Abstract
The present study investigated the mediating role of career adaptability in the relationship between youth-perceived contextual support and positive youth development on the basis of a survey of 1,047 students in 10th to 12th grades. Measurement model analysis revealed that career search self-efficacy (CSSE), goal capacity, academic self-efficacy, and intrinsic motivation all fit within a latent construct representing career adaptability. Subsequently, structural model analysis revealed that career adaptability fully mediates the relationship between contextual factors and positive youth development. In addition, these analyses identified eight specific indirect pathways: CSSE and goal capacity fully mediated the relationship between quality learning experience/social connection and decision-making readiness; CSSE and academic self-efficacy partially mediated the relationship between social connection and stress management, and they also acted as suppressor in the relationship between quality learning experiences and stress management. These findings establish notable implications for career counseling and intervention practices that are discussed in closing.
Introduction
Adolescence is a key period for establishing both contextual and psychological resources that help individuals adapt to educational and vocational transitions (Lent & Brown, 2013; Leong & Ott-Holland, 2014; Savickas, 2005). Necessary contextual resources include defined concepts such as social support and access to quality learning experiences in families, schools, communities, and other services (Benson, Scales, & Syvertsen, 2011; Flum & Blustein, 2000; Kenny & Bledsoe, 2005). In terms of personal psychological resources, the less defined concept of career adaptability has been identified as an important psychological resource to develop for youth’s ability to exercise lifelong learning and to manage changing professional situations (Savickas et al., 2009; Savickas & Porfeli, 2012). The need to support the development of career adaptability is especially salient for contemporary youth, who no longer approach career development through a stable and linear process (Vuolo, Mortimer, & Staff, 2014).
In response to the changing world of work and the destabilization of careers, today’s youth are confronted with especially challenging postsecondary transitions and new demands regarding college and career readiness (Voulo et al., 2014). In China, the number of students illustrates the importance of addressing these challenges: There were 9.4 million high school graduates who participated in the national college entrance exam and 4.7 million secondary vocational school graduates who applied for jobs in 2017 (Ministry of Education of the People’s Republic of China, 2017). These youth are navigating challenging transitions with limited and outdated career guidance in secondary schools. In addition, China is currently implementing a national educational reform (i.e., Gaokao reform), which aims to provide youth with even more opportunities to select learning subjects and to explore interests related to future major and career choices. More evidence-based interventions and career counseling practices are required to support youth self-exploration, career exploration, and career planning. Within this set of circumstances, it is crucial to identify contextual and psychological resources that affect positive youth development and encourage college and career readiness.
The present study was developed to investigate the degree to which contextual influences can predict positive youth development through career adaptability. Supportive environments—families, schools, peer relationships, and extracurricular activities—have been effective predictors of youth ability to improve career adaptability competence (Creed, Fallon, & Hood, 2009; Han & Rojewski, 2015; Hirschi, 2009; Kenny & Bledsoe, 2005; Yuen & Yau, 2015). In addition, career adaptability has been demonstrated to mediate the relationship between one’s perceived social support and his or her reported career concern (Creed et al., 2009), job satisfaction (Han & Rojewski, 2015), and career decision-making difficulty (Li, Hou, & Feng, 2013). Career adaptability has also been associated with some positive youth development indicators, including life satisfaction, sense of power, academic achievement, and career decidedness (Ginevra, Pallini, Vecchio, Nota, & Soresi, 2016; Hirschi, 2009; Negru-Subtirica & Pop, 2016; Santilli, Marcionetti, Rochat, Rossier, & Nota, 2017).
Career Adaptability
Developmental models of career choice and decision making have advanced educators’ understanding of the greater significance of “adaptability”—as a development asset—compared with career maturity (Savickas, 1997; Super & Knasel, 1981). Whereas the category of career maturity emphasizes one’s clear understanding of, and commitment to, a specific career choice (Crites, 1973; Super, 1957), adaptability denotes the malleable transactional resources and competencies that are needed for individuals to cope with more general tasks, transitions, and traumas (Savickas, 1997, 2005).
Savickas outlined four “Cs” that constitute an individual’s degree of career adaptability: career concerns, reflected in an awareness of the importance of future planning; career control over one’s vocational behaviors and decisions; career curiosity regarding knowledge of the self and the world of work; and career confidence, which denotes the ability to execute a course of vocational actions and to make career choices (Savickas & Porfeli, 2011). Rottinghaus, Day, and Borgen (2005), Rottinghaus, Buelow, Matyja, and Schneider (2012), as a complement to Savickas’ four “Cs,” described a model of career adaptability as one’s perceived capacity to plan and cope with a changing future, new work responsibilities, unforeseen events, as well as to assert one’s career agency (i.e., self-awareness, control, self-efficacy) and utilize his or her relational support. Creed et al. (2009) described career adaptability using Savickas’ earlier outline of five adaptability components: career planning, self-exploration, career exploration, decision making, and self-regulation (Savickas, 1997). These career adaptability models all addressed issues of preparing individuals for their career decision-making.
