Abstract
The return of concussed students and student-athletes to the classroom is commonly referred to as return-to-learn (RTL). RTL, however, is often overshadowed by returning a student-athlete back to athletic competition (return-to-play), with few recommendations and studies evaluating the effect of improper management of recovery from a concussion in an academic setting. Therefore, the research proposed here aims to track how symptom severity, student behaviors, and oculomotor performance formulate our ability to prognosticate how a student will respond to academic stimuli post-injury. This will be achieved by longitudinally tracking student-athletes as they recover from concussion, using a repeated measures design to sample data. The data was analyzed using an analysis of variance mixed effects model to understand the relationship between daily behaviors and symptom prevalence. The study identified overall time, caffeine intake, alcohol consumption, screen time, music listened to, physical activity, sleep duration, step count, and gender as significant factors associated with concussion symptom recovery and classroom management. Linear regression was utilized to correlate RTL recovery time to oculomotor scores, to preliminarily show how these scores can inform medical personnel when a student can return, unrestricted, to the classroom, and the types of accommodations to suggest for use in the classroom during recovery. Additionally, the Rochester Institute of Technology was used as a case analysis of current RTL procedures (athletic and academic management) to find areas of inefficiencies in providing timely and sufficient support to concussed students. The data collected and presented in this study was utilized to develop preliminary, evidence-based RTL guidelines to provide clinicians, athletic training staff, and university stakeholders with policies and practices to better ensure proper care is taken among students recovering from a concussion.
Library of Congress Subject Headings
Brain--Concussion--Rehabilitation; College athletes--Health and hygiene; College sports--Management
Publication Date
12-2022
Document Type
Thesis
Student Type
Graduate
Degree Name
Science, Technology and Public Policy (MS)
Department, Program, or Center
Public Policy (CLA)
Advisor
Zachary Bevilacqua
Advisor/Committee Member
Eric Hittinger
Advisor/Committee Member
Jennifer Bailey
Recommended Citation
Vanderhorst, Maya, "Policy Recommendations for Concussion Recovery: Using Evidence Based Data for a Safe Return to Learn in Student-Athletes" (2022). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/11346
Campus
RIT – Main Campus
Plan Codes
STPP-MS