Developing an Evidence-based Approach to Diagnose and Treat Adults With a History of Concussion
Emerging evidence suggests that concussions (a type of mild traumatic brain injury; mTBIs) may cause chronic neurological disturbances with effects lasting beyond 20 years, changing brain structure and nearly doubling the risks of developing dementia into old age. Yet diagnoses remain notoriously difficult, gender differences are poorly understood, and negligible therapies exist to manage and treat these long-term effects. This project proposes using a combination of NeuroTracker (a promising software-based cognitive assessment and intervention for mild TBIs), with the latest MRI techniques and blood-based biomarkers of brain function, to provide unprecedented assessment sensitivity of long-term concussion effects, comparing older male and female adults, with and without a history of concussion. Additionally, NeuroTracker will be used as a therapeutic intervention to improve outcomes in adults with histories of concussion, with the combined assessments measuring efficacy pre-post training. This project aims to comprehensively understand the impacts of mild brain traumas into later life, via both physical and functional biomarkers of brain health. It will also validate the value of NeuroTracker as an accessible training intervention for recovering cognitive functions impacted by earlier-life concussions.
• It will be based on age (60+ years) and history of concussion (with the most recent concussion occurring at least one year prior to the study). Consistent with the literature, the history of concussion will be determined by interviewing participants about their experience with each experience of concussion (e.g. how was the injury sustained (sports injury, vehicle accident, etc.), how long has it been since the injury, did they experience a loss of consciousness during the event, how was their concussion diagnosed, what were their symptoms and when did the symptoms resolve).
⁃ The interview will also gather information on age, sex, gender, education, occupation, and medical history (e.g. mood, medications). These variables will be coded and included in analyses, as appropriate. For example, years of education and years since the most recent concussion can be used as covariates.