Limits...
Spatial video geonarratives and health: case studies in post-disaster recovery, crime, mosquito control and tuberculosis in the homeless.

Curtis A, Curtis JW, Shook E, Smith S, Jefferis E, Porter L, Schuch L, Felix C, Kerndt PR - Int J Health Geogr (2015)

Bottom Line: In addition, SVG provides a means to spatially capture, map and archive institutional knowledge.SVG GIS output can be used to advance theory by being used as input into qualitative and/or spatial analyses.SVG can also be used to gain near-real time insight therefore supporting applied interventions.

View Article: PubMed Central - PubMed

Affiliation: Department of Geography, GIS Health and Hazards Lab, Kent State University, #413 McGilvrey Hall, Kent, OH, 44242, USA. acurti13@kent.edu.

ABSTRACT

Background: A call has recently been made by the public health and medical communities to understand the neighborhood context of a patient's life in order to improve education and treatment. To do this, methods are required that can collect "contextual" characteristics while complementing the spatial analysis of more traditional data. This also needs to happen within a standardized, transferable, easy-to-implement framework.

Methods: The Spatial Video Geonarrative (SVG) is an environmentally-cued narrative where place is used to stimulate discussion about fine-scale geographic characteristics of an area and the context of their occurrence. It is a simple yet powerful approach to enable collection and spatial analysis of expert and resident health-related perceptions and experiences of places. Participants comment about where they live or work while guiding a driver through the area. Four GPS-enabled cameras are attached to the vehicle to capture the places that are observed and discussed by the participant. Audio recording of this narrative is linked to the video via time stamp. A program (G-Code) is then used to geotag each word as a point in a geographic information system (GIS). Querying and density analysis can then be performed on the narrative text to identify spatial patterns within one narrative or across multiple narratives. This approach is illustrated using case studies on post-disaster psychopathology, crime, mosquito control, and TB in homeless populations.

Results: SVG can be used to map individual, group, or contested group context for an environment. The method can also gather data for cohorts where traditional spatial data are absent. In addition, SVG provides a means to spatially capture, map and archive institutional knowledge.

Conclusions: SVG GIS output can be used to advance theory by being used as input into qualitative and/or spatial analyses. SVG can also be used to gain near-real time insight therefore supporting applied interventions. Advances over existing geonarrative approaches include the simultaneous collection of video data to visually support any commentary, and the ease-of-application making it a transferable method across different environments and skillsets.

No MeSH data available.


Related in: MedlinePlus

Six different SVG intersect (each a different colored point) at a key location on the tornado path where multiple mortalities occurred.
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4528811&req=5

Fig1: Six different SVG intersect (each a different colored point) at a key location on the tornado path where multiple mortalities occurred.

Mentions: Six different SVGs were uploaded into the GIS. One manipulation included using a key word query to identify the locations of important phrases, such as “recovery”. By using the time stamp associated with each word coordinate, it is possible to return to the original transcription to gain further context of what was being described. Another easy task is to go to an area of importance, such as a particular street segment, to see what was described at that location. In Fig. 1 six different SVG intersect (each a different colored point) at a key location on the tornado path where multiple mortalities occurred. Although it is hard to read this graphic as whole, it should be thought of as a SVG index. By zooming into a location such as this, each GPS point, or displayed word, can be selected and matched back to the original transcription. Here the full commentary can be read and questions asked such as how do different people comment on this location, how many refer back to the events of the day, and how many comments focus more on recovery or the current setting. For any of these queries or manipulations, the associated video for that ride can be accessed to see exactly what was being described.gFig. 1


Spatial video geonarratives and health: case studies in post-disaster recovery, crime, mosquito control and tuberculosis in the homeless.

Curtis A, Curtis JW, Shook E, Smith S, Jefferis E, Porter L, Schuch L, Felix C, Kerndt PR - Int J Health Geogr (2015)

Six different SVG intersect (each a different colored point) at a key location on the tornado path where multiple mortalities occurred.
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4528811&req=5

Fig1: Six different SVG intersect (each a different colored point) at a key location on the tornado path where multiple mortalities occurred.
Mentions: Six different SVGs were uploaded into the GIS. One manipulation included using a key word query to identify the locations of important phrases, such as “recovery”. By using the time stamp associated with each word coordinate, it is possible to return to the original transcription to gain further context of what was being described. Another easy task is to go to an area of importance, such as a particular street segment, to see what was described at that location. In Fig. 1 six different SVG intersect (each a different colored point) at a key location on the tornado path where multiple mortalities occurred. Although it is hard to read this graphic as whole, it should be thought of as a SVG index. By zooming into a location such as this, each GPS point, or displayed word, can be selected and matched back to the original transcription. Here the full commentary can be read and questions asked such as how do different people comment on this location, how many refer back to the events of the day, and how many comments focus more on recovery or the current setting. For any of these queries or manipulations, the associated video for that ride can be accessed to see exactly what was being described.gFig. 1

Bottom Line: In addition, SVG provides a means to spatially capture, map and archive institutional knowledge.SVG GIS output can be used to advance theory by being used as input into qualitative and/or spatial analyses.SVG can also be used to gain near-real time insight therefore supporting applied interventions.

View Article: PubMed Central - PubMed

Affiliation: Department of Geography, GIS Health and Hazards Lab, Kent State University, #413 McGilvrey Hall, Kent, OH, 44242, USA. acurti13@kent.edu.

ABSTRACT

Background: A call has recently been made by the public health and medical communities to understand the neighborhood context of a patient's life in order to improve education and treatment. To do this, methods are required that can collect "contextual" characteristics while complementing the spatial analysis of more traditional data. This also needs to happen within a standardized, transferable, easy-to-implement framework.

Methods: The Spatial Video Geonarrative (SVG) is an environmentally-cued narrative where place is used to stimulate discussion about fine-scale geographic characteristics of an area and the context of their occurrence. It is a simple yet powerful approach to enable collection and spatial analysis of expert and resident health-related perceptions and experiences of places. Participants comment about where they live or work while guiding a driver through the area. Four GPS-enabled cameras are attached to the vehicle to capture the places that are observed and discussed by the participant. Audio recording of this narrative is linked to the video via time stamp. A program (G-Code) is then used to geotag each word as a point in a geographic information system (GIS). Querying and density analysis can then be performed on the narrative text to identify spatial patterns within one narrative or across multiple narratives. This approach is illustrated using case studies on post-disaster psychopathology, crime, mosquito control, and TB in homeless populations.

Results: SVG can be used to map individual, group, or contested group context for an environment. The method can also gather data for cohorts where traditional spatial data are absent. In addition, SVG provides a means to spatially capture, map and archive institutional knowledge.

Conclusions: SVG GIS output can be used to advance theory by being used as input into qualitative and/or spatial analyses. SVG can also be used to gain near-real time insight therefore supporting applied interventions. Advances over existing geonarrative approaches include the simultaneous collection of video data to visually support any commentary, and the ease-of-application making it a transferable method across different environments and skillsets.

No MeSH data available.


Related in: MedlinePlus