Dataset Information

A Conceptual Framework for Modelling Safe Walking and Cycling Routes to High Schools.

ABSTRACT: Active transport to or from school presents an opportunity for adolescents to engage in daily physical activity. Multiple factors influence whether adolescents actively travel to/from school. Creating safe walking and cycling routes to school is a promising strategy to increase rates of active transport. This article presents a comprehensive conceptual framework for modelling safe walking and cycling routes to high schools. The framework has been developed based on several existing relevant frameworks including (a) ecological models, (b) the "Five Es" (engineering, education, enforcement, encouragement, and evaluation) framework of transport planning, and (c) a travel mode choice framework for school travel. The framework identifies built environment features (land use mix, pedestrian/cycling infrastructure, neighbourhood aesthetics, and accessibility to local facilities) and traffic safety factors (traffic volume and speed, safe road crossings, and quality of path surface) to be considered when modelling safe walking/cycling routes to high schools. Future research should test this framework using real-world data in different geographical settings and with a combination of tools for the assessment of both macro-scale and micro-scale built environment features. To be effective, the modelling and creation of safe routes to high schools should be complemented by other interventions, including education, enforcement, and encouragement in order to minimise safety concerns and promote active transport.

SUBMITTER: Rahman ML

PROVIDER: S-EPMC7246540 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Conceptual Framework for Modelling Safe Walking and Cycling Routes to High Schools.

Rahman Mohammad Lutfur ML Moore Antoni A Smith Melody M Lieswyn John J Mandic Sandra S

International journal of environmental research and public health 20200510 9

Active transport to or from school presents an opportunity for adolescents to engage in daily physical activity. Multiple factors influence whether adolescents actively travel to/from school. Creating safe walking and cycling routes to school is a promising strategy to increase rates of active transport. This article presents a comprehensive conceptual framework for modelling safe walking and cycling routes to high schools. The framework has been developed based on several existing relevant fram ...[more]

PMID: 32397592

Similar Datasets

Project description:BackgroundThe literature has identified various factors that promote or hinder people's intentions towards COVID-19 vaccination, and structural equation modelling (SEM) is a common approach to validate these associations. We propose a conceptual framework called social media infodemic listening (SoMeIL) for public health behaviours. Hypothesizing parameters retrieved from social media platforms can be used to infer people's intentions towards vaccination behaviours. This study preliminarily validates several components of the SoMeIL conceptual framework using SEM and Twitter data and examines the feasibility of using Twitter data in SEM research.MethodsA total of 2420 English tweets in Toronto or Ottawa, Ontario, Canada, were collected from March 8 to June 30, 2021. Confirmatory factor analysis and SEM were applied to validate the SoMeIL conceptual framework in this cross-sectional study.FindingsThe results showed that sentiment scores, the log-numbers of favourites and retweets of a tweet, and the log-numbers of a user's favourites, followers, and public lists had significant direct associations with COVID-19 vaccination intention. The sentiment score of a tweet had the strongest relationship, whereas a user's number of followers had the weakest relationship with the intention of COVID-19 vaccine uptake.InterpretationThe findings preliminarily validate several components of the SoMeIL conceptual framework by testing associations between self-reported COVID-19 vaccination intention and sentiment scores and the log-numbers of a tweet's favourites and retweets as well as users' favourites, followers, and public lists. This study also demonstrates the feasibility of using Twitter data in SEM research. Importantly, this study preliminarily validates the use of these six components as online reaction behaviours in the SoMeIL framework to infer the self-reported COVID-19 vaccination intentions of Canadian Twitter users in two cities.FundingThis study was supported by the 2023-24 Ontario Graduate Scholarship.

Project description:BACKGROUND:Prognostic research has many important purposes, including (i) describing the natural history and clinical course of health conditions, (ii) investigating variables associated with health outcomes of interest, (iii) estimating an individual's probability of developing different outcomes, (iv) investigating the clinical application of prediction models, and (v) investigating determinants of recovery that can inform the development of interventions to improve patient outcomes. But much prognostic research has been poorly conducted and interpreted, indicating that a number of conceptual areas are often misunderstood. Recent initiatives to improve this include the Prognosis Research Strategy (PROGRESS) and the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) Statement. In this paper, we aim to show how different categories of prognostic research relate to each other, to differentiate exploratory and confirmatory studies, discuss moderators and mediators, and to show how important it is to understand study designs and the differences between prediction and causation. MAIN TEXT:We propose that there are four main objectives of prognostic studies - description, association, prediction and causation. By causation, we mean the effect of prediction and decision rules on outcomes as determined by intervention studies and the investigation of whether a prognostic factor is a determinant of outcome (on the causal pathway). These either fall under the umbrella of exploratory (description, association, and prediction model development) or confirmatory (prediction model external validation and investigation of causation). Including considerations of causation within a prognostic framework provides a more comprehensive roadmap of how different types of studies conceptually relate to each other, and better clarity about appropriate model performance measures and the inferences that can be drawn from different types of prognostic studies. We also propose definitions of 'candidate prognostic factors', 'prognostic factors', 'prognostic determinants (causal)' and 'prognostic markers (non-causal)'. Furthermore, we address common conceptual misunderstandings related to study design, analysis, and interpretation of multivariable models from the perspectives of association, prediction and causation. CONCLUSION:This paper uses a framework to clarify some concepts in prognostic research that remain poorly understood and implemented, to stimulate discussion about how prognostic studies can be strengthened and appropriately interpreted.

Project description:Over the past century, the environment of the Gulf of Mexico has been significantly altered and impaired by extensive human activities. A national commitment to restore the Gulf was finally initiated in response to the unprecedented Deepwater Horizon oil spill in 2010. Consequently, there is a critical need for an assessment framework and associated set of indicators that can characterize the health and sustainability of an ecosystem having the scale and complexity of the Gulf. The assessment framework presented here was developed as an integration of previous ecological risk- and environmental management-based frameworks for assessing ecosystem health. It was designed to identify the natural and anthropogenic drivers, pressures, and stressors impinging on ecosystems and ecosystem services, and the ecological conditions that result, manifested as effects on valued ecosystem components. Four types of societal and ecological responses are identified: reduction of pressures and stressors, remediation of existing stressors, active ecosystem restoration, and natural ecological recovery. From this conceptual framework are derived the specific indicators to characterize ecological condition and progress toward achieving defined ecological health and sustainability goals. Additionally, the framework incorporates a hierarchical structure to communicate results to a diversity of audiences, from research scientists to environmental managers and decision makers, with the level of detail or aggregation appropriate for each targeted audience. Two proof-of-concept studies were conducted to test this integrated assessment and decision framework, a prototype Texas Coastal Ecosystems Report Card, and a pilot study on enhancing rookery islands in the Mission-Aransas Reserve, Texas, USA. This Drivers-Pressures-Stressors-Condition-Responses (DPSCR4 ) conceptual framework is a comprehensive conceptual model of the coupled human-ecological system. Much like its predecessor, the ecological risk assessment framework, the DPSCR4 conceptual framework can be tailored to different scales of complexity, different ecosystem types with different stress regimes, and different environmental settings. Integr Environ Assess Manag 2019;15:544-564. © 2019 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Dataset Information

A Conceptual Framework for Modelling Safe Walking and Cycling Routes to High Schools.

Publications

A Conceptual Framework for Modelling Safe Walking and Cycling Routes to High Schools.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets