Unhealthy dietary behaviors and a decrease in physical activity are a major problem in adolescents and young adults [1
]. These unhealthy behaviors may lead to a higher risk of non-communicable diseases later in their lives [2
]. The prevalence of these unhealthy behaviors is not evenly distributed amongst different groups of young people [6
]. Students attending vocational education have less favorable health practices than students attending higher secondary education [8
]. In the Netherlands, many vocational students are overweight, show more sedentary behavior than recommended, do not engage in sufficient physical activity, and most do not meet the guidelines for fruit and vegetable consumption [9
]. The vocational education and training (VET) sector is regarded as critical to the Dutch economy because about 40% of the working population has obtained a vocational qualification [12
]. The acquisition of citizenship skills that refer to the willingness and ability to reflect on one’s lifestyle and care for one’s vitality as a citizen and employee are a key competence in the Netherlands and considered of great value in the future employability of Dutch vocational students [13
Most vocational students are in their late adolescence, ranging in age from 16 to 24 years old. Late adolescence is characterized by many cognitive changes, including changes in motivational processes [14
]. It is also a period of transition from adolescence to adulthood in which young people establish independence, adopt lasting health behavior patterns, and are at high risk of developing obesity and unhealthy dietary habits and physical activity practices [17
]. Therefore, it is highly relevant to promote healthy dietary and physical activity behaviors among adolescents and young adults, especially among those belonging to a vulnerable target group.
To develop effective intervention programs for vocational students, more research is needed to identify factors that predict the engagement in health behaviors among this population. A wide range of theoretical explanations provides a basis for understanding the determinants of behavior and behavior change [18
]. Several studies have reported that successful behavior change maintenance depends on motives, self-regulation, resources, habits, and environmental and social influences, and point out that motivation is a critical factor in supporting healthy dietary and physical activity behaviors [19
]. As a general theory of motivation, the Self-Determination Theory (SDT) is being applied to study motivation in numerous health care and health promotion contexts [23
]. SDT distinguishes different types of motivation on a continuum in terms of the degree to which the motivation is (non)self-determined: amotivation, controlled motivation, and autonomous motivation [25
]. Amotivation is a type of motivation in which an individual does not have any intention to perform a certain behavior. Autonomous motivation describes a self-determined type of motivation. In this type of motivation, behavior is performed for the individual’s sake and the goal is self-satisfaction. The motivation type between amotivation and autonomous motivation is controlled motivation, where the motivation to act is driven by external factors and is less self-determined than autonomous motivation. Driving factors can include social influences such as friends and family, or teachers [25
In early and mid-adolescence, high autonomous motivation is known to be related to increased fruit and vegetable intake [26
]. Furthermore, in Finnish vocational students aged 17–19 years, a higher level of autonomous motivation was related to increased physical activity [27
]. Similar results have been found in middle-school students aged 12 years and in children and adolescents aged up to 18 years old [28
]. Controlled motivation, on the other hand, shows a weak negative association with physical activity [30
]. Moreover, individuals who report amotivation to live healthily have poor uptake and adherence to health behaviors. They do not see any reason to change their behavior and are not likely to implement any changes [31
The evidence above shows that types of motivation influence the engagement in health behaviors in (young) adults and adolescents. However, most research on adolescents is focused on early or mid-adolescence. There is little research on the motivation to make healthy choices of late adolescents, particularly vocational students. Therefore, the purpose of this study is to examine the association between type of motivation and dietary and physical activity behaviors among adolescents and young adults in vocational education.
The study population characteristics can be found in Table 1
. The mean age of the study population was 17.8 (±1.9) years old. The majority of the sample had a normal weight (75%) and was female (62%). The type of VET program varied, but a large part of the sample followed the Lifestyle & Sports program (31%). All training levels were represented, but the majority of participants (66%) attended the highest level, level 4.
In Table 2
, descriptive statistics for dietary and physical activity behaviors can be found. The mean water consumption was 1086 mL/day, the mean soda consumption was 330 mL/day, and the mean consumption for diet soda was 133 mL/day. For fruit, the mean consumption was 0.9 pieces a day and the mean number of high-calorie snacks was 1.9 portions per day. Breakfast frequency was, on average, 4.7 days per week. Almost all participants met the guideline for diet soda, but only 12% met the guideline for fruit consumption. In addition, only a limited percentage of participants met the guideline for a maximum of three high-calorie snacks per week.
