Adolescents’ Family Socioeconomic Status,Teacher–Student Interactions,and Career Ambivalence/Adaptability: A Three-Wave Longitudinal Study

Abstract

Using three-wave longitudinal data, this study tested the potential mediating roles of teacher–student relationship quality and teachers’ career support efficacy in the association between Chinese adolescents’ family socioeconomic status (SES) and career development (N = 1410). Results showed that adolescents’ family SES at Wave 1 was negatively associated with their career ambivalence at Wave 3 via positive associations with both teacher–student relationship quality and teachers’ career support efficacy at Wave 2. Moreover, adolescents’ family SES at Wave 1 was positively related to career adaptability at Wave 3 via its positive association with teachers’ career support efficacy at Wave 2. This study highlighted the important role of teacher–student interaction in adolescents’ career development.

Keywords

family socioeconomic status teacher–student relationship quality teachers’ career support efficacy career adaptability career ambivalence chinese

Introduction

Adolescents in high schools are going through an important career transition period from forming the initial career self-concept to exploring their career interests and objectives (McWhirter et al., 2000; Savickas, 2002). One of the critical tasks of this period is developing career adaptability as well as avoiding career ambivalence while also coping with various other types of challenges associated with adolescence (Kasperzack et al., 2014; Savickas, 2013). Career adaptability refers to individuals’ readiness to prepare for and perform work roles (Savickas & Porfeli, 2012), which includes career concern, control, curiosity, and confidence. Career ambivalence refers to individuals’ contradictory thoughts, feelings, and intentions with respect to meaningful, identity-creating aspects of career (Kasperzack et al., 2014). Career ambivalence encompasses the ambiguity that individuals may face when the meaning of a career situation is vague and decisional opportunities are unknown. These two aspects of adolescents’ career development cover most of the core components career development that have been typically examined in prior research, including but not limited to career exploration, actions, goals, and (in)decision (Sawitri et al., 2015).

Adolescents’ abilities of achieving such career development goals may vary as a function of their family socioeconomic status (SES) (Ali & McWhirter, 2006; Hsieh & Huang, 2014; Huang & Hsieh, 2011), given that family SES, to a large extent, represents adolescents’ possessing of various capitals (physical, human, and social), which have been shown to be critical for career development via shaping adolescents’ differential access to relevant opportunities and resources (e.g., parental involvement and career exploration) (Bradley & Corwyn, 2002; Hu et al., 2020; Kay et al., 2017; Liu et al., 2020).

A slim body of research has examined the potential mediating role of family functioning (e.g., parenting) in the association between family SES and adolescents’ career development (Flouri et al., 2016; Lee, 2018). However, low family SES may also confer risk for adolescents’ career maladjustment by disrupting proximal interpersonal processes outside the family setting, particularly their interactions with teachers in the school context (Barbarin & Aikens, 2015), which has been under-examined in previous research. Thus, this study aims to narrow this gap by examining the associations between adolescents’ family SES and their career developmental outcomes (i.e., career adaptability and career ambivalence) and more importantly, the potential mediating roles of teacher–student interactions (i.e., teacher–student relationship quality and teachers’ career support efficacy) in such associations.

Theoretical Foundation

The current study was grounded in the social cognitive career theory (SCCT; Lent et al., 1994). According to this theory, individuals’ beliefs in their ability to successfully complete career-related tasks (i.e., self-efficacy) and their beliefs about the consequences of performing such tasks (i.e., outcome expectations) are important in achieving their desired career goals. The career choice goals, along with self-efficacy and outcome expectations, predict choice actions (e.g., career explorations). The SCCT also posits that individuals’ family SES, conceptualized as a critical component of person inputs or background contextual affordances, indirectly influences their career interests, career goals, and career-related behaviors via access to learning opportunities, which relates to the development of self-efficacy and outcome expectations in this context (Lent et al., 2000; Thompson & Dahling, 2012).

In particular, the SCCT highlights the crucial influences of teacher-student interactions as vital contextual sources of learning opportunities in shaping individuals’ cognitive capacities and career developmental outcomes as a result (Lent et al., 2000). Teachers as one of the background contextual affordances that could provide career role models and skill development opportunities to students, which, in turn, likely promote students’ self-efficacy and outcome expectations towards career (Wong et al., 2021). Further, the SCCT highlights that teachers’ emotional support or their relationship quality with students could facilitate students’ career actions towards their goals (Zhang et al., 2018). Thus, from an SCCT perspective, students’ family SES operates as a microsystemic factor that may affect their interactions with teachers (i.e., instrumental support and emotional connectedness), which, in turn, shape their career developmental outcomes ultimately (Flouri et al., 2016).

Informed by the aforementioned theoretical propositions, we hypothesize in the present study that adolescents’ family SES would be related to their career developmental outcomes through associations with teacher-student relationship quality and teacher career support efficacy.

Family SES and Career Development

Decades of research has shown that family SES is related to children’s developmental outcomes across multiple domains, and these associations are explicated specifically through shaping the various proximal processes occurring within the microsystems that children are embedded (Conger et al., 2010; Nomaguchi & Milkie, 2020). Empirical studies also have generally supported the proposition that family SES plays a vital role in career development. Hu and colleagues (2020) found in a sample of 224 college students that higher family SES related to more career exploration and goal persistence via lower perceived scarcity, which ultimately related to better person-job fit. Similarly, low family SES has been demonstrated as a critical risky factor for college students’ compromised career development, including career exploratory intentions, vocational aspirations, and career decision self-efficacy (Hsieh & Huang, 2014; Huang & Hsieh, 2011). However, these studies tend to focus on college students and thus it’s not clear whether family SES relate to critical indicators of career development (i.e., adaptability and ambivalence) among adolescents.

The potential mediating roles of teacher-student relationship quality and teachers' career support efficacy

Few studies have examined the link between family SES and adolescent career development, although the critical implications of family SES for adolescent development in other domains have been extensively documented (Lee et al., 2014; Letourneau et al., 2013). Furthermore, it also merits attention that numerous studies reveal that a great proportion of the associations between family SES and adolescents’ emotional (e.g., anxiety), cognitive (executive functioning), and behavioral outcomes (e.g., delinquency) are accounted for by the educational, vocational, and financial resources that parents provide to their children (Blustein et al., 2002; Corcoran, 1995; Flouri et al., 2016), leaving the potential roles of the other critical sources of support or guidance (e.g., from teachers) underexplored. In the career domain, although adolescents’ career exploration and preparation initially take place in the family (Savickas, 2005), teacher-student interactions have been documented as critical contributors to individuals’ career development (Kenny & Bledsoe, 2005; Patton & McMahon, 2006). Supportive or affective teacher-student relationships would contribute to adolescents’ positive career outcomes (Garcia et al., 2015; Gushue & Whitson, 2006; Metheny et al., 2008) by creating an accepting environment, offering care and support, and providing career-related instruction or information (Kenny & Bledsoe, 2005). Beyond the interactions between teachers and students, teachers’ support or guidance also can help facilitate students’ career development (Kenny & Medvide, 2013). In support of this idea, Kenny and her colleagues (2010) found that perceived automatic support from teachers was positively related to high school students’ career planning. Zhang et al. (2018) further clarified that teachers could promote students’ career-related decision-making by providing career-related informational, instrumental, and emotional support.

The SSCT posits that, apart from relationship factors, social cognitive factors (e.g., career self-efficacy) can serve as important motivating factors in shaping individuals’ career-related behaviors and career developmental outcomes (Lent & Brown, 2013). Career self-efficacy is positively related to beliefs about coping with career barriers (Lindley, 2006) and can be a powerful predictor of career planning and exploration for adolescence (Rogers & Creed, 2011). Thus, higher career self-efficacy will anticipate higher levels of career satisfaction and career performance (Conklin et al., 2013) and is linked to lower ambivalence during and after career decision-making (Kasperzack et al., 2014). Teachers’ career support efficacy, which derived from the concept of collective efficacy and represents the confidence about to what extent the support adolescents believe they would receive from their teachers, is especially important among all types of career self-efficacy throughout high school years (Cheung et al., 2013). It is obvious that adolescents’ behaviors and beliefs are not only affected by their own volition but also by the goals, wills, and efforts of their significant others (peers, parents, and teachers), which is especially true within the collectivism context like China (Cheung et al., 2013). Compared with parents or peers, teachers provide more professional and special career instructions for adolescents in the field of career exploration so that teachers’ support efficacy constitute a predominant factor in shaping adolescents’ career development.

In fact, previous studies found that students with low family SES were usually judged less favorably from teachers, had less affective teacher–student relationships, and perceived less teachers’ support than students from high SES background (Sikora, 2019; Veland et al., 2009), which in turn, would result in poor career development (Gushue & Whitson, 2006). Thus, teacher–student relationship quality and teachers’ career support efficacy are related but distinct and thus may serve as unique linking mechanisms in explaining how family SES relate to adolescents’ career developmental outcomes. Taken together, the current study sought to examine the unique roles of teacher-student relationship quality and adolescents’ perceived teacher career support efficacy in the association between adolescents’ family SES and adolescents’ career development outcomes.

Career education in Chinese Secondary Schools

Career-related education, guidance, and/or counseling did not exist when individuals’ job was guaranteed and allocated by the Chinese government during the period of planned economy (Zhang et al., 2002). Along with China’s reforms toward market economy, students can choose their own jobs freely but found themselves unprepared. Against this background and the impact of economic globalization, career education has gained increasing attention from Chinese government (Sultana, 2014). However, the National College Entrance Examination (NCEE) system, launched in the late 1970s, has resulted in a highly competitive, exam-oriented educational approach for the secondary schools in China (Zhou et al., 2016). Not until the reform of the NCEE system starting in 2014, career education did not officially emerge in China.

Despite that the Chinese government pays greater attention to career education and has issued several policies to promote the implementation of career education, there are several significant barriers to carry out career education in Chinese secondary schools (Wang & Wang, 2020). First, career-related courses are new to secondary students as they tend to have insufficient awareness of the importance of career education for their future. Moreover, teachers, especially full-time career educators, cannot receive formal career-related instruction training, and, to make things worse, psychological teachers, or even subject teachers in Chinese secondary schools take the responsibility of career education (Xie et al., 2019). To date, only a few Chinese secondary schools have successfully launched career education and most Chinese secondary school students in their senior years have very few opportunities for career-related instruction and training (Gu et al., 2020). However, due to the reform of the NCEE, it is important and urgent for secondary school students to receive professional and tailored career education (Liu et al., 2014). Under this situation, it is critical to examine whether teacher–student interactions, including their relationship quality and career-specific support efficacy, matter for Chinese secondary schools’ career education.

