Abstract
Purpose
To avoid indecisiveness and a lack of direction in making a successful career transition, it may be necessary to modify the career transition process through career mentorship (CM). The study aims to investigate career adaptability as pathways through which CM is related to trainees’ career transition.
Design/methodology/approach
A three times cross-sectional data were collected from 480 national industrial skills development program (NISDP) trainees among five industrial training fund (ITF) trainees in Southeastern Nigeria.
Findings
The analysis revealed that CM positively associated with the trainees’ career transition behaviors. CM is also positively associated with the trainees’ career adaptability. Also, career adaptability is positively associated with trainees’ career transition behaviors. Likewise, career adaptability mediated the link between CM and career transition behaviors.
Originality/value
Conducting the study in a previously neglected context extended our understanding of the indirect relationship between CM and trainees’ career transition behavior.
Keywords
Citation
Orji, C.T. and Herachwati, N. (2024), "Career transition and mentorship nexus: unmasking the mediating role of career adaptability", Higher Education, Skills and Work-Based Learning, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/HESWBL-06-2024-0176
Publisher
:Emerald Publishing Limited
Copyright © 2024, Chibueze Tobias Orji and Nuri Herachwati
License
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
The completion of vocational education and training (VET) and the transition to work are crucial steps in a person’s career path. However, many trainees struggle with making career-related decisions that can determine their future success (Sós, 2018). This is especially true in developing countries like Nigeria, where young people often lack direction when it comes to choosing a career and transitioning into the workforce. Career mentorship (CM) can be implemented to help trainees make better career choices and successfully transition into their chosen field.
CM plays a vital role in individual career development and smooth career transitions in practical skills training. Craig et al. (2013) define CM as a supportive relationship between a mentor (an experienced person) and a protégé (a less experienced person) that focuses on improving the protégé’s career development and behavior. The main goal of CM is to prevent career thwarting behavior and assist less experienced individuals in making necessary career changes and improvements (Scandura and Williams, 2004). In this study, CM refers to the connection between an experienced person and a trainee, aiming to help the trainee make adjustments in their career choice, decisions and development. Previous research (e.g. Ogbuanya and Chukwuedo, 2017; Rajabi et al., 2012) has shown that CM predicts career success and facilitates adjustments in career choices, decisions and development. Similarly, mentoring has been found to enhance an individual’s career development and behavior (Jyoti and Sharma, 2015). Therefore, the focus of this study is to optimize the career transition of trainees in industrial training fund (ITF) vocational training centers by providing them with the necessary support to make better career decisions.
Career transition is an ongoing process that involves difficult decisions and uncertainties (Ling and O’Brien, 2013). Trainees often struggle to find employment after completing their training, leading to career thwarting behaviors and jobs that offer limited opportunities for growth. Additionally, these trainees lack the traditional support systems and services needed to make better career decisions and avoid career thwarting behavior. Career development theorists have recognized the importance of psychological resources in helping individuals navigate the challenges of career-related decision-making (Hirschi and Valero, 2015). However, despite previous research on CM (e.g. Ogbuanya and Chukwuedo, 2017; Okolie et al., 2020), little is known about how CM activities can improve the career transition of trainees in vocational training centers. Existing studies have primarily focused on university students and vocational education students in developed countries, which may not be applicable to informal sector trainees in developing countries who face unique circumstances when making career decisions. This highlights a significant gap in both theoretical and empirical knowledge that should be systematically explored.
This study aims to address a research gap by examining the psychosocial construct that represents an individual’s coping resources for current and anticipated tasks in relation to career transition. The study seeks to provide insight into whether career adaptability, can optimize the career transition of trainees in vocational training centers. Career adaptability, which is an important resource for successful career transition Konstam et al. (2015), refers to a trainee’s readiness to cope with tasks related to preparing for and participating in the work role, as well as adapting to changes in work and working conditions (Savickas, 1997). The four global dimensions of career adaptability, known as adapt-abilities, include concern, control, curiosity and confidence and they aid in work-related transitions (Savickas, 2013). According to the career construction theory (CCT), vocational trainees should approach career tasks with concern for the future (planning), a sense of personal control over their career (decision-making, being decisive), curiosity about career options (exploring, being inquisitive) and confidence to construct a future and deal with career barriers (problem-solving, being efficacious (Hirschi et al., 2015; Savickas, 2005). These self-regulatory resources can be drawn upon by trainees during training mentorship to navigate complex or unfamiliar career development challenges toward a successful career transition (Porfeli and Savickas, 2012).