We propose an extended multidimensional career adaptability model. Our youth career adaptability model focuses specifically on malleable and transferrable skills with clear value for school-based efforts to promote positive youth development. This model conceptualizes youth career adaptability as a multidimensional capacity that is represented by the self-efficacy to perform career search activities, set and pursue goals, perform academic-related tasks, as well as by the intrinsic motivation for attending school (Baltes, 1996; Bandura, 1977; Deci & Ryan, 2000; Rottinghaus et al., 2012; Solberg, Good, Nord, Holm, et al., 1994). This model also utilizes the perspectives of multiple developmental psychology theories, including Bandura’s (1977) social cognitive theory (SCT), Deci and Ryan’s (2000) self-determination theory (SDT), and Baltes’ (1996) theory of selection, optimization, and compensation (SOC).
The proposed career adaptability model extends previous models in several complementary ways. First, it reflects a transition from a decision-making perspective to a developmental perspective, which, in turn, facilitates an emphasis on the theory of change and a related focus on assisting youth, so that they can thrive academically and prepare to face professional changes and transitions. Second, the constructs we included highlight specific malleable skill sets that practitioners and counselors can address in their career counseling services and interventions. And finally, although previous research has addressed confidence and curiosity in general (Rottinghaus et al., 2012; Savickas & Porfeli, 2011), this career adaptability model considers confidence and curiosity related to academic skills; we looked, specifically, at academic self-efficacy and intrinsic motivation for attending school, which are two key noncognitive academic competencies for youth to perform active learning, exploration, planning, and coping with challenges or changes. Youth with a higher degree of confidence in performing academic tasks and a higher degree of inquisitiveness about academic and vocational knowledge are more likely to achieve postsecondary success (Solberg, Howard, Gresham, & Carter, 2012). This is especially true in the Chinese educational context, where academic performance determines students’ eligibility for university and their major choices.
Self-efficacy
Measurements of self-efficacy—one’s perception of his or her capacities to organize and execute actions toward desired goals (Bandura, 1986)—typically utilize Bandura’s SCT, according to which career adaptability is fluid and subject to constant social learning and support (Lent & Brown, 2013). In this approach, self-efficacy includes content that reflects career confidence and career agency (Rottinghaus et al., 2012; Savickas & Porfeli, 2011). When youth apply self-efficacy to their career search process, it is called career search self-efficacy (CSSE); this specifically denotes an individual’s expectations and confidence regarding his or her ability to perform various career search activities, including personal exploration, career exploration, career planning, interviewing, and networking (Solberg, Good, Nord, Holm, et al. 1994; Solberg, Howard, Gresham, & Carter, 2012). Although self-exploration, career exploration, and career planning are commonly recognized dimensions of career adaptability in models that follow Savickas’ and Creed’s research (Creed et al., 2009; Savickas, 1997), CSSE is especially pertinent to youth who perform important activities associated with education and career exploration and planning (Solberg, Good, Fischer, Brown, & Nord, 1995; Solberg, Good, & Nord, 1994).
When youth apply self-efficacy to academic activities, it is called academic self-efficacy. High school youth’s educational attainment is fundamental to youth career preparation (Negru-Subtirica, Pop, & Crocetti, 2015; Vuolo et al., 2014). Those with higher academic performance and greater confidence in their academic abilities are more likely to perform successfully in their postsecondary education, make effective school-to-work transitions, and commit to careers that match their education (Savickas, 2005; Vuolo et al., 2014). Kenny and Bledsoe (2005) already have highlighted the importance of including educationally relevant components in attempts to measure career adaptability; the present study identifies academic self-efficacy as one of the prominent components of youth career adaptability, defined as the confidence youth have in their capacities to perform academic tasks in the classroom, on tests, in peer interactions, and in research.
Goal capacity
Explicit goals are critical for youth to gain direction and form self-regulatory behaviors (Lent, Brown, & Hackett, 1994), thereby driving individuals’ goal-directed efforts toward positive adaptation to challenges and changes (Creed, Buys, Tilbury, & Crawford, 2013). According to SOC theory, youth need to actively select personal goals, optimize adaptive capacities to attain desirable outcomes, adapt to constraints, and compensate for failed experiences when faced with educational and vocational transitions (Baltes, 1996; Salmela-Aro, 2009). This study highlights youth capacities for setting and pursing goals, acts which correspond to career concern (i.e., career planning) and career control in previous models (Creed et al., 2009; Rottinghaus et al., 2012; Savickas & Porfeli, 2011).
