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Journal Article

Citation

Harrison G, Grant-Muller SM, Hodgson FC. J. Transp. Health 2022; 24: e101335.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.jth.2022.101335

PMID

unavailable

Abstract

Introduction
Transport and health are complex, evolving and interacting systems, which are increasingly influenced by new and emerging data forms. In this study we address the research question, "How could New and Emerging Data Forms improve understanding of mobility behaviours, and the related health outcomes, of different population subgroups?"

Methods
We build on an existing causal loop diagram (CLD) of the transport-health system to include the influence of New Data & Technologies, through a novel online Delphi approach to system dynamics modelling.

Results
We present an improved CLD of the transport-health system and have identified the potential influence that Persuasive & Monitoring Technologies could have on transport-related health, including insights on the characteristics for representing and assessing them.

Conclusions
The findings presented in this study can improve the design of holistic future-focused transport, health and data policies and the application of system dynamics to these areas, and as such are of relevance to researchers, policy makers and system dynamics practitioners.


Language: en

Keywords

Causal loop diagram; Delphi; Group model building; New data; Policy; Transport-health

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