The Present Study

Although many studies have already paid attention to the unique effects of SES and teacher–student interactions on career development separately, there are some critical gaps needed to be addressed. First, although the potential mechanism of the association between family SES and career development has been investigated in previous work, most of which focused on family processes (Blustein et al., 2002; Lee, 2018), and the role of teachers in such associations still remains unclear. Besides, teachers in China usually have high levels of prestige and authority, and adolescents often spend most of the time interacting with their teachers in schooldays, and thus teachers are considered as equally, if not more, influential on adolescents’ development than their parents (Chen, 2005). Therefore, it is necessary to examine the mediating role of teacher-student interactions in explaining how family SES relates to adolescents’ career development.

Second, most previous studies adopted a cross-sectional design (e.g., Hsieh & Huang, 2014) and thus limit the examinations of the unfolding processes of the associations among SES, teacher–child interactions, and youth career development over time. The current study addressed these gaps using 3-wave data and control for baseline mediators, baseline outcomes, and potential covariates (Brown et al., 1999; Gushue & Whitson, 2006). In sum, based on previous empirical studies and theories, we hypothesized that family SES would be positively associated with teacher–student relationship quality and teachers’ career support efficacy, which further would be positively and negatively associated with career adaptability and career ambivalence, respectively.

Method

Participants and Procedures

Participants were recruited from two senior middle schools in the southwestern area of China (one was from the urban area and the other from the suburb area). We strategically chose these two schools given that the two schools were representative of the local secondary school in terms of the implementation of career education. Specifically, these two schools have started to incorporate career education into their curriculum. Full-time psychological teachers with bachelor’s degree in education in these two schools were in charge of the implementation of career education. In addition to tailored, regular career courses for students from Grade 10 to Grade 12, they also provide individual counseling service for students with career-related confusions and ambivalence. They also trained subject teachers to integrate career-related instruction into their officially assigned subjects.

Consent forms were obtained from both the adolescents and their parents. The assessment was conducted in the schools by the teachers, who had been trained by the research assistants beforehand. Adolescents completed all the questionnaires in the current study by themselves. At Wave 1 (W1), a total 1410 students at 10^th grade participated in the study. The Wave 2 (W2) (n = 1024) and Wave 3 (W3) (n = 999) data were obtained consecutively a year apart from the last wave.

Multivariate analysis of variances (MANOVA) was conducted to test if there were any differences in key study variables and demographics at Wave 1 between participants who participated in W3 and those did not. Only one noteworthy difference emerged (i.e., partial η² > .14; Bandalos, 2002) such that as compared to participants retained at W3, those who dropped out at W3 were more likely from the rural rather than from the urban area (partial η² = .243). This was conceivable given rural schools might have more student dropout rate than urban schools (Yi et al., 2012).

The final analytic sample was the 1410 participants at W1. Full Information Maximum Likelihood (FIML) estimation was adopted to deal with the missing data given that FIML offers substantial improvements over the deletion methods (e.g., deleting those who did not participant in the W2 or W3) by producing more accurate parameter estimates and using all the available data (Acock, 2005; Enders, 2013). For the 1410 students in the present study at W1, their age ranged from 13.15 to 19.27 years old (M = 15.26, SD = 0.51). Among them, 52.4% of them were girls, and 61.7% of them were from the urban senior middle school, and 38.3% from the rural senior high school. Their parents’ educational levels ranged from “elementary school or below” to “doctoral degree,” and most of them obtained the degree of “middle school” (32.7% for mothers, 30.2% for fathers) or “high school, vocational high school, or technical secondary school” (28.7% for mothers, 30.6% for fathers).

Measures

Family Socioeconomic Status (SES) at W1

In light of PISA 2009 (OECD, 2012), adolescents’ family SES was computed using 3 indices: mother’s and father’s education levels (“1 = elementary school or below,” “2 = middle school,” “3 = high school, vocational high school, or technical secondary school,” “4 = junior college,” “5 = undergraduate,” “6 = graduate,” and “7 = doctor”), and household possessions (14 items, asking adolescents whether they have some specific household items at home, e.g., “a computer”). The total score of household possessions was used. The factor loadings of the three indicators (r = .34 to .66) for the latent variable of SES ranged from .43 to .83. Cronbach’s α in the current study was .71.

Teachers’ Career Support Efficacy at W1 and W2

Teachers’ career support efficacy was assessed using the 6-item teachers’ career support efficacy subscale of the 18-item Collective Contribution to Career Efficacy Scale (CCCE; Cheung et al., 2013). CCCE assessed to what degree participants believe their parents, school, and teachers, or peers would support their career development. The rating scale ranged from 1 (“no confidence at all”) to 5 (“completely confident”). The 6 items specifically assessed students’ perceptions of teachers’ career support efficacy in self-appraisal, occupational information, goal selection, planning, problem solving, and role modeling (e.g., “Assist you to determine what your ideal job would be”). A previous study demonstrated that the CCCE had good reliability and validity in the Chinese sample (Cheung et al., 2013). Cronbach’s αs in the current study were .90 and .92 at W1 and W2, respectively.

