Data collection: A total of 976 Masters weightlifters from Australia, Canada, Europe, and the USA, ages 35 to 88 (51.1% female), completed an online survey in June 2021 that included questions on weightlifting injuries, chronic diseases, sport history, and training practices. 

Definition of injuries: Injuries were defined in relation to participation to weightlifting, namely whether training restriction occurred due to acute injuries sustained during weightlifting. The correspoding srurvey question was “Have you ever had training restrictions due to acute injuries sustained during or while performing weightlifting?” 

Purpose of the data collection:

To quantify acute injuries sustained during weightlifting that result in training restrictions and identify potential risk factors or preventative factors in Master athletes.  To evaluate potentially complex interactions of age, sex, health-related, and training-related predictors of injuries with machine learning algorithms. Ensembles of machine learning algorithms (support vector machines, generalized boosted methods,  random forests, one-layer neural network, and naïve Bayesian methods) were used for classification and prediction and compared to logistic regression models.

Individuals were invited to participate in the study through email, and newsletters by the national governing bodies of weightlifting, and via online platforms including Facebook and Instagram. The survey was administered online via Qualtrics (Provo, UT, USA). The survey was administered in June 2021 when the pandemic had already been in place for over a year.