scholarly journals An integrated approach to create a spatial database of parks for urban health research

Author(s):  
Mario Fontán-Vela ◽  
Roberto Valiente ◽  
Manuel Franco ◽  
Pedro Gullón
2018 ◽  
Vol 373 (1742) ◽  
pp. 20170022 ◽  
Author(s):  
Amy L. Milton ◽  
Emily A. Holmes

The science of mental life is critical for understanding both how we function, and impairments in our functioning. However, understanding the causal mechanisms underlying mental health disorders and developing new treatments are challenges too great to be solved by any individual approach. There is a growing awareness that translational research—from laboratory to patient and back again to animal models—will be critical for the improved understanding and treatment of mental health disorders. The motivation and intention to pursue translational approaches is therefore strong in mental health research, but critically, opportunities for interaction between basic scientists and clinicians are relatively limited, and vary depending on the institution in which researchers are working. This has promoted the development of a ‘culture gap’ between basic and clinical scientists that limits interaction and sharing of knowledge. Here, we provide 14 examples of contemporary translational research and call for an increased collaborative approach to mental health research that spans clinical diagnoses, levels of analysis and bridges between basic to clinical mental health sciences, including, but not limited to, psychology and neuroscience. What is needed is an inclusive and integrated approach, bringing together scientists working at all levels of enquiry with clinicians providing insights on what works (and what does not). To stimulate the much-needed innovation in therapeutic techniques, an analysis of component parts is critical. Our approach suggests simplifying complex behaviours into distinct psychological components. Asking collaboratively driven scientific questions about dysfunction will also benefit our fundamental understanding of mental life. This article is part of a discussion meeting issue ‘Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists'.


2020 ◽  
pp. 181-196
Author(s):  
Gina S. Lovasi ◽  
Steve Melly

This chapter serves to highlight strategies and challenges in bringing together multiple types of geographically referenced data for urban health research, such as linkage of electronic health records to area-based characteristics. The discussion highlights practical considerations that arise in data management, as well as strategies safeguard confidentiality.


2003 ◽  
Vol 10 (3) ◽  
pp. 267-274 ◽  
Author(s):  
BRIGIT OBRIST ◽  
PETER VAN EEUWIJK ◽  
MITCHELL G. WEISS
Keyword(s):  

2007 ◽  
Vol 84 (4) ◽  
pp. 469-471 ◽  
Author(s):  
Alan R. Fleischman

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yeferson Castaño Pineda ◽  
Juan Gabriel Piñeros Jiménez ◽  
Deisy Ríos Castro ◽  
Kamila Giraldo Quintero ◽  
Eliana Martínez Herrera

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Guibo Sun ◽  
Chris Webster ◽  
Michael Y. Ni ◽  
Xiaohu Zhang

Uncertainty with respect to built environment (BE) data collection, measure conceptualization and spatial scales is evident in urban health research, but most findings are from relatively lowdensity contexts. We selected Hong Kong, an iconic high-density city, as the study area as limited research has been conducted on uncertainty in such areas. We used geocoded home addresses (n=5732) from a large population-based cohort in Hong Kong to extract BE measures for the participants’ place of residence based on an internationally recognized BE framework. Variability of the measures was mapped and Spearman’s rank correlation calculated to assess how well the relationships among indicators are preserved across variables and spatial scales. We found extreme variations and uncertainties for the 180 measures collected using comprehensive data and advanced geographic information systems modelling techniques. We highlight the implications of methodological selection and spatial scales of the measures. The results suggest that more robust information regarding urban health research in high-density city would emerge if greater consideration were given to BE data, design methods and spatial scales of the BE measures.


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