Parental Career-Related Behavior Transitions and Career Adaptability Among Chinese Secondary Vocational Students: School Interpersonal Support as a Mediator

Parental Career-Related Behaviors and Adolescent Career Adaptability

Parental career-related behaviors encompass specific approaches parents use to influence their children's career development, including career support such as encouragement and advice, career interference such as imposing preferences, and lack of engagement such as unwillingness to participate (Dietrich & Kracke, 2009). According to CCT, these proximal parental behaviors constitute a primary social context that shapes adolescents’ career development by influencing their self-construction and adaptation behaviors (Savickas, 2013). Meanwhile, spillover theory suggests that experiences and dynamics within the family domain can extend into other life domains, such as school (Xu et al., 2023). Thus, the relationship between parental behaviors and adolescent career adaptability, occurring at the intersection of family and school contexts, constitutes a core topic in career development research that can be jointly elucidated by these two theoretical frameworks.

Extensive variable-centered studies have consistently associated parental career support with higher career adaptability across diverse populations, including Western and Chinese contexts, university students, and both general and vocational high school students (Guan et al., 2016; Liang et al., 2020; Parola & Marcionetti, 2022; Zeng et al., 2023). By contrast, the effects of parental interference and disengagement are more culturally specific. In individualistic Western societies, these behaviors typically correlate with negative outcomes such as career indecision (Dietrich & Kracke, 2009; Hlaďo et al., 2020; Parola & Marcionetti, 2022). However, findings in collectivist cultures like China are mixed. Some studies report non-significant effects among general high school students (Guan et al., 2016; Liang et al., 2020), while others identify adverse effects among vocational students (Wen et al., 2025). These inconsistencies suggest that parental behaviors operate within cultural and educational contexts. A key limitation of variable-centered approaches lies in examining parenting dimensions in isolation, thereby overlooking the complex configurations characteristic of real-world parenting (Abaied et al., 2022; Feng et al., 2024; Zhou et al., 2020).

Person-centered approaches such as latent profile analysis (LPA) address this limitation by identifying distinct patterns of parental career behaviors. Western studies have identified various parenting styles, including authoritative and controlling types, which correlate systematically with adolescent outcomes (Abaied et al., 2022; Ahn et al., 2023; Nelson et al., 2011). Recent applications in Chinese contexts have revealed unique profiles. For example, Feng et al. (2024) and Zhou et al. (2020) identified three distinct profiles among Chinese university and high school students, showing that combinations of high support and high interference, often described as controlling yet caring, can also promote positive adaptation. This reflects a culturally nuanced interplay between involvement and concern within Chinese families (Fang et al., 2021). These findings highlight the multidimensional nature of parental influences, transcending variable-centered constraints. However, such studies often assume behavioral stability, whereas parenting approaches evolve alongside adolescent development (Cumsille et al., 2009; Liang et al., 2023). This dynamic aspect is precisely what latent transition analysis (LTA) is designed to examine.

LTA captures how parental behavior profiles change over time, including pathways and probabilities of transitions between subtypes (Ahn et al., 2023; Liang et al., 2023). A 3-year longitudinal study by Liang et al. (2023) of 1,410 Chinese general high school students revealed that parental profiles show both stability and meaningful transitions, particularly from controlling or neglectful patterns to supportive behaviors. These shifts carry important implications for adolescent development and provide critical insight into parenting dynamics, thereby supporting the design of timely and context-sensitive interventions (Liang et al., 2023). Notably, secondary vocational students, whose education emphasizes employment and technical professional development (Xu et al., 2023), face considerations and challenges related to career transitions at an earlier stage (Yan et al., 2024). Consequently, the parenting strategies adopted by their parents may differ to a certain extent from those of parents with children in regular senior high schools (Zeng et al., 2023).