The mean time for weekly MVPA was 935 min, 161 min for vigorous physical activity, and 774 min for moderate physical activity. Overall, 49% met the guideline for MVPA. However, stratification by age group shows that 20% of participants younger than 18 years met the recommended level of MVPA (at least 60 min MVPA per day), while 79% of participants aged 18 years and over met the adult MVPA guideline of at least 150 min MVPA per week.
The median motivation scores are highest for autonomous motivation for both diet and physical activity (Table 3
), followed by controlled motivation and lastly amotivation. Controlled motivation shows higher values for physical activity than it does for diet. Apart from this, scores are similar for diet and physical activity.
and Table 5
show the associations of autonomous motivation, controlled motivation, and amotivation with physical activity and dietary behaviors, as determined by multilevel linear regression analysis. For dietary behavior (Table 4
), the final models showed an association between autonomous motivation and all dietary variables, except for diet soda. A negative association between autonomous motivation and amount of high-calorie snacks can be seen, meaning that with every increase of 1 in autonomous motivation score, 3.9 fewer high-calorie snacks are consumed. Autonomous motivation also showed a positive association with the fruit and water intake per day and the number of days in which breakfast was consumed. Controlled motivation showed no significant associations with any of the dietary variables. For amotivation, positive associations were found with the portions of high-calorie snacks consumed per week and with diet soda consumption, while a negative association was found with the number of days in which breakfast was consumed. The addition of covariates to the final models had little effect on the associations found in the unadjusted models. The exception was water intake, where the association with amotivation was no longer significant after adjustment for covariates. In the null models, the grouping structure of the population by VET program explained a small part of the variance in the dietary behaviors. The percentage of variance explained ranged from 0.1% for water intake to 8.6% for breakfast consumption.
For physical activity behavior (Table 5
), autonomous motivation was positively associated with the number of minutes per week MVPA in the final model. No other significant associations with motivation were found in the unadjusted or final models. In the null models, the grouping structure of the population by VET program explained a small part of the variance in the physical activity. The percentage of variance explained ranged from 0.7% for moderate physical activity to 9.5% for vigorous physical activity.
This study aimed to investigate the association between type of SDT motivation and diet and physical activity behaviors. A considerable number of vocational students do not comply with the dietary guidelines or physical activity recommendations. At the individual level, the type of motivation partly explained their dietary and physical activity behaviors.
Autonomous motivation was associated with consuming fewer unhealthy products per week and consuming more water, breakfast frequency, fruit consumption, and conducting more MVPA. For moderate and vigorous physical activity separately, no motivation type seems to be of influence. It seems that the association between autonomous motivation and physical activity concerns only the sum of moderate and vigorous physical activity. Autonomous motivation thus seems to explain most of the healthy dietary behaviors and physical activity behavior of vocational students. In previous studies, autonomous motivation is described as the type of motivation that facilitates persistence and sustainability of behavior due to its high levels of autonomy, while controlled motivation does not lead to sustainable behavior [25
]. This explains why autonomous motivation is important in healthy dietary behaviors and physical activity behavior in vocational students. Results of other studies seem to follow the same pattern: in early and mid-adolescents, autonomous motivation was found to be associated with increased fruit intake and increased physical activity [26
], and in vocational students, autonomous motivation was found to be associated with MVPA [27
Controlled motivation did not show an association with any variables: it does not appear to be enough to maintain the healthy lifestyle behaviors investigated in this study. It may not lead to sustainable behavior, because controlled motivation is characterized by lower levels of autonomy compared with autonomous motivation. This could lead to a relapse into old behavior, as the external factor that drove the controlled motivation is removed over time [46
Amotivation was associated with consuming more unhealthy products per week and consuming breakfast less often. This type of motivation seems to be associated with unhealthy dietary behaviors. A possible explanation for this negative association is the indifferent attitude that vocational students have toward making healthy lifestyle choices. Giles and Brennan [47
] found that British late adolescents (aged 18–25) are not willing to put much effort into adopting a healthy lifestyle and thus have a rather indifferent attitude to it. This seems to be the same in Dutch vocational students. If this indifferent attitude leads to amotivation, it could explain its negative effect on dietary behavior. Amotivation, however, also showed a significant positive effect on the consumption of diet soda. A possible explanation for this is the fact that such students show no awareness of calorie content in beverages. It was found that the most important factors for choosing beverages for college students (mean age 19 years) were taste and price [48
]. Therefore, health might not be an important factor for vocational students when consuming diet soda.
