Research Concept Matrix
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ToyokawldDewald2019.pdf
332 The Career DevelopmenT QuarTerly DECEMBER 2020 • VOLUME 68
© 2020 by the National Career Development Association. All rights reserved.
Received 07/15/19 Revised 10/26/19
Accepted 10/30/19 DOI: 10.1002/cdq.12240
Perceived Career Barriers and Career Decidedness of First-Generation College Students
Teru Toyokawa and Chelsie DeWald
We examined the effects of perceived career barriers on career decidedness among first-generation college (FGC) students (n = 149) and non-FGC students (n = 182) at a 4-year university (mean age = 19.3 years). Participants responded online to measures of perceived career barriers and career decidedness. Results indicated that FGC students scored higher on lack of support and lack of time and financial resources than non-FGC students. For both groups, higher levels of perceived lack of skills were related to lower levels of career decidedness, whereas greater levels of family-related responsibilities predicted higher levels of career decidedness. FGC student status moderated the association between perceived lack of time/financial resources and career decidedness. Further research is needed to investigate the differential effects of various domains of career barriers. Career counselors are advised to consider FGC students’ perceived career barriers in guiding students’ career exploration and decision-making.
Keywords: first-generation college students, career barriers, decision-making, transi- tion, career exploration
Despite the recent decrease in the number of first-generation college (FGC) students due to the increasing number of adults age 25 or over with bachelor’s degrees, there remain a large number of FGC students studying in higher education (Cataldi et al., 2018; Skomsvold, 2014). On the basis of the Educational Longitudinal Study of 2002 data regarding high school sophomores (Lauff & Ingels, 2013), 24% of those students who enrolled in postsecondary institutions were considered FGC students, whereas 42% were considered non-FGC students with at least one parent with a bachelor’s or higher degree. The remaining 34% were considered non-FGC students with at least one parent with some postsecondary education, but not a degree (Redford & Hoyer, 2017). Various reports commonly describe the lower rates of academic success of FGC students, compared with their non-FGC student counterparts, at universities and colleges. One report based on the analysis of attrition behavior with over 4,000 undergraduate students who attended 4-year colleges and univer- sities in 1991–1994 revealed that, after being admitted to universities and colleges, 51% of FGC students cannot complete their postsecondary education within 4 years compared with 26% of undergraduate students with at least one parent with a bachelor’s degree (Ishitani, 2006).
Teru Toyokawa, Department of Human Development, California State University San Marcos; Chelsie DeWald, Department of Psychology, Pacific Lutheran Univer- sity. Correspondence concerning this article should be addressed to Teru Toyokawa, Department of Human Development, California State University San Marcos, 333 South Twin Oaks Valley Road, San Marcos, CA 92096 (email: ttoyokawa@ csusm.edu).
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Even if they can complete their education, FGC students experience disadvantages in transitioning from school to work because of challenges and barriers to their career exploration and planning (Olson, 2014). Although FGC students’ academic challenges during education have been previously studied (Gibbons & Woodside, 2014; Pascarella et al., 2004), their challenges during the school-to-work transition have not been studied extensively. Therefore, it is crucial to understand factors associated with FGC students’ challenges in their exploration of future careers so that effective interventions and support resources can be provided to them to enhance their career development. In the present study, we aimed to investigate how FGC students perceive challenges and barriers in their career exploration processes.
Career Barriers
Challenges and disadvantages that people perceive and encounter in pursuing and developing their careers have been conceptualized as career barriers (Lent et al., 2000; McWhirter, 1997; Swanson et al., 1996; Swanson & Woitke, 1997). Career barriers denote “events or conditions, either within the person or in his or her environment, that make career progress difficult” (Swanson & Woitke, 1997, p. 446). Researchers have conceptualized career barriers as a multidomain construct. For example, Crites (1969) characterized career barriers as internal and external. Years later, Swanson and colleagues (Swanson et al., 1996; Swanson & Woitke, 1997) characterized career barriers as involving social, interpersonal, and attitudinal domains. Using open-ended questions, Luzzo (1993) categorized college students’ responses about past and future career barriers as related to family, study skills, ethnic identity, and finances.
