Natural History of Dry Eye Disease
Meng C. Lin, Professor
Optometry
Closed. This professor is continuing with Fall 2024 apprentices on this project; no new apprentices needed for Spring 2025.
Dry eye disease (DED) is pervasive with some reports estimating over 16 million adults diagnosed with DED in the United States. It has been well documented that race, sex, systemic conditions, medications, and contact lens use are among the risk factors for DED. There are numerous dry eye questionnaires and clinical tests used to aid in DED diagnosis. With so many DED diagnostic tools available, it is important to understand which may accurately and efficiently diagnose DED throughout adulthood. Additionally, it is important to understand the relationship between DED risk factors and the natural progression of DED over time. In this study, we aim to understand the natural history of dry eye disease in adults and investigate how to efficiently diagnose DED by administering a combination of questionnaires and clinical tests via a comprehensive evaluation on a recurrent basis.
Role: The undergraduate student will be responsible for the following:
- Understand ocular surface physiology
- Understand tear film physical properties
- Understand current study design and study aims
- Understand study protocol to effectively recruit subjects based on a
list of exclusion and inclusion criteria specific to the study
- Communicate details of the study with interested participants
- Schedule and keep track of participants’ appointments for the study
- Assist with obtaining non-invasive measurements of the ocular surface, once trained by the investigators
- Data management
- Help drafting a manuscript for publication upon study completion
This study will be a good opportunity for the student to take part in the process of research planning, data collection, and analysis. The student will gain knowledge in dry eyes, ocular surface physiology, clinical design, and scientific methodology.
Qualifications: It is important that the student has good communication skills and be comfortable interacting with participants. The student should be familiar with basic data management such as Microsoft Excel, REDCap, Google Workspace, or equivalent. It is important for the student to be able to work independently and as a team member. The ideal student would also be curious, proactive, and detail-oriented. A background in biology and interest in research would be beneficial in this role.
Day-to-day supervisor for this project: Dr. Jennifer Ding, Staff Researcher
Hours: 9-11 hrs
Biological & Health Sciences