The Mediating Role of School Interpersonal Support (Teacher Support and Peer Support)

As career preparation occurs mainly within the school environment, teacher and peer support serve as essential components of school resources (Chen et al., 2020; Rudolph et al., 2017). Scholars have emphasized the critical role of such school interpersonal support in promoting vocational students’ developmental outcomes (Hlaďo et al., 2020; Xu et al., 2023). CCT posits that individuals construct their careers by integrating personal characteristics with contextual opportunities and support (Savickas, 2013). Within this framework, school interpersonal support serves as a critical contextual resource that facilitates adaptive career behaviors. Furthermore, spillover theory provides a mechanism to explain how family dynamics influence these school-based resources; specifically, parental career-related behaviors may “spill over” into the school domain by shaping the quality of adolescents’ interactions with teachers and peers (Liu et al., 2022; Xu et al., 2023).

Teacher support, encompassing academic guidance, emotional care, and material assistance, has been shown to significantly promote career adaptability (Hlaďo et al., 2020; Lazarová et al., 2019; Sakiz et al., 2012). For instance, Lazarová et al. (2019) found a strong positive correlation between perceived teacher support and career adaptability among vocational students. When parents are unable to provide adequate educational or career guidance due to financial constraints, teacher support can compensate for these deficiencies and facilitate students’ transition into the workforce (Robb et al., 2007).

Peer support, which encompasses emotional, spiritual, and practical assistance among adolescents, serves as a key horizontal relational resource (Wentzel et al., 2010). Distinct from vertical support from adults, peer interactions significantly contribute to career development by enhancing decision-making capabilities and expanding career opportunities (Owusu et al., 2021). Empirical studies indicate that peer support helps youths overcome barriers through mutual assistance, thereby reducing unemployment risks (Felgenhauer et al., 2021). It also strengthens motivation for career exploration, fosters a sense of control over career development, and builds confidence in addressing professional challenges (Hlaďo et al., 2020; Owusu et al., 2021).

According to CCT, family and school contexts are fundamental to career adaptability development (Chen et al., 2020; Rudolph et al., 2017). Spillover theory complements CCT by extending its environment–interaction perspective, positing that family behavioral patterns exert cross-domain influences on school interpersonal dynamics. Specifically, positive parental involvement can promote a supportive school climate, thereby enhancing teacher autonomy support and peer information sharing (Liu et al., 2022; Xu et al., 2023), which in turn facilitates career adaptability. Conversely, negative parental behaviors may impair teacher attitudes and peer relationships (Chrispeels & Rivero, 2001; Gao et al., 2024), potentially suppressing adaptive outcomes. However, longitudinal studies are still necessary to systematically examine the mediating mechanisms of teacher and peer support in the relationship between parental career transition patterns and the career adaptability of secondary vocational students, thereby providing an empirical basis for developing targeted career adaptability interventions.

Participants and Procedures

We used cluster sampling to recruit students from four secondary vocational schools in Shandong and Jiangxi provinces, China. The first wave of data collection (T1) occurred in June 2022, yielding 1,094 valid questionnaires. Students completed the second wave (T2) in June 2023. Due to dropouts, leaves, or other reasons, some students participated only in the first survey. After excluding questionnaires with missing data, patterned responses, and those who completed only one survey, the final sample comprised 1,014 participants (retention rate = 92.69%).

The sample included 499 boys (49.2%) and 515 girls (50.8%), with 579 first-year students (57.1%) and 435 second-year students (42.9%). A majority of participants were from rural areas (853, 84.1%), while 161 (15.9%) were from urban areas. In Wave 1, the participants were 14–19 years old (Mage = 16.70, SD = 0.87). To assess potential attrition bias, t-tests were conducted on parental career-related behaviors, perceived teacher support, perceived peer support, and career adaptability between dropouts and retained participants. The t-values ranged from −1.14 to 1.46 (ps > 0.05), indicating that the sample attrition was random. This study was reviewed and approved by an institutional research ethics committee. Parental consent and adolescent assent were obtained before data collection.

