This quasi-experimental study was conducted over a five-week period from September to October 2024 at Jilin Medical University, Jilin Province, China. Ethical approval was obtained from the Institutional Ethics Committee of UCSI University (Approval No. IEC-2024-FOSSLA-0052). Two intact classes were randomly selected to participate in the study. All students in each selected class were invited to participate, no individual-level randomization was performed. Students majoring in Health Services and Management were assigned to the experimental group, while those majoring in Medical Information Engineering formed the control group. The experimental group consisted of 40 students (12 males and 28 females), and the control group consisted of 35 students (14 males and 21 females). Gender composition did not differ between groups, χ² (1, N = 75) = 2.47, p = 0.125.

This study used a quasi-experimental design with a waiting-list control. Two intact classes were selected for participation, allocation to condition followed pre-existing class membership rather than individual randomization (Johnson and Christensen, 2000). To mitigate selection bias, baseline (T1) measures were collected before the intervention, and baseline equivalence at T1 was assessed on demographics and outcomes. The experimental group received the Career Planning Education (CPE) intervention, and the control group was scheduled to receive it after study completion. Outcomes were assessed at T1 (pretest), T2 (immediate post-intervention), and T3 (4-week follow-up) following Lam and Santos (2018). This multi-wave data collection allowed for the evaluation of both immediate and sustained effects of the intervention.

All questionnaires were administered online using Questionnaire Star.¹ Prior to participation, students received detailed information about the study and provided written informed consent. Anonymity and confidentiality were strictly maintained throughout the research process.

Data was analyzed using SPSS 26. To evaluate Hypotheses, a multivariate analysis of variance (MANOVA) was conducted to assess group and time effects on CA and CDMSE.

The Career Planning Education (CPE) program was developed based on Career Construction Theory (Savickas, 2005), Social Cognitive Theory (Bandura, 1977) and informed by a comprehensive literature review. The theoretical structure of the program centered on two core components. The first, career adaptability, draws from Savickas’s four-dimensional framework, including career concern (future orientation and planning), career control (self-directed action), career curiosity (exploration of options), and career confidence (belief in one’s capacity to solve problems and achieve goals). The second component, career decision-making self-efficacy, is rooted in Bandura’s theory and includes five task dimensions, self-appraisal, occupational information gathering, goal selection, planning, and problem solving (Betz et al., 1996). Instructional strategies were also designed to activate the four sources of self-efficacy, performance accomplishments, vicarious learning, verbal persuasion, and physiological/emotional regulation, to enhance students’ beliefs in their capacity to make effective career decisions.

Although the overall structure of the CPE module could be applied to other disciplines, the curriculum in this study was tailored to allied medical students. Teaching materials drew on clinical cases, such as doctor-patient communication, interprofessional teamwork and competency frameworks for health professionals. Group activities required students to examine typical career trajectories of allied health workers in China, to compare different specialties and practice settings, and to link their own plans to concrete stages of medical training such as internship. In doing so, the module integrated general career-planning skills with the exploration of professional identity in medicine.

To ensure content validity and contextual relevance, the draft program was reviewed by three experts in career education and psychology, whose feedback was incorporated prior to implementation.

To ensure instructional fidelity, lecturers received targeted training sessions covering the program’s theoretical foundations, research framework, and detailed lesson plans.

The primary objective of the program was to shift the focus of career education from traditional person-job matching to the active construction of a lifelong career path. The program’s objectives were to enhance students’ self-understanding (interests, abilities, and values), broaden their career awareness, strengthen decision-making skills, and support the formulation of both short- and long-term career goals.

The program adopted a group-based learning model. To promote active participation and reduce anxiety associated with group work, students were allowed to form self-selected groups of 4–6 members. This approach fostered a psychologically safe and emotionally supportive environment, aligning with Bandura’s concept of physiological and emotional regulation as a source of self-efficacy.

