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Craig Pickering

Researcher at University of Central Lancashire

Publications -  47
Citations -  1255

Craig Pickering is an academic researcher from University of Central Lancashire. The author has contributed to research in topics: Athletes & Caffeine. The author has an hindex of 15, co-authored 45 publications receiving 828 citations.

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Wake up and smell the coffee: caffeine supplementation and exercise performance—an umbrella review of 21 published meta-analyses

TL;DR: It is suggested that caffeine ingestion improves exercise performance in a broad range of exercise tasks and the magnitude of the effect of caffeine is generally greater for aerobic as compared with anaerobic exercise.
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Are the Current Guidelines on Caffeine Use in Sport Optimal for Everyone? Inter-individual Variation in Caffeine Ergogenicity, and a Move Towards Personalised Sports Nutrition.

TL;DR: The drivers of this inter-individual variation in caffeine response are reviewed, focusing on the impact of common polymorphisms within two genes, CYP1A2 and ADORA2A, as well as current knowledge deficits in this area, along with future associated research questions.
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Do Non-Responders to Exercise Exist—and If So, What Should We Do About Them?

TL;DR: It is suggested that it is unlikely that global non-responders to exercise exist, and this insight serves to encourage health professionals to create more nuanced, efficacious, and individually-focused exercise prescriptions designed to circumvent and overcome apparent non-responsiveness.
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Caffeine and Exercise: What Next?

TL;DR: It is proposed that a better understanding of the wider, non-direct effects of caffeine on exercise, such as how it modifies sleep, anxiety, and post-exercise recovery, will ensure athletes can maximize the performance benefits of caffeine supplementation during both training and competition.
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A genetic-based algorithm for personalized resistance training

TL;DR: The results indicate that matching the individual's genotype with the appropriate training modality leads to more effective resistance training and the developed algorithm may be used to guide individualised resistance-training interventions.