Broadly, my research focuses on applying new methods to improve the design and evaluation of nutrition behavior change interventions.
Can studying differences in implementation and context during a school-based nutrition intervention RCT provide actionable direction for program improvement?
- Hierarchical Linear modeling
- Mixed Methods
- Qualitative Methods
- universally challenging food environment
- individual students responded differently to the same intervention
- students’ varying degrees of behavior change were linked to different psychological and social characteristics
I identified four unique profiles, or “phenotypes,” of behavior change and related psychosocial mediators among these students. This research was awarded a student research award at the Society for Nutrition Education and Behavior annual conference and led to my pursuit of a precision medicine equivalent for behavioral nutrition interventions.
Current Research: Psychosocial Phenotyping
How can computational methods help us identify psychosocial phenotypes?
In a project funded by a New York Academy of Sciences Sackler Institute for Nutrition Early Career Award, I aim to
- identify the psychosocial phenotypes that exist among residents of Washington Heights, a predominantly Latino community in NYC with high levels of diabetes and health disparity
- develop a mobile application that identifies individuals’ psychosocial phenotypes
Current Research: Mechanisms of Behavior Change
What are the mechanisms by which we can use digital technology to intervene on mediators of nutrition behavior?
- experiments on a social computing platform, LabInTheWild, that engages online volunteers in behavioral research
- a nutrition knowledge test that asked participants to compare the macronutrient content of real meal photos
Read press from Harvard School of Engineering and Applied Sciences here
These results suggest the potential for social computing as a setting for nutrition education. A second series of studies examining the influence of peer and expert explanations on attitudes about the healthfulness of controversial foods will launch Spring 2017 and aims to elucidate the spread of misinformation about nutrition and identify approaches for nutrition experts to debunk such myths. Findings from this research will help me select more effective intervention strategies when developing tailored nutrition interventions.
Identifying psychosocial phenotypes with data science methods and linking them to specific mediators and defined mechanisms for behavior change will lead to more efficient and more personalized tailoring of theory-based nutrition interventions.
In future research, I plan to use psychosocial phenotypes to select representative community members to participate in the user-centered design of a tailored nutrition intervention and assess the generalizability of these methods in other communities.