Previous studies on career adaptability have primarily focused on the relationship between social support and career adaptability. For instance, a study by Hlad′o et al. (2020) on vocational upper secondary students in the Czech Republic revealed that different sources of social support were associated with career adaptability components. The career construction model of adaptation (Parola and Marcionetti, 2022) also suggests that career decision-making difficulties and life satisfaction are important outcomes of adaptation, and career adaptability is a crucial resource for achieving positive adaptation outcomes. Additionally, career adaptability has been conceptually and empirically linked to successful career transitions (Ghosh et al., 2019). However, there is a lack of empirical research exploring the mediating roles of career adaptability dimensions (i.e. concern, control, curiosity and confidence) in these associations. Therefore, this study aims to determine the causal relationships between CM, career concern, career control, career curiosity, career confidence and career transition as well as the mediating roles of career adaptability dimensions in these relationships. The study is grounded in CCT, and specifically focuses on the construct of career adaptability which helps to understand the self-regulatory capacities that enable individuals to navigate unknown, complex and ambiguous career challenges and tasks (Savickas, 2005).
Overall, this study will contribute to the existing literature on CM and career transition by proposing and testing a model that incorporates career concern, career control, career curiosity and career confidence as mediating variables through which CM influences career transition. Data were collected at three points of measurement, and a robust empirical analysis was conducted using multiple regression and BC bootstrap with regression estimates.
Theoretical and hypotheses development
CM is essential to career development, choice making, transitions and success (Ogbuanya and Chukwuedo, 2017). CM can contribute to career changes and improvements through career, psychological or instrumental support to foster smooth career transition (Renn et al., 2014). However, CCT offers a powerful framework for understanding the messy environments in which career transitions occur and in turn provides a practical tool for helping individuals adapt to change. Thus, to understand how participation in CM influences career transition and adaptability, we draw upon CCT; (Savickas, 2005); as a framework. CCT suggests that individuals actively shape their careers by finding meaning in their work experiences and career goals. That is, they impose directions on their careers when they engage in passionate relational career, psychological or instrumental support to reflect on various life roles as a trainee to enhance their career development and behavior. By reflecting on experiences in these roles, individuals are able to align their career experiences with their aspirations (Savickas, 2013).
Career mentorship, career adaptability and career transitioning behavior
The completion of career training and the subsequent transition to work are important steps on the career pathway. Graduate trainees who move directly from career training into the workforce face some of the most challenging developmental tasks of making important career-related decisions that can determine their future success (Hlaďo et al., 2019). Career mentoring is a crucial factor in the successful transition and employment of unemployed youths (Jyoti and Sharma, 2015; Ogbuanya and Chukwuedo, 2017). Renn et al. (2014) recognized that mentor career support is necessary for the career development of students during transition. Mentoring is a passionate exchange where a more experienced person (mentor) provides career, psychological or instrumental support to a less experienced person (protégé) in order to enhance their career development and behavior (Craig et al., 2013). Its primary purpose is to help the less experienced person develop their career and overcome career obstacles (Ogbuanya and Chukwuedo, 2017). Career development theorists have long been interested in exploring the psychological resources that can help individuals successfully manage their careers (Hirschi and Valero, 2015). Previous studies have shown that CM predicts career-related behaviors and performance in practical skills (Ogbuanya and Chukwuedo, 2017), students’ career ambitions, interests, personal development plans and employability (Okolie et al., 2020); and career success and intention to learn on or for the job (Koen et al., 2012; Rajabi et al., 2012). Therefore, we argue that trainees who are mentored during career training may exhibit enhanced career and psychological behaviors to overcome the most challenging developmental tasks of their lives, which involve making important career-related decisions that can determine their future success (Koen et al., 2012; Sós, 2018). Based on the discussion so far and our theoretical argument, we hypothesize the following:
CM is directly and positively associated with trainees’ career transitioning (a) readiness, (b) confidence, (c) control, (d) support and (e) independence
CM is directly and positively associated with trainees’ career adaptability (a) concern, (b) control (c) curiosity and (d) confidence.
Career adaptability as a mediator
Career adaptability, an important component of CCT, refers to the self-regulatory strengths that individuals possess and use in response to present or future vocational tasks (Savickas, 1997). The construct of career adaptability reflects the internal resources that enable people to manage their career-related tasks and transitions, as well as adapt to social changes (Porfeli and Savickas, 2012). Numerous studies have demonstrated the crucial role of career adaptability in successfully
Navigating the school-to-work transition (Konstam et al., 2015; Van der Horst et al., 2017). Research has also shown that higher levels of career adaptability increase an individual’s likelihood of finding a suitable job (Koen et al., 2012). Therefore, individuals who possess career adaptability qualities such as planning (concern), decisiveness (control), self-efficacy in mastering career tasks (confidence) and active exploration (curiosity) are more likely to transition back to work successfully and secure high-quality employment (Hlad′o et al., 2020; Van der Horst et al., 2017). In fact, the development of adaptable behavior during CM may indirectly influence an individual’s career transition. Drawing on prior evidence and CCT principles, we anticipate that career adaptability may directly associate and influence how CM indirectly facilitates the transition of trainees from career training to the workforce (see Figure 1). Thus, we hypothesized the following:
Career adaptability (concern, control, curiosity and confidence) is directly and positively associated with trainees’ career transitioning (namely, (a) readiness, (a) confidence, (c) control, (d) support and (e) independence).