To support learning and reflection, students used a career development handbook to record their insights throughout the course. They were encouraged to share their reflections either within small groups or through class-wide presentations. This process represents performance accomplishments, the most powerful source of self-efficacy in Bandura’s framework, as it allows students to experience and demonstrate mastery.

Additionally, structured peer feedback was incorporated during group discussions, enabling students to observe others’ progress and receive constructive input. This reflects the mechanism of vicarious learning, where observing peer performance and receiving encouragement enhances students’ belief in their own abilities.

Throughout the sessions, instructors provided targeted verbal encouragement to affirm students’ efforts and progress, particularly during reflection sharing and group discussions. This strategy aligns with Bandura’s concept of verbal persuasion, which emphasizes the role of positive reinforcement in strengthening learners’ beliefs in their own capabilities.

The program spanned 5 weeks and consisted of two 1.5-h sessions per week, totaling 10 sessions in all. The full curriculum schedule is shown in Table 1.

All measures employed in this study were previously validated and demonstrated good reliability in Chinese samples. All items were rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).

Both instruments were pilot tested with a randomly selected class of 41 students majoring in Health Inspection and Quarantine. The results demonstrated excellent internal consistency in the current context, with Cronbach’s α values of 0.98 for the Career Adapt-Abilities Scale-China Form (CAAS-CF) and 0.98 for the Career Decision-Making Self-Efficacy Scale-Short Form (CDMSE-SF). These findings provide a solid psychometric foundation for the main study.

Descriptive statistics for career adaptability (CA) and career decision-making self-efficacy (CDMSE) across the three time points and two groups are presented in Table 2. Normality was assessed using skewness and kurtosis values, which are commonly used indicators of distribution shape. According to Bulmer (1979), values between −1 and +1 suggest approximate normality. All variables at the three points met this criterion (see Table 2), supporting the use of parametric statistical analyses.

Independent samples t-tests were conducted to examine baseline equivalence. Results indicated no significant differences between the experimental and control groups on career adaptability (t = 0.190, p = 0.850) or career decision-making self-efficacy (t = 1.624, p = 0.109), suggesting group equivalence at baseline.

The assumption of homogeneity of variance was tested using Levene’s test, all p-values exceeded 0.05, supporting the assumption of equal variances.

A Pearson correlation analysis was conducted between career adaptability and career decision-making self-efficacy at the pretest (Time 1) across the full sample. The results indicated a significant positive correlation (r = 0.778, p < 0.01), suggesting that the two constructions are related, thereby supporting the use of Multivariate Analysis of Variance (MANOVA) to examine the effects of the intervention.

These findings justified the use of MANOVA to examine the effects of the career planning education program on both dependent variables simultaneously.

To examine the overall effect of the career planning education (CPE) program on career adaptability (CA) and career decision-making self-efficacy (CDMSE), MANOVA was conducted. The model included group (experimental vs. control) as the between-subjects factor and time (T1: pretest, T2: posttest, T3: follow-up) as the within-subjects factor. A MANOVA revealed a significant Group × Time interaction, Wilks’ Λ = 0.957, F (4, 436) = 2.304, p = 0.049, partial η² = 0.022, indicating that changes in CA and CDMSE over time differed between the experimental and control group, with greater gains in the experimental class. Univariate tests are summarized in the next sections.

CA increased from M = 3.545 (T1) to M = 4.007 (T2), p < 0.05 (Table 3, Figure 1), partial η² = 0.072. CDMSE increased from M = 3.251 (T1) to M = 3.814 (T2), p < 0.05 (Table 3, Figure 2), partial η² = 0.087. Thus, H1 was supported.

CA. T3 (M = 3.740) was not significantly higher than T1 (M = 3.545), p > 0.05, partial η² = 0.014 (Table 3; Figure 1), indicating attenuation from the posttest peak (T2 = 4.007) and no reliable maintenance above baseline. CDMSE. T3 (M = 3.601) remained significantly higher than T1 (M = 3.251), p < 0.05, partial η² = 0.014 (Table 3; Figure 2), consistent with partial maintenance despite attenuation from T2 = 3.814. Thus, H2 was not supported as stated, although CDMSE showed partial maintenance above baseline whereas CA did not.

