journal of career assessment 2014 xu 1069072714553073

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Article

Ambiguity ToleranceWith Career Indecision:An Examination of theMediation Effect of Career Decision-Making Self-Efficacy

Hui Xu1

and Terence J. G. Tracey1

AbstractThe mediation of career decision-making self-efficacy on the link of ambiguity tolerance (AT) withcareer indecision was examined in a sample of college students ( N ¼ 253). It was hypothesized thatAT could help reduce career indecision through increasing career decision-making self-efficacy,where this effect would vary by different types of indecision. Results supported the differentialmediation hypothesis, finding that career decision-making self-efficacy mediated the link of ATwith lack of motivation, general indecisiveness, lack of information, and inconsistent information.

The mediation effect of career decision-making self-efficacy on the link of AT with lack of motiva-tion was relatively weak. The implications of this study are discussed and suggestions for futureresearch are provided.

Keywordsambiguity tolerance, career decision-making self-efficacy, career indecision, career counseling

Career decision making is conceived by many theorists (e.g., Holland, 1997; Parsons, 1909;Sampson, Lenz, Reardon, & Peterson, 1999) as a process of collecting information about oneself

and the world of work and then using information to find an area of match. However, this processdepends upon the quality of information gathered and also the ability to put the informationtogether in terms of determining a reasonable match. It is a difficult process and is fraught withambiguity. So a key aspect in career decision making is the ability to deal with this ambiguity.Xu and Tracey (2014) revealed that ambiguity tolerance (AT) was negatively associated withcareer indecision, where individuals who were tolerant of ambiguity had less indecision. Asself-efficacy has been acknowledged as a central variable closely linking to a variety of career out-comes (Lent & Brown, 2013; Lent, Brown, & Hackett, 1994), we sought to examine whether

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Arizona State University, Tempe, AZ, USA

Corresponding Author:Hui Xu, Counseling & Counseling Psychology, MC-0811, Arizona State University, Tempe, AZ 85287, USA.Email: [email protected]

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career decision-making self-efficacy could help explain the positive effect of AT in regard tocareer decision making. The focus of this study was to examine the mediation effect of career decision-making self-efficacy on the link of AT with career indecision.

AT With Career Decision Making Career decision making has been conceptualized for a long while as a process of collecting infor-mation regarding the vocational world and the self and then using the information collected to find an area of match, as Parsons (1909) proposed. This model is based on rational choice theory, whichinvolves the key hypothesis that people have access to all the information and can make a rationalchoice based on the information. However, this hypothesis is commonly unmet because of theinevitable variance in the information available and the common conflicts in the information thatis available (Xu & Tracey, 2014). This informational ambiguity is especially salient in career deci-sion making because of the lack of clear criteria for the optimal career choice and the increasing

complexity of the vocational world in the 21st century.There has been research supporting the role of informational ambiguity in complex decision

making. Kahneman and Tvesky’s groundbreaking work (Kahneman & Tversky, 1979; Tversky& Kahneman, 1981) has demonstrated that uncertainty plays a significant role in the decision-making process, which cannot be explained by the rational choice theory. As opposed to therational choice theory conceiving decision making as a process of comparing expected utilities,Kahneman and Tversky found that in the condition of loss or gain, people tend to prefer or avoid uncertainty, respectively (Kahneman & Tversky, 1979; Tversky & Kahneman, 1981). The resultsthus portrayed uncertainty as an important factor in the complex decision-making process. Hsu,Bhatt, Adolphs, Tranel, and Camerer (2005) portrayed ambiguity as a construct of a high level

of uncertainty and differentiated ambiguity tasks from regular uncertain tasks. They conceived uncertainty as a product due to known event probabilities and conceived ambiguity as a productdue to unknown event probabilities. Neuropsychological evidence of the functional magneticresonance imaging supported the conceptual differentiation by finding the activation of the orbi-tofrontal cortex and the amygdala only in the ambiguous condition. The informational ambiguityis salient in career decision making because the career decision-making process has few clues tothe prospect of any career choice and is of extensive uncertainty (Xu & Tracey, 2014). Given thisrole, it is expected that how people handle informational ambiguity would affect career decision-making outcomes.