CM will positively influence career transitioning (namely, (a) readiness, (a) confidence, (c) control, (d) support and (e) independence) through the discrete dimensions of career adaptability (namely, (a) concern, (b) control, (c) curiosity and (d) confidence).
Method
Participants and procedure
Drawing on earlier studies of CM (e.g. Ogbuanya and Chukwuedo, 2017; Okolie et al., 2020), we sampled the national industrial skills development program (NISDP) trainees of ITF to participate in the study. The NISDP is a skills acquisition program by ITF aimed at youths aged between 18 and 35. It was established as a key component of the National Industrial Revolution Plan (NIRP) and has provided training in various trades and crafts to over 100,000 Nigerians. Beneficiaries have been trained in more than 30 trades and crafts, including tailoring and fashion design, paint making, bead making, plumbing and pipe fitting, farming, confectionery, welding and fabrication, ICT, electrical installation, carpentry and woodwork, cosmetology, GSM repairs and plaster of Paris (POP). Other areas of training include animal fattening, goat rearing and milk processing, agric. service providing, motor mechanic, tie and dye, shoes and bag making, aluminum fabrication, hair dressing, event management/interior decoration, process control instrumentation, industrial/domestic electrical installation technology, fish farming and tiling, among others. We used these categories of trainees are because they are undecided and lack proper direction in making a successful career transition, thus, modifying their career transition process might be necessary. Data were collected at three points in time, with one-month interval between waves, from full-time trainees in all the ITF training centers in the Southeastern region of Nigeria. Prior to administering the measures, each participant was assigned a special code number and requested to provide the number in their subsequent responses. Then, in the administered questionnaire, the participants were also informed of the purpose of the research and confidentiality was assured. At Time 1, we collected data on gender, age, skill areas and the independent variable – CM. At Time 2, we contacted only the participants who took part in Time 1 to respond to surveys for the mediator variables (i.e. career adaptability – concern, control, curiosity and confidence). At Time 3, we administered the career transition measure only to participants who completed the Time 2 survey. Out of the 690 trainees initially contacted, we received 625 (90.6%) responses at Time 1. Of the 625 participants sampled at Time 2, we received 536 (85.8%) responses. At Time 3, we received 498 (92.9%) responses from the sampled participants. The attrition rate of participants from Time 1 to Time 3 was 30.7%.
We subsequently used the unique code numbers to match the data of each participant from the three waves and found that 480 responses were usable for analysis. Our three-wave data collection technique was acceptable, as a minimum of three-wave studies with the same participants is necessary for a decent mediation analysis in time-lagged models (Ugwu et al., 2023). We also believe that our one-month time intervals between T1 and T2, and T2 and T3 are suitable, as shorter measurement intervals have more power to detect an effect and lead to more accurate estimates of population parameters (Schoemann et al., 2017). Collecting the data at three-time points from the same participants using the same questionnaire with one-month time lag measurement intervals was to help mitigate concerns associated with common method bias. The data for this study were collected between September and December 2023. The following highlights the strengths of our study: the sample is unique, as more research on CM among NISDP trainees is needed; the size and composition of the sample are good; the research design, which collects data through multiple waves is helpful; the analytic approach is thoughtful, and there is reasonable justification for the multi-wave process. The participants consisted of both male (N = 198, Mage = 25.05) and female students (N = 282, Mage = 26.84) from various skill areas. These skill areas included electrical and solar installation (N = 53; 11%), furniture making and upholstery (N = 21; 4.4%), plumbing and pipe fitting (N = 21; 4.4%), tiling (N = 32; 6.7%), computer maintenance and GSM repairs (N = 93; 19.4%), fish and poultry farming (N = 70; 14.6%), hairdressing and beauty therapy (N = 61; 12.7%), garment making (N = 47; 9.8%) and catering services (N = 82; 17.1%).
Ethical considerations
We first obtained ethical approval and informed consent from trainees through ITF as well as their trade instructors who planned, organized and delivered training. Secondly, in the questionnaire, the participants were also informed of the purpose of the study, and confidentiality was maintained. Consequently, no trainee’s name or institution’s identity was retrieved or reported in order to protect the rights and welfare of the research participants.
