Training

SCIENTIFIC SESSION

Anatomy and physiology of network meta-analysis

Speaker: Sergio Núñez de Arenas Arroyo

Sergio Núñez de Arenas Arroyo is a physiotherapist who graduated from the University of Castilla-La Mancha. After graduating, he combined clinical practice with a research collaboration grant in the Department of Nursing, Physiotherapy and Occupational Therapy at the University of Castilla-La Mancha, from 30/10/2019 to 19/06/2020. In addition, during this academic year, he completed his Master’s Degree in Socio-Health Research.

In 2020, he replaced his clinical practice with a contract funded by a research project entitled: “Physical activity prescription: from the evidence to the patient (PAFEP). Since 01/10/2020, through a Predoctoral Researcher Training contract, he has been working on his doctoral thesis while carrying out his research work at the Centre for Socio-Health Studies (a multidisciplinary research centre affiliated with the Faculty of Nursing, Cuenca).

Since beginning as a researcher in training, he has published 20 articles in JCR journals (of which 5 are network meta-analyses), has presented 33 posters/papers at international conferences and has taught classes in various modules of the degree course in Physiotherapy (Toledo) and the degree course in Nursing (Cuenca), as well as supervising several undergraduate dissertations.

Brief Description of the Session

In the last decade, network meta-analysis has become a “hot” research topic increasingly adopted by researchers in the biomedical field.

We are used to comparing the direct effect of two different interventions to find out which might be more effective in improving a given parameter. However, when we have a network of various treatments, in addition to the direct evidence, indirect evidence also comes into play. This is why the fundamentals of network meta-analysis can seem a little abstract. Therefore, the aim of this session will be to review, in small steps, the theory behind this statistical method, in order to gain a better understanding of it and be able to implement it more easily in our day-to-day research work.

The main points to be addressed in this session will be: