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openaire: EC/H2020/856602/EU//FINEST TWINS Funding Information: KH is supported by Academy of Finland as part of PLANhealth Project (13297753). KH would also like to acknowledge FinEst (H2020 grant 856602) for supporting this study. SM was supported by an Australian National Health and Medical Research Council Early Career Fellowship (#1121035) and a University of Melbourne Faculty of Medicine, Dentistry and Health Sciences Research Fellowship. EI is supported by the Medical Research Council [MC_UU_12015/7, MC_UU_00006/5]. MS is supported by a Health Research Council of New Zealand Sir Charles Hercus Research Fellowship (Grant number 17/013). Neighbourhoods for Active Kids was funded by the Health Research Council of New Zealand (grant number 14/436). Authors would like to acknowledge prof. Marketta Kyttä her contribution to this research. Publisher Copyright: © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Measures of individual mobility, such as activity space, have been previously used to help improve our understanding of individuals’ interactions with their everyday environments. However, such methods have rarely been adopted in studying children's physical activity and active travel behavior. In this study, we use a combination of participatory mapping and accelerometer data collected from children aged 8–13 years living in Tāmaki Makaurau/Auckland, Aotearoa/New Zealand, to describe children's travel behavior and explore associations of active travel, physical activity, and socio-demographic characteristics with environmental attributes. The results from this study reveal complex associations between these different layers. Density of cycling routes was consistently associated with higher levels of physical activity captured via moderate-to-vigorous physical activity (MVPA), prevalence of active travel, and total activity space exposure. Nevertheless, population density, greenspace, and land-use mix revealed varying associations across different activity behaviors including MVPA, number of steps, and prevalence of active travel. The results from this study not only reassert the complexity of person–environment relationships, but also highlight the potential impacts of measurement and analytical methods on the study results. The novel combination of participatory mapping and accelerometer data together with activity space analysis provided new analytical insights which we discuss in this paper. This study concludes by reporting its observations and envisioning future research directions.

Additional file 8.

Additional file 2. Structured process to classify fidelity outcomes.

Additional file 1. Search terms and records identified.

Additional file 9. Forest and funnel plots for physical activity outcomes.

Additional file 6.

Additional file 5. Publications excluded with reasons at stages 1 and 2 of full-text screening.

Additional file 9.

Additional file 7.

Additional file 8. Quality assessment ratings for activity behaviour outcomes (physical activity and sedentary behaviour combined).

Additional file 3.

Additional file 2.

Additional file 5.

Additional file 1.

Additional file 7. Quality assessment ratings and classification results for fidelity outcomes.

Additional file 3. Hierarchies used to select activity behaviour outcomes.

Additional file 4.

Additional file 6. Table of descriptive characteristics of studies (n = 51) included in systematic review of school-based activity behaviour interventions.

Additional file 4. Formulae used for meta-analyses of physical activity and sedentary behaviour outcomes.

Additional file 1. STROBE statement checklist of items for cross-sectional studies.