Empirical studies have examined effects of perceived barriers on career outcomes using multiple barrier domains. For example, Luzzo (1996) reported that the number of barriers to future career develop- ment perceived by college students was significantly and negatively correlated with their career decision-making self-efficacy, whereas the number of family-related barriers was positively associated with career decision-making self-efficacy. Urbanaviciute et al. (2016) found that internal career barriers (e.g., lack of abilities) but not external barriers (e.g., lack of employment opportunities) perceived by undergraduate students in universities in Lithuania predicted students’ vocational identity commitment through the mediating variable of academic major satisfac- tion. They argued that internal barriers had a greater negative effect on vocational outcomes because students considered internal career-related barriers as personal hindrances that could be more permanent, whereas external career barriers were regarded as contextual or environmental hindrances. This finding suggests the importance of treating perceived career barriers as a multidomain construct and examining the differen- tial effects of various domains of career barriers on people’s particular career outcomes. Studying Korean college students, Lee et al. (2008) examined distinct profiles based on students’ perceptions of career bar- riers in various domains (e.g., financial and physical health problems, lack of vocational information) to identify four profiles (i.e., salient in internal career barriers, salient in external barriers, low in both domains of barriers, and high in both domains of barriers). These researchers also
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found that students with different profiles also differed in personality traits and other attributes (e.g., hardiness, optimism, locus of control).
As the aforementioned studies illustrate, assessing career barriers as a multidomain construct is considered useful in understanding career devel- opment processes. However, most existing studies of career barriers and their effects on career outcomes have used the aggregated scores of various domains of the construct (e.g., Gnilka & Novakovic, 2017; Gushue et al., 2006; Luzzo & McWhiter, 2001; Mejia-Smith & Gushue, 2017; Raque- Bogdan & Lucas, 2016). In the present study, we addressed this limitation by using multiple domains of FGC students’ perceptions of career barriers to examine their unique effects on levels of the career decision-making process.
Perceived Career Barriers and Career Outcomes
Previous studies have indicated that FGC students report more perceived career barriers than do non-FGC students (Gibbons & Borders, 2010; Raque-Bogdan & Lucas, 2016). Compared with non-FGC students, FGC students perceive less family support for attending college (Gibbons & Borders, 2010; York-Anderson & Bowman, 1991), lack of support from faculty or mentors and an unwelcoming environment on campus (Owens et al., 2010), lower levels of social and financial support (Mehta et al., 2011; Mitchall & Jaeger, 2018), lack of knowledge and skills with respect to opportunities for career exploration and networking that schools provide (Parks-Yancy, 2012), lack of a professional/career network (Tate et al., 2015), and role strains (Storlie et al., 2016). Although research evidence has accumulated regarding FGC students’ perceptions of career-related barriers and their effects on career outcomes, very few empirical studies have directly compared FGC students and non-FGC students on career- related barriers. Additionally, very few studies have examined how FGC students’ perceived career barriers influence their career decision-making processes. Social cognitive career theory (Lent et al., 1994, 2000) is particularly relevant to the investigation of such influence.
Social cognitive career theory focuses on three major cognitive- person constructs (i.e., self-efficacy, outcome expectations, and goals) to explain processes through which people may develop career interests, make career choices, and pursue a certain career. This theory considers contextual influences as barriers, which are related closely to person fac- tors, such as gender, race/ethnicity, and predispositions, in one’s career choice process. Some career-related barriers FGC students may face are considered external, such as harsh economic conditions, relatively high rates of youth unemployment, changes in the nature of jobs, and less availability of jobs because of globalization or outsourcing. Other barri- ers may be considered internal, such as lack of skills required for certain occupations and low levels of motivation for job training. Although these different types of barriers are assumed to have different influences on people’s career behaviors (Swanson et al., 1996), very few empirical studies have examined FGC students’ career-related barriers from this perspective. Therefore, it is imperative for researchers to understand how the different domains of career barriers may variously influence career outcomes of FGC students.
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Purpose of the Study
To fill the aforementioned gaps in the literature, we examined whether there would be mean differences in the multiple domains of career bar- riers between FGC and non-FGC students. We also investigated how the different domains would predict FGC students’ career decidedness, using scores on multiple domains of career-related barriers rather than assessing total barrier scores. Finally, we examined whether FGC student status would moderate the association between varying domains in career barriers and decision-making.