Teacher–Student Relationship Quality at W1 and W2

Teacher–student relationship quality was assessed using the 23-item Student–Teacher Relationship Scale (Pianta, 2001). This scale included four subscales: intimacy (7 items, e.g., “I feel like I can confide in my teacher.”), conflict (7 items, e.g., “I have a bad relationship with my teacher.”), support (5 items, e.g., “When I’m in trouble, my teacher would always help me in time.”), and satisfaction (4 items, e.g., “Generally speaking, I’m satisfied with the relationship between my teacher and me.”). Students responded to the items on a 5-point scale from 1 (“not apply to me at all”) to 5 (“completely apply to me”). The scale had good reliability and validity in Chinese samples (Pianta, 2001). Confirmatory Factor Analysis (CFA) was conducted to test the structural validity of the scale in this study. The “intimacy” dimension was removed due to the low factor loading (i.e., 0.27 for W1 and 0.16 for W2) and the “conflict” dimension was reverse recoded. Factor loadings for the indicators at W1 and W2 (rs = .32 to .58) were between .49 and .86. Cronbach’s αs were .86 and .88 for W1 and W2, respectively.

Career Ambivalence at W1 and W3

Career ambivalence was assessed using the 4-item Ambivalence in Career Decision-Making Scale (Kasperzack et al., 2014). The scale assessed individuals’ uncertainty and indecision regarding to career decision-making (e.g., “I have mixed feelings concerning my intended field of study/my intended professional training.”) and was rated on a 5-point scale ranging from 1 (“never”) to 5 (“always”). Previous studies demonstrated the scale had good reliability and validity in Chinese samples (e.g., Zhou et al., 2020). Cronbach’s αs in current study were .84 and .88 for W1 and W3, respectively.

Career Adaptability at W1 and W3

Career adaptability was assessed using the 24-item Career Adapt-Abilities Scale (Savickas & Porfeli, 2012). This scale included four subscales (each subscale has 6 items): concern (e.g., “Preparing for the future”), curiosity (e.g., “Exploring my surroundings”), control (e.g., “Keeping upbeat”), and confidence (e.g., “Performing tasks efficiently”). Participants were asked to rate the items on a 5-point scale from 1 (“Definitely not like me”) to 5 (“Very much like me”). The scale had good reliability and validity in Chinese samples (Liang et al., 2020). In the current study, factor loadings of the indicators (rs = .62 to .86) were between .77 to .96 at W1 and W3. Cronbach’s αs in current study were .96 and .98 for W1 and W3, respectively.

Covariates at W1

Adolescents’ age in years, gender (“0 = boy” or “1 = girl”), and school (“0 = Urban senior middle school”, “1 = Rural senior middle school”) at W1 were collected as covariates given their potential relations with key study variables (Brown et al., 1999; Gushue & Whitson, 2006).

Data Analytic Approach

The mediating model was examined using Mplus 8.7 (Muthén & Muthén, 1998–2017). Specifically, we tested the associations between SES at W1 and career ambivalence or career adaptability at W3 via teachers’ career support efficacy or teacher-student relationship quality at W2, while controlling for career ambivalence, career adaptability, teachers’ career support efficacy, teacher–student relationship quality, and covariates at W1. Among the key variables, SES, teacher–student relationship quality, and career adaptability were constructed as latent variables and the unidimensional constructs of teachers’ career support efficacy and career ambivalence were specified as manifest variables. Moreover, given that adolescents were nested in classes, the “TYPE = COMPLEX” procedure in Mplus was used to handle the hierarchical data structure (Muthén & Muthén, 1998–2017).

Model fit indices like the chi-square with its degree of freedom (χ²), the root mean square error of approximation (RMSEA; acceptable < .08, good < .05; Steiger, 1990) with its 90% confidence interval (CI), the comparative fit index (CFI; acceptable > .90, good > .95; Bentler, 1990), and the standardized root mean square residual (SRMR; acceptable < .08, good < .05) were used to test the model-data correspondence (Kline, 2015). The mediating effect was estimated by the bias-corrected bootstrapped standard errors and confidence intervals with 5000 bootstrap resamples (Preacher & Hayes, 2008). Specifically, 95% bias-corrected bootstrapped CIs around the unstandardized indirect associations that do not include 0 reflect significant indirect effects.

Results

Descriptive statistics and correlations of key variables and covariates are displayed in Table 1. Most of the correlations between key variables were in the expected directions. Correlations among indicators of teacher–student relationship and career adaptability were medium to large (i.e., .32 to .86) in magnitude.

Table 1.

Descriptive statistics and correlations among key variables and covariates.