Measure
Confirmatory factor analysis (CFA) was conducted on all measurement scales using AMOS 24.0 to calculate the data fit indexes for each scale. The following criteria were used to assess the data fit: x2/df ≤ 0.3; CFI, IFI and TLI ≥0.90; SRMR ≤0.08; RMSEA ≤0.06; PClose ≥0.05 (Hu and Bentler, 1999; Kline, 2023). The thresholds for composite reliability (CR) and McDonald’s omega (ω) coefficients were set at ≥0.70 and ≥0.60, respectively. Discriminant validity (DV) was determined by comparing the square root of average variance extracted (AVE) with the correlation of latent variables in the CFA (Hayes and Coutts, 2020).
Career mentorship
The eight-item vocational mentoring subscale (Scandura, 1992) was used to measure this variable. A sample items included “my mentor has given advice on my intended career.” The original scale had a Cronbach’s α = 0.89, and the response scale ranged from (1 = Strongly disagree to 7 = Strongly agree). The present study, a one-factor model showed a satisfactory data fit: χ2 = 51.62; df = 14; χ2/df = 3.6; CFI = 0.98; TLI = 0.98; IFI = 0.98; SRMR = 0.02, RMSEA = 0.08 and PClose = 0.03, with the reliability and validity values: CR = 0.93, AVE = 0.65, DV = 0.85 and ɷ = 0.92.
Career adaptability
The 24-item career adapt-abilities scale international form version 2.0 was adopted (Savickas and Porfeli, 2012). The original scale has four subscales comprising: concern (6 items, ɷ = 0.94) with an item “I Think about what my future will be like”, control (6 items, ɷ = 0.94) with an item “I make decisions by myself”, curiosity (6 items, ɷ = 0.85) with an item “I Look for opportunities to grow as a person”, and confidence (6 items, ɷ = 0.94) with an item “I take care to do things well”. Responses ranged from (1 = strongly disagree to 5 = strongly agree). The one-factor CFA model yielded a satisfactory data fit: χ2 = 1,161.04.3; df = 250; χ2/df = 4.64; CFI = 0.97; TLI = 0.96; IFI = 0.97; SRMR = 0.03; RMSEA = 0.06 and PClose = 0.04, with the reliability and validity values: CR = 0.96, AVE = 0.72, DV = 0.85 and ɷ = 0.879.
Career transitions inventory
This was measured using the 40-item career transition inventory (Heppner, 1991, 1998). The original scale has five subscales comprising: readiness (13 items, ɷ = 0.92) with an item “I believe I am ready to risk some of the security I now have in my current career in order to gain something better, confidence (11 items, ɷ = 0.91) with an item “the risk of changing careers seems serious to me”, control (6 items, ɷ = 0.93) with an item “the outcome of this career transition process is really up to those who control the system”, support (5 items, ɷ = 0.93) with an item “significant people in my life are actively supporting me in this career transition” and independence (5 items, ɷ = 0.91) with an item “my family are important to me but I can’t put too much importance on their desires with regards to this career transition”. Responses ranged from (1 = strongly disagree to 6 = strongly agree). The five-factor CFA model yielded a good data fit: χ2 = 2,872.5; df = 682; χ2/df = 4.21; CFI = 0.90; TLI = 0.90; IFI = 0.90; SRMR = 0.06; RMSEA = 0.08 with the reliability and validity values: readiness: CR = 0.95, AVE = 0.60, DV = 0.76; confidence: CR = 0.96, AVE = 0.71, DV = 0.84; control: CR = 0.91, AVE = 0.52, DV = 0.72; support: CR = 0.92, AVE = 0.75, DV = 0.87; independence: CR = 0.90, AVE = 0.82, DV = 0.91 and overall ɷ = 0.879.
Strategies for analysis
The descriptive statistics and bivariate correlation were estimated using SPSS version 25. Reliability and validity of the instrument were assessed using AMOS 24.0 and PROCESS Macro for SPSS to examine the direct and specific indirect effects between the variables. All estimates were calculated using maximum likelihood with bias-corrected (BC) 5,000 resample bootstrapping at a 95% confidence interval (Hayes, 2017). The model included CM at T1 as the independent variable, career adaptability at T2 and career transitioning at T3 as the dependent variable (see Figure 1). Other variables such as gender, age and skill areas were not hypothesized but allowed to correlate within waves in the model. Thus, a full panel design was assessed. To examine the direct and indirect relations between variables and test for mediation, we used PROCESS Macro (Model 4) to compute the regression estimates. Mediation was considered significant when the confidence intervals (CI) did not include zero, indicating a significant indirect relationship.