We chose career decidedness as the major outcome variable. For FGC students, many of whom are considered emerging adults (Arnett, 2000), career exploration and decision-making are important develop- mental tasks during the transition from school to work. Regarding FGC students’ career-related barriers, previous studies have reported that FGC students’ perceived barriers in decision-making in math/science careers were negatively correlated with those students’ intention and goals in pursuing math/science-related careers (Garriott et al., 2013). Previous studies have examined various antecedents of career decidedness among emerging adults, including vocational identity (Vondracek et al., 1995), leisure and work engagement (Konstam & Lehmann, 2011), career self- efficacy (Luzzo, 1996; Xu & Tracey, 2015), and career adaptability and future orientation (Ginevera et al., 2016). Although there is much evidence for the linkage between career-related barriers and career decision self- efficacy (e.g., Gnilka & Novakovic, 2017; Mejia-Smith & Gushue, 2017; Wright et al., 2014), only a few studies have examined the effect of college students’ perceptions of career-related barriers on their decision-making in future occupations (Creed et al., 2004; Holland et al., 1980). These studies suggest that career-related barriers have negative effects on FGC students’ career decision-making. The barriers and disadvantages FGC students tend to experience are assumed to influence their occupational exploration and career decision-making. Therefore, in order to support and help FGC students to make career-related decisions, research is needed to better understand the effects of FGC students’ perceived career bar- riers on their career decision-making. Toward this end, we tested three hypotheses based on our foregoing literature review:
Hypothesis 1: FGC students will report higher levels of perceived career- related barriers than will non-FGC students.
Hypothesis 2: Perceived career barriers will be negatively associated with career decidedness.
Hypothesis 3: FGC student status will moderate the relation between perceived career barriers and career decidedness, with career-related barriers associated more strongly with career decidedness for FGC students than for non-FGC students.
Method
Participants We collected data from 353 undergraduate students at a liberal arts uni- versity in the Pacific Northwest. For the present study, 14 students who
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were over age 25 were excluded. After an additional eight participants who had missing data were excluded, the final sample consisted of 331 students (229 women, 102 men). The mean age of the participants was 19.3 years (SD = 1.36, range = 17–25). Out of the 331 students, 149 (45%) were FGC students. Regarding the students’ academic standing, 175 (52.9%) reported being in their first year, 67 (20.2%) reported be- ing in their sophomore year, 56 (16.9%) reported being in their junior year, 31 (9.4%) reported being in their senior year, and two (0.6%) were unidentified. In terms of the participants’ racial/ethnic backgrounds, 224 (67.7%) identified as European American/White, 41 (12.4%) as biracial or multiracial, 28 (8.5%) as Asian American/Asian, 20 (6.0%) as Hispanic American/Latinx, nine (2.7%) as African American/Black, eight (2.4%) as Native Hawaiian/Pacific Islander, and one (0.3%) as American Indian.
Procedure
We recruited participants through the psychology department’s research participant pool during the years 2015–2017. Most participants were in the introductory psychology course. After students signed up for the present study, they were invited to a computer lab by undergraduate research assistants and were asked to respond to online surveys with Google Forms administered through one of the computers in the room. Students who completed the survey earned credits for their courses.
Measures Career decidedness. We used the six-item Career Decidedness Scale (Lounsbury, Hutchens, & Loveland, 2005; Lounsbury, Saudargas, et al., 2005) to assess participants’ levels of decidedness about their careers. The Career Decidedness Scale measures the relatively narrow trait of career decidedness. Compared with other career decision scales—for example, Osipow et al.’s (1976) Career Decision Scale—this measure is short and easy to administer. It has good psychometric properties with high reliability (e.g., a = .91) and validity (e.g., a significant and nega- tive correlation with Osipow et al.’s, 1976, scale; positive correlations with Big Five personality traits, general life satisfaction, and sense of identity). Participants rated each item using a 5-point Likert-type scale (1 = least likely, 5 = most likely). Sample items include “I have made a definite decision about a career for myself,” “I am sure about what I eventually want to do for a living,” and “I go back and forth on what career to go into” (reverse scored). In present study, the Cronbach’s alpha for the Career Decidedness Scale was .91.