	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	M	SD
1. ME (W1)	1																					2.83	1.36
2. FE (W1)	.66	1																				3.15	1.38
3. HP (W1)	.36	.34	1																			11.69	2.31
4. TCSE (W1)	.13	.09	.15	1																		3.06	0.83
5. TSRC (W1)	.07	−.07	.02	.15	1																	3.92	0.85
6. TSRSP (W1)	.15	.13	.16	.44	.32	1																3.46	0.67
7. TSRSA (W1)	.70	.06	.06	.19	.48	.39	1															3.36	0.65
8. TCSE (W2)	.12	.14	.16	.35	.13	.28	.15	1														3.00	0.83
9. TSRC (W2)	.05	.04	.08	.11	.32	.20	.16	.15	1													3.93	0.85
10. TSRSP (W2)	.15	.15	.17	.26	.22	.41	.18	.44	.32	1												3.48	0.63
11. TSRSA (W2)	.12	.14	.14	.13	.23	.22	.25	.20	.58	.42	1											3.45	0.61
12. CAMB (W1)	−.07	−.08	−.08	−.06	−.10	−.10	−.14	−.06	−.14	−.09	−.15	1										3.08	0.91
13. CACCT (W1)	.18	.19	.25	.34	.00	.26	.12	.25	.10	.20	.10	-.10	1									3.43	0.75
14. CACTR (W1)	.10	.09	.17	.26	.05	.25	.13	.24	.11	.22	.12	-.10	.62	1								3.78	0.72
15. CACUR (W1)	.18	.17	.23	.31	−.02	.25	.09	.25	.07	.22	.07	-.06	.73	.69	1							3.48	0.75
16. CACFD (W1)	.15	.17	.21	.30	.02	.25	.13	.23	.10	.19	.12	-.12	.69	.77	.76	1						3.60	0.72
17. CAMB (W3)	−.08	−.06	−.09	−.13	−.07	−.16	−.11	−.14	−.17	−.16	−.18	.33	-.12	-.14	-.13	-.12	1					2.70	0.86
18. CACCT (W3)	.17	.20	.16	.20	.07	.19	.14	.29	.06	.22	.10	-.07	.43	.34	.38	.36	-.09	1				3.63	0.72
19. CACTR (W3)	.13	.16	.14	.20	.11	.19	.14	.29	.14	.25	.14	-.09	.37	.41	.36	.40	-.14	.77	1			3.82	0.70
20. CACUR (W3)	.20	.22	.15	.21	.05	.20	.13	.28	.07	.22	.09	−.07	.43	.38	.42	.40	-.09	.86	.82	1		3.65	0.71
21. CACFD (W3)	.17	.20	.14	.23	.07	.22	.15	.31	.08	.26	.09	−.09	.40	.40	.40	.42	-.13	.81	.86	.86	1	3.70	0.72
Covariates
Gender (W1)	.04	.02	.13	.04	.20	.08	.05	−.05	.21	.07	.16	−.03	−.03	−.09	−.08	−.12	−.06	−.03	−.09	−.08	−.11	47.6%^a
Age (W1)	−.16	−.20	−.09	−.04	.00	−.07	−.03	−.02	−.03	−.11	−.09	.08	−.05	−.03	−.01	−.04	.10	−.03	−.02	−.05	−.03	15.26	0.51
School (W1)	−.38	−.40	−.35	−.24	.08	−.18	−.04	−.16	.00	−.19	−.09	.12	−.23	−.06	−.19	−.17	.15	−.16	−.14	−.15	−.15	61.7%^a

Note. Bolded coefficients were significant at p < 0.05 (two-tailed); ME, mother’s education level; FE, father’s education level; HP, household possessions; TCSE, teachers’ career support efficacy; TSRC, teacher–student relationship: Conflict (reverse coded); TSRSP, teacher–student relationship: Support; TSRSA, teacher–student relationship: Satisfaction; CAMB, career ambivalence; CACCN, career adaptabilities: Concern; CACTR, career adaptabilities: Control; CACUR, career adaptabilities: Curiosity; CACFD, career adaptabilities: Confidence; W1, wave 1; W2, wave 2; W3, wave 3.

The percentage of boys or the percentage of students from the urban senior middle school.

The mediating model (Figure 1) demonstrated a good fit to the data: χ² (203) = 1032.362, p < .001; RMSEA = .054 with a 90% CI [.051, .057]; CFA = .924; and SRMR = .057. SES at W1 was directly associated with career adaptability at W3 (β = .124, p < .001) but not career ambivalence at W3 (β = .031, p = .49).

Figure 1.

Associations among family SES (W1), teachers’ career support efficacy (W2), teacher–student relationship (W2), career ambivalence (W3), and career adaptability (W3). Note. Black, solid lines indicate significant coefficients and gray, dotted lines indicate non-significant coefficients. Standardized coefficients are reported. The correlations among key variables and covariates are omitted for clarity. W1, Wave 1; W2, Wave 2; W3, Wave 3; *p < .05; **p < .01; ***p < .001 (two-tailed).

Three indirect pathways were identified after controlling for teachers’ career support efficacy, teacher–student relationship quality, career ambivalence, career adaptability, and covariates at W1. First, family SES at W1 was associated positively with teacher-student relationship quality at W2 (β = .148, p < .001) which, in turn, was associated negatively with career ambivalence at W3 (β = −.162, p < .001). Moreover, family SES at W1 was associated positively with teachers’ career support efficacy at W2 (β = .131, p < .001), which, in turn, was negatively and positively associated with career ambivalence at W3 (β = −.074, p < .05) and career adaptability at W3 (β = .138, p < .001), respectively.