Measures

Data Analyses

First, data was entered and organized using SPSS 26.0 software. Descriptive statistics and correlation analysis were conducted on the study variables. Second, Mplus 8.3 was employed to perform LPA and LTA. LPA is a latent class analysis technique that identifies the most meaningful, parsimonious, and statistically reasonable number of model subgroups based on a set of continuous observed indicators. This is achieved through fit indices and subgroup structure explanations (Collins & Lanza, 2009). Participants are then assigned to their respective subgroups. The criteria for assessing the best-fitting model include lower Akaike information criterion (AIC), Bayesian information criterion (BIC), and sample size-adjusted Bayesian information criterion (aBIC); entropy > 0.80; and significant Lo-Mendel-Rubin (LMR) and bootstrapped likelihood ratio test results (Lo et al., 2001). Additionally, the minimum number of participants in any latent subgroup must not be less than 5% of the total sample. LTA explores transitions between latent subgroups at different time points, describing dynamic changes through conditional probabilities.

Finally, to test the mediating effect, path analysis was conducted using Mplus 8.3 This approach was selected because the independent variable (patterns of change in parental career-related behavior) is multi-categorical, which was dummy-coded with the stable high-quality career nurturing (SH) group as the reference, while the mediating variables (perceived teacher support, perceived peer support) and the dependent variable (career adaptability at Time 2) are continuous. Bootstrap resampling (5,000 iterations) was employed to assess the significance of indirect effects (Hayes & Preacher, 2014; Muthén & Muthén, 2017). To minimize interference from other variables, the analysis controlled for demographic variables such as gender, grade, family location, family SES, and career adaptability at Time 1 (Table 1).

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Table 1.

Descriptive Statistics and Pearson Correlation Coefficient.

	1	2	3	4	5	6	7	8	9
Key study variables
1. Teacher support T1	1
2. Peer support T1	0.37**	1
3. Support T1	0.25**	0.20**	1
4. Interference T1	−0.19**	−0.23**	−0.30**	1
5. Lack of engagement T1	−0.19**	−0.23**	−0.63**	0.36**	1
6. Support T2	0.26**	0.24**	0.05	−0.21**	0.08	1
7. Interference T2	−0.17**	−0.24**	−0.23**	0.47**	0.21**	−0.14**	1
8. Lack of engagement T2	−0.22**	−0.24**	−0.25**	0.23**	0.25**	−0.37**	0.33**	1
9. Career adaptability T2	0.44**	0.50**	0.19**	−0.25**	−0.17**	0.41**	−0.33**	−0.39**	1
M	3.70	2.70	2.82	2.53	2.06	2.80	2.55	2.18	3.36
SD	0.83	0.85	0.90	0.94	0.81	1.04	0.84	0.81	0.43
Covariates
10. Gender	0.02	−0.07*	0.08**	0.04	−0.06	0.05	−0.02	−0.09**	−0.03
11. Grade	0.02	0.08*	0.11**	−0.10**	−0.06*	−0.01	−0.08*	−0.07*	0.05
12. Family location	0.10**	0.07*	0.04	−0.03	−0.05	0.10**	−0.04	−0.10**	0.12**
13. Family SES	0.24**	0.12**	0.16**	−0.05	−0.07*	0.22**	−0.02	−0.04	0.12**
14. Career adaptability T1	0.44**	0.33**	0.36**	−0.32**	−0.32**	0.15**	−0.20**	−0.17**	0.27**

Note: N = 1014. SES = Socioeconomic status. *p < 0.05, **p < 0.01. T1 = Time 1, T2 = Time 2.

Descriptive Statistics and Correlations

Means, standard deviations, and correlations for the study variables are shown in Table 2. Significant associations were found among almost all the main study variables (ps < 0.05), except the correlation between Support T1 and Support T2 (p = .11), and Lack of Engagement T1 and Support T1 (p = .79).

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Table 2.

Model Fit Indices for Tests of Longitudinal Measurement Invariance of the Parental Career-Related Behaviors Scale (PCB).