Intrinsic motivation
Finally, SDT addresses the role of intrinsic motivations in shaping individuals’ self-regulation (Ryan & Deci, 2000) and increasing their career adaptability (Duffy & Blustein, 2005; Ye, 2015). Close and Solberg (2008) demonstrated that intrinsic motivation (e.g., “because I enjoy school,” “because education is import to the goals I have”) is a critical resource for youth to utilize in achieving academic success, coping with distress, and preparing for postsecondary transitions. This study proposed that intrinsic motivation for attending school (i.e., I enjoy school, recognize the meaning of school) constitutes another major dimension of youth career adaptability. It reflects the dimension alternately covered by Savickas’ curiosity and Rottinghaus’ highlights of basic needs of autonomy (Rottinghaus et al., 2012; Savickas & Porfeli, 2011).
Contextual influences
Figure 1 presents the proposed relationship between career adaptability, contextual factors, and positive youth development. It is proposed that youth who perceive their learning experiences and social connections positively are likely to develop better career adaptability and, in turn, better engage in decision making and stress management. Youth naturally look to their schools, families, and friends for support and guidance when they perform career exploration actions and face professional challenges and changes (Flum & Blustein, 2000; Kenny & Bledsoe, 2005). Multiple international studies including research done in Australia, Switzerland, China, Korea, and the United States (Creed et al., 2009; Han & Rojewski, 2015; Hirschi, 2009; Kenny & Bledsoe, 2005; Yuen & Yau, 2015) have established that social connections (i.e., social connectedness, social support) are effective predictors of career adaptability. This study also investigated the degree to which students were engaged in quality learning experiences described in the Guidepost for Success, a national transition framework initiated by the National Collaborative for Workforce and Disability for Youth (NCWD-Youth). The framework describes five areas of learning experiences that provide theoretical support for promoting positive youth development (Solberg, Howard, Gresham, & Carter, 2012): (a) school-based preparatory experiences, (b) career preparation and work-based learning experiences, (c) youth development and leadership, (d) connecting activities, and (e) family involvement and support (NCWD-Youth, 2009).
Structural model of contextual influences predicting positive youth development through career adaptability.
Positive youth development
According to the American School Counseling Association’s (ASCA’s) national model (ASCA, 2015), school counselors should focus on three domain areas—academic, career, and social/emotional development—to promote students’ positive growth through designing, implementing, and evaluating programs. Unlike the traditional “problem-centered” youth development approach, positive youth development focuses on proactive learning and thriving across contexts (Larson, 2000; Zarrett & Lerner, 2008). Career adaptability can predict positive youth development, as demonstrated by its effects on sense of power, life satisfaction, academic achievement, and decidedness (Ginevra et al., 2016; Hirschi, 2009; Negru-Subtirica & Pop, 2016; Santilli et al., 2017). Although a variety of outcomes that are predicted by contextual factors and career adaptability have been explored, few studies have discussed the significance of youth readiness in making educational and vocational choices and developing youth stress resilience (Rottinghaus et al., 2012; Rudolph, Lavigne, & Zacher, 2017; Walsh & Savickas, 2016). The present study examined career decision-making readiness and stress management that reflect the social/emotional development and career development described by ASCA. Academic development was not examined due to confidentiality concerns of releasing students’ grades.
The present study
This study builds on previous research in three ways: (a) It extends existing career adaptability models into a model that is appropriate to apply to today’s high school–aged youth and inform school-based career counseling and intervention practices, (b) it highlights the mediation role of career adaptability in linking contextual influences and positive youth development, (c) given the size of China’s youth population and its unique educational context, an investigation of Chinese youth significantly extends the reach of previous studies.
Method
Participants
The present study is based on a survey of Chinese high school students. The sample consisted of 1,047 students enrolled in 10th grade (71.3%), 11th grade (18.4%), and 12th grade (10.2%). The sample was comprised of 494 males (47.2%) and 553 females (52.8%) enrolled in four urban high schools in an eastern–central coastal province of mainland China, Jiangsu, which is a province with second highest GDP in 2017.