Results
Preliminary analysis
The preliminary analysis as revealed in Table 1 displays the outcome of the correlation matrix for all the variables in the study. As shown, the bivariate correlations aligned with our expectations, with significant correlations observed, except for the non-significant correlation between age and career adaptability, as well as career transition readiness, control, support and independence. To examine common method bias (CMB), Harman’s one factor test was performed using factor analysis. The factor explained only 43.04% of the total variance, which was well within the acceptance range of 50% (Harman, 1967). The result indicated the absence of any issue with the instrument and the data.
Testing of hypotheses
To test the hypotheses, we used the Hayes-PROCESS Macro 4.2 to analyze both the discrete direct and indirect relationships in the study. We applied “Model 4” and selected BC 5,000 resample bootstraps at a 95% confidence interval to determine the relationships. In Table 2, the analysis revealed that CM was positively associated with career transitioning readiness (β = 0.337, t(478) = 3.431, p < 0.0001), confidence (β = 0.195, t(478) = 2.246, p < 0.0001), control (β = 0.171, t(478) = 2.781, p < 0.0001), support (β = 0.155, t(478) = 0.051, p < 0.0001) and independence (β = 0.190, t(478) = 3.036, p < 0.0001), indicating that hypotheses 1a-e were fully accepted. As revealed also in Table 2, the analysis of hypotheses 2(a-d) revealed that CM was positively associated with career adaptability concern (β = 0.698, t(478) = 39.170, p < 0.0001), career adaptability control (β = 0.677, t(478) = 37.043, p < 0.0001), career adaptability curiosity (β = 0.522, t(478) = 28.226, p < 0.0001) and career adaptability confidence (β = 0.399, t(478) = 14.487, p < 0.0001), indicating full support of the hypothesis.
Table 3 revealed the results of the direct effect of all the career adaptability dimensions on career transition readiness, confidence, control, support and independence, as well as the indirect effects of CM on career transition via all the career adaptability dimensions. The analysis revealed that career adaptability concern was positively associated with career transitioning readiness (β = 0.60, t(478) = 4.91, p < 0.0001), confidence (β = 0.54, t(478) = 4.92, p < 0.0001), control (β = 0.27, t(478) = 3.45, p < 0.0001), support (β = 0.18, t(478) = 2.80, p < 0.0001) and independence (β = 0.18, t(478) = 2.56, p < 0.0001). Career adaptability control was positively associated with career transitioning readiness (β = 0.59, t(478) = 4.97, p < 0.0001), confidence (β = 0.63, t(478) = 5.96, p < 0.0001), control (β = 0.23, t(478) = 3.05, p < 0.0001), support (β = 0.26, t(478) = 4.29, p < 0.0001) and independence (β = 0.19, t(478) = 3.21, p < 0.0001). Career adaptability curiosity was positively associated with career transitioning readiness (β = 1.73, t(478) = 18.79, p < 0.0001), confidence (β = 1.32, t(478) = 14.88, p < 0.0001), control (β = 0.83, t(478) = 12.82, p < 0.0001), support (β = 0.39, t(478) = 6.58, p < 0.0001) and independence (β = 0.38, t(478) = 6.65, p < 0.0001). Career adaptability confidence was positively associated with career transitioning readiness (β = 1.14, t(478) = 18.15, p < 0.0001), confidence (β = 0.77, t(478) = 12.26, p < 0.0001), control (β = 0.50, t(478) = 11.21, p < 0.0001), support (β = 0.21, t(478) = 5.05, p < 0.0001) and independence (β = 0.22, t(478) = 5.69, p < 0.0001), indicating that hypothesis 3a was fully accepted.
As also reported in Table 3, we explored the indirect effects of CM on career transition (readiness, confidence, control, support and independence) via the discrete dimensions of career adaptability (H3b). In line with our expectations, we found that career adaptability concern mediated the connection between CM and career transition readiness (β = 0.42, CI = 0.25 to 0.59), confidence (β = 0.37, CI = 0.23 to 0.52), control (β = 0.19, CI = 0.08 to 0.30), support (β = 0.12, CI = 0.04 to 0.21) and independence (β = 0.11, CI = 0.02 to 0.20); career adaptability control mediated the connection between CM and career transitioning readiness (β = 0.40, CI = 0.23 to 0.58), confidence (β = 0.42, CI = 0.28 to 0.58), control (β = 0.16, CI = 0.05 to 0.26), support (β = 0.18, CI = 0.04 to 0.25) and independence (β = 0.13, CI = 0.05 to 0.21); career adaptability curiosity mediated the connection between CM and career transitioning readiness (β = 0.90, CI = 0.78 to 1.02), confidence (β = 0.69, CI = 0.58 to 0.81), control (β = 0.43, CI = 0.35 to 0.52), support (β = 0.20, CI = 0.14 to 0.27) and independence (β = 0.19, CI = 0.14 to 0.26) and career adaptability confidence mediated the connection between CM and career transitioning readiness (β = 0.45, CI = 0.37 to 0.54), confidence (β = 0.31, CI = 0.24 to 0.38), control (β = 0.20, CI = 0.15 to 0.25), support (β = 0.08, CI = 0.05 to 0.12) and independence (β = 0.09, CI = 0.06 to 0.12), indicating that all the results were separately significant. Thus, H3b is supported.
