplied these together for indirect effects. Using these product terms we examined the 95% confidence intervals (Preacher, Rucker, & Hayes, 2007). According to Shrout and Bolger (2002), if the confidence intervals for these indirect effects do not include zero, the mediations are deemed statistically significant at p b .05. The indirect effect of concern on academic satisfaction as mediated by CDSE was significant (95% CI [.07, .27], β = .16, SE = .001), the indirect effect of control on academic satisfaction as mediated by CDSE was significant (95% CI [.01, .33], β = .15, SE = .001), and the indirect effect of confidence on academic satisfaction by CDSE was also significant (95% CI [.05, .43], β = .22, SE = .001. Finally, the indirect effect of control on academic satisfaction as mediated by work volition was significant (95% CI [.01, .21], β = .10, SE = .001). 7. Discussion The goal of the current study was to examine the relations of the four components of career adaptability and academic satisfaction and assess the degree to which work volition and career decision self-efficacy (CDSE) mediated these relations. Supporting previous research linking career adaptability with GPA (Ӧncel, 2014), and the adapt-ability resource optimism predicting academic adaption among undergraduates over time (Perera & McIlveen, 2014), results demonstrated moderate correlations between each component of adaptability and academic satisfaction. For undergraduate students in our sample, the greater control, concern, curiosity, and confidence they had around their career, the more satisfied they were in the academic domain. As research continues to grow on the adaptability construct, particularly among undergraduate students, these correlations suggest that feeling adaptable in one's career may link not only to positive vocational outcomes but current academic satisfaction. Feeling adaptable in one's career – a goal in the future – may allow for more satisfaction during one's present academic life. We hypothesized that work volition and CDSE would mediate these links given the proposition that feeling adaptable in one's career would predict control and confidence in one's career decision making, which would ultimately predict academic satisfaction; the more students feel volitional and efficacious about their eventual decisions, the more they will feel satisfied in their current academic life. These hypotheses were partially supported. Both work volition and CDSE were direct, significant predictors of academic satisfaction. Also, after introducing work volition and CDSE as mediators in the structural model, the relations of all four career adaptability components to academic satisfaction were non-significant. However, only four of the potential eight paths connecting the components of adaptability to the mediator variables were significant. Thus, although testing all variables at once in the structural model eliminated significant relations between adaptability and satisfaction, work volition and CDSE only partially explained these effects. CDSE was found to be the more robust mediator variable, having a stronger relation to academic satisfaction, being predicted by three adaptability components (concern, control, and confidence), and serving as a significant mediator for each of these variables to academic satisfaction. The links of these variables make conceptual sense. Feeling concern, control, and confidence over one's career in general would likely be predictive of feeling confident specifically in one's career decision making. When students feel confident in their career decisions, satisfaction within the academic domain to prepare one for that career likely follows. These findings mirror research on general self-efficacy and academic outcomes (e.g., Multon, Brown, & Lent, 1991) as well as domain specific self-efficacy and academic satisfaction (Flores et al., 2014; Lent, Taveira, Sheu, & Singley, 2009; Lent et al., 2007). Work volition was also found to be a significant mediator, but only with the control component of career adaptability. It is important to note that although both of these variables concern feelings of control, their bivariate correlation was .40, suggesting that the control component of adaptability is related to, but distinct from, feelings of control specifically in career decision making. In the full model this was the strongest of the four significant relations from adaptability to the mediator variables, and implies that work volition may be particularly important in explaining the link between career control and academic satisfaction. Specifically, having general feelings of control over one's career may predict higher levels of academic satisfaction in part due to increased perceptions of the freedom to choose one's future career. Like adaptability, work volition is construct gaining more research attention over the last several years, and the strength of its link to both concern and academic satisfaction (even after accounting for CDSE) speak to idea that this construct is important in the career development and academic process. As noted by Blustein and colleagues (Blustein, Kenna, Gill, & DeVoy, 2008; Duffy, Bott, Torrey, & Webster, 2013; Duffy & Dik, 2009), because the sense of choice in one's career is so central to one's career development experiences, incorporating this construct into larger vocational and academic theories may allow added insights into why people feel satisfied in school and work, especially those with added barriers to selecting desired careers. Finally, it is noteworthy that curiosity did not significantly relate to work volition, CDSE, or academic satisfaction in the full model. Although feeling curious in the vocational domain is important as it promotes exploration, after accounting for all other model variables it appears to have little effect on feelings of control and confidence in career decision-making or on satisfaction within the academic domain. Curiosity might be more important in predicting other vocational outcomes (e.g. self-exploration, environmental exploration, career optimism, Cai et al., 2015; Tolentino et al., 2014), but less so with the variables assessed in the current study.

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In sum, adding to the growing literature on career adaptability, the results of this study demonstrate that all four components of adaptability correlate with academic satisfaction and the relation of three of these four components to academic satisfaction is mediated by work volition and CDSE. Specifically, control was mediated by both work volition and CDSE and concern and confidence were meditated by CDSE. These results suggest that students with higher concern, control, and confidence in their careers may be more satisfied in the academic domain due, in part, to increased feelings of control and confidence in their career decision making. At a broader theoretical level, findings also support the idea that feeling adaptable (career adaptability) may predict adapting (work volition and CDSE), which in turn predicts adaptation (academic satisfaction). In particular, considering that CDSE was the dominant predictor in the model and specifically assesses adapting behaviors around one's career, results add to the literature connecting adaptability, adapting, and adaptation (Hirschi, Herrmann, & Keller, 2015; Hirschi & Valero, 2015). 7.1. Limitations, future directions, and practical implications The results and conclusions presented above need to be considered in light of a number of limitations, all of which inform directions for future research. First, the cross-sectional data of the present study preclude the possibility of determining causality between the study variables. Thus, it is possible that hypothesized paths may actually be in the reverse order, with work volition and career decision self-efficacy predicting career adaptability. Future studies should obtain data at multiple time points and implement experimental methods in an attempt to determine the causal mechanisms of these variables. Similarly, we surveyed only a select group of students currently in the academic domain — undergraduates. Given that CCT (Savickas, 1997) in concerned with vocational development across the lifespan, scholars should attempt to examine how the study variables relate among students over time. Third, although a strength of our manuscript is that almost half of our sample was non-Caucasian, in regard to sex, our sample was just over 70% female. In order to increase the generalizability of these findings, efforts should be made to obtain samples that are diverse in regard to both ethnicity and sex. Lastly, our data relied solely on self-report data, but obtaining informant data on the study variables – specifically career adaptability – would strengthen future research. From a practical perspective, the results of our study may be useful for counselors working with students who are dissatisfied academically. Specifically, focusing on how students feel about their careers – often a future goal and primary reason for attending college – may promote greater satisfaction in college. Considering the strength of CDSE and work volition in the larger structural equation model, these may be ideal targets of career interventions. First, counselors are encouraged to understand how much choice students feel in their career decision making and in turn what barriers may be restricting this choice. Often these barriers are insurmountable, but some may be malleable by working with the students to find untapped resources to address these hurdles. Second, it is important to assess a student's self-efficacy in implementing their career choices. 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