Measures
Participants completed a series of web-based measurements of eight specific categories: (a) Quality Learning Experiences, (b) Social Connections, (c) CSSE, (d) Goal Setting, (e) Motivation for Attending School, (f) Academic Self-Efficacy, (g) Career Decision-Making Difficulty, (h) Stress. All scales were translated from English and adopted into the Chinese context using a back translation approach by a group of four researchers from both the United States and China. To establish the face validity of each of the translated scales, two focus groups were conducted with groups consisting of eight Chinese high school students each. In addition, pilot study data gathered from 258 students in 10th and 11th grades were used for a series of exploratory factor analyses—utilizing maximum likelihood extraction method and oblique rotation to—select and modify scale items. Only items with loadings larger than 0.40 were considered for further analysis (Thompson & Daniel, 1996). Items with loadings greater than 0.32 across more than one factor were reviewed and rephrased, or excluded for further analysis, due to interpretational reasons (Tabachnick & Fidell, 2007).
Measures of contextual factors
Quality Learning Experiences Scale
The Quality Learning Experience Scale (Solberg, Howard, Gresham, & Carter, 2012) consists of 45 items that were based on the five categories of youth postsecondary transition described in the Guidepost for Success (NCWD-Youth, 2009). Higher scores indicate greater perceived access of quality learning experiences (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). Through the pilot study, 30 items were selected and grouped into five similar subscales: Education and Career Exploration, Extracurricular/Youth Leadership, Connecting Activity, Caring Adults Engagement and Support, and In-School Career Development Activities. Cronbach’s alpha ranged from .80 to .92.
Social Connections Scale
The Social Connections Scale (Close & Solberg, 2008) consists of 18 items that measure one’s connection to families, teachers, and peers. Higher scores indicate a higher degree of perceived connections to families, teachers, and peers (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). Each of the 18 items was selected for inclusion based on the pilot study through which three subscales were identified: Family Connection, Teacher Connection, and Peer Connection. Cronbach’s alpha ranged from .86 to .90.
Measures of career adaptability
Career Search Self-Efficacy Scale
The Career Search Self-Efficacy Scale (Solberg, Good, Nord, Holm, et al., 1994) consists of 34 items that measure one’s confidence in his or her capacities to successfully perform various career-search activities. Higher scores indicate one’s greater belief in his or her ability to perform career-related searching tasks (1 = not confident at all, 2 = not too confident, 3 = neutral, 4 = somewhat confident, 5 = very confident). Through the pilot study, 26 items were selected and four subscales were identified: Self-Exploration, Career Exploration, Career Planning, and Networking. Cronbach’s alpha ranged from .90 to .95.
Goal Capacity Scale
The Goal Capacity Scale (Howard, Ferriari, Nota, Solberg, & Soresi, 2009) is a 19-item instrument developed based on Baltes’ SOC model (Baltes, 1996). It measures the degree to which students select and establish goals, optimize their educational and occupational activities to reach these goals, and identify obstacles that may impede their goal pursuits (Solberg, Howard, Gresham, & Carter, 2012). Higher scores indicate a respondent’s greater capacity to set and pursue goals (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). Through the pilot study, 17 usable items were identified and—for the purposes of this study—13 items from the Goal Setting and Goal Pursuit subscales were selected for inclusion in the proposed model. Cronbach’s alpha was .92 and .90.
Academic Self-Efficacy Scale
The Academic Self-Efficacy Scale (Solberg et al., 1998) consists of 25 items that measure the degree of confidence that respondents have in their ability to perform a variety of academic and school-related tasks. Higher scores indicate a greater degree of confidence that an individual can successfully perform activities associated with being a student at school (1 = not confident at all, 2 = not too confident, 3 = neutral, 4 = somewhat confident, 5 = very confident). The pilot study used 20 items and identified four subscales for use in the study: Social Tasks, Class and Test, Peer Interaction, and Information Search. Cronbach’s alpha ranged from .84 to .92.
Motivation for attending school
The Academic Motivation Scale (Close & Solberg, 2008) consists of 14 items that assess students’ reasons for attending school. Higher scores indicate a greater motivation to attend school due to students’ deeming it enjoyable and meaningful (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). All 14 items were kept through the pilot study—for the purposes of this study—only nine items from the subscales Enjoy School and Recognize the Meaning of School were utilized as the subscale External Motivation was eliminated. Cronbach’s alpha was .86 and .90.
Measures of youth development outcomes
Stress
The Stress Scale (Solberg, Hale, Villarreal, & Kavanagh, 1993) is a 22-item scale that measures how often an individual has experienced stress during the past month. Higher scores indicate higher self-reported levels of stress (1 = never, 2 = rarely, 3 = sometimes, 4 = very often, 5 = always). The pilot study selected 17 items and identified three subscales to use in the final study: Social Stress, Financial Stress, and Academic Stress. Cronbach’s alpha ranged from .87 to .93. The scale was then reverse coded so that the same data could be used to reflect youth stress management.