Perceived career barriers. A 22-item measure of perceived career barri- ers was developed for this study by modifying items from McWhirter’s (1997) and Swanson et al.’s (1996) perceived career barriers measures. To construct a relatively short scale with a wide range of career barriers domains, we combined some of the items from the existing measures and changed their wording. For example, instead of adopting such items as “being treated differently because of my ethnic/racial background” and “experiencing racial discrimination in promotions in job/career,” we used the item “discrimination because of my race and ethnicity.”
Of the 27 items initially pooled for this study, 23 items reflected 27 items in the scales of career and educational barriers by McWhirter
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(1997) and 63 items in Swanson et al.’s (1996) measure. Four items (e.g., “discrimination because of my sexual orientation,” “not willing to relocate far from my family”) were added by the first author of the present study. The following instructions preceded the items: “Below are challenges that you may and/or have experienced in pursuing your future occupation. Please rate how likely you think each challenge will interfere with your future occupational pursuits.” Participants rated each item in terms of how likely it was that it would interfere with their future occupational pursuits using a 5-point Likert-type scale (1 = least likely, 5 = most likely). Sample items include “lack of skills needed for the occupation I want to pursue,” “no support for my plans from my professor(s),” “having a child (currently or in future),” and “time it will take to finish additional training/education.”
We performed an exploratory factor analysis of the 27 items using principal factors extraction with promax rotation. After deleting five items because of their low factor loadings (less than .35), we reanalyzed the data with 22 items. Using the scree plot, we explored four-factor, five-factor, and six-factor solutions. The final analysis suggested a five- factor solution as shown in Table 1. The five factors were interpreted as Lack of Skills and Knowledge (seven items; a = .87), Discrimination (five items; a = .66), Lack of Social Support (four items; a = .70), Linked Lives (i.e., responsibilities for marriage/family life; three items; a = .73), and Lack of Time and Financial Resources (three items; a = .70). Mean scores on each domain were used in the subsequent analysis. Higher scores indicated greater likelihood that participants perceived certain career-related barriers.
Results
Descriptive and subsequent analyses were performed using IBM SPSS Statistics for Windows (Version 24). Table 2 presents the means, stan- dard deviations, and zero-order correlation coefficients for the major study variables. For both FGC and non-FGC students, perceived career barriers for the domains lack of skills and knowledge and lack of social support were significantly and negatively related to career decidedness. For non-FGC students only, the domain of lack of time and financial resources was also negatively related to career decidedness. For demo- graphic variables, racial/ethnic minority status was related to greater levels of perceived discrimination for both FGC and non-FGC students. Additionally, racial/ethnic minority status was related to greater levels of perceived lack of social support and lack of time and financial resources for FGC students, whereas racial/ethnic minority status was associated with stronger perception of family responsibilities for non-FGC students.
To test Hypothesis 1, we conducted a multivariate analysis of covariance with five domains of perceived career barriers as the dependent variables, FGC student status as the independent variable, and demographic vari- ables (i.e., age, gender, and race/ethnicity) as covariates. We used Type III sums of squares because of unique cell sizes (Lewis & Keren, 1977). With the use of Wilks’s criterion, the analysis revealed an overall effect of FGC student status, F(5, 320) = 3.03, p = .011, partial h2 = .05, Λ = .96. Univariate analysis results revealed that with gender and racial/ethnic minority status controlled, FGC students scored significantly higher on
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Item
TABLE 1
Factor Analysis of the Perceived Career Barriers Measure
27. Lack of clear direction in life
24. Lack of motiva- tion in pursuing occupation
26. Lack of confidence in abilities
4. Lack of skills needed for the occupation
8. Lack of talent 17. Lack of
knowledge of work key steps
18. Unable to get into training program
7. Racial/ethnic discrimination
19. Sexual orientation discrimination
13. Religious discrimination
20. Health condition 2. Gender/sex
discrimination 16. Others’ disbelief
in my obtaining occupation
3. No support for my plans from friends
22. No support for my plans from parent(s)
10. No support of plans from my professor(s)
14. Getting married (currently or in future)
21. Having a child (currently or in future)
5. Family responsibilities
1. Money problems 9. Lack of money for
additional training 12. Time it will take to
finish additional training
Note. Factor loadings over .39 appear in bold. Eigenvalues for Factors 1–5 are 6.46, 2.12, 1.51, 1.35, and 1.14, respectively. Percentages of variance for Factors 1–5 are 29.39, 9.64, 6.88, 6.12, and 5.16, respectively. Factor 1 = Lack of Skills and Knowledge; Factor 2 = Discrimination; Factor 3 = Lack of Social Support; Factor 4 = Linked Lives; Factor 5 = Lack of Time and Financial Resources; P = pattern coefficient; S = structure coefficient.