Discussion
The present study examined a model in which career adaptability was proposed to mediate the relationship between CM and career transitioning among ITF NISDP trainees in Southeastern Nigeria. Consistent with Hypothesis (1a – 1e), the results revealed that CM is positively associated with career transitioning: (a) readiness, (b) confidence, (c) control, (d) support and (e) independence. This finding can be elucidated using Renn et al. (2014) that explained the importance of CM in building the skills the vocational skills trainees need to make successful career transitions. This finding aligns with previous studies that found a relationship between CM and career transition (e.g. Chukwuedo et al., 2023; Renn et al., 2014).
Similar to Hypothesis 1a - 1e, the results of our study also exposed that CM is positively associated with the NISDP trainees career adaptability: (a) concern, (b) control, (c) confidence and (d) curiosity, supporting Hypotheses 2a – 2d. This can be understood by comparing it to Kanten et al. (2017) study which revealed that mentoring functions, which is labeled as role modeling, have significant effects on student’s career adaptability, career optimism and career self-efficacy levels. This finding also agrees with earlier studies (e.g. Umukoro and Okurame, 2018) that found a link between CM and career adaptability.
Furthermore, comparable to Hypotheses 2a – 2d, the results revealed that career adaptability (a) concern, (b) control, (c) confidence and (d) curiosity are positively associated with trainees career transitioning (a) readiness, (b) confidence, (c) control, (d) support and (e) independence, supporting Hypotheses 3a. These findings corroborate earlier studies (e.g. Ghosh et al., 2019; Magnano et al., 2021) that found a statistically significant positive association between career adaptability and career transitions among others. Thus, the construct of career adaptability may be capturing exploratory career behaviors, such as being concerned and planful about their careers, that may be important for student veterans’ readiness to make career transitions.
Furthering our findings, the outcomes of H3b revealed that the dimensions of career adaptability (concern, (b) control, (c) confidence and (d) curiosity) discretely mediate the CM and the NISDP trainees career transitioning (a) readiness, (b) confidence, (c) control, (d) support and (e) independence nexus. This is another novel contribution of the study. Our findings, therefore, explain that CM leads to career adaptability which then enhances the trainee’s transition from training to work. Although to our knowledge this is the first study to demonstrate that career adaptability dimensions discretely mediate the CM–career transitioning affiliation, the outcomes support and complement those of previous studies that have tested mediation in relation to CM and learners’ careers prospects (Okolie et al., 2020).
Implications for theory and practice
This study contributes to the existing literature and theories on career construction, mentoring, adaptability and transition. It extends the literature on career mentoring by introducing a self-regulatory construct that connects CM and career transition. Similarly, our study adds to the prior body of knowledge on mentoring literature by investigating mediator models of the four global dimensions of career adaptability among NISDP trainees. We have analytically proven the serial multiple mediating roles of career adaptability (Hirschi et al., 2015; Savickas, 2005) on the relationships between CM and career transition. Finally, our study has added to the existing theories and literature on mentoring and career transition by confirming previous studies on the relationship between mentoring and career progress. We have proven that career mentoring influences career transition (e.g. Chukwuedo et al., 2023; Renn et al., 2014). We have also empirically proven the relationships of career mentoring with career adaptability (Umukoro and Okurame, 2018).
In addition to the theoretical implications of the current study, our findings have important practical implications. Not much research has focused on informal sector vocational programs, especially among NISDP trainees in Nigeria. The results of our study also have implications for vocational training centers and research experts in terms of training measures to address uncertainty and a lack of direction in making a successful career transition. We found a significant relationship between CM and career transition through career adaptability. It would be helpful for experts in vocational training institutions to integrate mentoring functions into their training programs. Our findings have important implications for the vocational training program. Training providers should integrate structured CM opportunities, pairing trainees with experienced mentors who can provide tailored guidance and support. Regular, scheduled interactions between mentors and trainees should be facilitated to ensure ongoing support and feedback, enhancing trainees’ career transition behaviors and adaptability. Training programs should offer additional coaching focused on managing career transitions. Vocational institutions should collaborate with formal vocational institutions to provide certified mentoring programs for their instructors to assist in training for smooth career transition.
