Research in Lyme Disease shows that it is very hard to identify clinically meaningful improvement for chronic patients whose symptoms tend to wax and wane. Our team developed a diagnostic tool - General Symptom Questionnaire (Fallon et all., 2019, PMID: 31867334) and gathered a lot of data on patients who attended our center for research and/or treatment. The purpose of the proposed study is to analyze the existing data to find clinically meaningful cut-offs on the scale that can inform clinicians on whether the patient improved or not. If you are interested in psychometrics and want to contribute to understanding of how the chronic disease evolves, this is the project for you.

The tasks may involve conducting data analysis (like PCA, decision tree), learning about recent trends in psychometrics (like longitudinal item response theory), writing -up manuscript on the results and participating in the annual conference on Lyme Disease.

This is an UNPAID research project.

Faculty Advisor

  • Professor: Mara Kuvaldina
  • Center/Lab: Lyme and Tick-borne Diseases Research Center
  • Location: 1051 Riverside Drive, New York, NY 10032
  • Our research agenda focuses on post-treatment Lyme disease chronic patients with persistent symptoms. Our research studies are varied, ranging from clinical treatment to the collection of biological samples for precision medicine investigations, to neuroimaging studies to identify aberrant brain-body circuits, to probing national medical record databases.

Project Timeline

  • Earliest starting date: 10/15/2022
  • End date: 12/31/2023
  • Number of hours per week of research expected during Fall 2022: ~10

Candidate requirements

  • Skill sets: experience with psychometrics will be a plus, R and or Python, PCA and decision tree techniques
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: No
  • Additional comments: While we cannot offer any financial support currently, this may change during the spring semester. This project assumes a co-authorship on a scientific publication.