This study shows that risk behaviours and depressive symptoms are prevalent among adolescents and young adults attending vocational education. The results suggest that clustering of risk behaviours occurs. More specifically, the risk behaviours examined occured in two clusters: substance use (i.e. alcohol use, cannabis use and cigarette smoking) and problem behaviours (i.e. incurring debts, truancy and delinquency). Furthermore, both clusters of risk behaviours were associated with depressive symptoms. In addition, various demographic characteristics were associated with the clusters of risk behaviours and depressive symptoms.
Each of the individual risk behaviours was prevalent among the study population, with truancy having an especially high prevalence. That is, more than 4 out of 5 students had been truanting in the first two months of education. This is very worrying since truancy is a risk factor for school dropout, as are the other risk behaviours included in this study [5-9]. To the best of our knowledge, there have been no previous studies examining the prevalence of truancy (in hours) among students attending vocational education, as registered by a school registration system. Most often truancy is measured by self-report measures, which is a less objective measure than a school registration system.
The prevalence of cannabis use, cigarette smoking, depressive symptoms and incurring debts was high, though comparable with other studies among students attending vocational education [29,30,39]. However, binge drinking was more prevalent in our study (50.5%) compared to the study of Vogel et al. in which 33.2% of students attending vocational education reported having been binge drinking in the past 4 weeks . This discrepancy may be due to differences in the level of education; the study by Vogel et al. included students from all four levels of vocational education, whereas our study only included students from the two lowest levels. Students at a lower education levels have a greater tendency to drink large amounts of alcohol compared to students at higher levels of education . This difference is probably attributable to the fact that students at lower levels spend more time with their peers and are not supervised by their parents as much, both of which are associated with more drinking . Studies examining the prevalence of delinquency among adolescents and young adults attending vocational education seem to be lacking and therefore more research is needed. This is especially true given that more than 10% of students in our study reported that they were questioned at a police station in the past year after being accused of breaking the law.
Two clusters of risk behaviours were identified (i.e. substance use and problem behaviours). The clustering of substance use-related risk behaviours (i.e. alcohol use, cannabis use, and cigarette smoking) was also found in other studies among adolescents in general [15,16,21], whereas prior research among students attending vocational education showed an association between binge drinking, cannabis use and cigarette smoking . The clustering of the use of different substances has been explained by so-called gateway theories and by a shared determinant that increases the risk of using substances in general. Gateway theories state that the use of one substance leads to experimentation and use of other substances . Alternatively, a shared determinant, such as a personality trait (e.g. novelty seeking) that makes it more likely a student will experiment with substances, or an environment in which students are exposed to substance use and/or abuse by the example of parents or friends, could increase students’ risk of multiple substance use .
The other cluster, problem behaviours, comprised the risk behaviours incurring debts, truancy and delinquency. Although previous research showed an association between incurring debts and delinquency , between delinquency and truancy [8,44], and between incurring debts and active participation at school among students , it appears that the clustering of these three has never before been investigated. The clustering of these risk behaviours may be explained by the Strain Theory, which posits that financial problems are a source of strain in young people . If these youngsters are not capable of dealing with strain in a legal manner, the risk of committing a minor violation, e.g. truancy or substance use, and delinquency may increase. Although the use of substances by adolescents is considered illegal behaviour in some countries, in the Netherlands the use of substances by adolescents is legal. That is, until 2013 the purchase of alcohol and cigarettes was allowed for those 16 and over (starting in 2014 the age was raised to to 18), and the use of cannabis is allowed for those 18 and over.
The clustering of risk behaviours suggests that interventions should preferably focus on multiple risk behaviours simultaneously rather than on separate risk behaviours in order to lessen the burden on public health services [17,18]. Because multiple risk behaviours were relatively common in the study population, preventive interventions targeting students attending vocational education and focusing on multiple behaviours simultaneously could be especially beneficial. However, to date, most intervention programmes still take a single risk behaviour approach, instead of an integrated one . The finding of separate clusters indicates that some combinations of risk behaviours, i.e. those which form clusters could potentially be responsive to an integrated prevention approach. Moreover, it is of interest to examine whether the risk behaviours included in certain clusters have a shared determinant, such as a personality trait (e.g. novelty seeking) or a specific family environment (e.g. an environment with a lot of violence). Although the present research only focused on risk behaviours, some of the most promising intervention programme approaches for reducing multiple risk behaviours simultaneously address multiple domains of risk and protective factors predictive of risk behaviour .
Furthermore, our study shows that both clusters of risk behaviours were associated with depressive symptoms. This observation supports findings by Clark et al. and Boys et al., which demonstrate that adolescents who engaged in more health risk behaviours (i.e. smoking, alcohol, and/or drug use) were at increased risk of depressive symptoms [23,24]. Therefore, if multiple risk behaviours are evident in adolescents and young adults, it could be useful to screen for and address depressive symptoms, whereas if depressive symptoms are evident it could be useful to screen for and address multiple risk behaviours. This approach may help to improve the early identification of those at risk of multiple risk behaviours and/or depressive symptoms.
Moreover, to determine which students are at risk of multiple risk behaviours or depressive symptoms, it was also examined if demographic characteristics could help identify at risk students. Results showed that students with a non-Dutch ethnic background reported less substance use than students of Dutch descent. This may) be due (at least partly) to their cultural and/or religious beliefs and practices related to smoking, drinking alcohol and using drugs . However, students of non-Dutch descent more often reported problem behaviours compared to students with a Dutch background. Older students and students who were a parent also more often reported problem behaviours compared to their younger counterparts and to adolescents who were not a parent yet. This observation is in line with previous research showing that ethnic minority students, older students, and students who are a parent, are at increased risk of dropout . Finally, girls more often reported depressive symptoms compared to boys, which is also supported by previous research .
The present study has some limitations. As this is a cross-sectional study, we cannot determine the direction of association between risk behaviours and depressive symptoms. While earlier research has identified depression as a predictor of risk behaviours, research has also shown that risk behaviours can be predictors of depression. Furthermore, a third factor may make youth susceptible to both depression and a wide range of behaviours [48-50]. Although our population reflects the average population in vocational schools in the Netherlands as regards age, gender, and ethnicity [29,30,39], this study was only conducted among students in the Netherlands in the two lowest levels of vocational education. Therefore, generalization to other education levels and countries should be done with caution. Moreover, almost 30% of students did not provide written consent, mainly because they were absent during the assessment and participating students for whom truancy information was not available were more likely to display risk behaviours and depressive symptoms than students for whom truancy information was available. This could have affected the generalisability of the results since non-participating students were not included in the analyses and students for whom truancy information was missing were not included when calculating prevalence of risk behaviour clusters. This limitation probably means that the prevalence of risk behaviour clusters has been underestimated. Furthermore, potential underestimation of risk behaviours clusters may have also led to underestimation of the association between risk behaviours clusters and depressive symptoms. Another limitation is the use of self-reporting for most variables included in this study, which may have resulted in less reliable outcomes. Nevertheless, research suggests that, for example, self-reported alcohol consumption among adolescents is generally valid .