.84
.81
.79
.72
.64 .63
.56
–.05
.07
–.15
.19 .00
.01
.11
.03
.18
.00
.13
–.25
–.08 .04
.24
h2 Factor 5
SP
Factor 4
SP
Factor 3
SP
Factor 2
SP
Factor 1
SP
.82
.80
.83
.76
.70 .72
.61
.24
.25
.12
.40 .26
.35
.41
.32
.40
.13
.20
.10
.30 .42
.40
–.04
.06
.03
–.11
.12 –.01
.01
.73
.71
.69
.66 .47
.04
.00
–.09
.04
–.06
–.04
.10
–.06 .01
.04
.25
.33
.34
.24
.37 .30
.25
.72
.64
.68
.70 .55
.33
.33
.21
.30
.24
.25
.40
.22 .31
.30
.00
.02
–.03
.19
.14 .18
–.20
.03
–.05
.12
–.07 –.09
.73
.69
.66
.56
–.04
–.08
.27
.07 .10
–.18
.33
.36
.34
.46
.44 .45
.12
.30
.21
.33
.27 .18
.75
.75
.65
.63
.15
.14
.40
.20 .28
.09
–.06
.01
.02
.09
–.04 –.01
.02
–.06
–.13
.14
–.02 .07
–.06
.06
–.03
.01
.91
.87
.60
–.03 –.13
.30
.10
.17
.21
.22
.15 .17
.17
.22
.11
.35
.25 .29
.15
.25
.14
.18
.87
.83
.70
.18 .13
.42
–.01
–.11
.08
–.05
–.07 .04
.30
.06
–.06
–.15
–.01 .25
.07
.00
.11
–.09
–.04
–.14
.18
.90 .86
.39
.32
.26
.42
.28
.26 .33
.50
.27
.16
.08
.27 .41
.23
.21
.23
.13
.17
.11
.33
.85 .87
.54
.67
.64
.70
.61
.53
.54
.48
.52
.44
.53
.51
.37
.57
.58
.44
.43
.76
.71
.61
.74
.79
.43
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the domains of lack of social support, F(1, 327) = 4.01, p = .046, partial h2 = .01, and lack of time and financial resources, F(1, 327) = 10.28, p = .001, partial h2 = .03. According to Cohen (1988), the effect sizes for these group differences were small (less than .01) to moderate (less than .06). The result indicates that the data partially supported Hypothesis 1.
To test Hypotheses 2 and 3, we ran a series of hierarchical multiple regression analyses. Prior to regression analyses, multivariate assumptions were checked on the basis of tests for normality of residuals, pairwise linearity, and leverage. On the basis of the means of Cook’s D (.003) and leverage (.027), no violation of assumptions of normality was found, and no cases that significantly influenced estimated parameters were found. In addition, we conducted a multicollinearity test based on variance inflation factor and tolerance to examine multicollinearity among the predictor variables. Results showed that the predictors used for the subsequent analyses, including two interaction terms, had no indication of multicollinearity (variance inflation factor less than 2.0 and tolerance greater than .52).
To test Hypothesis 2, we entered participant demographics (i.e., age, gender, and race/ethnicity) into the regression equation at Step 1, followed by participants’ FGC student status at Step 2. Then, the five domains of perceived career barriers were entered simultaneously at Step 3. Table 3 presents the results of the regression analyses. When demographic variables were entered into the equation at Step 1, none of the demographic variables except for students’ age significantly predicted students’ career decidedness. Age significantly and positively predicted career decidedness, B = .09, SE = .04, β = .11, p = .040, with older students having clearer decisions about their future career. When
TABLE 2
Means, Standard Deviations, and Intercorrelations Between Variables by First-Generation College Student Status
Variable
1. Age 2. Gendera
3. Racialb
4. CD 5. Skills 6. Support 7. Discrim 8. Linked 9. Time
M SD
4
Note. Below the diagonal are correlation coefficients, means, and standard deviations for first- generation college students (n = 149). Above the diagonal are correlation coefficients, means, and standard deviations for non-first-generation college students (n = 182). Racial = racial/ ethnic minority status; CD = career decidedness; Skills = lack of skills and knowledge; Support = lack of social support; Discrim = discrimination; Linked = linked lives; Time = lack of time and financial resources. aFor gender, 0 = male, 1 = female. bFor racial/ethnic minority status, 0 = nonminority, 1 = minority. *p ≤ .05. **p ≤ .01.
