Threatening and nurturing mental health: insights from Danish elite athletes on the dynamic interplay of factors associated with their mental health.

Introduction: Numerous factors have been identified that potentially influence athletes' mental health. Given the predominant focus in the literature on athletes' mental health risk factors, our study aimed to explore elite athletes' perceptions of factors associated with their mental health and thriving based on the combination of holistic developmental and ecological approaches.

Methods: Seven Danish international elite athletes representing diverse sports were interviewed twice.

The impact of injuries on sports-related analgesic use in Danish youth elite athletes: A 4-week prospective cohort study.

Objectives: Investigate the association between injury severity and sports-related analgesic use, and explore the types and reasons for analgesic use in Danish youth elite athletes.

Design: 4-week prospective cohort study.

Methods: 713 youth elite athletes (44 % female) aged 15-20 years provided information on demographics, sports specific questions, and injury severity.

Stage 2 Registered Report: Anomalous perception in a Ganzfeld condition - A meta-analysis of more than 40 years investigation.

This meta-analysis is an investigation into anomalous perception (i.e., conscious identification of information without any conventional sensorial means).

Popping Pills in Youth Elite Sports-Fact or Fiction? A 36-Week Prospective Cohort Study of Analgesic Use in 1195 Youth Elite Athletes and Student Controls.

To investigate analgesic use in a cohort of Danish youth elite athletes and compare weekly analgesic use over 36 weeks to student controls. We also investigated and compared reasons for analgesic use and types of analgesics used. Prospective cohort study.

Finite-Time Lyapunov Exponents of Deep Neural Networks.

We compute how small input perturbations affect the output of deep neural networks, exploring an analogy between deep feed-forward networks and dynamical systems, where the growth or decay of local perturbations is characterized by finite-time Lyapunov exponents. We show that the maximal exponent forms geometrical structures in input space, akin to coherent structures in dynamical systems. Ridges of large positive exponents divide input space into different regions that the network associates with different classes.