How do sports injury epidemiological outcomes vary depending on athletes' response rates to a weekly online questionnaire? An analysis of 39-week follow-up from 391 athletics (track and field) athletes.

Objective: To explore how sports injury epidemiological outcomes (i.e., prevalence, average prevalence, incidence, burden, and time to first injury) vary depending on the response rates to a weekly online self-reported questionnaire for athletes.

Understanding the first injury in athletics and its effect on dropout from sport: an online survey on 544 high-level youth and junior athletics (track and field) athletes.

Objective: To describe the first injury and to investigate whether it plays a role in altering athletics' sustainable practice.

Methods: We conducted a cross-sectional study using an exploratory survey on the first injury and its consequences on athletics practice. In 2021, we asked all high-level athletes licensed with the French Federation of Athletics (FFA) under 18 years, under 20 years and under 23 years categories between 2007 and 2021.

Perceptions and beliefs on sports injury prediction as an injury risk reduction strategy: An online survey on elite athletics (track and field) athletes, coaches, and health professionals.

Objectives: To explore perceptions and beliefs of elite athletics (track and field) athletes, coaches, and health professionals, towards the use of injury prediction as an injury risk reduction strategy.

Design: Cross-sectional study.

Method: During the 2022 European Athletics Championships in Munich, registered athletes, coaches, and health professionals were asked to complete an online questionnaire on their perceptions and beliefs of injury prediction use as an injury risk reduction strategy.

Epidemiology of injuries in elite Women's Artistic Gymnastics: a retrospective analysis of six seasons.

Background: Women's Artistic Gymnastics (WAG) is a sport well known for requiring a heavy and difficult training load from a younger age to reach a high level of performance. This also is associated with an injury risk. Epidemiological studies are thus needed to improve injury prevention strategies.

Relationship between a daily injury risk estimation feedback (I-REF) based on machine learning techniques and actual injury risk in athletics (track and field): protocol for a prospective cohort study over an athletics season.

Introduction: Two-thirds of athletes (65%) have at least one injury complaint leading to participation restriction (ICPR) in athletics (track and field) during one season. The emerging practice of medicine and public health supported by electronic processes and communication in sports medicine represents an opportunity for developing new injury risk reduction strategies. Modelling and predicting the risk of injury in real-time through artificial intelligence using machine learning techniques might represent an innovative injury risk reduction strategy.