Model	χ 2	df	CFI	TLI	RMSEA[90% CI]	SRMR	ΔCFI	ΔRMSEA
Configural invariance	1742.200	396	0.960	0.956	0.058 [0.055, 0.061]	0.039	–	–
Weak invariance	1377.277	405	0.971	0.969	0.049 [0.046, 0.051]	0.037	+0.011	−0.009
Strong invariance	1635.321	462	0.965	0.967	0.050 [0.047, 0.053]	0.039	−0.006	+0.001

Measurement Invariance across Time

To evaluate whether the latent transition patterns could be validly interpreted as true change, we conducted a measurement invariance assessment of the PCB across T1 and T2. Following established procedures (Putnick & Bornstein, 2016), we tested configural, metric, and scalar invariance. The results supported strong invariance: the scalar invariance model fit the data well (CFI = 0.965, TLI = 0.967, RMSEA = 0.050 [90% CI: 0.047, 0.053]), and the degradation in fit from the metric model was negligible (ΔCFI = -0.006, ΔRMSEA = +0.001), meeting the recommended criteria (Chen, 2007) (see Table 2). This provides empirical support that the scale measured the same constructs equivalently over time, strengthening the interpretation of our LTA results as reflecting genuine developmental change.

Latent Profile Analysis of Parental Career-Related Behaviors

To identify latent subgroups of parental career-related behaviors, LPA was conducted using the 15 items of the PCB. The model selection process at each time point is detailed as follows: At T1, the AIC, BIC, and aBIC indices decreased as the number of subgroups increased from 1 to 5. Although the five-subgroup model had an entropy value greater than 0.8, its LMR test was not statistically significant (p > .05). Comparing the four-subgroup and three-subgroup models, the decreases in AIC, BIC, and aBIC were minimal. Therefore, considering model parsimony and interpretability, the three-subgroup model was chosen as the optimal model at T1. At T2, similar trends were observed, with AIC, BIC, and aBIC decreasing as the number of subgroups increased. The five-subgroup model again had an entropy value greater than 0.8, and all LMR values were less than 0.05. Given the minimal changes in fit indices when comparing the four-subgroup and three-subgroup models, the three-subgroup model was deemed optimal at T2 as well. This model selection is detailed in Table 3.

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Table 3.

Model Fit Indices for Latent Profile Analyses.

Profiles	AIC	BIC	ABIC	pLMRT	pBLRT	Entropy	Group sizes
T1 (N = 1014)
1class	46,120.30	46,267.95	46,172.66
2class	41,917.08	42,143.48	41,997.38	<0.001	<0.001	0.957	0.35/0.65
3class	40,225. 75	40,530. 89	40,333. 97	<0.001	<0.001	0 . 936	0 . 39/0 . 32/0 . 29
4class	39,910.59	40,294.48	40,046.74	0.040	<0.001	0.926	0.27/0.29/0.39/0.05
5class	39,684.68	40,147.31	39,848.76	0.481	<0.001	0.892	0.26/0.37/0.18/0.13/0.06
T2 (N = 1014)
1class	46,448.81	46,596.46	46,501.18
2class	43,663.37	43,889.77	43,743.67	<0.001	<0.001	0.867	0.53/0.47
3class	42,593. 42	42,898. 56	42,701. 64	<0.001	<0.001	0 . 869	0 . 35/0 . 36/0 . 29
4class	41,921.60	42,305.49	42,057.76	0.006	<0.001	0.877	0.13/0.28/0.29/0.30
5class	41,448.14	41,910.77	41,612.22	0.004	<0.001	0.875	0.13/0.25/0.28/0.12/0.22

Note: Values in bold indicate the best-fitting model. AIC = Akaike information criterion; BIC = Bayesian information criterion; aBIC = sample size-adjusted Bayesian information criterion; pLMRT = p-values for Lo-Mendell-Rubin adjusted ***likelihood ratio test for k vs. k − 1 profiles; pBLRT = p-values for bootstrapped likelihood ratio test.

Among them, subgroup 1 (T1, 39.3%; T2, 35.1%) had the highest score in career support and the lowest scores in career interference and lack of engagement, and thus it was thus named the “Support” group. Subgroup 2 (T1, 32.2%; T2, 36.1%) had relatively high scores in career interference and lack of engagement and a relatively low score in career support, and thus it was named the “Interference-lack of engagement” group. Subgroup 3 (T1, 28.5%; T2, 28.8%) had relatively high scores in both career support and career interference and a relatively low score in lack of engagement, and thus it was named the “Support-Interference” group. These subgroups are illustrated in Figures 1 and 2.

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Figure 1.

Latent profile of parental career-related behaviors at T1.

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Figure 2.

Latent profile of parental career-related behaviors at T2.

