Rationale for Community-Based GIS and Spatial Analytic Methods

As noted earlier, with the rapid proliferation of mobile devices and sensor technology, science has become a way of life.32-35 Citizen scientists have empowered themselves and are using mobile devices or sensors (e.g., citizen sensors) to record their locations, daily activities, healthcare facilities, building heights, farmers markets, food stores and restaurants, blood pressure, duration of sleep, or body weight. The data are recorded using a specific metric that may consist of non-numeric or numeric attributes with a unit. Several options for data collection and infographics are available. An engaged community can define measures by attaching descriptors, blogging, goal setting, and self-monitoring or by tracking their summary health reports using infographics and other visual tools and analytics. Integrated wearable sensor technologies are available with GIS/ GPS trackers and spatial analytic methods for collecting, mapping, visualizing, and analyzing data anytime, anywhere. These technologies empower citizens with

Study

Approach

Use of GIS and Spatial Analytics

Comments

Dulin et al.12

Outcomes measured using CBPR and Geospatial Modeling

Community health needs assessment

Analysis of the patterns of healthcare access

Evaluation of intervention impact over time

GIS was used in supportive role by the research team to collect data and create geospatial models

Dulin et al.18

Geospatial models used to target interventions in neighborhoods

Data management

Implementation of interventions

Data validation using qualitative methods and surveys

GIS was used in supportive role by the research team to collect data and create geospatial models

GIS used to facilitate focus group discussions and decision-making

Ranking variables and assigning weights using the analytic hierarchy process for input into the geospatial models

Attribute assessment and evaluation

Jung31

Qualitative

geovisualization

Children’s meaning of community

Social network analysis

Identifying racial groups

Analysis of social proximity

Community photo mapping

Visualization of community resources

Community mapping

Study

Approach

Use of GIS and Spatial Analytics

Comments

Driedger et al.29

Health decision support system using GIS

Map production and a collaborative Web- based GIS tool

EYEMAP

development

Mapping

functionality

Web-based mapping tool

Cartographic design Data sharing

Dennis et al.3

Participatory photo mapping

Integration of digital tools, narrative interviewing, and participatory protocols

GIS and photo mapping used to support focus group discussions

Castleden et al.30

Participatory

photovoice

Mapping food environment

Mapping open space and safety

Culturally appropriate method

Community photo mapping

Visualization of community resources

Photovoice used to address environment and health questions

Brown et al.2

Physical activity and urban park benefits measured using GIS

Tested user usability of PPGIS website

Use of Google maps interface

Identification of park benefits

Supporting urban park studies

Park classification and

mapping

GIS used to study

physical activities and

benefits

Chirowodza et al.17

Geospatial methods used to target HIV interventions

Community health needs assessment

Identifying study sites and location

Identifying contextual factors

Implementation of interventions

Community mapping

Visualization of community resources

(continued)

Table 4.1 Continued

Study

Approach

Use of GIS and Spatial Analytics

Comments

Hill et al.29

Physical activity and food environment measured using CBPR and GIS

Analysis of patterns of physical activity and food environment

Development of walkability index

Implementation of interventions

GIS used to facilitate focus group discussions and decision-making

GIS used to facilitate the discussion of causal model of geographic influences

Spatial analysis conducted to determine spatial autocorrelation

Aronson et al.,20 Wood,13 Deeds et al.,21 and Topmiller et al.22

Neighborhood

mapping

Multilayered GIS approach

Community health needs assessment

Study of urban infant mortality prevention program

Integration of GIS, environmental audits, group narratives, and sketch mapping

Creation of geospatial measures

Identification of neighborhood characteristics and social determinants of health

Integration of multiple levels of data into maps and perspectives into policy action

Community mapping

timely information and actionable intelligence to engage in leisure activities and enhance healthy living.

A curiosity to learn and gain knowledge about their community’s health status motivates citizens to partner with scientists. Together, they systematically ask specific research questions, formulate hypotheses, design experiments, ensure proper collection of primary data, and verify or reject the hypothesis using collected observations. Throughout the scientific process, citizen scientists are encouraged and given equal opportunity to actively engage by challenging and contributing useful ideas that promote the community’s health. The ultimate goal of academic, scientific, or community partnership is to obtain credible and actionable scientific results that produce positive benefits.

O’Fallon and Dearry1 have outlined eight key CBPR benefits to scientists and communities if there is active participation, engagement, and honest communication among all partners in the scientific process: (1) increased relevance of research question; (2) increased quantity and quality of data collection; (3) increased use and relevance of data; (4) increased dissemination; (5) research translated into policy; (6) emergence of new research questions; (7) research and intervention extended beyond specific project; (8) builds infrastructure and sustainability.

The framework presented in Figure 4.1 can be used to (1) inform the comprehensive community needs assessment process, (2) guide the action plan, (3) facilitate the design of multilevel intervention plans (from individual/micro-level to institution and community/macro-level); and (4) increase the transferability of lessons learned. The framework integrates new tools, social network analysis methods and measures, and strategies, and is fused with the knowledge and expertise of a transdisciplinary team to work on multiple datasets at the individual or population level to influence health. The framework is inspired by the CBPR approach, multilevel intervention perspectives, public health perspectives, health literacy, behavioral psychology, statistical modeling, GIS approaches, and health disparities research.1-3,10-27-36

 
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