The prominence of sedentary behavior research in health science has grown rapidly. With this growth there is increasing urgency for clear, common and accepted terminology and definitions. Such standardization is difficult to achieve, especially across multi-disciplinary researchers, practitioners, and industries. The Sedentary Behavior Research Network (SBRN) undertook a Terminology Consensus Project to address this need. First, a literature review was completed to identify key terms in sedentary behavior research. These key terms were then reviewed and modified by a Steering Committee formed by SBRN. Next, SBRN members were invited to contribute to this project and interested participants reviewed and provided feedback on the proposed list of terms and draft definitions through an online survey. Finally, a conceptual model and consensus definitions (including caveats and examples for all age groups and functional abilities) were finalized based on the feedback received from the 87 SBRN member participants who responded to the original invitation and survey. Consensus definitions for the terms physical inactivity, stationary behavior, sedentary behavior, standing, screen time, non-screen-based sedentary time, sitting, reclining, lying, sedentary behavior pattern, as well as how the terms bouts, breaks, and interruptions should be used in this context are provided. It is hoped that the definitions resulting from this comprehensive, transparent, and broad-based participatory process will result in standardized terminology that is widely supported and adopted, thereby advancing future research, interventions, policies, and practices related to sedentary behaviors.

Background: Society has to cope with a large burden of health issues. There is need to find solutions to prevent diseases and help individuals live healthier lifestyles. Individual needs and circumstances vary greatly and one size fit all solutions do not tend to work well. More tailored solutions centred on individuals’ needs and circumstances can be developed in collaboration with these individuals. This process, known as co-creation, has shown promise but it requires guiding principles to improve its effectiveness. The aim of this study was to identify a key set of principles and recommendations for co-creating public health interventions. Methods: These principles were collaboratively developed through analysing a set of case studies targeting different health behaviours (such as reducing sitting and improving strength and balance) in different groups of people (such as adolescent schoolgirls and older adults living in the community). Results: The key principles of co-creation are presented in four stages: Planning (what is the purpose of the co-creation; and who should be involved?); Conducting (what activities can be used during co-creation; and how to ensure buy-in and commitment?); Evaluating (how do we know the process and the outcome are valid and effective?) and Reporting (how to report the findings?). Three models are proposed to show how co-created solutions can be scaled up to a population level. Conclusions: These recommendations aim to help the co-creation of public health interventions by providing a framework and governance to guide the process. Background: Due to the chronic disease burden on society, there is a need for preventive public health interventions to stimulate society towards a healthier lifestyle. To deal with the complex variability between individual lifestyles and settings, collaborating with end-users to develop interventions tailored to their unique circumstances has been suggested as a potential way to improve effectiveness and adherence. Co-creation of public health interventions using participatory methodologies has shown promise but lacks a framework to make this process systematic. The aim of this paper was to identify and set key principles and recommendations for systematically applying participatory methodologies to co-create and evaluate public health interventions. Methods: These principles and recommendations were derived using an iterative reflection process, combining key learning from published literature in addition to critical reflection on three case studies conducted by research groups in three European institutions, all of whom have expertise in co-creating public health interventions using different participatory methodologies. Results: Key principles and recommendations for using participatory methodologies in public health intervention co-creation are presented for the stages of: Planning (framing the aim of the study and identifying the appropriate sampling strategy); Conducting (defining the procedure, in addition to manifesting ownership); Evaluating (the process and the effectiveness) and Reporting (providing guidelines to report the findings). Three scaling models are proposed to demonstrate how to scale locally developed interventions to a population level. Conclusions: These recommendations aim to facilitate public health intervention co-creation and evaluation utilising participatory methodologies by ensuring the process is systematic and reproducible.

Objective Certain exercise prescriptions for patients with cancer may improve self-reported quality of life (QoL) and self-reported physical function (PF). We investigated the effects of exercise on QoL and PF in patients with cancer and studied differences in effects between different intervention-related and exercise-related characteristics. Design We searched four electronic databases to identify randomised controlled trials investigating exercise effects on QoL and PF in patients with cancer. Pooled effects (Hedges’ g) were calculated using Comprehensive Meta-Analysis software. Subgroup analyses were conducted based on intervention dimensions, including timing, duration and delivery mode, and exercise dimensions, including frequency, intensity, type and time (FITT factors). Results We included 74 exercise arms. Patients who were randomised to exercise interventions had significantly improved QoL (g=0.15, 95% CI (0.10 to 0.20), n=67 exercise arms) and PF (g=0.21, 95% CI (0.15 to 0.27), n=59 exercise arms) compared with patients in control groups. We found a significant between-group difference for exercise delivery mode, with significant beneficial effects for supervised exercise interventions (g=0.20, 95% CI (0.14 to 0.26) for QoL and g=0.27, 95% CI (0.20 to 0.33) for PF), but not for unsupervised interventions (g=0.04, 95% CI (−0.06 to 0.13) for QoL and g=0.09, 95% CI (−0.01 to 0.19) for PF). No statistically significant differences in intervention effects were found for variations in intervention timing, duration or exercise FITT factors. Unsupervised exercise with higher weekly energy expenditure was more effective than unsupervised exercise with lower energy expenditure (z=2.34, p=0.02). Conclusions Exercise interventions, especially when supervised, have statistically significant and small clinical benefit on self-reported QoL and PF in patients with cancer. Unsupervised exercise intervention effects on PF were larger when prescribed at a higher weekly energy expenditure.

Summary: Evidence for adverse health effects of excessive sedentary behaviour in children is predominantly based on cross‐sectional studies, measuring TV viewing as proxy for sedentary behaviour. This systematic review and meta‐analysis summarizes the evidence on the prospective relationship between childhood sedentary behaviour and biomedical health indicators, overall and stratified by type of sedentary behaviour (TV viewing, computer use/games, screen time and objective sedentary time).PubMed, EMBASE, PsycINFO and Cochrane were systematically searched till January 2015. Methodological quality of all included studies was scored, and a best evidence synthesis was applied.We included 109 studies of which 19 were of high quality. We found moderate‐to‐strong evidence for a relationship of overall sedentary time with some anthropometrics (overweight/obesity, weight‐for‐height), one cardiometabolic biomarker (HDL‐cholesterol) and some fitness indicators (fitness, being unfit). For other health indicators, we found no convincing evidence because of inconsistent or non‐significant findings. The evidence varied by type of sedentary behaviour. The meta‐analysis indicated that each additional baseline hour of TV viewing (β = 0.01, 95%CI = [−0.002; 0.02]) or computer use (β = 0.00, 95%CI = [−0.004; 0.01]) per day was not significantly related with BMI at follow‐up.We conclude that the evidence for a prospective relationship between childhood sedentary behaviour and biomedical health is in general unconvincing.

This review is an update of a previous review published in 2010, and aims to summarize the available studies on the measurement properties of physical activity questionnaires for young people under the age of 18 years.