Limitations of the study and suggestions for future studies
Despite the novel contribution to research and vocational training implementation, we acknowledge the deficiencies of the study. First, the sample size and homogeneity of the participants in the NISDP may limit the generalizability of the findings to other students who undertake a career transition module. To address this limitation, we utilized the 5,000 resample bootstrapping method to minimize the effect size limitation (Hayes, 2017). However, future studies may consider conducting a multi-group study to compare NISDP trainees who undertake CM with those from other training programs that do not include CM to examine their effects on trainees’ career transition. Additionally, due to the cross-sectional nature of the study, the findings may differ when using experimental or longitudinal designs. We recommend using experimental or longitudinal research measures to replicate this study. Despite these limitations, this study has made relevant contributions to the understanding of the relationship between CM and career transition.
Conclusion
Our study contributes to the existing literature on the indirect relationship between CM and career transitioning, specifically through the dimensions of career adaptability (concern, control, curiosity and confidence). The outcomes of our study are particularly relevant due to the high levels of indecisiveness and lack of direction that trainees often experience when attempting to make a successful career transition. We therefore recommend that training institutions enhance their programs by incorporating career support initiatives, such as CM, in order to positively influence the career transition behaviors of trainees.
Figures
Figure 1
Conceptual model
Descriptive statistics and correlation matrix
| M | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Gender | 1.59 | 0.49 | 1 | |||||||||||
| 2 | Age | 26.10 | 3.57 | 0.247** | 1 | ||||||||||
| 3 | Skill areas | 5.65 | 2.50 | 0.304** | 0.805** | 1 | |||||||||
| 4 | CM | 17.26 | 10.18 | 0.266** | −0.046 | 0.004 | 1 | ||||||||
| 5 | CA-concern | 12.68 | 8.14 | 0.262** | −0.035 | 0.039 | 0.873** | 1 | |||||||
| 6 | CA-control | 12.66 | 8.00 | 0.264** | −0.013 | 0.058 | 0.861** | 0.926** | 1 | ||||||
| 7 | CA-curiosity | 17.11 | 6.72 | 0.265** | 0.003 | 0.054 | 0.791** | 0.788** | 0.810** | 1 | |||||
| 8 | CA-confidence | 20.87 | 7.37 | 0.214** | 0.026 | 0.078 | 0.552** | 0.543** | 0.549** | 0.808** | 1 | ||||
| 9 | CT-readiness | 48.30 | 13.36 | 0.217** | 0.023 | 0.094* | 0.578** | 0.592** | 0.590** | 0.783** | 0.754** | 1 | |||
| 10 | CT-confidence | 42.20 | 11.28 | 0.198** | 0.098* | 0.163** | 0.514** | 0.541** | 0.558** | 0.702** | 0.634** | 0.868** | 1 | ||
| 11 | CT-control | 22.13 | 7.67 | 0.178** | 0.052 | 0.118** | 0.473** | 0.480** | 0.470** | 0.647** | 0.597** | 0.810** | 0.854** | 1 | |
| 12 | CT-support | 17.34 | 6.26 | 0.196** | 0.035 | 0.062 | 0.455** | 0.453** | 0.479** | 0.517** | 0.419** | 0.373** | 0.356** | 0.304** | 1 |
| 13 | CT-independence | 17.10 | 6.20 | 0.208** | 0.029 | 0.063 | 0.493** | 0.480** | 0.489** | 0.545** | 0.455** | 0.423** | 0.411** | 0.393** | 0.892** |
Note(s): M = mean; CM = career mentorship; CA = career adaptability; CT = career transitioning; **p < 0.01; *p < 0.05. M = mean. SD = standard deviation
Source(s): Table by authors
Result of unmediated effect of career mentorship, career transitioning and career adaptability
| Path | 5000 BC bootstrap with 95% CI | ||||
|---|---|---|---|---|---|
