Evidence map›Paper›PMID 38307539›Full record

SynthesisBMJ open2024

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research.

Amber L Pearson, Calvin Tribby, Catherine D Brown, Jiue-An Yang, Karin Pfeiffer, Marta M Jankowska

Abstract readSystematic Review
In one paragraph

Synthesis in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Urban greenspace and dementia: Measures, mechanisms, and methodological guidance.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
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

6 authors.

Amber L PearsonCS Mott Department of Public Health, Michigan State University, Flint, MI, USA apearson@msu.edu.ORCID 0000-0002-8848-1798
Calvin TribbyDepartment of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, USA.
Catherine D BrownDepartment of Geography, Environment and Spatial Sciences, Michigan State University, East Lansing, Michigan, USA.ORCID 0009-0007-3038-4745
Jiue-An YangDepartment of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, USA.
Karin PfeifferDepartment of Kinesiology, Michigan State University, East Lansing, Michigan, USA.
Marta M JankowskaDepartment of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, USA.

Funding

Impact of ecological park restoration on health in low income neighborhoods: A natural experimentR01CA239187 · NCI · MICHIGAN STATE UNIVERSITY · PI PEARSON, AMBER L. · 2019 to 2023
$3.1M
Death Receptor-mediated Apoptosis and Therapy Strategies in Ovarian CancerR01CA123197 · NCI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI ZHOU, TONG · 2007 to 2011
$2.1M
NCI NIH HHS R01 CA123197NCI NIH HHS R01 CA239187
6 · The paper itself

Abstract

Global Positioning System (GPS) technology is increasingly used in health research to capture individual mobility and contextual and environmental exposures. However, the tools, techniques and decisions for using GPS data vary from study to study, making comparisons and reproducibility challenging.

objectivesThe objectives of this systematic review were to (1) identify best practices for GPS data collection and processing; (2) quantify reporting of best practices in published studies; and (3) discuss examples found in reviewed manuscripts that future researchers may employ for reporting GPS data usage, processing and linkage of GPS data in health studies.

designA systematic review. DATA SOURCES: Electronic databases searched (24 October 2023) were PubMed, Scopus and Web of Science (PROSPERO ID: CRD42022322166). ELIGIBILITY CRITERIA: Included peer-reviewed studies published in English met at least one of the criteria: (1) protocols involving GPS for exposure/context and human health research purposes and containing empirical data; (2) linkage of GPS data to other data intended for research on contextual influences on health; (3) associations between GPS-measured mobility or exposures and health; (4) derived variable methods using GPS data in health research; or (5) comparison of GPS tracking with other methods (eg, travel diary). DATA EXTRACTION AND SYNTHESIS: We examined 157 manuscripts for reporting of best practices including wear time, sampling frequency, data validity, noise/signal loss and data linkage to assess risk of bias.

resultsWe found that 6% of the studies did not disclose the GPS device model used, only 12.1% reported the per cent of GPS data lost by signal loss, only 15.7% reported the per cent of GPS data considered to be noise and only 68.2% reported the inclusion criteria for their data.

conclusionsOur recommendations for reporting on GPS usage, processing and linkage may be transferrable to other geospatial devices, with the hope of promoting transparency and reproducibility in this research. PROSPERO REGISTRATION NUMBER: CRD42022322166.

Indexed as

Geographic Information SystemsData CollectionEnvironmental ExposureHumansReproducibility of Resultsaccelerometerbuilt environmentexposomegeographic information systemimputationmobility

Identifiers

PMID38307539
PMCPMC10836389

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.