Career Decision-Making Difficulty Scale
The Career Decision-Making Difficulty Scale (Nota, Soresi, Solberg, & Ferrari, 2005) consists of 16 items that measures whether a student is ready for, and engaged in, making educational and vocational choices. Higher scores indicate a greater level of decision-making difficulty that indicates an individual’s lack of readiness for making career decisions (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). All the 16 items were selected from the pilot study and three subscales were identified: Indecisive, Undecided, and Lack of Information. Cronbach’s alpha ranged from .89 to .91. This scale was reverse coded so that the same data could be used to reflect youth’s career decision-making readiness.
Data analytic procedure
Data were analyzed in two stages: a measurement model analysis stage and a structural model analysis stage (Anderson & Gerbing, 1988). All analyses in the present study were carried out using the STATA 14.0 statistical program.
Measurement model analysis
Confirmatory factor analyses (CFAs) were employed for our measurement model analysis; this approach best served our goal of examining the predetermined factor structure of eight scales for a sample of Chinese high school youth. We conducted two CFAs of the data. The first CFA model focused on verifying scale constructs. A simultaneous CFA model was conducted that included all eight latent constructs in one model. The model parceled items and utilized unit-weighted total score of each subscale to reduce computational difficulty and facilitate interpretation of the latent construct (Gorsuch, 1983; Thompson, 1990). The second CFA model focused on a higher level career adaptability construct. Using parceling items, the proposed four dimensions CSSE (i.e., self-exploration, career exploration, career planning, networking), goal capacity (i.e., goal setting, goal pursuit), academic self-efficacy (i.e., social task, class and test, peer interaction, information search), and intrinsic motivation for attending school (i.e., enjoy school, recognize the meanings of school) were mapped onto a second-order latent construct of career adaptability. Chi-square statistic along with its degree of freedom and p value as well as other fit indices less affected by sample size and model misspecification were assessed to evaluate the overall degree of model fit (Hooper, Coughlan, & Mullen, 2008; Hu & Bentler, 1999; Martens, 2005): root mean square error of approximation (RMSEA < 0.08 acceptable, <0.05 excellent; Browne & Cudeck, 1993), Tucker–Lewis index (TLI > 0.90 acceptable, >0.95 excellent; Tucker & Lewis, 1973), the comparative fit index (CFI > 0.90 acceptable, >0.95 excellent; Bentler, 1990), and standardized root mean square residual (SRMR < 0.08 acceptable, <0.05 excellent; Hu & Bentler, 1999).
Structural model analysis
We conducted mediation analyses using structural equation modeling (SEM) approach. SEM is generally superior to the multiple regression approach in the context of mediation analysis because it simplifies classic multistep analysis (Baron & Kenny, 1986) and considers a variety of data with greater sophistication by allowing a mediation model to function with multiple mediators (Gunzler, Chen, Wu, & Zhang, 2013; MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002). SEM addresses mediation analysis by testing indirect effects that reveal the difference between total effect and the direct effect; this directly addresses the nature of mediation—how the predictor variable influences the outcome variable through the mediator. Therefore, SEM yields a higher level of statistical power, without increasing the Type I error rate, than the complicated multiple mediation models. In the present study, the direct and indirect effects were estimated using the default maximum likelihood in SEM analysis. Standard errors and confidence intervals (CIs) were obtained through a bootstrapping resampling approach; bootstrapping is free from the unrealistic normality assumption, maintains better control over Type I error, and it is especially powerful for assessing and comparing indirect effects in a multiple mediator model. A single, simple-to-use SEM and resampling method allow researchers to obtain total indirect effect that shows the degree to which the hypothesized mediating variables mediate the relationship between predictor and outcome variables, as well as allow researchers to compare relative magnitudes of each specific indirect effect that is associated with each of the mediators in a model (Preacher & Hayes, 2008).
Reflecting the analytical methods described above, the first mediation model directly incorporated three latent constructs into one single analysis that addressed the role of career adaptability in mediating the relationship between contextual influence and positive youth outcome (Martens, 2005). Quality learning experience and social connections were two indicators of exogenous latent variable contextual influence; stress management and decision-making readiness served as two indicators of endogenous latent variable positive youth development; CSSE, goal capacity, academic self-efficacy, and intrinsic motivation served as four indicators of the latent mediator variable career adaptability. To further explore the theoretical importance of specific mediator variables in explaining the relationship between exogenous and endogenous variables, the second mediation analysis used SEM for a path model to test the ways in which four endogenous mediator variables (i.e., CSSE, goal capacity, academic self-efficacy, and intrinsic motivation) link two exogenous predictor variables (i.e., quality learning experience and social connection) and two endogenous outcome variables (i.e., stress management and career decision-making readiness). The residuals associated with the four mediators were allowed to covary, and errors of two endogenous outcome variables were allowed to covary as well (Acock, 2013; Preacher & Hayes, 2008). Both the mediation models utilized aggregate scores of the eight scales. The same goodness-of-fit indices described in the CFA method were utilized to decide to what extent the proposed structural model accurately represents the data.