At T2, the experimental group exceeded the control group on CA (4.007 vs. 3.588), p < 0.05 (Table 4), partial η² = 0.056. At T2, the experimental group exceeded the control group on CDMSE (3.814 vs. 3.525), p < 0.05 (Table 4), partial η² = 0.023.

At T3, the experimental group exceeded the control group on CA (3.740 vs. 3.653), p > 0.05 (Table 4), partial η² = 0.003. At T3, the experimental group exceeded the control group on CDMSE (3.601 vs. 3.589), p > 0.05 (Table 4), partial η² = 0.000.

Thus, H3 was supported at post-test (T2), but the between-group differences were no longer significant at follow-up (T3).

The findings provide strong support for Hypothesis 1, confirming the effectiveness of the structured Career Planning Education (CPE) intervention in enhancing Career Adaptability (CA) among the experimental group. Specifically, the significant increase in CA from pre-test to post-test, coupled with the experimental group’s significantly higher scores compared to the control group at post-test, highlights the immediate impact of the intervention.

However, a slight decline in CA scores was observed at follow-up (T3), with the experimental group scoring lower than at post-test. Although the Time 3 scores remained higher than the pre-test and were still above those of the control group, these differences were not statistically significant. This reduction may reflect the natural attenuation of intervention effects over time, particularly in the absence of continued reinforcement or structured follow-up activities. It is also possible that students, having returned to their regular academic routines, shifted focus away from career-related tasks, which could have contributed to the diminished gains. Given that the observed magnitudes at T3 were very small, the lack of statistical significance may also reflect limited statistical power at the current sample size rather than a true absence of effects.

In contrast, the control group did not exhibit significant changes across any of the three time points, suggesting that natural development or repeated questionnaire exposure alone was insufficient to meaningfully enhance CA. These results suggest that targeted career planning education can promote students’ adaptability in the short term in navigating career development tasks and transitions.

From a theoretical perspective, the CA findings are consistent with Career Construction Theory (Savickas, 2005), which conceptualizes adaptability as a set of resources for managing career tasks and transitions. In the present study, however, CCT was not used in isolation or in a simple one-to-one mapping onto the four CA dimensions. Rather, activities for allied medical students combined CCT with Social Cognitive Theory by using the same teaching tasks to build adaptability resources and to provide efficacy-enhancing experiences. For example, sessions on medical career paths asked students to draw career lifelines, construct family career trees and write “future-self” reflections linked to clinical roles, while discussing real cases of specialty choices. These exercises were intended to strengthen career concern, control and curiosity (CCT), and at the same time to offer mastery and vicarious experiences that support self-appraisal and information gathering in medical career decision-making (SCT). Group work in which students compared residency and specialty options, analyzed doctor-patient communication scenarios and planned their own stages of training was designed to enhance career confidence and openness to change, while providing structured practice in planning and problem solving. Taken together, these elements suggest that the CPE module operated as an integrated, theory-driven curriculum rather than a simple direct intervention targeting the four CA dimensions alone.

The findings of this study are consistent with prior research demonstrating the value of structured, theory-informed interventions in improving career adaptability (CA). For example, Teychenne et al. (2019) showed that even a brief online module, when aligned with Career Construction Theory, could produce measurable gains in CA among undergraduates. Similarly, Kepir Sávoly and Tuzgol Dost (2020) reported that a transition-focused program led to sustained CA improvements among senior students, echoing the short-term gains in the present study. Bal and Arikan (2020) further emphasized the effectiveness of multi-session curricula that incorporate self-reflection and decision-making, core elements also embedded in the current CPE intervention. In the context of medical education, Hur et al. (2018) found that targeted coaching reduced career indecision, a result that complements the improvements in career adaptability observed in our participants. Moreover, Gai et al. (2022) provided evidence from Chinese students that motivational interviewing can enhance CA, particularly among those with low baseline adaptability, aligning closely with the gains seen in our experimental group. More recent curriculum-integrated, online and life-design interventions show similar patterns of improvement in CA (Kim, 2022; Wetstone and Rice, 2023; Cardoso et al., 2022; Soares et al., 2022).

