Lessons Learned and Next Steps for Analysis of a Fresh Produce Delivery Program for Food Insecure Patients in Durham, NC

During the course of this fellowship, the natural unfurling of a research project has ensued. Scientific progress is built on failure; learning to handle failures is a part of scientific life. Learning to be flexible as projects change course is also imperative as a community health scientist. I have learned valuable lessons from this project, but see clear next steps and ways to improve analyses in the future which can be of further help to the organization and the community it serves.


Lessons Learned

I am driven towards helping those who find themselves in situations similar to my own. Those with chronic diseases, in low-income situations, and part of minority communities are particularly near and dear to my heart, so this project working with low-income, minority, food insecure patient data was a natural calling. But it is challenging to come into a project with enthusiasm and think you will be able to run certain analyses, but then learn that the data is not able to support such analyses. This is what happened. I was excited to use survey data to measure the potential effectiveness of a fresh produce delivery program to food insecure patients, but the survey data did not have the correct questions asked or the correct controls to be able to support analysis of the program as an intervention. Instead, I have had to change my way of thinking and change the scope of the project due to limitations of the data, which is how it should be. You cannot make data do what you want it to do; you can only work within its limitations.

Scientific failures are failures in name only. In reality, they are lessons learned that continually improve the project. With perspective, what seems like limiting failures are actually opportunities to explore other avenues. So, I have designed the analysis as a cross-sectional study of the delivery program participant’s demographics. In addition, since there are survey measures for pre- and during COVID, I am able to measure food insecurity and stress scores as they are impacted by COVID, which has shed new light on how the program participants have been coping with the pandemic. What an opportunity, and I have happily shifted gears towards these analyses.


Next Steps

Overall, my contributions have helped to frame the data that this program has towards exploring its food recipients and making internal improvements. I have helped to describe what additional steps they need to take and what additional data needs to be gathered in order to explore the actual efficacy of the program. New surveys for participants are now being designed and will be employed soon. Ideally moving forward, this program will improve food security and stress levels in these patients, and can be used as a model framework for other communities. Further down the line, the hope is that programs such as this one will improve health conditions in the community, but this would require major shifts in food insecurity over a longer term in order to be able to measure changes. I look forward to the continued betterment of community health through nutritional access – a lofty goal, but a necessary and long-awaited one.