To examine the indirect effects, the present study estimated standard errors and implemented 95% bias-corrected CIs for all direct and indirect estimates. Specifically, we requested 1,000 replications from the analysis tool and obtained normal-based bootstrapped CIs around the indirect effect (MacKinnon, Lockwood, & Williams, 2004). A mediation effect occurs when the indirect effect is significant and the 95% CIs of the indirect effect via the mediator do not include zero (MacKinnon et al., 2002).
Results
Table 1 presents the means and standard deviations of all measures as well as the correlations among them. All measures were significantly correlated with each other.
Means, Standard Deviations, Internal Consistency Coefficients, and Goodness-of-Fit Indices for Eight Chinese Scales.
Note. QLE = Quality Learning Experience; SC = Social Connections; CSSE = Career Search Self-Efficacy; ASE = Academic Self-Efficacy; IM = Intrinsic Motivation; SM = Stress Management (reverse coded from stress); DMR = Decision-Making Readiness (reversed coded from decision-making difficulty).
p < .05.*p < .01. ***p < .001.
CFA Measurement Model Statistics
The first CFA model fit results verified the quality of each scale and the model yielded significant standardized factor loadings within the range .69 to .96 and excellent model fit indices: χ2(267) = 1,156.34, p < .001, RMSEA = 0.06, CFI = 0.95, TLI = 0.94, SRMR = 0.03.
The results of the second-order CFA of career adaptability measurement model indicated that four first-order factors and one second-order factor exhibit an excellent estimation of the factor structure presented in the data: χ2(47) = 345.04, p < .001, RMSEA = 0.08, CFI = 0.97, TLI = 0.96, SRMR = 0.04. All standardized loading coefficients were significant as they fell within the range .67 to .94. The CFA test confirmed the validity of the second-order career adaptability construct in which the four proposed components (i.e., CSSE, goal capacity, academic self-efficacy, intrinsic motivation) mapped onto one factor, namely, that which has been conceptualized as career adaptability.
Structural Model Statistics
Mediation effect of the latent variable career adaptability
Quality learning experience and social connection were treated as two exogenous variables that predict two endogenous variables stress management and career decision-making readiness whereas the second-order career adaptability was treated as the mediator. Age and gender exhibited only weak correlations with career decision-making readiness and stress management (
Specifically, contextual factors had a significant effect on career adaptability (β = .86, p < .001), which, in turn, directly predicted positive youth development (β = .65, p < .001). Contrarily, when the mediator variable career adaptability was included, contextual factors did not directly predict positive youth development (β = .01, p = .95). When career adaptability was excluded from the model, the total effect of the contextual influences on the positive youth development turned to be significant (β = .57, p < .001). Therefore, the results of our study show a significant indirect effect with a 95% CI not containing zero ([0.23, 0.48]) of contextual influences on positive youth development (β = .56, p < .001).
Mediation effect of each career adaptability dimension
To understand the mechanism of the specific mediation effect, the present study tested the hypothesized path model shown in Figure 2. When all paths were included, five direct paths were identified as nonsignificant and excluded as their standardized path coefficients for the total effects were close to zero and their p value was larger than .05: two paths toward stress management from goal capacity and intrinsic motivation; three paths toward decision-making readiness from academic self-efficacy, intrinsic motivation, and social connection.
Specific mediation effects of four career adaptability dimensions.
The final model (see Figure 2) generated an excellent fit to the data: χ2(5) = 11.04, p = .051, RMSEA = 0.03, CFI = 0.99, TLI = 0.99, SRMR = 0.02. All standardized regression weights were significant and fell within the range −.09 to .45, except the direct effect of quality learning experience to decision-making difficulty (β = −.04, p = .32). This final model explained a moderate amount of variance in the variables (CSSE = 45.19%, goal capacity = 49.92%, academic self-efficacy = 37.68%, intrinsic motivation = 35.18%, stress management = 24.50%, and decision-making readiness =17.98%).