The results provide clear evidence that the Career Planning Education (CPE) intervention had a significant and positive impact on students’ career decision-making self-efficacy (CDMSE) in the short term. The substantial increase from pretest to posttest within the experimental group, as well as the significantly higher posttest scores compared to the control group, demonstrate the immediate effectiveness of the program in boosting confidence in making informed career decisions.

Although a slight decline in CDMSE was observed at the follow-up (T3), the experimental group still maintained a within-group score significantly higher than at pretest, indicating attenuation with limited maintenance relative to baseline; notably, between-group differences at T3 were nonsignificant. The lack of a statistically significant difference between the experimental and control groups at Time 3 may reflect the attenuation of intervention impact in the absence of ongoing reinforcement. It is also important to consider that the control group exhibited a relatively higher baseline score at pretest, which, although not statistically significant, may have reduced the observable between-group difference at follow-up. In addition to attenuation and baseline imbalance, because the observed effects at T3 were very small, our sample may not have had enough power to detect them.

In contrast, the control group showed no significant changes across the three time points, implying that the natural maturation process or repeated exposure to the measurement alone was insufficient to significantly enhance their decision-making self-efficacy. Taken together, these findings highlight the short-term efficacy and partial long-term sustainability of the CPE intervention, while also pointing to the importance of continuous support in maintaining growth in CDMSE.

From a theoretical standpoint, these CDMSE findings are consistent with Social Cognitive Theory (Bandura, 1977, 1986), which views self-efficacy as shaped by performance accomplishments, vicarious experiences, verbal persuasion and physiological states. For example, group tasks in which students compared specialty options, analyzed doctor-patient communication scenarios or discussed typical dilemmas faced after employ were designed to provide mastery experiences and modeling, as students practiced information gathering, goal selection, planning and problem solving in realistic medical contexts. Class presentations and peer feedback on individual career plans offered further opportunities for verbal persuasion and for observing how peers approached similar decisions, while the use of small, self-selected groups and structured reflection aimed to provide an emotionally safe environment for exploring uncertainties about the future. These same activities were also intended to strengthen adaptability resources, so that the module operated as an integrated CCT- and SCT-informed curriculum rather than two separate, direct interventions targeting CA and CDMSE in isolation.

The present findings align with existing studies demonstrating the effectiveness of theory-based career interventions in enhancing CDMSE. Similar improvements were reported by Talib et al. (2015) and Lam and Santos (2018), whose programs emphasized identity exploration and career knowledge. While those interventions yielded short-term gains, the current study extends the evidence by demonstrating partially sustained effects at follow-up. Studies by Osborn et al. (2020) and Chukwuedo et al. (2021) further support the value of structured guidance, reflection, and metacognitive skill-building in strengthening decision-related self-efficacy. Additionally, research by EI Naggar et al. (2021) and Putri et al. (2019) highlight the role of contextualized career support among medical students. Meta-analytic evidence also points to robust effects: Özlem (2019) found that career interventions for university students were associated with a large overall increase in CDMSE, and Sharapova et al.’s (2023) review of school-based career guidance reported consistent benefits for students’ career-related beliefs, including decision-making self-efficacy. Echoing our pattern, a recent review of school-based career interventions reported consistent gains in both CA and CDMSE, with stronger short-term effects on CDMSE and weaker maintenance at follow-up (Wang et al., 2024). This supports our finding of within-group maintenance for CDMSE at T3 and underscores the need for post-course boosters and spaced practice.