Analysis of Latent Transitions of Parental Career-Related Behaviors of Secondary Vocational Students and Latent Transition Patterns

LTA is based on conditional probabilities, which can illustrate the transition patterns of parental career-related behaviors across two time points. Given the optimal division of latent profiles into three groups at both T1 and T2, LTA was conducted in this study. The results, presented in Figure 3, indicate that the “Support” group had the highest probability of remaining in the same group (72%). In comparison, the “Interference-lack of engagement” group (50%) and the “Support-Interference” group (48%) had similar probabilities of transitioning.

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Figure 3.

Stabilities and transitions of parental career-related behaviors.

Based on the transition trends of the participants across the two time points, this study categorized the transition patterns into four types. First, participants who remained in the “Support” group at both time points were labeled as the “Stable High-Quality Career Nurturing” group (abbreviated as SH). Second, participants who consistently stayed in the “Interference-lack of engagement” group or the “Support-Interference” group were labeled as the “Stable Low or Lower-Quality Career Nurturing” group (abbreviated as SL). Third, participants also demonstrated a transition pattern from a lower quality career nurturing group to a higher quality one. Therefore, those who transitioned from the “Interference-lack of engagement” group to the “Support-Interference” group or the “Support” group, as well as those who transitioned from the “Support-Interference” group to the “Support” group, were labeled as the “Career Nurturing Improvement” group (abbreviated as CI). Fourth, participants also showed a transition pattern from a higher quality career nurturing group to a lower quality one. Hence, those who transitioned from the “Support” group to the “Support-Interference” group or the “Interference-lack of engagement” group, as well as those who transitioned from the Support-Interference group to the “Interference-lack of engagement” group, were labeled as the “Career Nurturing Decline” group (abbreviated as CD). For detailed transition probabilities, see Table 4.

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Table 4.

Composition Sources Subgroups of Latent Transition Patterns in Parental Career-Related Behaviors.

Latent Transition Patterns	Composition of Latent Transition Patterns
SH (N = 285; 28.11%)	S to S (N = 285)
SL (N = 311; 30.67%)	I-IE to I-IE (N = 167)	S-I to S-I (N = 144)
CI (N = 175; 17.26%)	I-IE to S-I (N = 108)	S-I to S (N = 15)	I-IE to S (N = 52)
CD (N = 243; 23.96%)	S to I-IE (N = 69)	S to I-S (N = 37)	S-I to I-IE (N = 137)

Note: Names and abbreviations of different latent profile subgroups: support group = S, interference-lack of engagement group = I-IE; support-interference group = S-I; names and abbreviations of different latent transition patterns: stable high-quality career nurturing group = SH, stable low or low-quality career nurturing group = SL, career nurturing improvement group = CI; career nurturing decline group = CD.

Mediation of School Interpersonal Support (i.e., Teacher Support and Peer Support) Between Parental Career-Related Behaviors Transition Patterns and Career Adaptability

To test the hypothesized parallel mediating mechanisms, we conducted path analysis using Mplus 8.3. The independent variable was the multi-categorical latent transition pattern, dummy-coded with the stable high-quality career nurturing (SH) group as the reference. Career adaptability at Time 2 (T2) was the dependent variable. Perceived teacher support and perceived peer support at Time 1 (T1) were specified as parallel mediators. All continuous variables were standardized. The model controlled for gender, grade, family location, family SES, and career adaptability at T1.

We employed a model constraint approach to estimate and compare the specific indirect effects. Using the maximum-likelihood estimator with bootstrapping (5,000 resamples), we calculated the indirect effects for each transition pattern (SL, CI, CD) through each mediator (teacher and peer support). Crucially, pairwise contrasts between the two specific indirect effects (peer support path vs. teacher support path) were formally tested within the same model to determine if their magnitudes differed significantly.

The results (see Figure 4 and Table 5) supported the mediating roles. More importantly, the model comparisons confirmed that for each transition pattern—SL (Δβ = 0.06, p < .01), CI (Δβ = 0.04, p < .05), and CD (Δβ = 0.04, p < .05)—the mediating pathway via peer support was significantly stronger than the pathway via teacher support.