5 6 7 8 9 M SD3
— –.04 –.14 .12 –.04 –.01 –.05 .03 –.07
19.24 1.34
21
–.06 —
–.03 .23** .05 –.09 .07 .16 .19*
0.68 0.47
.00 .03
— –.03 .14 .19* .16* –.01 .18*
0.40 0.49
.10 –.04 .01
— –.28** –.16* –.12 .13 .10
3.59 1.07
.02 .15* .11 –.41**
— .63** .54** .21** .52**
2.39 0.89
–.04 .06 .07 –.21** .45**
— .45** .21** .29**
1.82 0.72
–.01 .20** .30** –.09 .24** .35**
— .38** .43**
1.67 0.63
.00 .10 .20** .08 .16* .26** .29**
— .30**
2.58 1.00
.06 .13 .13 –.21** .46** .31** .31** .25**
—
3.26 0.96
19.30 0.70 0.26 3.60 2.31 1.64 1.53 2.45 2.88
1.38 0.46 0.44 1.07 0.82 0.63 0.55 1.03 0.95
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the contribution of participants’ FGC student status was examined at Step 2, it did not predict the outcome variable significantly, B = .01, SE = .12, β = .00, p = .968. At Step 3, when perceived career-related barriers were added, results showed that participants who perceived greater likelihood of experiencing lack of skills and knowledge showed lower levels of career decidedness, B = –.52, SE = .08, β = –.41, p < .001. Participants’ perceptions of greater likelihood of experiencing linked lives also showed higher levels of career decidedness, B = .16, SE = .06, β = .15, p = .005. The result indicates that the data partially supported Hypothesis 2.
Finally, to further test Hypothesis 3, we added the interaction terms of FGC student status and each of the five domains of perceived career barriers at Step 4. The interaction terms were created by multiplying FGC student status as a categorical variable and each of the centered variables of the five domains of career barriers. Prior to regression analyses, all the continuous variables (i.e., perceived career barriers and age) were mean centered. Analysis with interaction terms revealed that
TABLE 3
College Students’ Career-Related Barriers Predicting Career Decidedness
Variable Step 1 Age Gendera
Racialb
Step 2 FGCc
Step 3 Skills Support Discrim Linked Time Step 4 FGC × Skills FGC ×
Support FGC ×
Discrim FGC × Linked FGC × Time
Constant F f 2
Note. Adj. = adjusted; Racial = racial/ethnic minority status; FGC = first-generation college student; Skills = lack of skills and knowledge; Support = lack of social support; Discrim = discrimination; Linked = linked lives; Time = lack of time and financial resources. aFor gender, 0 = male, 1 = female. bFor racial/ethnic minority status, 0 = nonminority, 1 = minority. cFor FGC, 0 = no, 1 = yes. *p ≤ .05. **p ≤ .01. ***p ≤ .001.
B SE β
.01
.01
.16***
.18*
Career Decidedness
Model 4
B SE β
Model 3
B SE β
Model 2
B SE β
Model 1Adj. ΔR 2
.09* .20 .00
.04 .13 .13
.11 .20 .00
.09* .20 .00
.01
.04 .13 .13
.12
.11 .09 .00
.00
.09* .24* .07
–.01
–.52*** –.02 –.07 .16** .10
.04 .12 .12
.11
.08 .10 .11 .06 .07
.11 .10 .03
–.01
–.41 –.01 –.04 .15 .09
.09* .23 .05
–.03
–.52*** –.09 –.05 .17** –.08
–.05 .16
–.10
–.02 .42**
.04 .12 .12
.11
.11 .14 .15 .08 .09
.17 .20
.22
.12 .14
.12 .10 .02
–.01
–.41 –.05 –.03 .16 –.07
–.03 .07
–.04
–.01 .26
3.45*** .11 2.17
3.45*** .12 1.61
3.41*** .12 7.75***
3.39*** .12 6.08*** 0.22
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the moderating effect of FGC student status on the association between lack of time and financial resources as the perceived career barrier and career decidedness was significant, B = .42, SE = .14, β = .26, p = .002. Figure 1 presents regression lines plotted based on the result of the regression analysis. Simple slope analysis suggested that the regression coefficient of the slope for FGC students was significant, B = .39, p = .001, whereas the coefficient of the slope for non-FGC students was not significant, B = –.03, p = .76. This result suggests that the positive relation between lack of time and financial resources as a career barrier and career decidedness exists only for FGC students. The result indicates that the data partially supported Hypothesis 3.
