Evidence map›Paper›PMID 28219378›Full record

ArticleInternational journal of health geographics2017

From urban planning and emergency training to Pokémon Go: applications of virtual reality GIS (VRGIS) and augmented reality GIS (ARGIS) in personal, public and environmental health.

Maged N Kamel Boulos, Zhihan Lu, Paul Guerrero, Charlene Jennett, Anthony Steed

Abstract readEditorial
In one paragraph

Article in International journal of health geographics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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  5. Analysis of Bank Credit Risk Evaluation Model Based on BP Neural Network.Computational intelligence and neuroscience · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Maged N Kamel BoulosThe Alexander Graham Bell Centre for Digital Health, Moray College UHI, University of the Highlands and Islands, Moray Street, Elgin, IV30 1JJ, Scotland, UK. maged.kamelboulos@uhi.ac.uk.
Zhihan LuDepartment of Computer Science, University College London, 66-72 Gower Street, London, WC1E 6EA, England, UK.
Paul GuerreroDepartment of Computer Science, University College London, 66-72 Gower Street, London, WC1E 6EA, England, UK.
Charlene JennettDepartment of Computer Science, University College London, 66-72 Gower Street, London, WC1E 6EA, England, UK.
Anthony SteedDepartment of Computer Science, University College London, 66-72 Gower Street, London, WC1E 6EA, England, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The latest generation of virtual and mixed reality hardware has rekindled interest in virtual reality GIS (VRGIS) and augmented reality GIS (ARGIS) applications in health, and opened up new and exciting opportunities and possibilities for using these technologies in the personal and public health arenas. From smart urban planning and emergency training to Pokémon Go, this article offers a snapshot of some of the most remarkable VRGIS and ARGIS solutions for tackling public and environmental health problems, and bringing about safer and healthier living options to individuals and communities. The article also covers the main technical foundations and issues underpinning these solutions.

Indexed as

City PlanningCivil DefenseEnvironmental HealthGeographic Information SystemsHumansPublic HealthUser-Computer InterfaceVideo GamesARGIS (augmented reality GIS)Emergency trainingEnvironmental planningPhysical activityPokémon GoPublic healthSmart citiesUrban planningVRGIS (virtual reality GIS)

Identifiers

PMID28219378
PMCPMC5319160

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.