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Figure 4.

The mediation model of school interpersonal support between different latent transition patterns and career adaptability.

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Table 5.

The Results of the Mediation Effect Test.

Group (vs. SH)	Mediation Path	Standardized Indirect Effect (β)	Proportion of Total Effect	Bootstrap 95% CI (Unstandardized)	Effect Difference (TS - PS)
SL→	TS→CA T2	−0.04***	8.8%	[-0.06, -0.02]	0.06**
	PS→CA T2	−0.09***	23.1%	[-0.12, -0.06]
CI→	TS→CA T2	−0.04***	23.6%	[-0.07, -0.03]	0.04*
	PS→CA T2	−0.07***	46.5%	[-0.12, -0.06]
CD→	TS→CA T2	−0.06***	12.4%	[-0.09, -0.04]	0.04*
	PS→CA T2	−0.10***	20.9%	[-0.13, -0.07]

Note. “Stable high-quality career nurturing group” serves as the reference group, with gender, grade, their family location, family socioeconomic status, and career adaptability at T1 time as control variables.

Transition patterns: stable high-quality career nurturing group = SH; stable low or low-quality career nurturing group = SL; career nurturing improvement group = CI; career nurturing decline group = CD; TS = teacher support; PS = peer support.

In summary, the analysis supports Hypothesis 4, indicating that both sources of school interpersonal support mediate the relationship, with peer support playing a consistently and statistically larger role than teacher support.

Subgroups and Characteristics of Career-Related Parental Behaviors among Secondary Vocational Students

Parents of secondary vocational students exhibit both similarities and differences in career-related parental behaviors when compared to parents of general high school students, a pattern that reflects the unique socioeconomic and cultural conditions shaping this group (Zhou et al., 2020). For instance, the “Interference-lack of engagement” subgroup was observed only among secondary vocational students’ parents. These parents may struggle to participate effectively in their children's career development; constrained economic conditions and lower educational attainment (Zheng et al., 2022) may hinder them from providing resources or professional guidance (Schmid & Garrels, 2021). Consequently, their children may perceive a lack of parental involvement. At the same time, within a collectivist cultural context that emphasizes parental responsibility, these same parents may attempt to influence their children's career decisions based on their own limited experiences (Ren & Pope Edwards, 2015). This apparent contradiction aligns with the family investment model, which posits that family income and parental education levels, among other factors, can shape the choice and implementation of parenting strategies (Bradley & Corwyn, 2002; Shin & McCoy, 2022).

On the other hand, the “Support-Interference” subgroup was identified in both general high school students and secondary vocational students. This subgroup exhibits parenting that combines emotional and resource support with strict control (Zheng et al., 2022). These parents are actively involved in their children's career development but, influenced by Confucian culture, often impose expectations, dominate decision-making, and restrict explorations deemed “unrealistic” (Guan et al., 2016). Notably, in families with limited resources, parents may be more inclined to exercise control to mitigate risks and encourage early employment rather than further education (Nurrachmat & Sastiono, 2022). Such strategies may inadvertently undermine adolescents’ career autonomy and exploratory motivation (Xiang & Liu, 2018), thereby exerting a complex influence on their career adaptability. Overall, the diversity and complexity of secondary vocational students’ parental career-related behaviors highlight the unique needs and challenges for providing career guidance to this population.

The Latent Transition Patterns of Parental Career-Related Behaviors and Their Impact on Subsequent Career Adaptability of Secondary Vocational Students

From a dynamic perspective based on LTA, this study systematically characterized the group heterogeneity of career-related behaviors among parents of secondary vocational students and identified the latent transition patterns of these behaviors as they evolve.

The results indicated that the “Support” group exhibited the highest stability, while the “Interference-Lack of Engagement” and “Support-Interference” groups had higher probabilities of transitioning between subgroups. Specifically, about half of the parents in the “Interference-lack of engagement” group remained in the same group, while the other half transitioned to a higher quality career nurturing group. This finding suggests that these parents may have gradually recognized their children's need for greater autonomy in career exploration, thereby adjusting their behaviors to increase more positive career discussions and adapting to their children's evolving needs. Similarly, it is noteworthy that if the “Support-Interference” group did not maintain its status at T2, it was likely to transition to the “Interference-lack of engagement” group. This may be because as secondary vocational students grow, their need for autonomy in career exploration increases. However, due to limitations in family resources and parental career guidance abilities (Schmid & Garrels, 2021), students may perceive a decline in adequate support from their parents, leading to the perception of parental disengagement.

