The JUMP-in study showed a strong intervention effect on sport participation, which confirms previous findings
. However, no intervention effect on their hypothesized mediators was found. In addition, no significant intervention effects on outdoor play and screen behaviors or their hypothesized mediators were found.
Despite our finding that none of these mediators were significantly impacted by the intervention, sport participation was positively affected by the intervention. As several hypothesized mediators based on social cognitive models (e.g. pros, cons, intention) were not associated with behavior it suggests that our theoretical assumptions of the intervention were not entirely valid. Thus, other (unmeasured) mechanisms by which the intervention impacted sport participation must be in place. The JUMP-in intervention was based on the EnRG-framework, a dual process model combining social cognitive and social-ecological theories
. Based on the EnRG-framework we assumed that by changing the environment we would directly and indirectly (by changing children’s cognitions) change behavior. We therefore targeted several environmental constructs (e.g. organize enjoyable after school sport activities and adapted sport offers) to facilitate participation in organized sport and positively change children’s cognitions towards PA. However, primary schoolchildren’s behavior may be less planned than adults’ behavior and other unconscious/unreasoned processes directly triggered by environmental cues (e.g. availability and parental influences) might influence their behavior
. Moreover, primary schoolchildren might have low autonomy, and many decisions regarding their acts are made by their parents. Consequently, the environment might primarily have a direct influence on primary schoolchildren’s behavior instead of an indirect one via cognitive influences. Social cognitive models such as the theory of planned behavior and ASE model as applied and measured in this study, may not fit well for predicting primary schoolchildren’s behavior. As we did not measure the children’s perceived environment, we were not able to assess whether change in environmental constructs yielded by the intervention, directly affected children’s sport participation. Further research on the JUMP-in data, analyzing changes in potential environmental mediators reported by other sources (e.g. parents) should provide more insight into the working mechanisms of the intervention.
Other explanations for the limited intervention effect on any of the potential mediators might be due to unsuccessful intervention strategies. These intervention strategies might simply not have been effective or strong enough to be able to change the potential mediators; they could have mismatched the measured mediating variables, or they were not sufficiently implemented to bring about change in the mediators. Next, as primary schoolchildren have limitations in general cognitive competencies, especially in ability to think abstractly and perform detailed recall, children are less likely to make accurate self-report assessments of past activities and cognitions than adults
[30, 33]. Other measures such as objective measures or interviews, or combining measures might be more reliable to better characterize primary schoolchildren's activity levels and potential mediators.
The lack of intervention effect on outdoor play, screen behaviors and mediators might also be due to an insufficient implementation of the intervention. Results of the process evaluation
 showed that JUMP-in is currently embedded in the Amsterdam policy as well as in the organizational structure and daily practices of all participating sectors. However, despite the successful embedding, process data showed some hampering factors of its implementation. An overall impeding factor was the complexity of the multilevel program involving collaborations between multidisciplinary organizations. Consequently, implementers needed more time than expected to synchronize and fine-tune organizational procedures. Further, the comprehensive study measurements took additional time. Two schools decided to postpone the implementation of the in-class lessons. In addition, implementers recommended a simplification of methods, instruments, protocols and tasks of the program components
. Lastly, as our a priori power calculation was based on detecting change in sport participation, and not on detecting changes in outdoor play, screen behaviors or any of the potential mediators, our study might have lacked power for detecting change in the other constructs.
The lack of effect on outdoor play and screen behaviors suggests that the school setting might not be the sole channel to influence leisure time activities. As these behaviors are typically performed after school hours, a combination of school-based and family-based intervention strategies may be needed to improve these behaviors, involving the social and physical home environment. JUMP-in did not directly target reducing screen time, but we expected that by targeting outdoor play and sports, screen behaviors would be targeted indirectly. Apparently, this was not the case. This confirms the findings of Biddle and colleagues
, who examined the temporal patterns of activity and sedentary behaviors in children. They found that TV viewing and sports/exercise participation do not compete for similar time periods on a day but might be able to coexist. This supports the evidence that sedentary behaviors are not just the opposite of PA behaviors and therefore need specific strategies to be influenced.
Still, significant associations between changes in potential mediators (i.e. social support, self-efficacy, habit strength, enjoyment, parental rules, availability and perceived barriers) and changes in behaviors were identified. This confirms the relevance of these constructs in changing these specific behaviors, and that these constructs might be potential mediators. Future intervention studies should search for better or more intensive strategies to affect these potential mediators. The negative association found between intention and sport participation could be explained by the way we measured intention (“Do you intend to increase your sport participation within one month?”). We measured intention to change sport participation in stead of intention to participate in sports. Items measuring change are less appropriate measures for mediation analysis. Future studies should take their measures into account when planning to conduct a mediation analysis.
To our knowledge this is the first study examining the mediators of a PA intervention, and the second examining the mediators of screen behaviors in this age group. Importantly, few studies have used appropriate statistical tests to assess mediators in obesity prevention studies
. The need for well -conducted mediation analyses in obesity prevention studies has been noted in previous literature
[19, 41, 42]. Our mediation analysis was based on theoretical models such as the EnRG framework and ASE model, providing the opportunity to test these models. In addition the intervention strategies were carefully matched to the targeted mediators, and were tested in a pilot study and adapted based on a process evaluation
[21, 28]. A final strength was that our program was implemented by the local partners themselves and integrated into a real-world setting, which prevented overestimation of effects due to unrealistic controlled conditions.
Our study was however subject to some potential limitations. First, the measurement of mediators and outcomes relied on child-report. As discussed above, due to limited general cognitive competencies in children, our results may be biased. Future research is need that focuses on the development of (a combination of) valid, reliable and sensitive mediator measures in primary schoolchildren
. Second, most of our mediator measures were translated and adapted from existing validated questionnaires because validated Dutch measures were not available, but were not tested for validity or sensitivity. Additionally, to limit participant burden some of the potential mediating variables were assessed by one item, which could have influenced the construct validity and reliability. Next, we assumed a causal association between the potential mediating variables and the outcome variables. We are however aware of the fact that a reciprocal association could exist, wherein changes in the behaviors could have influenced some of the potential mediators. Finally, the process evaluation presented information regarding hampering factors in the implementation and weaknesses in the program strategies. It is impossible to evaluate to what extend these elements were responsible for the lack of change in the mediators.
With these strengths and limitations in mind, future interventions are recommended examining how to effectively improve leisure time behavior such as outdoor play and screen behaviors through school-based interventions. Effective intervention strategies targeting these behaviors should involve the family setting and the physical and social local environment. Other potential strategies include environmental adaptations such as attractive playgrounds, school policy and rules. Actually, these components have been integrated in the recently renewed JUMP-in program. Next, just motivating parents to stimulate and support their children to be physically active, as done in the JUMP-in program, seems not enough. More attention for parental skills is needed in addition to attractive and tailored information. In addition, as suggested by libertarian paternalism, more attention should be paid to the healthy choice as the easy choice in terms of availability, safety and attractiveness of public space to behave physically active
. This new perspective has been recently integrated in a new integral healthy lifestyle intervention that focuses on the physical and social environment of primary schoolchildren.