A Community-Based Participatory Research Approach to Hurricane Katrina: When Disasters, Environmental Health Threats, and Disparities Collide

2020 ◽  
Vol 110 (10) ◽  
pp. 1485-1489
Author(s):  
Maureen Lichtveld ◽  
Hannah Covert ◽  
Jane El-Dahr ◽  
L. Faye Grimsley ◽  
Richard Cohn ◽  
...  

In 2005, Hurricane Katrina resulted in long-term flooding of 80% of New Orleans, Louisiana. Mold-infested homes gave rise to concerns about increased childhood asthma. To address these concerns, a diverse community–academic partnership used a community-based participatory research (CBPR) approach to implement the Head-off Environmental Asthma in Louisiana (HEAL) study in 2007. The study examined the relationship between post-Katrina mold and other environmental exposures and asthma morbidity, while testing an asthma counselor (AC) intervention. Both the AC intervention and the CBPR approach were effectively implemented in the postdisaster setting. However, homes had lower levels of mold and other allergens than expected, possibly because of the timing of environmental sampling. Also, HEAL illustrated the vulnerability of the study community, especially to the interconnected threats of health disparities, environmental health stressors, and disasters. We examine the implications of these threats for public health science, policy, and practice, not only through the lens of Hurricane Katrina but also for future disasters faced by communities in the Gulf Coast and nationally.

2018 ◽  
Vol 8 (3) ◽  
pp. 150 ◽  
Author(s):  
Melissa Olfert ◽  
Makenzie Barr ◽  
Kristin Riggsbee ◽  
Kendra Kattelmann ◽  
Krista Leischner ◽  
...  

Background: Using a Community-Based Participatory Research (CBPR) approach may increase the likelihood of relevance and acceptability of the designed intervention, especially on a college campus. Furthermore, recruiting and training college students to design a social marketing framed healthy lifestyle intervention for their peers will allow the intervention to be tailored to the needs of the campus. Objectives: To describe the process of online-course training college students to develop a campus-based, social marketing health promotion intervention. Methods: Four universities recruited current college students (18+ y.o.) to develop a social marketing and environmental intervention (SMEI), which was completed during a 16-week, online/in-person hybrid semester course. Researchers and Extension professionals trained students to design 24 weeks of intervention events that would be implemented the upcoming year. Results: Seventy-eight students enrolled in the study and social marketing and environmental intervention course among the four intervention states (Florida = 30, South Dakota = 8, Tennessee = 13, West Virginia = 27); students were predominately Caucasian (65.8%), females (84.0%), and sophomore status in college (64.9%). Throughout the semester, students assessed their campus environments, set priorities, and developed weekly events and resources needed to implement the intervention on their campuses. By the end of the semester, with researcher support, students had designed 24 weeks of intervention events (marketing, recruiting, and implementation) focusing on nutrition/food/diet, physical activity, stress management, sleep, and time management. These events and resources were catalogued into a digital toolkit of instructions and activities for each week of intervention events. Conclusion: Using a Community-Based Participatory Research approach with college students interested in health allows for the development of an intervention that stems from grass roots efforts and is tailored to the acceptability and needs of their peers.


Author(s):  
Tarun Reddy Katapally

UNSTRUCTURED Citizen science enables citizens to actively contribute to all aspects of the research process, from conceptualization and data collection, to knowledge translation and evaluation. Citizen science is gradually emerging as a pertinent approach in population health research. Given that citizen science has intrinsic links with community-based research, where participatory action drives the research agenda, these two approaches could be integrated to address complex population health issues. Community-based participatory research has a strong record of application across multiple disciplines and sectors to address health inequities. Citizen science can use the structure of community-based participatory research to take local approaches of problem solving to a global scale, because citizen science emerged through individual environmental activism that is not limited by geography. This synergy has significant implications for population health research if combined with systems science, which can offer theoretical and methodological strength to citizen science and community-based participatory research. Systems science applies a holistic perspective to understand the complex mechanisms underlying causal relationships within and between systems, as it goes beyond linear relationships by utilizing big data–driven advanced computational models. However, to truly integrate citizen science, community-based participatory research, and systems science, it is time to realize the power of ubiquitous digital tools, such as smartphones, for connecting us all and providing big data. Smartphones have the potential to not only create equity by providing a voice to disenfranchised citizens but smartphone-based apps also have the reach and power to source big data to inform policies. An imminent challenge in legitimizing citizen science is minimizing bias, which can be achieved by standardizing methods and enhancing data quality—a rigorous process that requires researchers to collaborate with citizen scientists utilizing the principles of community-based participatory research action. This study advances SMART, an evidence-based framework that integrates citizen science, community-based participatory research, and systems science through ubiquitous tools by addressing core challenges such as citizen engagement, data management, and internet inequity to legitimize this integration.


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