Incidence of Acute Injuries in Boxing

QUALITY ASSURANCE PLAN:

Master of Science (MSc) student monitored the data and guaranteed high data quality. Data was protected according to the Act on Data Protection and the Processing of Personal data (Icelandic law) and stored at the University of Iceland. Data was registered into Microsoft Excel and shared through a secure network with project advisors to promote transparency.

DATA CHECKS:

Data was checked for outliers.

SOURCE DATA VERIFICATION:

Data from printed out questionnaires, text messages and telephone calls was transferred manually to excel by the MSc student who double checked every information to makes sure there were no mistakes.

DATA DICTIONARY:

CTE: chronic traumatic encephalopathy; KO: knock out; TKO: technical knock out; TBI: traumatic brain injury; t-tau protein: total tau protein.

STANDARD OPERATION PROCEDURES:

Boxers were recruited through the MSc students visits to 7 boxing gyms in Iceland. Boxers got an oral introduction, followed by an invitation to participate in the study. After giving a written consent, subjective and objective outcome measures were collected by the MSc student and 2-3 trained research assistants.

Data was analysed by the MSc student using Microsoft Excel and SAS Analytics Software.

The MSc student was responsible for reporting adverse events and change management.

SAMPLE SIZE ASSESSMENT:

Sample size was set at 30 participants. To ensure that enough subjects finished the study after dropouts, for prediction analyses and the opportunity for subgroup analyses, at least 60 subjects were needed.

PLAN FOR MISSING DATA:

If data would have been found to be missing by any reason, each incident would be assessed by the MSc student and her advisors. Imputation methods might be used, the subject involved might have been asked to do a measurement or answer questionnaire again (depending on the time that has passed from the measurement/questionnaires until data is discovered missing) or the subject involved might be removed from the study.

STATISTICAL ANALYSIS PLAN:

Data analyses and statistics Database monitoring was performed by the MCs student and an advisor, independent of sponsors and competing interests.

Excel spreadsheets were used to calculate injury incidence per 100 participants, per 1,000 hours of training and per 100 fight participations, while injuries were calculated in number per participant after adjusting for dropouts. Injury incident rate was calculated for each location and each type of injuries. Analysis of variance (ANOVA) and t-tests were used to compare means. Chi-square test (χ2) was used to compare injury frequencies of different locations and different types of injuries between different training levels and to compare the difference in injury severity according to sex, training level, whether injury occurred during a training or a bout, age, years of training, injury location and injury type. Logistic regression was used to assess possible risk factors including BMI, age, sex, participants' dominant side, training level, years of boxing, whether participants were participating in other sports, number of hours spent training during the study period, number of hours spent training on average per week, participant competing in a bout during the study period, previous boxing related injuries, and loss in a bout during the study period.

Inclusion criteria

• ≥18 years old
• currently training actively
• ≥ 6 months boxing experience OR currently training at an advanced level

Exclusion criteria

• < 18 years old
• not training actively
• < 6 months boxing experience OR not currently training at an advanced level