Table 2 shows the direct, indirect, and total effects of the final model. Three of the four career adaptability variables functioned as significant mediators, which were affected by both perceived social connection and quality learning experience; only CSSE and goal capacity directly affect youth career decision-making readiness; and, only CSSE and academic self-efficacy directly affect youth stress management. Specifically, CSSE and goal capacity fully mediated the relationship between quality learning experiences and decision-making readiness, as indicated by the significant indirect effect (β = .21, p < .001, 95% CI = [0.13, 0.19]), the insignificant direct effect (β = −.04, p = .24, CI = [−0.12, 0.03]), and the significant total effect (β = .16, p < .001, CI = [0.07, 0.17]). CSSE and goal capacity also fully mediate the relationship between social connection and decision-making readiness, as indicated by the significant indirect effect (β = .15, p < .001, CI = [0.14, 0.23]), the removed insignificant direct effect (β = .06, p = .16, CI = [−0.02, 0.14]), and the significant total effect (β = .15, p < .001, CI = [0.14, 0.23]). Furthermore, CSSE and academic self-efficacy partially mediate the relationship between social connections and stress management as indicated by a significant indirect effect (β = .16, p < .001, 95% CI = [0.12, 0.20]), a reduced but statistically significant direct effect (β = .21, p < .001, CI = [0.13, 0.30]), and a significant total effect (β = .37, p < .001, CI = [0.31, 0.44]). In addition, this model revealed the presence of a suppression effect that the association between quality learning experience and stress management was suppressed by CSSE and academic self-efficacy, with significant direct (β = −.09, p = .039, CI = [−0.18, 0.01]) and indirect effects (β = .14, p < .001, CI = [0.06, 0.11]) in completely opposite signs and, thus, altogether canceled out the total effect β = .05, p = .280, CI = [−0.02, 0.08]; MacKinnon, Krull, & Lockwood, 2000; Tzelgov & Henik, 1991). As a result, eight significant indirect pathways were identified. Results showed that all eight indirect pathways were significant with standardized coefficients ranging from .05 to .15 that denoted different degrees of indirect effect for those pathways (see Table 2).
Path Estimates, SEs, and 95% CIs for Contextual Influences Predicting Positive Youth Development Outcomes Through Four Career Adaptability Mediators, With and Without Mediator.
Note. CI = confidence interval; CSSE = career search self-efficacy; QLE = quality learning experience; ns = nonsignificant.
Maximum likelihood estimates.
1,000 bootstrapped samples.
p < .05. **p < .01. ***p < .001.
Discussion
The objective of this study is to understand the career development of high school youth in China by examining the construct of career adaptability, its influential factors, and its pathways toward positive youth development. With respect to measurement properties, the present study found that four key capacities (i.e., CSSE, goal capacity, academic self-efficacy, and intrinsic motivation for attending school) map onto one construct of career adaptability, which is conceptualized as a youth’s regulatory abilities and inner resources for coping with changing situations both inside and outside of his or her school. This finding establishes the validity of an extended conceptualization of career adaptability by focusing on how the construct can be applied within school-based intervention and program design.
The multi-dimensional career adaptability construct allows us to build a structural model that can identify the mediation effects of the four career adaptability variables in the relationship between contextual influences and positive youth development. Results of this single structural model showed that the relationship between contextual influence and positive youth development can be mediated by the latent mediation variable: career adaptability. Furthermore, results of the test of eight specific indirect pathways provide new insights regarding how each of the four career adaptability dimensions (i.e., CSSE, goal capacity, academic self-efficacy, intrinsic motivation) functions as a significant and distinct mediator in the relationship between contextual factors and positive youth development.
Only CSSE and goal capacity mediate the relationship between contextual influences and youth career decision-making readiness. Youth who received greater quality learning experience and greater social connections are more likely to be prepared in making decisions. This is largely because perceived quality learning experiences are important for developing one’s confidence in executing career search activities related to self-exploration, career exploration, career planning, networking, and developing one’s abilities in setting and pursuing goals, which, in turn, make one become decisive in his or her educational and career choices. In addition, our study demonstrates that only CSSE and academic self-efficacy mediate the relationship between Chinese adolescents’ perceived contextual influences and stress management. Youth who received more positive social connections were less likely to suffer from stress. That is largely because the perceived social connections are important for one to build confidence in his or her career search abilities as well as abilities to perform academic tasks; this confidence, in turn, promotes the development of stress management strategies that help students to experience less stress. Furthermore, a suppression type of mediation effect was found in the relationship between quality learning experiences and stress management, in which CSSE and academic self-efficacy act like suppressors. Although we hypothesized that quality learning experiences would be associated with greater stress management, this interesting finding indicates that Chinese youth who have access to a variety of learning experiences, yet who are unable to develop CSSE and academic self-efficacy, are at risk of more stress. By developing higher academic confidence and education/career search confidence, counselors and administrators can help youth become more resilient to stress and maximize the effectiveness of social connections and quality learning experiences.
