Health assets and active lifestyles during preadolescence and adolescence: highlights from the HBSC/WHO health survey and implications for health promotion

The present chapter discusses the assets model as a theoretical approach to the study of health behavior and health promotion. The model emphasizes people’s talents, competences, and resources. In this chapter, a health asset is defined as any factor or resource that maximizes the opportunities for individuals, local communities, and populations to attain and maintain health and well-being. This perspective expands and complements the current medical model as it focuses on the development of a sense of empowerment in community members to prevent and manage their own health. Therefore, in this chapter we address the concepts of salutogenesis, social support, resilience, coping, self-regulation, social capital, and personal and social competence, which are central to the development of individuals’ potential to manage and savor their own health, creating the conditions for self-fulfillment. Additionally, we demonstrate how the assets model guides the study of children’s and adolescents’ health in the Portuguese Health Behaviour in School-aged Children study (www.hbsc.org), concentrating on areas such as active lifestyles and quality-of-life perception. Finally, we present a roadmap for action that emphasizes the need to identify the factors that make children and adolescents happy and healthy individuals, while minimizing risks and problems they naturally encounter throughout their development. We also argue for the need to involve young people in discussions concerning their health and health promotion practices, focusing on the development of talents, capabilities, and positive expectations for the future.

A signaling visualization toolkit to support rational design of combination therapies and biomarker discovery: SiViT

Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the intrinsic complexity of pathway networks. Systems biology approaches afford better understanding of complex, dynamical interactions in signalling pathways targeted by anticancer drugs. However, adoption of dynamical modelling by clinicians and biologists is impeded by model inaccessibility. Drawing on computer games technology, we present a novel visualisation toolkit, SiViT, that converts systems biology models of cancer cell signalling into interactive simulations that can be used without specialist computational expertise. SiViT allows clinicians and biologists to directly introduce for example loss of function mutations and specific inhibitors. SiViT animates the effects of these introductions on pathway dynamics, suggesting further experiments and assessing candidate biomarker effectiveness. In a systems biology model of Her2 signalling we experimentally validated predictions using SiViT, revealing the dynamics of biomarkers of drug resistance and highlighting the role of pathway crosstalk. No model is ever complete: the iteration of real data and simulation facilitates continued evolution of more accurate, useful models. SiViT will make accessible libraries of models to support preclinical research, combinatorial strategy design and biomarker discovery.