Background: Healthy sleep is crucial for the physical and mental wellbeing of adolescents. However, many adolescents suffer from poor sleep health. Little is known about how to effectively improve adolescent sleep health as it is shaped by a complex adaptive system of many interacting factors. This study aims to provide insights into the system dynamics underlying adolescent sleep health and to identify impactful leverage points for sleep health promotion interventions.
Methods: Three rounds of single-actor workshops, applying Group Model Building techniques, were held with adolescents (n = 23, 12-15 years), parents (n = 14) and relevant professionals (n = 26). The workshops resulted in a multi-actor Causal Loop Diagram (CLD) visualizing the system dynamics underlying adolescent sleep health. This CLD was supplemented with evidence from the literature. Subsystems, feedback loops and underlying causal mechanisms were identified to understand overarching system dynamics. Potential leverage points for action were identified applying the Action Scales Model (ASM).
Results: The resulting CLD comprised six subsystems around the following themes: (1) School environment; (2) Mental wellbeing; (3) Digital environment; (4) Family & Home environment; (5) Health behaviors & Leisure activities; (6) Personal system. Within and between these subsystems, 16 reinforcing and 7 balancing feedback loops were identified. Approximately 60 potential leverage points on different levels of the system were identified as well.
Conclusions: The multi-actor CLD and identified system dynamics illustrate the complexity of adolescent sleep health and supports the need for developing a coherent package of activities targeting different leverage points at all system levels to induce system change.
Introduction: Early motor development has been found to be a predictor of exercise behavior in children and adolescents, but whether this reflects a causal effect or confounding by genetic or shared environmental factors remains to be established.
Methods: For 20,911 complete twin pairs from the Netherlands Twin Register a motor development score was obtained from maternal reports on the timing of five motor milestones. During a 12-year follow-up, subsamples of the mothers reported on the twins' ability to perform seven gross motor skills ability (N = 17,189 pairs), and weekly minutes of total metabolic equivalents of task (MET) spent on sports and exercise activities at age 7 (N = 3632 pairs), age 10 (N = 3735 pairs), age 12 (N = 7043 pairs), and age 14 (N = 3990 pairs). Multivariate phenotypic and genetic regression analyses were used to establish the predictive strength of the two motor development traits for future exercise behavior, the contribution of genetic and shared environmental factors to the variance in all traits, and the contribution of familial confounding to the phenotypic prediction.
Results: Significant heritability (h2) and shared environmental (c2) effects were found for early motor development in boys and girls (h2 = 43-65%; c2 = 16-48%). For exercise behavior, genetic influences increased with age (boys: h2age7 = 22% to h2age14 = 51%; girls: h2age7 = 3% to h2age14 = 18%) paired to a parallel decrease in the influence of the shared environment (boys: c2age7 = 68% to c2age14 = 19%; girls: c2age7 = 80% to c2age14 = 48%). Early motor development explained 4.3% (p < 0.001) of the variance in future exercise behavior in boys but only 1.9% (p < 0.001) in girls. If the effect in boys was due to a causal effect of motor development on exercise behavior, all of the factors influencing motor development would, through the causal chain, also influence future exercise behavior. Instead, only the genetic parts of the regression of exercise behavior on motor development were significant. Shared and unique environmental parts of the regression were largely non-significant, which is at odds with the causal hypothesis.
Conclusion: No support was found for a direct causal effect in the association between rapid early motor development on future exercise behavior. In boys, early motor development appears to be an expression of the same genetic factors that underlie the heritability of childhood and early adolescent exercise behavior.
Background: Non-communicable diseases (NCDs) are the leading causes of death worldwide. Systems approaches have potential for creating sustainable outcomes at scale but have rarely been used to support scale up in physical activity/nutrition promotion or NCD prevention more generally. This review aimed to: (i) synthesise evidence on the use of systems approaches in scaling up interventions targeting four behavioural risk factors for NCDs; and (ii) to explore how systems approaches have been conceptualised and used in intervention implementation and scale up.
Method: Seven electronic databases were searched for studies published 2016-2021. Eligible studies targeted at least one of four NCD behavioural risk factors (physical inactivity, tobacco use, alcohol consumption, diet), or described evaluation of an intervention planned for or scaled up. Studies were categorised as having a (i) high, (ii) moderate, or (iii) no use of a systems approach. A narrative synthesis of how systems approaches had been operationalised in scale up, following PRISMA guidelines.
Results: Twenty-one intervention studies were included. Only 19% (n = 4) of interventions explicitly used systems thinking to inform intervention design, implementation and scale up (targeting all four risk factors n = 2, diet n = 1, tobacco use n = 1). Five studies ('high use') planned and implemented scale up with an explicit focus on relations between system elements and used system changes to drive impact at scale. Seven studies ('moderate use') considered systems elements impacting scale-up processes or outcomes but did not require achieving system-level changes from the outset. Nine studies ('no use') were designed to work at multiple levels among multiple agencies in an intervention setting, but the complexity of the system and relations between system elements was not articulated. We synthesised reported barriers and facilitators to scaling up, and how studies within each group conceptualised and used systems approaches, and methods, frameworks and principles for scaling up.
Conclusion: In physical activity research, and NCD prevention more broadly, the use of systems approaches in scale up remains in its infancy. For researchers, practitioners and policymakers wishing to adopt systems approaches to intervention implementation at scale, guidance is needed on how to communicate and operationalise systems approaches in research and in practice.
Trial registration: PROSPERO (CRD42021287265).
Increasing physical activity in patients offers dual benefits, fostering improved patient health and recovery, while also bolstering healthcare system efficiency by minimizing costs related to extended hospital stays, complications, and readmissions. Wearable activity trackers offer valuable opportunities to enhance physical activity across various healthcare settings and among different patient groups. However, their integration into healthcare faces multiple implementation challenges related to the devices themselves, patients, clinicians, and systemic factors. This article presents the Wearable Activity Tracker Checklist for Healthcare (WATCH), which was recently developed through an international Delphi study. The WATCH provides a comprehensive framework for implementation and evaluation of wearable activity trackers in healthcare. It covers the purpose and setting for usage; patient, provider, and support personnel roles; selection of relevant metrics; device specifications; procedural steps for issuance and maintenance; data management; timelines; necessary adaptations for specific scenarios; and essential resources (such as education and training) for effective implementation. The WATCH is designed to support the implementation of wearable activity trackers across a wide range of healthcare populations and settings, and in those with varied levels of experience. The overarching goal is to support broader, sustained, and systematic use of wearable activity trackers in healthcare, therefore fostering enhanced physical activity promotion and improved patient outcomes.
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