At the group level, the type of VET program did not explain a large part of the variance in the dietary and physical activity behaviors. It was expected that program type was an important factor of clustering in the data because the social norm is very important for young adults [47
]. The low ICC could be because the group-level variable used to adjust for clustering of the data might have been too heterogeneous. Social norms may have more influence in more homogeneous groups, such as class level instead of the type of VET program.
4.1. Limitations, Strengths, and Recommendations
The first limitation of this study is the use of self-administered questionnaires. This may have caused recall bias. In the case of diet and physical activity questions, participants tend to be too positive about their habits [49
]. In this study, recall bias could have led to an overestimation of the diet and physical activity behavior of the study population. Additionally, the SQUASH questionnaire is known to overestimate the physical activity that participants conduct, which could have caused an overestimation of the physical activity of vocational students [50
]. The exact effect that these possible overestimations might have had on the found associations cannot be inferred. Secondly, the cross-sectional nature of this study is a limitation as the type of motivation and behavior were measured at the same time, so their interrelationship does not necessarily reflect a causal relationship. In absence of a time dimension, for example, it is not possible to determine whether higher scores on autonomous motivation precede healthier dietary behaviors.
Finally, the study population consisted of vocational students from three VET school locations in the metropolitan area of the Netherlands. This makes the results not automatically applicable to VET programs in general. Female students were overrepresented in the sample, which may have caused an overestimation of the diet and physical activity behavior of the study population because being female is related to having healthier lifestyle habits [41
]. Furthermore, the sample included a large number of Lifestyle & Sports students. This type of VET program attracts students who are interested in sports and lifestyle. Therefore, this could have caused an overestimation of the diet and physical activity behavior of the study population, especially in the amount of physical activity vocational students engage in. The effects that the abovementioned factors had on the associations cannot be inferred. The external validity of this study could thus be improved by obtaining a more representative sample of vocational students.
Despite the abovementioned limitations, to our knowledge, this study is one of the first that reports associations between type of SDT motivation and dietary and physical activity behavior of vocational students. Therefore, it provides new and much-needed insights into their motivation and health behavior. Moreover, the large sample size of the study increased its reliability. Furthermore, the use of multilevel analyses strengthened the study’s conclusions because variability due to clustering of the data was accounted for.
For future research, we recommend diving deeper into the topic of SDT and self-directed health behaviors among vocational students. More insight is needed into the three basic psychological needs—autonomy, competence, and relatedness—and their relationship with autonomous motivation and amotivation, to develop health-promoting interventions for this group. In addition to diet and physical activity behavior, more variables can be investigated to get a more complete picture of the determinants of vocational students’ health behavior. For example, we chose dietary behaviors that are frequent in the school environment, but other dietary behaviors that are more common in the students’ home environment (such as vegetable consumption) are also interesting to investigate further.
The results of this study show a clear association of autonomous motivation with dietary behavior and MVPA in vocational students. This implies that autonomous motivation is a reasonable target in the development of health-promoting interventions.
A review by Ng et al. [23
] showed that enhancing autonomous motivation led to beneficial health outcomes. Furthermore, satisfying basic psychological needs was found to be important. To enhance autonomous motivation, autonomy-supportive interventions must focus on four SDT components. First, they must increase the sense of competence of participants. Second, these feelings of competence must be coupled with feelings of autonomy. Third, interventions must make sure to give participants a sense of security or relatedness. Lastly, extrinsic rewards must be avoided as they stimulate controlled motivation instead of autonomous motivation [46
]. One possible intervention to enhance autonomous motivation is motivational interviewing, as this is a method to adhere to behavior change with many parallels with the mentioned SDT concepts [51
]. In adolescents, motivational interviewing was found to be effective in promoting several healthy behaviors [52
]. In addition, peer relations have a positive effect on autonomous motivation. In adults with weight management goals, for example, it was found that autonomy support by significant others led to satisfaction of psychological needs, which is beneficial for autonomous motivation [53
]. Gairns et al. [54
] found that high school students showed stronger autonomous motivation for participation in a physical education class when they felt a positive relatedness with their classmates. In the context of VET qualification, Lifestyle & Sports students, for example, may learn how to motivate a target population such as their fellow students in other VET programs to improve health-related behaviors. In this way, they may act as a significant other but also improve the competences they need as future professionals.