David Dunne

Liverpool John Moores University | LJMU · School of Sport and Exercise Sciences

Purpose: Here we assess the feasibility of using machine learning models to non-invasively predict muscle glycogen use during exercise. Methods: Two data sets comprised of: 1. Open-source group data from 166 studies, 2. Manually compiled granular data reported at an individual level from 8 studies published subsequently from the first data set matc...

Background It has recently been identified that manipulating carbohydrate availability around exercise activity can enhance training-induced metabolic adaptations. Despite this approach being accepted in the athletic populations, athletes do not systematically follow the guidelines. Digital environments appear to allow nutritionists to deliver this...

Aim: This study aimed to explore athletes' experiences and opinions of communication strategies in applied sports nutrition, as well as capture suggestions for future mobile app supportive solutions. Methods: A qualitative approach was used for this research. Data was generated from semi-structured focus groups (n = 9) with a purposive sample of 4...

This study aimed to explore how social media is being used by sports nutritionists as part of service provision, as well as practitioners' experiences and opinions of its use in practice. An exploratory sequential mixed methods approach was used during this research. Forty-four sports nutritionists completed an online survey detailing their persona...