One functional way of handling informational ambiguity could be building tolerance withambiguity. AT has been defined as the way individuals perceive and respond to ambiguous situa-tions or stimuli characterized by an array of unfamiliar, complex, or inconsistent clues (Budner,1962; Furnham & Ribchester, 1995). According to Furnham and Ribchester (1995), people withlow levels of AT tend to experience stress, react prematurely, and avoid ambiguous stimuli, whilethose with high AT perceive ambiguous situations/stimuli as desirable and interesting and do notdeny or distort the complexity of incongruity. Therefore, AT portrays the individual difference interms of how people handle information unavailability and conflict (i.e., ambiguity) and would beanticipated to relate to career decision-making outcomes as argued earlier.

There has been empirical evidence supporting the positive link of AT with career decision mak-ing. Endres, Chowdhury, and Milner (2009) found support for the link of AT with self-efficacy in acomplex decision task, suggesting that AT is a positive attribute in ambiguous decision-making

situations. Xu and Tracey (2014) have found that AR negatively predicted different areas of career indecision directly when controlling for amount of career exploration regarding the self and theworld of work. A key assumption made in this study was that the association of AT with career decision making would be mediated by career decision-making self-efficacy.

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Mediation of Career Decision-Making Self-Efficacy The construct of career decision-making self-efficacy was largely derived from Bandura’s seminalwork of general self-efficacy (Betz & Luzzo, 1996; Taylor & Betz, 1983), which postulated self-

efficacy to be an important mediator of individual behaviors, goals, and outcomes (Bandura,1977). As a domain-specific self-efficacy, career decision-making self-efficacy describes an individ-ual’s belief regarding his or her ability to successfully complete tasks necessary to making career decisions. Based on Crites’ (1978) model of career maturity, five processes of career decision mak-ing were conceived as critical for career decisions and thus these five processes were regarded as thespecific behavioral domains where career decision-making self-efficacy should be measured (Betz& Luzzo, 1996; Taylor & Betz, 1983). These five domains consisted of (a) self-appraisal, (b) occu- pational information, (c) goal selection, (d) planning, and (e) problem solving.

Along with Bandura’s (1977) work, the Social Cognitive Career Theory (SCCT; Lent & Brown,2013; Lent et al., 1994) proposed career decision-making self-efficacy to be a pivotal mediator

explaining the career decision-making behaviors and the decision-making outcomes. The link of career decision-making self-efficacy with career indecision has been well studied and solidlysupported by previous research. Betz, Klein, and Taylor (1996) revealed a strong association of career decision-making self-efficacy with career decision certainty and career indecision. Brownet al.’s (2012) study indicated that lack of career decision-making self-efficacy marked one type of career indecision. Osipow and Gati (1998) also showed that career decision-making self-efficacywas strongly associated with two measures of career indecision. Using a meta-analytic approach,Choi et al. (2012) revealed a large association of career decision-making self-efficacy with career indecision among the existing studies.

A key structural path from AT to career decision-making self-efficacy and then to career inde-cision was proposed in this study based on the arguments of SCCT. The SCCT emphasizes the preceding social learning experiences, which forms the foundation of the self-efficacy beliefs. Theself-efficacy beliefs then act as the pivotal internal cognitive unit affecting the subsequent beha-viors and outcomes. One could argue that individuals with low AT tend to have less positiveexperiences in the decision-making processes either in the career domain or in other life domains because they are likely to have difficulty in handling complex decision-making situations. Thesenegative experiences would then be expected to form the basis of beliefs regarding one’s career decision-making abilities, which could lead to less adaptive career decision-making behaviors and greater career indecision.

However, the research has demonstrated that career indecision is not a unidimensional con-struct (e.g., Brown et al., 2012; Gati, Krausz, & Osipow, 1996). Gati, Krausz, and Osipow’s

(1996) multi-dimensional model of career indecision was developed based on an adaptation of decision-making theory to the context of career decisions. It originally proposed three overarchingdomains of career indecision, consisting of lack of readiness, lack of information, and inconsistentinformation. There has been a good deal of data supporting the reliability and validity of thismodel among college students (e.g., Gati et al., 1996; Gati & Saka, 2001; Osipow & Gati,1998). However, the previous research has also indicated that the three indicators of the lack of readiness domain diverged from each other as demonstrated in the low correlations among theindicators and the low alpha coefficients compared to the other two domains (e.g., Gati et al.,1996; Gati & Saka, 2001; Osipow & Gati, 1998). This suggested that lack of readiness was a lesshomogeneous factor. Instead, lack of readiness should be treated more as three distinct indecision

types. Based on these previous findings, we specified and adopted a revised model in the currentstudy by breaking down the lack of readiness domain into three indecision types, anticipating thatit would be a better representation of the data. The five resulting domains of career indecision werethus lack of motivation (RM), general indecisiveness (RI), dysfunctinal beliefs (RD), lack of

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information (LI), and inconsistent information (II). Xu and Tracey (2014) provided support for the structural validity of this revised model in the findings of satisfactory model data fit and factor loadings. The revised multidimensional model acknowledged the various aspects of career indecision and enabled us to investigate the potentially differential predictions on domains of career indecision.

We hypothesized that the mediation effect of career decision-making self-efficacy occurs onthe paths from AT to all the five domains of career indecision. As argued earlier, people with poor AT are more likely to have poor self-efficacy regarding career decision making. They would beanticipated to have less motivation for career decision making, as it could be a challenging activityfor them to avoid. They tend to have more general indecisiveness and dysfunctional beliefs, asthey hold less faith with their career decision-making abilities and with the possibilities of opti-mizing their career choices. With the poor self-efficacy in mind, they are also likely to have moreinformation deficit and conflict, as they tend to engage in less functional information searchingand integration behaviors.

However, the associations of career decision-making self-efficacy with lack of motivation, gen-eral indecisiveness, and dysfunctional beliefs were proposed to be weaker than the ones with lack of information and inconsistent information. We argued that poor information collecting behaviorsresulting from poor self-efficacy could largely contribute to lack of information and inconsistentinformation, whereas individual values and personality independent of self-efficacy could signifi-cantly account for lack of motivation, general indecisiveness, and dysfunctional beliefs. The differ-ential hypotheses resonated with Gati et al.’s (1996) indecision model that lack of motivation,general indecisiveness, and dysfunctional beliefs were grouped together as they were more of chronological and characteristic issues arising before the career decision-making progress, whilelack of information and inconsistent information were grouped together as they were more of devel-

opmental and behavioral issues arising during the career decision-making process. Osipow and Gati(1998) have shown a similar pattern of differential associations between career decision-makingself-efficacy with different domains of indecision in the findings of stronger correlations betweencareer decision-making self-efficacy with lack of information and inconsistent information.

Based on Xu and Tracey (2014)’s preliminary finding of AT being negatively associated withcareer indecision, this study was intended to advance the research topic by investigating how thiseffect occurs and specifically examine one possible meditational path proposed by an importantcareer model of SCCT. The meditational examination has never been conducted regarding the link of AT with career indecision to our best knowledge and the mechanism of how AT leads to lesscareer indecision is still unclear. The mediation of career decision-making self-efficacy is espe-cially important for career counseling practice with the SCCT framework, where career decision-making self-efficacy is the central vehicle of the model and insights regarding the pre-dictors of self-efficacy are needed for a more effective intervention. Xu and Tracey (2014) inves-tigated the link of AT with career indecision in a sample of major undecided freshman students. Inorder to enhance generalizability, a more diverse sample that varied from the one used by Xu and Tracey (2014) was selected in this study, consisting of both major decided and undecided studentsin various grades.

