ArticleTransactions in GIS : TG2018
Geographic Information Science and the Analysis of Place and Health.
Article in Transactions in GIS : TG, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- Commentary on Pessar et al.: 'Downscaling' United States state cannabis policy to investigate environmental and social impacts on cannabis use.Addiction (Abingdon, England) · 2025Article
- Beyond absolute space: modeling disease dispersion and reactive actions from a multi-spatialization perspective.International journal of geographical information science : IJGIS · 2025Article
- Using EMA to explore the role of Black adolescents' experiences in activity spaces in momentary negative emotion and marijuana use.Health & place · 2024Article
- River dataset as a potential fluvial transportation network for healthcare access in the Amazon region.Scientific data · 2023Article
- Geospatial Perspectives on the Intersection of Chronic Disease and COVID-19.Preventing chronic disease · 2022Article
- Mapping urban greenspace use from mobile phone GPS data.PloS one · 2021Article
- Returning to our roots: The use of geospatial data for nurse-led community research.Research in nursing & health · 2019Article
- Dynamic Estimation of Individual Exposure Levels to Air Pollution Using Trajectories Reconstructed from Mobile Phone Data.International journal of environmental research and public health · 2019Article
- Geographic Imputation of Missing Activity Space Data from Ecological Momentary Assessment (EMA) GPS Positions.International journal of environmental research and public health · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The representation of place is a key theoretical advancement that Geographic Information Science can offer to improve the understanding of environmental determinants of health, but developing robust computational representations of place requires a substantial departure from conventional notions of geographic representation in Geographic Information Systems (GIS). Unlike conventional GIS representations based on either objects or locations, we suggest place representation should incorporate dynamic subjective, experiential, and relational aspects of place, as the influence of place on health behavior concerns not only the features that can be objectively observed at a particular location but also the environmental perceptions of the individual, as molded by biological, social, and experiential characteristics. In addition, assessments of environmental exposures on health outcomes should focus on individuals' time-activity patterns and microenvironment profiles, which form a potentially unique personalized exposure environment for each individual. Addressing these representational challenges via collaborative research has the potential to advance both Geographic Information Science and health research.
Identifiers
What OpenQuestion holds
Registered trials
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.