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mGeohealth: emerging applications of mobile technology

Project Description

Health and medical geography approaches have normally focused on residence-based conceptualisations as an approximation for multiple types of exposure. This is a ‘static’ place or point in time, usually a home address or a fixed administrative boundary, perhaps measured once every several years. However, we now are able to more accurately measure, the ‘true’ exposure, which can be captured ‘dynamically’; people moving between many places, places with differing environments and characteristics. This changes the quantum of data involved, the processing required and complexity of the challenges when using established statistical and geographical methods. From the literature, it is well recognised that place can be an important influence on health, either positive or negative; where we live matters for our health.

New methods and technologies, such as real-time personal mobile location data, afford an opportunity for new(er) approaches, with richer, large, fine-grained spatial data sources. However, these new data sources and accompanying methods bring with them a variety of new challenges, biases and opportunities. We propose an mGeoHealth, that is, the use of location-based applications for smart devices (e.g. smartphones and smart watches) in health. This means that mGeoHealth does not necessarily focus on adopting completely new technologies, but it aims to utilise readily available of smart devices, that are subsequently enhanced by suitable software or applications.

We wish to explore an mGeoHealth that sits at the intersection of the fields of mHealth (mobile health) and Health and Medical Geography (GeoHealth). As such it is a combination of two distinct, yet relatively unconnected domains. A focus on mGeoHealth is timely as it is a burgeoning area of specialised endeavour which is often missed broad(er) fields of mHealth or Health and Medical Geography. This new project can draw on a rich heritage of geographical endeavour, whilst adapting to new(er) methods of data collection and associated methods. To demonstrate the approach, we will use a series of real-life examples of data collections and associated analytics for discussion. We are particularly focused on mobility and movement as a source of exposure to environments (e.g. physical, social and so on) and also how mobility could exacerbate or ameliorate existing inequalities in health. This could be as diverse as exposure to air pollution or social connections. We will also explore the possibility of technology itself, to further alter health inequality.

Funding Notes

The Geospatial Research Institute Toi Hangarau (GRI) is pleased to offer ONE PhD scholarship as a supplement to the University of Canterbury PhD scholarship. This scholarship is available only to a new PhD applicant who will complete research towards an approved geospatial project. The scholarship value is NZ$9,000 per year plus up to NZ$2,000 for travel and other costs per year, in addition to the University of Canterbury scholarship: the total package is worth up to NZ$33,000 per year, plus tuition fees. For more details and to apply, please see here: View Website

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