Discussion
We examined levels of FGC students’ perceived career barriers compared with those of non-FGC students. We also investigated the effect of FGC student status on the association between perceived career barriers and career decidedness. We hypothesized that FGC students would perceive more barriers than would non-FGC students. Our findings partially supported this hypothesis. Compared with their non-FGC student counterparts, FGC students scored significantly higher on two domains of perceived career barriers among the five domains that were examined: lack of social support and lack of time and financial resources for ad- vanced training in the process of exploring future careers. Our finding of greater levels of perceived career-related barriers for FGC students compared with non-FGC students is consistent with prior studies that reported differences in aggregated scores on perceived career-related barriers between the two groups of students. However, because most previous studies with FGC students did not use multiple domains of career-related barriers, this finding is valuable in better understanding
FIGURE 1
Moderating Effect of First-Generation College Student Status on the Association Between Lack of Time and
Financial Resources and Career Decidedness
= Non-first-generation college students = First-generation college students
–1 SD (–0.97) +1 SD (0.97) Lack of Time and Financial Resources
4.0 —
3.5 —
3.0 —
2.5 —
—
C a
re e
r D
e ci
d e
d n
e ss
—
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how FGC students and non-FGC students experience challenges in their career exploration and planning differently when multiple domains of career barriers are assessed.
As hypothesized, students who perceived greater levels of lack of skills and knowledge showed lower levels of career decidedness for their future occupations. Previous studies with college students have reported that perceived career-related barriers were negatively associated with career decision-making self-efficacy (Luzzo, 1996; Mejia-Smith & Gushue, 2017). It could be possible that, compared with FGC students’ percep- tion of contextual hindrances, their perception of internal hindrances such as lack of skills and knowledge may influence their efficacy more in dealing with tasks relating to career decision-making negatively. This may, in turn, lead to their lower levels of career decision-making.
Regarding differential effects of perceived career barriers on FGC students’ career decidedness, students’ perception of lack of skills and knowledge was negatively associated with career decidedness. In contrast, the greater levels of perceived influence of taking responsibilities for spouse and family members had a positive effect on career decidedness. Although such opposite effects of different domains of career-related barriers were unexpected, these findings suggest that the effects of perceived career barriers should not be understood simply as negative on students’ career outcomes. Rather, various domains of career barriers could have differential effects so that people’s perceptions of career barriers could function as adaptive or motivating factors under certain circumstances (Swanson et al., 1996).
The positive effect was also found for lack of time and financial re- sources as a barrier. When the moderating effect of FGC student status on the association between students’ perception of lack of time and financial resources as a barrier and career decidedness was examined, this barrier predicted career decidedness positively for FGC students, but not for non-FGC students. A majority of FGC students have multiple obligations outside of school, including family and work responsibili- ties (Engle & Tinto, 2008). Therefore, exploring career options with limited time and financial resources may be a common challenge, yet something that FGC students may be expected to overcome. In the present study, FGC students may have interpreted lack of time and financial resources as a challenging (but not threatening) context in that their levels of motivation increased for bettering their own and their family’s financial situations and moving forward by obtaining secure, well-paying jobs. Studying a sample of students at a German university, Hirschi et al. (2013) also found a positive effect of students’ perception of career barriers on proactive career behaviors (i.e., ca- reer engagement). These researchers explained the positive effect of perceived barriers by considering several factors, such as self-efficacy beliefs and motivation for pursuing career goals.
The negative and positive effects of perceived career barriers must be understood in relation to how individuals would interpret certain demands afforded by environments. As social cognitive career theory (Lent et al., 2000) describes, people may regard any given demand by an environment as a barrier, challenge, or opportunity, depending on how they perceive it. In the present study, FGC and non-FGC students’
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perceived career barriers were assessed with a list of short phrases (e.g., “discrimination because of my gender/sex,” “lack of money for further training/education,” “lack of confidence in abilities”). Therefore, there is much room for respondents’ various interpretations of those career barrier items. Additionally, how FGC and non-FGC students scored on perceived career barriers on the basis of their self-report was pos- sibly influenced by individual attributes, such as personality traits (e.g., optimism, proactivity, positive vs. negative affectivity, coping efficacy; Lent at al., 2000). These speculations, however, need to be empirically tested by future research.
Implications for Career Counseling Career counselors should understand that various types of career-related barriers might have differential effects on young people’s career decision- making, depending on students’ backgrounds, such as FGC student status, gender, race/ethnicity, personality traits, and cognitive style. It is imperative for career and guidance counselors not only to be aware of various types of career-related barriers perceived by students in general but also to understand that certain types of barriers have effects particu- larly on FGC students versus non-FGC students. Using opportunities to discuss perceived barriers with FGC students, career counselors could help FGC students gain knowledge and develop skills and abilities that would be effective in coping with the career-related barriers that these students perceive in exploring and obtaining occupations in the future.
A high school counselor could provide a similar socialization context for students through initiating a conversation about challenges and barriers that high school students may encounter in their vocational future and possible options and coping strategies to help them deal with these barriers. For FGC students, and first-generation high school students who make the transition from high school to college, such a conversation could help compensate for the knowledge and skills that these students may lack compared with non-first-generation students.
Similarly, FGC students could benefit through meeting with a career counselor or using various on-campus programs and workshops offered by the career center to develop skills and gain knowledge in exploring and preparing for their future occupations, which non-FGC students may be able to prepare for by means of their parents’ introduction to these skills and knowledge. To enhance FGC students’ perceived skills and knowledge to explore their career, we recommend that specific and concrete guidance be provided for these students in terms of skills and knowledge, such as how to approach professors for reference requests, how to network at career fairs, and how to discuss both the breadth and the depth of their education experience during job interviews. Career center staff, in creating such opportunities for FGC students, need to be sensitive to these students’ lifestyles. For example, in offering services, staff should keep in mind issues of work-family-school conflict that many FGC students contend with.
Limitations and Future Research We used a convenience sample with data collected at a private liberal arts university. Therefore, there is a lack of variability in the study par-
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ticipants’ demographic backgrounds (e.g., socioeconomic and racial/ ethnic backgrounds). With respect to participants’ academic standing, one half of the participants were first-year students, which could influence the levels of career decidedness reported by these students, particularly FGC students who perceived lack of time and financial resources for their career decision-making. Even though such students may have de- cided to pursue particular occupations, such decision-making, without developing specific academic skills and considering further training for occupations aspired to because of lack of time and financial resources, could be regarded as premature or as occupational foreclosure (Olson, 2014; Skorikov & Vondracek, 1998). Our study was cross-sectional, so causal relations between FGC student status, career barriers, and career outcome cannot be determined. Because we used similar items based on existing measures of career barriers, our results could be compared with those of previous studies. However, there may be challenges or barriers that are unique to FGC students (e.g., lack of understanding of academic life; Covarrubias & Fryberg, 2015), which we were not able to assess in this study. Additionally, the effect sizes of the significant results reported in this study were small or medium at most. Therefore, those results require readers’ special caution in considering the practical implications of the study findings.
Future research is needed to examine FGC students from various types of schools at different geographic locations to ensure study participants’ diverse backgrounds. In addition, studies are needed to explore career- related barriers that may be unique to FGC students, and researchers should consider investigating the differential effect of various types of career barriers on career outcomes. Finally, future research should examine how various barriers perceived by FGC students would influ- ence one another (e.g., lack of familial support leading to less use of campus resources).
Our study adds evidence to the current literature for the differential effect of perceived career barriers as contextual factors on the process of career decision-making for FGC and non-FGC students. Our findings also provide evidence suggesting the significance of understanding differential effects of various domains of perceived career barriers on FGC students’ career decision-making and other career outcomes. Further investigation of both overall and domain-specific effects of young people’s perceptions of career-related barriers could help career service providers to better support FGC students’ career development.
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