Examining firearm recoil on neurometabolic changes associated with traumatic brain injury

Methods

Summary

This investigation utilizes a non-randomized, experimental design to examine the neurometabolic changes on skeet and trap shooters independently following repetitive gunshot.  These neurometabolic changes will be assessed through measuring the kinetic energy of the firearm and physiological differences in shooters during a typical round of skeet and trap. To recruit participants, fliers and sign-up sheets will be available at the desired, local gun club and shooting range. Incentives will be possible for those participating in the form of a gift card raffle. Following the shooting session, participant blood biomarkers will be analyzed and compared to gunshot recoil. These techniques will be used to determine is gunshot recoil causes a neurometabolic cascade, therefore making the shooter susceptible to concussion. 

Challenges

The most challenging experience with the project was recruitment of participants. However, the team has successfully gained consent from the desired gun club in order to recruit participants. We are hopeful to recruit 10-25 skeet and trap shooters for the study.

Pre Analysis Plan

For blood analysis of biomarkers S100B, GFAP, and UCH-L1, ELISA Kits will be used. After blood analysis, Collected data will be analyzed using Excel or SPSS Statistical Package for the Social Sciences.  Increased frequency of recoil may result in multiple acceleration and deceleration patterns introduced to the brain, therefore resulting in a neurometabolic cascade.  Kinetic energy of the firearm and physiological differences in shooters will be compared to changes in neurometabolic proteins.  Descriptive statistics will be used to report the demographics of the participants.  Means and standard deviations will be calculated for age, height, weight, and blood markers.  Frequencies and percentages will be calculated for gender, race, ethnicity and BMI.

Paired t-tests will be used to determine differences in neurometabolic blood biomarkers.  If neurometabolic changes are significant, these data will be compared to physiological differences in shooters.  Body weight and height will be used as comparable variables when assessing neurometabolic changes in shooters.  Correlation statistics will be used to determine the degree of relationship between recoil and body weight as well as between recoil and neurometabolic markers.  Logistic regression analysis will be used to determine possible relationships between recoil and BMI and recoil and gender.  Lastly, the Chi-squared
test of association will be used to determine group differences among gender, or BMI, with those whom did and did not demonstrate significant changes in biomarkers pre and post intervention.