Cross-sectional design limits the ability to capture longterm physiological and health changes

The gap

Evidence profile

Sourced from the limitations section and future work of the source papers, classified as general, drawn from work published between 2024 and 2026, spanning 2 journals. Those papers have been cited 18 times in total.

Supporting evidence — 3 representative gaps

• Ageing, Sex Differences, and REDs Risk in Endurance Runners: An Integrated Cross-Sectional Study Protocol (2026) · Sports · doi

  cross-sectional design limits the ability to capture longterm physiological and health changes, - selection bias due to the highly specific, motivated, and generally health-conscious subgroup of master endurance runners, - indirect estimation of VO2max from maximal power output during cycle ergometry may systematically underestimate aerobic capacity, - cycling efficiency and the translation of Wmax to VO2max may vary by age and sex, - the generalisability of findings will be limited to older endurance runners rather than the general ageing population

  generallimitations section
  Keywords: cross-sectional design limits ability capture longterm physiological health
• Six Weeks of High-Intensity Interval Training vs. Small-Sided Games: Effects on Physical Performance in Female Basketball Players (2026) · Sports · cited 1× · doi

  aerobic capacity (VO 2 max) was estimated using an indirect method (30-15 IFT) which may be influenced by participants' motivation and testing conditions - training adaptations and interindividual heterogeneity in performance responses may have been impacted by variations in recovery status, sleep quality, and energy availability - the constancy of the administered training stimulus may have been impacted by the inability to accurately measure external and internal training loads outside of the intervention sessions - the lack of hormonal and molecular markers - the six-week duration of the intervention does not allow conclusions about long-term effects and the sustainability of the observed improvements - the absence of follow-up after the intervention - factors such as nutrition, recovery, and additional physical activities were not fully controlled and may have influenced performance outcomes

  generallimitations section
  Keywords: aerobic capacity max was estimated using indirect method
• The Effects of CrossFit® Practice on Physical Fitness and Overall Quality of Life (2024) · International Journal of Environmental Research and Public Health · cited 17× · doi

  Future studies on CrossFit® should investigate the long-term cardiovascular health effects of repeated workouts, especially among recreational participants and across differ- ent levels of training experience. While acute reductions in systolic and diastolic blood pressure have been observed following CrossFit® sessions, it remains unclear whether these hypotensive effects persist with long-term participation. In addition, the impact of repeated exposure to high-intensity CrossFit® on the VO2 max, HRV, sympathetic and parasym- pathetic balance and overall cardiovascular health warrants investigation for multiple reasons, particularly in optimizing training protocols to improve cardiovascular function and aerobic capacity (supporting sustained health benefits). Understanding how different CrossFit® workout types (e.g., metabolic conditioning and strength training) affect VO2 and autonomic regulation will provide insights for the design of physical fitness programs that enhance heart health while minimizing cardiovascular risks. Furthermore, upcoming research could examine sex-based differences in cardiovascu- lar adaptations, as hormonal influences and the muscle composition may contribute to the distinct responses and recovery requirements in males and females. Recovery strategies after intense CrossFit® sessions also need further investigation to promote both muscu- lar and cardiovascular recovery. Although high-intensity workouts impose considerable metabolic stress and elevate the VO2 levels, there is limited knowledge of how recreational CrossFitters recover from such exertions. Studies should analyze the recovery timeline using biomarkers (e.g., creatine kinase, total antioxidant status and malondialdehyde) and functional performance tests (e.g., countermovement jumps and prone planks) to develop effective strategies that support muscle function and cardiovascular recovery. These in- sights could aid in injury prevention, promote optimal recovery and support long-term physical activity (ultimately contributing to overall health). Integrating advanced technologies like surface electromyography and artificial intelli- gence for real-time physiological and biomechanical data analysis (e.g., muscle activation patterns, kinematics and kinetics) will enable wearable devices to provide immediate feedback, optimizing performance and movement quality. By capturing joint angles, limb velocities and muscle forces, these devices could help CrossFitters to correct inefficient movement patterns, reducing the injury risk and enhancing the training effectiveness. Up- to-date technologies have the potential to democratize sophisticated data analytics, bringing insights previously limited to research and high-performance settings to all CrossFit® prac- titioners. Machine learning algorithms could further personalize feedback, adapting the advice to each individual’s biomechanics and physiological responses over time. This ap- Int. J. Environ. Res. Public Health 2025, 22, 19 8 of 11 proach could improve the training safety and effectiveness by offering real-time customized guidance aligned with each participant’s biomechanics and conditioning level.

  generalfuture workevidence 5/5
  Keywords: crossfit cardiovascular health recovery training muscle long term high performance time effects repeated workouts recreational

Questions about this gap