Research HypothesisTo sum up, the model of the hypothesized structural relations is depicted in Figure 1. As noted

earlier, AT predicts career decision-making self-efficacy (path a) because ambiguity-tolerant peopletend to have positive decision-making experiences and could form a better decision-making self-efficacy. Career decision-making self-efficacy predicts all the five domains of career indecision(paths b, c, d, e, and f) because people confident in their career decision-making skills tend to have


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validity of the CDDQ. This study found a coefficients of .70, .72, .52, .96, and .93 for the RM, RI,RD, LI, and II scales, respectively.

ProcedureCollege students participating in career development, introduction to psychology, or universityorientation classes were invited to participate in this study as an extra credit opportunity. Volun-tary participants filled a demographic questionnaire and the package of research instrumentsonline. All the individual responses were kept as anonymous and confidential through analysis.Of the 260 total participatns, 7 participants withdrew from the study and did not answer theCDDQ. They were not included in the final data set. According to the setting of the online survey, participants were required to answer all items before they could move to the next part. Thus, therewere no missing data in the final data set.

AnalysisMplus 7 was employed to conduct the latent variable Structural Equation Modeling (SEM) becausesuch an approach would enable the examination among error-free latent contstructs instead of error-laden manifest variables. Given the low reliability of some of the indecision scales, suchan approach makes the most sense. The means for the five subscales of MSTAT-II, correspondingto the five theoretical stimulus types, were used as the indicators of the latent AT. The means for the five subscales of CDSE-SF, corresponding to the five theoretical behavioral domains crucial tocareer decision making, were used as the indicators of the latent career decision-making self-efficacy. The manifest items of the RM, RI, and RD subscales of CDDQ were used as the indica-tors of the latent RM, RI, and RD domains. The subscales under the domains of LI and II were used as the indicators of the latent LI and II domains.

The latent variable SEM enabled us to examine the structural relations without the confound of the measurement error and thus results in a more precise examiantion. The fit of the modelswould be evaluated using the criteria recommended by Hu and Bentler (1999) which includerobust chi-square, comparative fit index (CFI), root mean square error of approximation (RMSEA),and standardized root mean square residual (SRMR). With the purpose of making the statistical testsrobust to nonnormality, we adopted the robust maximum likelihood parameter estimation. A nested model comparison approach was used to precisely examine which model represented the data better.Differences between nested models were compared using the Santorra–Bentler scaled chi-squaredifference test (Muthén & Muthén, 2012).

The SEM bias-corrected bootstrapping approach ( n ¼ 1,000) of mediation test was used in thisstudy, given its superior performance in the simulaiton studies (Cheung & Lau, 2008). As Cheungand Lau (2008) suggested if the 95 % confidence interval (CI) does not contain zero, then the media-tion effect is significant at the a level of .05.

ResultsTable 1 showed the means, SDs, and bivariate correlations of AT, career decision-making self-efficacy, and domains of career indecision. Table 2 summarizes the fit indices of all the models.We first examined the measurement model of the proposed model (Model 1), in which career

decision-making self-efficacy mediates the relation of AT to different domains of career indecision.The measurement model was found to fit the data adequately with respect to the RMSEA (.066)

and the CFI (.90); however the SRMR (.093) was above the recommended levels. An examination of the modification indices as well as the factor loadings indicated that 1 item (CDDQ10) in the RD

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scale had significant cross loadings on all the other domains of career indecision (i.e., RM, RI, LI,and II) and on CDSE, whereas its factor loading on the latent RD was poor (.12). The CDDQ10literally asked individuals the degree to which ‘‘I expect that through the career I choose I will fulfillall my aspirations.’’ It was plausible to suggest that the career belief reflected in this item was moreassociated with the individual optimism or self-efficacy, instead of the dysfunctional rigidity amongthe population being investigated in this study. We thus dropped this item in the following analysisand examined the revised measurement model (Model 2) again. As can be seen by the values of CFI(.92), RMSEA (.060), and SRMR (.065), this model fits the data acceptably. The individual factor loadings for all the latent factors were found to be significant and of moderate to large magnitude,

further supporting the structure validity of all the latent variables.We then examined the full structural model (Model 3.1). The values of CFI (.91) and RMSEA

(.064) indicated an adequate model data fit. However, one problem with structural analysis based on cross-sectional data is that the reverse model could fit the data equally or even better. We thus

Table 2. Summary of Model Fit Index for Model Comparison.

w2 df Comparative

Fit Index

Root Mean SquareError of Approximation

Standardized RootMean Square

ResidualEstimate90% Confidence

Interval

Model 1 measurement 639.71 303 .90 .066 [.059, .073] .093Model 2 revised measurement 529.49 278 .92 .060 [.052, .067] .065Model 3.1 structural 574.70 283 .91 .064 [.056, .071] .083Model 3.2 structural alternative 600.27 283 .90 .067 [.059, .074] .107Model 4 modified structural 529.49 278 .92 .060 [.052, .067] .065Model 5 parsimonious 530.23 279 .92 .060 [.052, .067] .066Model 6.1 (b ¼ c ¼ e ¼ f) 540.02 282 .92 .060 [.052, .068] .069Model 6.2 (b ¼ e) 538.65 280 .92 .060 [.053, .068] .069Model 6.3 (b ¼ f) 537.45 280 .92 .060 [.053, .068] .068Model 6.4 (c ¼ e) 532.51 280 .92 .060 [.052, .067] .067Model 6.5 (c ¼ f) 531.87 280 .92 .060 [.052, .067] .067Model 7 final 532.67 281 .92 .059 [.052, .067] .067

Note. N ¼ 253.

Table 1. Means, Standard Deviations, Cronbach a , and Correlations of Variables.

M SD Ca AT CDSE RM RI RD LI

AT 3.20 0.49 .82 – CDSE 3.64 0.56 .94 .30** – RM 2.93 1.52 .70 .26** .32** – RI 5.46 1.83 .72 .45** .38** .26** – RD 4.56 1.35 .52 .18** .02 .08 .17** – LI 3.48 1.74 .96 .37** .58** .56** .45** .15* – II 3.24 1.69 .93 .27** .50** .57** .37** .11 .86**

Note. N ¼ 253. AT ¼ Ambiguity Tolerance (MSTAT-II); CDSE ¼ Career Decision Self-Efficacy–SF; RM ¼ CDDQ-Lack of Motivation; RI ¼ CDDQ-General Indecisiveness; RD ¼ CDDQ-Dysfunctional Beliefs; LI ¼ CDDQ-Lack of Information;II ¼ CDDQ-Inconsistent Information.*p < .05.**p < .01.


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tested the alternative model (Model 3.2) of career decision-making self-efficacy leading to AT and to career indecision. As can be seen from the values of CFI (.90), RMSEA (.067), and SRMR (.107),the model fit was marginal. The original model had slightly better fit indicators, indicating that theoriginal structural model was a better representation of the data than the alternative one.

However, the value of SRMR (.083) of the original structural model (Model 3.1) was above theideal level, indicating that this model was a mediocre representation of the data. The significantresult of the corrected chi-square difference test also indicated that this model omitted someimportant paths in the saturated model, scaled Dw2 (5, N ¼ 253) ¼ 59.97, p < .05. The modificationindices suggested that AT directly predicted the five domains of career indecision (i.e., RM, RI,RD, LI, and II) as well. We thus specified a modified model (Model 4) based on Model 3.1 butadding the paths from AT to lack of motivation (path g), general indecisiveness (path h), dysfunc-tional beliefs (path i), lack of information (path j), and inconsistent information (path k). TheModel 4 was found to fit the data adequately as can be seen from the values of CFI (.92), RMSEA(.060), and SRMR (.065). This model included all the possible structural paths and thus repre-

sented the data equivalently as the saturated measurement model. The examination of theindividual regression coefficients revealed one nonsignificant path from career decision-makingself-efficacy to dysfunctional beliefs (path d), indicating that career decision-makingself-efficacy was not associated with dysfunctional beliefs.