The bias-corrected bootstrapped estimates for the indirect effects are demonstrated in Table 2. Specifically, Family SES at W1 was related to career ambivalence at W3 via teacher–student relationship quality at W2 (b = −.026, SE = .010, 95% CI [-.052, −.005], β = −.024) and teachers’ career support efficacy at W2 (b = −.024, SE = .006, 95% CI [-.024, .002], β = −.010). Moreover, family SES at W1 was associated with career adaptability at W3 via teachers’ career support efficacy at W2 (b = .015, SE = .005, 95% CI [.005, .037], β = .018). The magnitudes of the identified indirect effects were generally small in magnitude (Kenny, 2012).

Table 2.

Specific effects for indirect pathways based on bias-corrected bootstrapped estimates.

Specific indirect pathways	Bootstrapped estimates for indirect effects
Specific indirect pathways	b	SE	95% CI	β
SES (W1) → Career ambivalence (W3)
Teachers’ career support efficacy (W2)	-.011	.006	[−.020, −.001]	−.010
Teacher–student relationship (W2)	-.026	.010	[−.045, −.009]	−.024
SES (W1) → Career adaptability (W3)
Teachers’ career support efficacy (W2)	.015	.005	[.008, .031]	.018
Teacher–student relationship (W2)	.008	.007	[−.004, .031]	.009

Note. W1, Wave 1; W2, Wave 2; W3, Wave 3. Bolded indirect pathways were significant based on bias-corrected bootstrapped 95% confidence interval (CI). b, unstandardized coefficient; SE, standard error; CI, confidence interval for the standardized coefficient; β, standardized coefficient. Standardized indirect effects around .01 were “small,” effects around .09 were “medium,” and effects around .25 were “large” (Kenny, 2012).

Discussion

The call for examining the contribution of family SES to adolescents’ career development has been urged repeatedly (Blustein, 2011; Diemer & Rasheed Ali, 2009). The current study responded to this call by unfolding the underlying processes in the association between family SES and adolescents’ career development using a three-wave longitudinal design. We found that teacher–student relationship quality and teachers’ career support efficacy served as the mediators that explained how family SES related to adolescents’ career development. This study contributed to the literature in at least two ways. First, the documented mediating roles of teacher-student transactions in the association between SES and adolescents’ career development expand the explanatory pathways beyond family processes (e.g., Lee, 2018). Second, the current study used a 3-wave longitudinal design and controlled for the potential effects of baseline for the mediators and outcomes as well as a critical set of covariates, and thus provided a rigorous test of our hypotheses.

The Contribution of Family SES to Adolescents’ Career Development

This study extends the contribution of family SES to adolescents’ emotional, cognitive, and behavioral adjustment to their career developmental outcomes. This is important given that adolescents’ adaptive career developmental outcomes not only can instill confidence in dealing with the challenges during the critical transition to adulthood, but also can promote their learning motivation, self-efficacy, and social adaptability as well as deterring the development of problem behaviors (Germeijs & Verschueren, 2007; Ginevra et al., 2018; Stipanovic et al., 2017).

Note that family SES related directly to career ambivalence and was associated both directly and indirectly with career adaptability and career ambivalence via either with teacher-student relationship quality or teachers’ support efficacy. The identified differentiated linking mechanisms for career adaptability versus career ambivalence highlight the importance of incorporating both adaptive and maladaptive indicators of career development in exploring antecedents of adolescents’ career development (Zhou et al., 2020). Specifically, career adaptability represents adolescents’ resources (i.e., concern, control, curiosity, and confidence) in adjusting themselves when facing career challenges or accomplishing career responsibility (Savickas & Porfeli, 2012); career ambivalence refers to adolescents’ contradictory thoughts, feelings, and/or intentions before or after career decision, which is inevitable and quite common during adolescence (Kasperzack et al., 2014). They are related but distinct constructs and awaits further examination in terms of their antecedents, outcomes, and influencing mechanisms across the adolescence stage.

The Mediating Roles of Teacher–Student Relationship Quality

The identified mediating role of teacher–student relationship quality in the association between family SES and adolescents’ career ambivalence is consistent with propositions from the general Family Investment Model (FIM; Conger & Donnellan, 2007), the Family Stress Model (FSM; Masarik & Conger, 2017), and the specific Lent et al.’s (2000) SSCT. Family economic status is associated with the amount and quality of resources that parents are able to invest in either parenting processes/parent–child relationship or learning materials to their children (Liang et al., 2020). Adolescents tend to perceive a sense of uncertainty and threat in terms of their future careers (e.g., competing for limited college entrance and job vacancies) and thus they have to learn to allocate their resources to meet their respective needs (Melloy et al., 2018). Similar to their parents’ investment strategies, as compared to students from low SES families, those from high SES families are more likely to invest in social resources that can increase long-term payoffs, for instance, striving to achieve good quality of relationship with teachers (Mittal & Griskevicius, 2014).

Moreover, teachers tend to form low expectation towards students from low SES families and thus may engage in less interactions with them than students from SES families (Borman & Overman, 2004), which, not surprisingly, would result in less affective teacher-student relationships. The compromised teacher–student relationship quality, in turn, could make adolescents from low SES families less engaged and motivated in career exploration (Yıldırım, 2012), and deteriorate their career development as a result. Future studies are warranted to delineate (a) adolescents’ resource allocation processes and (b) teachers’ beliefs and behaviors towards students from disparate SES families underlying the association between family SES and teacher–student relationship quality.