| Β | SE | t | LL | UL | |
| CM → CT-readiness | 0.337*** | 0.098 | 3.431 | 0.144 | 0.530 |
| CM → CT-confidence | 0.195*** | 0.087 | 2.246 | 0.024 | 0.366 |
| CM → CT-control | 0.171*** | 0.062 | 2.781 | 0.050 | 0.292 |
| CM → CT-support | 0.155*** | 0.051 | 3.036 | 0.055 | 0.255 |
| CM → CT-independence | 0.190*** | 0.049 | 3.844 | 0.093 | 0.287 |
| CM → CA-concern | 0.698*** | 0.017 | 39.170 | 0.663 | 0.733 |
| CM → CA-control | 0.677*** | 0.018 | 37.043 | 0.641 | 0.713 |
| CM → CA-curiosity | 0.522*** | 0.019 | 28.226 | 0.486 | 0.558 |
| CM → CA-confidence | 0.399*** | 0.028 | 14.487 | 0.345 | 0.454 |
Note(s): ***p < 0.001. BC = bias corrected. CI = confidence interval; CM = career mentorship; CA = career adaptability; CT = career transitioning; SD = standard deviation; LL = lower limit; UL = upper limit
Source(s): Table by authors
Result of direct effect of career adaptability and career transitioning, with subsequent mediation model
| Pathways | 5000 BC bootstrap with 95% confidence interval | |||||||
|---|---|---|---|---|---|---|---|---|
| Direct effect | Indirect effect | |||||||
| β(SE) | t | LL | UL | β | SE | LL | UL | |
| CM → CA-concern → CT-readiness | 0.60(0.12) | 4.91*** | 0.36 | 0.85 | 0.42 | 0.09 | 0.25 | 0.59 |
| CM → CA-concern → CT-confidence | 0.54(0.11) | 4.92*** | 0.32 | 0.75 | 0.37 | 0.07 | 0.23 | 0.52 |
| CM → CA-concern → CT-control | 0.27(0.08) | 3.45*** | 0.11 | 0.42 | 0.19 | 0.05 | 0.08 | 0.30 |
| CM → CA-concern → CT-support | 0.18(0.06) | 2.80*** | 0.05 | 0.30 | 0.12 | 0.04 | 0.04 | 0.21 |
| CM→ CA-concern → CT-independence | 0.16(0.06) | 2.56*** | 0.04 | 0.28 | 0.11 | 0.04 | 0.02 | 0.20 |
| CM → CA-control → CT-readiness | 0.59(0.12) | 4.97*** | 0.36 | 0.83 | 0.40 | 0.09 | 0.23 | 0.58 |
| CM → CA-control → CT-confidence | 0.63(0.11) | 5.96*** | 0.42 | 0.83 | 0.42 | 0.08 | 0.28 | 0.58 |
| CM → CA-control → CT-control | 0.23(0.08) | 3.05*** | 0.08 | 0.38 | 0.16 | 0.05 | 0.05 | 0.26 |
| CM → CA-control → CT-support | 0.26(0.06) | 4.29*** | 0.14 | 0.39 | 0.18 | 0.04 | 0.10 | 0.25 |
| CM → CA-control → CT-independence | 0.19(0.06) | 3.21*** | 0.08 | 0.31 | 0.13 | 0.04 | 0.05 | 0.21 |
| CM → CA-curiosity → CT-readiness | 1.73(0.09) | 18.79*** | 1.55 | 1.91 | 0.90 | 0.06 | 0.78 | 1.02 |
| CM → CA-curiosity → CT-confidence | 1.32(0.09) | 14.88*** | 1.15 | 1.49 | 0.69 | 0.06 | 0.58 | 0.81 |
| CM → CA-curiosity → CT-control | 0.83(0.06) | 12.82*** | 0.70 | 0.96 | 0.43 | 0.04 | 0.35 | 0.52 |
| CM → CA-curiosity → CT-support | 0.39(0.06) | 6.58*** | 0.27 | 0.51 | 0.20 | 0.03 | 0.14 | 0.27 |
| CM → CA-curiosity → CT-independence | 0.38(0,06) | 6.65*** | 0.27 | 0.49 | 0.19 | 0.03 | 0.14 | 0.26 |
| CM → CA-confidence → CT-readiness | 1.14(0.06) | 18.15*** | 1.01 | 1.26 | 0.45 | 0.42 | 0.37 | 0.54 |
| CM → CA-confidence → CT-confidence | 0.77(0.63) | 12.26*** | 0.65 | 0.89 | 0.31 | 0.04 | 0.24 | 0.38 |
| CM → CA-confidence → CT-control | 0.50(0.04) | 11.21*** | 0.41 | 0.59 | 0.20 | 0.03 | 0.15 | 0.25 |
| CM → CA-confidence → CT-support | 0.21(0.04) | 5.05*** | 0.13 | 0.28 | 0.08 | 0.02 | 0.05 | 0.12 |
| CM → CA-confidence → CT-independence | 0.22(0.04) | 5.69*** | 0.15 | 0.29 | 0.09 | 0.02 | 0.06 | 0.12 |
Note(s): ***p < 0.001. BC = bias corrected. CI = confidence interval; CM = career mentorship; CA = career adaptability; CT = career transitioning; SD = standard deviation; LL = lower limit; UL = upper limit; Direct effect here = career adaptability – career transition relationship path
Source(s): Table by authors
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