We then continued to specify a more parsimonious model (Model 5) by dropping the nonsigni-ficant path in Model 4 (path d). As can be seen from the values of CFI (.92), RMSEA (.060), and SRMR (.066), this model was found to fit the data adequately. The scaled chi-square differencetest indicated that this model did not significantly worsen the model data fit compared to Model4 and the measurement model, scaled Dw2 (1, N ¼ 253) ¼ .37, p > .05.

Based on Model 5, we constrained the paths b, c, e, and f in Model 6.1 to test whether there were

differential predictions of career decision-making self-efficacy on different domains of indecision.This model was found to fit the data adequately as can be seen from the values of CFI (.92),RMSEA (.060), and SRMR (.069). The corrected chi-square difference test between Model 6.1and Model 5 was significant, scaled Dw2 (3, N ¼ 253) ¼ 7.81, p < .05, indicating that the fully con-strained model was a worse representation of the data and thus there were differences in the paths b, c, e, and f. We then constrained one pair of paths each time (i.e., b ¼ e, b ¼ f, c ¼ e, and c ¼ f respectively) to precisely examine the hypothesis of differential predictions.

Model 6.2 constrained the paths b and e. As can be seen from the values of CFI (.92), RMSEA(.060), and SRMR (.069), this model fits the data adequately. The corrected chi-square differencetest between Model 6.2 and Model 5 was significant, scaled Dw2 (3, N ¼ 253) ¼ 7.14, p < .05, indi-cating that paths b and e were different. It was thus suggested that career decision-making self-efficacy was more predictive of lack of information than lack of motivation.

Model 6.3 constrained the paths b and f. As can be seen from the values of CFI (.92), RMSEA(.060), and SRMR (.068), this model fits the data adequately. The corrected chi-square differencetest between Model 6.3 and Model 5 was significant, scaled Dw2 (3, N ¼ 253) ¼ 6.18, p < .05, indi-cating that paths b and f were different. It was thus suggested that career decision-making self-efficacy was more predictive of inconsistent information than lack of motivation.

Model 6.4 constrained the paths c and e. As can be seen from the values of CFI (.92), RMSEA(.060), and SRMR (.067), this model fits the data adequately. The corrected chi-square differencetest between Model 6.4 and Model 5 was not significant, scaled Dw2 (3, N ¼ 253) ¼ 2.33, p >.05, indicating that path c and path e were equal. It was thus suggested that career decision-

making self-efficacy was equally predictive of lack of information and general indecisiveness.Model 6.5 constrained the paths c and f. As can be seen from the values of CFI (.92), RMSEA

(.060), and SRMR (.067), this model fits the data adequately. The corrected chi-square differencetest between Model 6.5 and Model 5 was not significant, scaled Dw2 (3, N ¼ 253) ¼ 1.63, p > .05,

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indicating that paths c and f were equal. It was thus suggested that career decision-making self-efficacy was equally predictive of inconsistent information and general indecisiveness.

Using these results, we specified a partially constrained model (Model 7) in which paths c, e,and f were set to be equal. Model 7 was found to fit the data adequately as can be seen from thevalues of CFI (.92), RMSEA (.059), and SRMR (.067). The corrected chi-square difference testindicated that Model 7 did not significantly worsen the model data fit compared to Model 5, scaled Dw2 (2, N ¼ 253) ¼ 2.29, p > .05. Therefore, this model was endorsed as the final model based onthe revised indecision model (see Figure 2 for all the standardized coefficients).

Although we used an altered model of indecision in our analysis, based on past research, wealso examined our model using Gati et al. (1996)’s original indecision model in relation to AT and career decision-making self-efficacy. The values of CFI (.92), RMSEA (.074), and SRMR (.060)indicated that the structural model was an acceptable representation of the data. The regressioncoefficients also revealed a similar structural pattern (i.e., differential paths) with the final model(Model 7). However, the poor factor loading of dysfunctional beliefs on lack of readiness (.15) brought into question the construct validity of Gati et al. (1996)’s original model in the current

sample. Therefore, our final model based on the revised indecision model was selected as the bestrepresentation of the data.