The Mediating Role of Teacher Career Support Efficacy

The current findings also highlight the unique contribution of teachers’ support efficacy, which explained how family SES related to both career adaptability and ambivalence. This is in accordance with the proposition of the SCCT that teachers’ career efficacy is a motivating factor (Lent & Brown, 2013) that could promote career planning (Kenny et al., 2010) and was associated negatively with career ambivalence (Kasperzack et al., 2014).

Note that we actually assessed adolescents’ perceived teacher support efficacy, which may represent the extent of students’ perception of resource scarcity from a life history perspective (Hu et al., 2020). Specifically, students from low SES families tend to perceive higher resource scarcity, leading to less goal persistence and career exploration (Hu et al., 2020), so that they would experience more career ambivalence and develop compromised career adaptability. Again, teachers may hold low expectations towards adolescents from low SES families, providing limited support such as career-related guidance and emotional support and thus these students may ultimately develop diminished self-improvement, self-exploration, and employment skills (Zhang et al., 2018).

This finding is critical given the current imbalanced implementation of career education across different geographic regions of China, which is closely associated with the unbalanced economic development status across regions (Xie et al., 2019). Schools in economically developed regions (such as Beijing, Shanghai, and Guangdong province) have sufficient funding to recruit full-time career teachers with professional training in career education and provide specific career curricula and workshops to students. However, such curricula or workshops are basically absent in schools located in economically underdeveloped regions (such as remote and rural areas) (Wang & Wang, 2020). The currently identified contribution of both teacher–child relationship quality and more importantly, teacher career support efficacy to adolescents’ career adaptability and ambivalence highlight potential avenues to improve career education in China, especially for children from economically disadvantaged families. Certainly, replications of our identified associations in schools without full-time career-specific teachers are warranted in future studies.

Limitations and Future Directions

There were some limitations and corresponding future study directions that should be noted. First, the measurements of the current study relied on adolescents’ self-reports, which might suffer from common method bias. Although we used a longitudinal design, future studies can adopt multi-informant approach (e.g., incorporating teachers’ reports) to further minimize it. Second, the regional sample of the current study precluded the generalizability to a broader extent. Thus, future studies should recruit a more representative sample to replicate the findings. Moreover, in the current study, findings in the Chinese collectivism culture might differ from other countries (e.g., individualism in western countries). For example, social support is valued in collectivism culture, but it might not be that favored in some individualism countries (Uchida et al., 2008). Researchers can also conduct studies in different cultures or countries to document these potential differences. Lastly, contextual theories suggested that it was important to identify the unique roles of different social relationships on individuals’ career development (e.g., Patton & McMahon, 2006). Future studies can address this issue by incorporating adolescents’ multiple relational sources (e.g., parents, teachers, peers, and communities) and identifying their conjoining and unique effects on adolescents’ career development.

Implications for Practice

In the light of the findings, there are several practical implications for teachers or counselors. First, as adolescents’ career development is affected not only by family SES but also by teacher–student interactions, teachers should pay more attention to students with low family SES who are generally at risk in poor career development, and make sure every student has optimum career development chance and guidance. Second, given the important roles of teacher support and affective teacher-student relationships on adolescents’ career development (e.g., Metheny et al., 2008), schools should launch programs to improve the frequency and the quality of teacher-student interactions pertaining to career development, such as holding advisory sessions regularly to increase opportunities of one-on-one interaction and guidance among teachers and students (Kenny & Medvide, 2013). Last, since teacher’s career support efficacy promoted adolescents’ career development, we also suggest counselors to set up teacher learning seminars or communities to encourage them to reflect on their own teaching behaviors and how their expectation or belief would affect their students, and accordingly make a change (Barbarin & Aikens, 2015).

Footnotes

Acknowledgments

We thank the staff of this project for their unending contributions to this work and the students, teachers, and administrators who made this research possible.

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Preparation of this article was supported by the Fundamental Research Funds for the Central Universities (2019NTSS04 to Hongjian Cao and 2021NTSS61 to Yue Liang) and a grant from China Postdoctoral Science Foundation (2020M680420 to Lifen Zheng).

ORCID iD

Nan Zhou

Author Biographies

Dr. Lifen Zheng is a postdoctoral researcher at Faculty of Education, Beijing Normal University, Beijing, China. She obtained her PhD degree at the Beijing Normal University. She does research in Educational Neuroscience and Educational Psychology. Her research focuses on the neural mechanism underlying effective teaching and learning. She applies fNIRS-based hyperscanning method to explore the association between interpersonal neural synchronization and learning effect / teacher–student relationship. Her publications have appeared in Human Brain Mapping, Social Cognitive and Affective Neuroscience, Nature Communications, Cerebral Cortex, NeuroImage, etc. She likes playing badminton in her leisure time. Address: Room 323, National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, China, 100875. Email: zhenglifen@bnu.edu.cn

Mr. Haoran Meng is a postgraduate at Faculty of Education, Beijing Normal University, Beijing, China. His research focuses on parenting behaviors, youth career development, and smartphone use and addiction. His publications have appeared in Developmental Psychology and Journal of Behavioral Addictions. He likes playing badminton in his leisure time. Address: Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, China, 100875. Email: menghr810@163.com

