Unraveling the school-to-work transition of non-engaged youth: A continuous-time Markov chain analysis

It is widely acknowledged that school-to-work transitions (SWTs) for non-engaged youth (NEY) often involve not just one status change but multiple status changes, and are frequently dynamic, nonlinear, and complex. However, less attention has been paid to analyzing and visualizing the transition from one status to another, especially under different interventions, within the SWT process. In our study, we utilized longitudinal data from a sample of 228 NEY aged 14–29 (M = 18.90; 48.25 % males) in Hong Kong to examine the changes in transitional status among NEY using Markov chain analysis. Additionally, we compared the changes in the transitional statuses between NEY who received only information-oriented interventions and those who received both information-oriented and experiential interventions. Our analysis presents a transition probability matrix that quantifies transition probabilities among not only conventional education and employment statuses but also NEY’s new pursuits, such as fill-in jobs, serious leisure development (SLD), and vocational education and training (VET). Additionally, our study highlights the significance of the fill-in job, VET, and SLD statuses, which showcase their multiple, complex, and critical functions deserving further attention. Furthermore, our research found a synergistic effect of combining the information-oriented and experiential interventions that bring about positive outcomes in terms of multiple status changes. In sum, our findings offer a nuanced yet comprehensive perspective for understanding NEY’s dynamic and complex transitions among different SWT statuses, shedding light on the varying multiple status changes under distinct interventions.