Based on these transition trends, this study categorized the career nurturing transition patterns into four distinct groups: SH group (N = 285; 28.11%), SL group (N = 311; 30.67%), CI group (N = 175; 17.26%), and CD group (N = 243; 23.96%). The analysis showed that the distribution of these four transition patterns was relatively balanced, reflecting that during this period, the career nurturing behaviors of parents exhibited both “stability” and “fluctuation,” as well as “improvement” and “decline” coexisting. Furthermore, compared to students in the SH group, those in the SL group and the CD group exhibited significantly lower levels of career adaptability. This finding underscores that both continuous and intermittent negative career nurturing behaviors by parents can lead to decreased career adaptability among secondary vocational students, thereby enriching the understanding of the antecedents of adolescents’ career adaptability.

The Mediating Effect of School Interpersonal Support (Teacher Support and Peer Support)

This study reveals the underlying conditions and mechanisms linking different patterns of parental career-related behavior transitions to the subsequent career adaptability of secondary vocational students, highlighting teacher support and peer support as two indirect factors. The results indicate that, compared to the SH group, students in other groups perceived less school support, which consequently led to lower levels of career adaptability. This finding underscores the collective influence of parents, teachers, and peers on adolescents’ career development (Hlaďo et al., 2020), supports CCT, and provides new evidence for the spillover effects among family, school, and individual factors.

Specifically, when parents provide consistent and positive career support (e.g., career guidance, encouragement of interests, and home-school collaboration), secondary vocational students can have positive psychological experiences, even under conditions of limited family economic capital. These experiences can be transferred to the school environment, manifesting in more proactive teacher–student communication, peer cooperation, and academic engagement (Hoferichter et al., 2022; Liu et al., 2022; Xu et al., 2023). In turn, teachers and peers tend to offer more supportive feedback, further enhancing the students’ career adaptability (Hlaďo et al., 2020).

In contrast, when parents adopt consistently or intermittently negative parenting behaviors related to career development (e.g., emotional detachment, excessive intervention, or a laissez-faire approach that places full responsibility on the school), students are more likely to exhibit decreased motivation, interpersonal conflict, and behavioral issues at school (Wen et al., 2025). These behaviors may reduce the willingness of teachers and peers to provide support (Hlaďo et al., 2020). This situation not only hinders the development of career adaptability but may also increase the risk of behavioral problems and school dropout (Pan et al., 2021; Zhao et al., 2017).

Notably, this study found that the career nurturing improvement (CI) intervention had no significant direct effect on T2 career adaptability (β = −0.047). This finding appears inconsistent with previous literature linking positive parenting to adolescent career adaptability (Feng et al., 2024; Liang et al., 2023; Zhou et al., 2020) and may be explained by two contextual factors. First, adolescents with a history of maladaptive parenting often exhibit delayed trust in parental support (Sychynska, 2025). Coupled with relatively lower family SES and cultural capital sometimes observed among the secondary vocational student population (Chu et al., 2015; Wang & Guo, 2019), parental capacity to provide timely and effective career resources is often constrained (Schmid & Garrels, 2021; Zheng et al., 2022), thereby attenuating the intervention's immediate impact. Second, this result highlights the critical mediating role of school support, aligning with research that identifies teacher and peer support as pivotal for translating contextual resources into career adaptability (Hlaďo et al., 2020; Xu et al., 2023). Positive parenting changes, such as greater career awareness, likely require activation through structured school-based guidance and peer interaction to become actionable student competencies. Thus, while not diminishing the long-term value of parenting, this pattern underscores schools as a central vehicle for converting family inputs into measurable adolescent outcomes.