Mr. Shaofan Wang is a postgraduate at Faculty of Education, Beijing Normal University, Beijing, China. His research focuses on adverse childhood experiences, youth career development, educational economics, and smartphone use and addiction. He likes playing badminton and listening to music in his leisure time. Address: Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, China, 100875. Email: wsf6688@mail.bnu.edu.cn

Dr. Yue Liang is an Assistant Professor at School of Social Development and Public Policy, Beijing Normal University, Beijing, China. She obtained her PhD degree at the University of North Carolina-Greensboro. She does research in Developmental Psychology. Her research focuses on child development, including moral development and career development. Her publications have appeared in Journal of Counseling Psychology, Journal of Family Psychology, Applied Developmental Science, and etc. She likes playing video games and hiking. Address: Room 2007, North Main Building, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, China, 100875. Email: liangyue1989@gmail.com

Miss Ruihong Nie is a teacher in charge of students’ mental health in Baoan High School Group Tangtou School, Shenzhen, China. She got her master degree in the Department of Psychology, Beijing Normal University. Her research interests include students’ career development, mental health within family and school contexts. Her publications have appeared in journals such as Psychological Development and Education, Mental Health Education, and etc. She likes traveling and cooking. Address: No. 8 Yingcai Road, Baoan High School Group Tangtou School, Shenzhen, China. Email: ruihong9502@163.com

Dr. Lianjiang Jiang is an Assistant Professor at Faculty of Education, The University of Hong Kong, Hong Kong, China. He obtained his PhD degree in English language Education at the University of Hong Kong. His research interests include second language writing, digital multimodal composing, and new literacy studies. His publications have appeared in journals such as TESOL Quarterly, Language Teaching Research, System, ELT Journal, Journal of Second Language Writing, Computer Assisted Language Learning, Journal of Language, Identity, and Education, Schools: Studies in Education, Teaching and Teacher Education, Educational Studies, Asia-Pacific Journal of Teacher Education, Asia-Pacific Education Researcher, and Discourse and Communication. He likes cooking and reading in his leisure time. Address: MWC656, Pokfulam, HKSAR, Email: jljiang@hku.hk

Dr. Beilei Li is an Assistant Professor at Faculty of Education, Beijing Normal University, Beijing, China. She obtained her PhD degree at Beijing Normal University. She does research in Educational Psychology and Developmental Psychology. Her research focuses on adolescents’ bullying within primary and secondary school contexts. Her publications have appeared in Psychological Development and Education, Journal of Educational Psychology, and etc. She likes cooking and traveling. Address: Room 530, Ying Dong Building, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, China, 100875. Email: beileili@aliyun.com

Dr. Hongjian Cao is currently working as an Associate Professor at the Faculty of Education, Beijing Normal University, Beijing, China. In 2017, he obtained his Ph.D. from the Department of Human Development and Family Studies at the University of North Carolina-Greensboro, USA. His primary research interest centers on: Family processes and child development; Maternal well-being during the transition to parenthood; early childhood maltreatment and subsequent adjustment; couple relationship well-being and its key predictors; parent-child and couple relationships within families headed by LGBTQ* parents; and the implications of technology use (e.g., Internet gaming and cellphone use addiction) for human development. His publications have appeared in a number of prestigious peer-reviewed journals in the areas of family studies and developmental psychology, including Journal of Marriage and Family, Trauma, Violence, & Abuse, Developmental Psychology, Journal of Child Psychology and Psychiatry, Journal of Family Theory & Review, Journal of Personality, Journal of Sex Research, Archives of Sexual Behavior, Computers in Human Behavior, et al. He is currently serving as the Associate Editor for Journal of Social and Personal Relationships, Consulting Editor for Journal of Research on Adolescence, and Editorial Board Member for Journal of Family Theory & Review, and Family Relations. During his spare time, he loves playing tennis. Mailing Address: 512 Ying Dong Building, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing, China, 100875. Phone: 086–15010244340, Fax: 086–010-58800967, Email: caohongjian1020@gmail.com

Dr. Nan Zhou (Corresponding author) is currently working as an Associate Professor at the Faculty of Education, Beijing Normal University, Beijing, China. In 2016, he obtained his PhD degree from the Department of Human Development and Family Studies at the University of North Carolina-Greensboro. He does research in Educational Psychology, Clinical Psychology and Developmental Psychology. His research focuses on child and youth development and particular adjustment problems (i.e., problematic internet use and behavior problems) in family and peer contexts, including marital conflict, maternal employment, and deviant peer affiliation. His research is grounded in bioecological theory and theories of family processes and development. His publications have appeared in Journal of Child Psychology and Psychiatry, Developmental Psychology, Journal of Research on Adolescence, Journal of Marriage and Family, Trauma, Violence, & Abuse, Journal of Personality, Journal of Family Psychology, Journal of Counseling Psychology, Computers in Human Behavior, Family Process, and etc. He is currently serving as the Associate Editor for Journal of Social and Personal Relationships, and Editorial Board Member for Journal of Applied Developmental Psychology, and Journal of Family Psychology. He likes playing video games and badmintons. Address: Room 528, Ying Dong Building, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, China, 100875. Email: nanzhouchina@gmail.com

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