Table 3 presented the results of the SEM bias-corrected bootstrapping analysis of the mediationeffect of career decision-making self-efficacy based on the final model. As can be seen from the

Figure 2. The final model. Note. AT ¼ ambiguity tolerance; CDSE ¼ career decision self-efficacy; RM ¼ lack of motivation; RI ¼ general indecisiveness; RD ¼ dysfunctional beliefs; LI¼ lack of information; II ¼ inconsistentinformation.


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95% CIs for the paths a and b [ .20, .04], a and c [ .20, .08], a and e [ .28, .11], and a and f [ .24, .10], it was well supported that career decision-making self-efficacy mediated the predictions of AT on lack of motivation, general indecisiveness, lack of information, and incon-sistent information. Results suggested that people with high AT tend to have a better career decision-making self-efficacy, which could contribute to the relief of career indecision due tolack of motivation, general indecisiveness, lack of information, or inconsistent information. Themediation effect of career decision-making self-efficacy on the link of AT with dysfunctional beliefs was not revealed in the current study.

Discussion

Overall, the key structural hypothesis that career decision-making self-efficacy mediated the link of AT with career indecision was supported by the current results, although variations existed withdifferent domains of career indecision. Career decision-making self-efficacy was found to mediatethe link of AT with lack of motivation, general indecisiveness, lack of information, and inconsis-tent information, while the link of career decision-making self-efficacy with dysfunctional beliefswas not revealed in this study. The results thus suggested that individuals with more tolerance toambiguity tend to have better self-efficacy regarding career decision making and consequentlytend to have more motivation for career decision making, less general indecisiveness, less infor-mational deficit, and less informational conflict. The SCCT (Lent & Brown, 2013; Lent et al.,1994) has proposed career decision-making self-efficacy to be a pivotal mediator explaining theoutcome of the career decision-making process and the close connection of career decision-making self-efficacy with career indecision has been unequivocally demonstrated (Choi et al.,2012). Although Xu and Tracey (2014) have revealed the negative association of AT with career indecision, this study further suggested that the benefits of AT with respect to career decision mak-ing could be attributable to the increased self-efficacy beliefs regarding one’s critical career decision-making skills. Since the current data were only cross-sectional, a longitudinal examina-tion in the future would be helpful providing more validity to the temporal mediation hypothesis.

The differential associations of career decision-making self-efficacy with different domainsof career indecision were supported in this study, although the differential pattern was not exactlythe same as we hypothesized. The results showed that the association of career decision-makingself-efficacy with lack of motivation was weaker than the ones with general indecisiveness, lack of

information, or inconsistent information. It was thus suggested that an increased career decision-making self-efficacy resulted from more tolerance with ambiguity would be more beneficial withthe issues of general indecisiveness, informational deficit, and informational conflict in career decision making than with the issue of motivation shortage. This piece of data was consistent with

Table 3. The SEM Bias-Corrected Bootstrapping Test of the Mediation Effect of Career Decision-MakingSelf-Efficacy.

Independent Variable Mediator Variable Dependent Variable Estimate

95% Confidence

IntervalAmbiguity tolerance Career decision-making

self-efficacyLack of motivation .12 [ .20, .04]General indecisiveness .14 [ .20, .08]Dysfunctional beliefs .00 [.00, .00]Lack of information .19 [ .28, .11]Inconsistent information .17 [ .24, .10]

Note. N ¼ 253.

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Gati et al. (2013)’s finding that the effect of a career workshop on lack of motivation was smallcompared to the effect on other domains of career indecision and career decision-making self-efficacy, thus calling for more future research investigating the important predictors unique to thisdomain. It was plausible that individual value could be a promising candidate. The differentialassociations also resonated with the distinction between career indecision and career indecisive-ness (Germeijs, Verschueren, & Soenens, 2006) that indecision is more associated with career cognition/behaviors and indecisiveness is more associated with chronic dispositions.