Practical Implications
The career adaptability model and the mediation models tested in this study, treated as empirical evidence, generate valuable implications for secondary practitioners to use as they design career interventions, programs, and counseling services that will help build greater CSSE, goal capacity, academic self-efficacy, and intrinsic motivation in high school youth. First, this study highlighted the need to incorporate strategies that make ongoing efforts to strengthen the quality of connections that youth develop with their family, educators, and peers as well as to encourage creating environment for quality learning experiences that youth receive both in and out of school. The study findings also indicate that there is a notable group of youth for whom access to quality learning experiences and social connections is not enough to achieve positive youth development outcomes. For these youth, it is important to consider personalized and differentiated career development interventions (Solberg, Howard, et al., 2012; Solberg, Phelps, Haakenson, Durham, & Timmons, 2012). Therefore, parents, families, and peers need to focus on improving malleable inner resources highlighted by the present study such as self-efficacy, goal capacity, and intrinsic motivation as a part of their typical support to improve youth career adaptability and strengthen positive development outcomes. This is especially important for minority and/or at-risk youth, who should be researched as research participants of future studies of career adaptability.
According to different magnitudes of the eight indirect effects showed in Table 2, CSSE and academic self-efficacy play greater mediating roles than goal capacity. Therefore, interventions may start with self-efficacy for favorable outcomes (Chen & Solberg, 2017). For example, future interventions and curriculum designs could be adapted to reflect the four sources of individuals’ sense of self-efficacy: personal mastery experiences, vicarious experience, social persuasion, and emotion arousal (Bandura, 1977, 2012; Pajares, 2002). Although intrinsic motivation is not identified as a significant mediator in the present study, practices and future research should continue exploring intrinsic motivation because it is a construct associated with other three career adaptability dimensions.
In addition, the present study provides insights that Chinese practitioners and policy makers can use to assist students who are going through high school during periods of education reform (i.e., Gaokao reform). The majority of existing Chinese studies have focused on college students who immediately face school-to-work and life transitions (Guan et al., 2013; Hou & Liu, 2014; Yuen & Yau, 2015). Understanding the pathways through which current Chinese high school–aged youth develop stress and indecision would increase the understanding of why particular problems happen, as well as the ways in which evidence-based programs can tackle these problems.
Limitation and Future Research
There are some limitations associated with this study that need to be taken into account when interpreting and drawing conclusions from the results. First, the results of mediation effects relied on cross-sectional self-report data, which have been criticized as an unconvincing way to make causal statements (Maxwell, Cole, & Mitchell, 2011). Second, the number of 10th-grade participants (71.3%) is much larger than 11th-grade (18.4%) and 12th-grade (10.2%) participants mainly due to senior students’ tight schedules for the national college entrance examination preparation. This will not affect the reliability but may affect the generalizability of our model. Finally, although we followed steps strategically designed for measurement translation and revision, the validity and reliability of Chinese version scales need to be further tested through the use of larger and more representative populations.
With these limitations in mind, we suggest that future researchers may extend this study through the following investigations. First, researchers may look at contextual factors separately to get a more in-depth understanding of the way in which contextual factors generate impacts. For example, they should examine how each of the social connections between students and their teachers, families, and peers plays a role in affecting youth career adaptability and positive youth development. Second, gender, grade, and other demographic variables need to be further studied, to reveal the underlying mechanism of how they may serve as a moderator in the mediation model. In addition, a follow-up cross-cultural comparison study may determine whether the present model can be applied across cultures and aide researchers’ efforts to understand the underlying cultural and societal basis in youth career development and youth career adaptability. More important, future research needs to examine the expanded self-regulatory career adaptability model longitudinally both to capture youth development changes over time more accurately and to demonstrate the causal relationship between contextual factors and positive youth development through career adaptability more effectively.
Conclusion
The present study provides strong evidence that youth career adaptability is a multidimensional construct that can be represented by four malleable self-regulatory capacities: CSSE, goal capacity, academic self-efficacy, and motivation for attending school. This study also demonstrated that career adaptability serves as an important mediator in the pathways from youth’s perceived contextual influences to positive youth development. The distinct mediating roles of the four representative dimensions reveal eight significant indirect pathways from youth access to social connection and quality learning experiences to youth stress management and decision-making readiness. These findings contribute to existing Chinese and international literature that has explored the youth career adaptability model and the mediating roles played by multiple dimensions of career adaptability and the pathways between contextual influences and youth development outcomes. The findings also provide implications for educators, school counselors, parents, and policy makers who seek to promote positive youth development through intervening contextual factors and career adaptability competencies.
Footnotes
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.