Furthermore, our analysis identifies a distinct pattern in vocational schools’ interpersonal support dynamics: peer support exerts a stronger mediating effect than teacher support, a finding that diverges from Wang et al.'s (2024) general high school-based results and underscores the need for a vocational education-specific ecological interpretation. Secondary vocational schools’ teaching staff shortages and insufficient professional knowledge reserves (Fan et al., 2024; Mahir et al., 2019) weaken students’ perceptions of teacher support, and García-Moya et al. (2023) note that robust teacher support alleviates academic stress while inadequate support correlates with higher stress and strained teacher–student relationships. Vocational learning's collaborative, practice-centric ecology amplifies peer roles, as shared tasks foster cohesive informal learning communities (Wen et al., 2025); meanwhile, vocational education's core goals generate needs that peer groups’ accessible, egalitarian dynamics (Baliclic et al., 2025) uniquely address, with students prioritizing peer-derived resources (Felgenhauer et al., 2021; Hoferichter et al., 2022) over formal teacher guidance. Ultimately, instructional support limitations and the learning environment's collaborative attributes shape the interpersonal support landscape, elevating peer support to a central mediating role and establishing peer influence as a primary developmental resource.

Based on these findings, it is recommended that future interventions establish institutionalized home-school collaboration mechanisms to transform positive parenting practices into systematic support resources within the school ecology. Meanwhile, while ensuring the quality of teacher support, efforts should be made to systematically develop and strengthen peer support systems, thereby effectively optimizing the career development pathways of secondary vocational students.

Theoretical and Practical Contributions

By analyzing a representative sample of Chinese vocational secondary students, this study elucidates the mechanism underlying the link between parental career-related behaviors and students’ career adaptability while providing actionable guidance for fostering such adaptability.

Theoretically, this study transcends the variable-centered limitations of prior research on parental career-related behaviors through an innovative individual-centered longitudinal design. This design identifies distinct latent profiles of parental career-related behaviors and explores their temporal transitions, extending CCT (Savickas, 2013) by suggesting that parental career-related behaviors can differ between vocational secondary and general high school students. Indeed, significant within-group heterogeneity in parental career-related behaviors may exist even within seemingly homogeneous demographic or cultural groups. More importantly, it reveals that parental career behaviors are not static but dynamically adjust to influence adolescent career adaptability through directional associations with teacher and peer support in school contexts, enriching the dynamic perspective on family factors’ role in career development within this theoretical framework. Additionally, the study extends spillover theory's application to family-school cross-system interactions by identifying the directional spillover mechanism from family to school. Spillover theory posits that emotions, behaviors, and resource experiences in one social system such as the family can transfer to another such as the school to impact cross-system interactions and developmental outcomes (Liu et al., 2022; Repetti, 1987). The present findings demonstrate that variations in the quality and mode of parental career guidance shape students’ perceptions of teacher and peer support to influence their career adaptability, broadening spillover theory's scope, establishing a theoretical link between the two theories, and advancing understanding of multi-contextual interaction and cross-system spillover in adolescent development.

Practically, this study offers targeted guidance for vocational secondary educators, policymakers, and families whose collaborative framework holds unique value in optimizing career support effectiveness compared with fragmented single-agent strategies. For educators, establishing systematic home-school collaboration mechanisms including parent workshops (Ayub, 2017), bidirectional digital communication channels, and parent open days (Fan et al., 2024) is foundational, while strengthening career guidance teachers’ professional competence through specialized training and personalized tools (Suryadi et al., 2020) alongside peer support systems complements this mechanism to boost students’ career development engagement. For policymakers, earmarking special funds for home-school collaboration infrastructure and teacher training is essential, as is promoting social resource integration through school–enterprise partnerships for skill workshops and training bases (Fan et al., 2024) to bridge family support and vocational opportunities. For families, providing feedback on continuous or intermittent negative career nurturing behaviors is crucial given their direct and spillover-related adverse impacts, whereas prioritizing supportive career guidance (Liang et al., 2023) maximizes positive family-to-school spillover effects.

Although designed for vocational secondary schools, the core principles of home-school collaboration, teacher professional development, social resource integration, and positive family guidance offer implications for other educational settings including general high schools and vocational training institutions, with context-specific adaptations remaining imperative.