Submitted by Nadir Basilio (nadirsb@uninove.br) on 2020-11-09T20:41:38Z No. of bitstreams: 1 Erika Kajiyama Ikeda.pdf: 1507334 bytes, checksum: d2c40945f4586af7655b46902996f0d5 (MD5) Made available in DSpace on 2020-11-09T20:41:38Z (GMT). No. of bitstreams: 1 Erika Kajiyama Ikeda.pdf: 1507334 bytes, checksum: d2c40945f4586af7655b46902996f0d5 (MD5) Previous issue date: 2020-06-23 O ecossistema da Internet das Coisas (IoT) traz uma nova perspectiva além das discussões da tecnologia em direção à criação de inteligência em um mundo interconectado. Nesse contexto, o principal desafio é criar um ambiente capaz de responder aos usuários e organizações em tempo real. Assim, esta pesquisa tem como objetivo desenvolver um modelo para explorar a relação entre IoT e Gestão do Conhecimento (GC) para gerar inteligência e conectividade a partir de um ecossistema inteligente da IoT. O desenho da pesquisa foi dividido em quatro fases. Na primeira, realizamos uma pesquisa exploratória e preliminar com base em 140 artigos para entender o objeto de estudo. Após essa fase, obtivemos 92 artigos de uma Revisão Sistemática da Literatura. Como resultado dessas duas fases, mapeamos os elementos da IoT, incluindo conectividade e inteligência, e evidenciamos que as tecnologias da IoT podem suportar a GC, o que chamamos de facilitadores de GC. No entanto, encontramos uma falta de estudos relacionados a GC apoiando os ecossistemas de IoT. Assim, na terceira fase, propusemos um modelo baseado na intersecção da literatura em ecossistema de IoT e GC. Este modelo foi composto por processos de GC, capacitadores de GC, ecossistema de IoT, conectividade e inteligência. Na quarta fase, revisamos o modelo com base na coleta de dados e no método de entrevista em profundidade aplicada em 12 entrevistados que tenham trabalhado com projetos de IoT. Confirmamos as perspectivas centradas em dados ou nos usuários dos ecossistemas da IoT, dos elementos da IoT e do suporte potencial do processo de GC para possibilitar as implementações do ecossistema de IoT. Assim, este estudo contribuí com duas novas visões, que chamamos de “Orientado a Inteligência” e “Orientado a Agregação de Valor”. Bem como a importância do uso de processos de GC, principalmente do processo de Integração de Conhecimento e do papel de um integrador de soluções na formação e manutenção de ecossistemas de IoT inteligentes and conectados. Essa integração traz o papel vital dos gerentes de projeto para lidar com a complexidade desse tipo de projeto devido à necessidade de gerenciar o conhecimento para realizar as entregas do projeto com as partes interessadas internas e externas. Assim, no ecossistema de IoT, é crucial entender o contexto de negócios, ter o conhecimento das tecnologias e saber como integrá-las e gerenciar todas as partes interessadas. The Internet of Things (IoT) ecosystem brings a new perspective beyond the technology's discussions towards the creation of intelligence in an interconnected world. In this context, the main challenge is to create an environment capable of responding to the users and organizations in real-time. Thus, this research aims to develop a model to explore the relationship between IoT and KM to generate intelligence and connectivity in IoT smart ecosystem. The research design was divided into four phases. In the first, we conducted an exploratory and preliminary search based on 140 articles to understand the object of study. After this phase, we reached 92 articles from a Systematic Literature Review. As a result of these two phases, we mapped the IoT elements, including connectivity and intelligence, as well, we evidenced that IoT technologies can support KM, which we call KM enablers. Therefore, we found a lack of studies related to KM supporting IoT ecosystems. Thus, in the third phase, we proposed a model based on the intersection of the IoT ecosystem and KM literature. This model was composed of KM processes, KM enablers, IoT ecosystem, connectivity, and intelligence. In the fourth phase, we reviewed the model based on data collection and the in-depth interview method with 12 interviewees who have worked with IoT projects. After the analysis, as findings, we confirmed the data-centric or user-centric perspectives of the IoT ecosystems, the IoT elements, and the potential support of the KM process to enable the IoT ecosystem implementations. Consequently, this study contributed with two new visions, which we call "Intelligence-Oriented" and "Value Add-Oriented". Besides, the importance of the use of KM processes, mainly the Knowledge Integration process and the role of a solution integrator for an IoT ecosystem more intelligent and connected. This integration brings the vital role of the project managers to cope with the complexity of this kind of project due to the need to manage the Knowledge to accomplish the project deliverables with internal and external stakeholders. Thus, in the IoT ecosystem, it is crucial to understand the business context, to have the know-how of the technologies, and know-how to integrate them and manage all the stakeholders.

Table S1. Information about observed variables and their descriptive statistics. (NÂ =â 1085) (DOCX 63.7 kb)

Hypothesised indirect relationships between childrenâ s school travel behaviour and the built environment, the social environment, household and child characteristics, and household and child beliefs. (DOCX 95.1 kb)

The hypothesised full structural equation modelling. (DOCX 561 kb)

Unstandardised estimated coefficients of the structural equation model of children’s active travel to school. Root mean square error of approximation (RMSEA) = 0.04, comparative fit index (CFI) = 0.94, Tucker-Lewis index (TLI) = 0.92. (DOCX 606 kb)

Hypothesised direct relationships between childrenâ s school travel behaviour and the built environment, the social environment, household and child characteristics, and household and child beliefs. (DOCX 98.3 kb)

Funder: Obayashi Foundation; doi: http://dx.doi.org/10.13039/501100008042, BACKGROUND: Although it is globally known that Japan has high prevalence of active school travel among children, there are few international studies on Japanese children's school travel. Moreover, only few studies have focused on the differences in their mode of travel between to-school and from-school. This study examined the associations of neighborhood built, safety, and social environments with walking to/from school among elementary school-aged children in Chiba, Japan. METHODS: We conducted an online survey with 1545 parents of children aged 6-12 years residing in Chiba between 25 and 27 November 2020 during the COVID-19 pandemic. A neighborhood was defined as the area of a postcode provided by the participants. Each neighborhood environment was assessed based on the built environment (new town designation, walkability, distance to school, population density), social environment (neighborhood cohesion and connection), and safety (CCTVs, a road section for walking alone, safety volunteers). Neighborhood walkability was measured using subscales of the Neighborhood Environment Walkability Scale (youth and abbreviated versions) including crime safety and traffic safety. Parents' perceived influence of COVID-19 on school commuting and after-school activities were also included in the model as covariates. Walking to and from school were separately analyzed using multinomial logistic regressions, where new towns and walkability were computed separately as explanatory variables. RESULTS: Four fifths of children walked to and from school daily. Walking to school was positively associated with crime safety, neighborhood connections, and schools sited in new towns. Walking from school had positive associations with traffic safety, neighborhood cohesion, and CCTVs, but negative associations with safety volunteers and after-school activities. The presence of a section for walking alone and perceived influence of COVID-19 had negative associations with walking to and from school. CONCLUSIONS: Recent social changes such as declining birthrate, decline in public elementary schools, and increasing after-school activities may change parental attitudes toward children's walking to/from school, and subsequently, their mode of school travel over time. To maintain the high prevalence of walking to/from school in Japan, multidisciplinary approaches involving different stakeholders from education, public health, and urban planning are required to overcome sectionalism and support this behavior in the long term.

BACKGROUND: This article reports the methods and findings for Aotearoa New Zealand's 2022 Report Card on Physical Activity for Children and Youth indicators, and on inequities within these indicators. METHODS: Grades were assigned to indicators using the Active Healthy Kids Global Alliance criteria depending on data availability, and inequities reported based on gender, ethnicity, disability status, area-level socioeconomic deprivation, urbanicity, and school year. Two additional indicators were included in this report card: Sleep, and Physical literacy. RESULTS: Grades were assigned to indicators as follows: Overall physical activity: C+, Organised sport and physical activity: B-, Physical literacy: B, Active transportation: D, Sedentary behaviours: C-, Sleep: B+, Whānau (family) and peers: D, School: C+, Government: A. Inequities across all socio-demographic variables were observed. An 'inconclusive' grade was assigned to the Active play, Physical fitness, and Community and Environment indicators due to insufficient data. CONCLUSION: It is imperative that targeted, comprehensive, and population-specific approaches are implemented to support health-promoting physical activity behaviours and reduce inequities among children and youth in Aotearoa. There is a need to promote all dimensions of physical activity (overall activity, active play, recreation, organised sport, active transportation) and the reduction of screen time through policy, research, evidence-based social marketing campaigns, and urban design. Regular, nationally representative surveys that enable the consistent and regular measurement of key Report Card indicators are needed.

Graphical abstract, Highlights • School travel policy and practices predominantly focus on road traffic safety. • Support from local government was the anchor of school travel policies and practices. • Safe pedestrian crossings around school may facilitate active school travel. • Biking and public transport to school was inequitable by school socioeconomic status. • An intersectoral approach is needed to support active school travel., Active school travel contributes to children’s physical, mental and social wellbeing. The prevalence of children’s active school travel, however, has been declining in many developed countries. Gaining insights into school culture and environments in relation to school travel behaviour is crucial to inform interventions. Using a multiphase mixed methods approach, this study aimed to provide a comprehensive understanding of how school policies and practices supported or inhibited school travel behaviour in Auckland, New Zealand. Data were drawn from Neighbourhoods for Active Kids, a cross-sectional study of 1085 children aged 8–13 years between February 2015 and December 2016. School representatives were interviewed regarding their policies and practices related to school travel behaviour and traffic around school, and the data were analysed thematically. An overarching theme, sub-themes and categories were contextualised for quantitative modelling using objectively measured school variables (school socioeconomic status, active school travel programme, built environments around school). Mixed effects multinomial logistic regression models were employed to determine associations between school travel mode and objectively measured child (sociodemographic characteristics, traffic safety perceptions) and school variables. Safety was the core concept of school travel policies, procedures and programmes. Significant differences in child variables, school socioeconomic status, and cycle lanes and traffic lights around school were found between children who actively travelled or used public transport to school and those driven to school. Overall, this study demonstrated the important role of school policy and procedures and the potential application of an intersectoral approach for interventions to support changes in school travel behaviour.