Among the five domains of career indecision, the domain of dysfunctional beliefs was notfound to associate with career decision-making self-efficacy, indicating that the positive effectof AT with dysfunctional beliefs revealed in Xu and Tracey (2014)’s study was not directly related to an increased career decision-making self-efficacy. Characteristics of dysfunctional beliefs arethe rigidity and the compulsivity of beliefs. The research has demonstrated the relation of cogni-tive inflexibility with obsessive–compulsive personality traits (DeBerry, 2012) and the rigidity of attitudes (Martin & Rubin, 1995). Together with these studies, this study suggested that the pos-

itive effect of AT with dysfunctional beliefs did not go through the cognitive beliefs regardingone’s career decision-making skills, rather it might be mediated by another cognitive orienta-tion––the cognitive flexibility. It would be interesting to see future research investigating the med-iation of cognitive flexibility on the link of ambiguity with career indecision, especially thedomain of dysfunctional beliefs.

Along with the indirect effect of AT on domains of career indecision through career decision-making self-efficacy, this study also revealed significant direct predictions of AT on all the fivedomains of career indecision. This finding was consistent with the previous research portrayingAT as one important predictor accounting for some unique variances in career indecision. Xuet al. (2014) have found that environmental exploration and self-career exploration did not contrib-

ute to the relief of career indecision as much as Parsons (1909) proposed. Xu and Tracey (2014)revealed that AT additively predicted domains of career indecision when controlling for the amountof career exploration. This study extended this research line by showing that AT accounted for theunique variance in career indecision that could not be explained by the construct of self-efficacy,which has been acknowledged as a central variable in the career development research (Lent &Brown, 2013; Lent et al., 1994). The incremental validity of AT in predicting career indecision indi-cated in this study thus further supported the important role of AT in career decision making. Indi-viduals of high tolerance with ambiguity were likely to show a pattern of less career indecisionacross different indecision domains, which warranted the necessity and benefits of addressing thistopic in career counseling.

There are several limitations regarding the conclusions drawn from this study. First, the studyonly sampled college students so that the results cannot be generalized to younger or older individ-uals. The study is cross sectional and thus the sequential ordering of variables cannot be definitivelydetermined. Longitudinal examinations are needed. Further, although the study supported therevised indecision model used, it was different from the one proposed by Gati et al. (1996) and thisdifference could be attributable to sample error. However, a similar structure was supported in Xuand Tracey (2014), providing some support for the indecision dimensions used in this study.

On a whole, this study addressed one important question regarding how AT leads to less career indecision through the mediation of enhanced career decision-making self-efficacy. Although the bivariate association of AT with career indecision has been revealed in Xu and Tracey’s (2014)study, the mechanism of this effect has not been explored. Limited knowledge about the mechanism

makes the substantive meaning of the construct of AT with respect to career indecision unclear and thus prevents it from generating greater application in career counseling. This study provided another piece of evidence in addition to Xu and Tracey (2014) supporting the importance of AT withcareer decision making. More importantly, AT has been revealed by this study to lead to less


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career indecision through one specific path mediated by career decision-making self-efficacy,which additionally helps explain the positive effect of AT with respect to career decision making.Along with the general mediation pattern, this study also found differential predictions of career decision-making self-efficacy on different domains of career indecision, suggesting that anincreased self-efficacy resulted from more AT would have differential effects on differentdomains of indecision. Specifically, the domains of lack of motivation and dysfunctional beliefstended to benefit less as opposed to general indecisiveness, lack of information, and inconsistentinformation. As the association of career decision-making self-efficacy with career indecision has been solidly revealed (Choi et al., 2012), this study adds into the literature by revealing heteroge-neity in the efficacy–indecision link. Thus, although the substantive utility of AT in career coun-seling is further supported by this study, intervention strategies tailed to different indecision typesare also warranted.

Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

FundingThe author(s) received no financial support for the research, authorship, and/or publication of this article.

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