Category / Featured academics

Health Promotion article is being read

Our article ‘Understanding health education, health promotion & public health’ [1] is getting read according to ResearchGate.  This conceptual/ theoretical paper was published open access in late 2021 in the Journal of Health Promotion and it reached 4,500 reads yesterday. Whilst the web side of the journal suggests today that the PDF of the paper has been downloaded 8,511 times.

 

Prof. Edwin van Teijlingen

Centre for Midwifery & Women’s Health (CMWH)

 

 

Reference:

  1. van Teijlingen, K. R., Devkota, B., Douglas, F., Simkhada, P.,  van Teijlingen, E. R. (2021). Understanding health education, health promotion and public health. Journal of Health Promotion, 9(1): 1–7. https://doi.org/10.3126/jhp.v9i01.40957

The last BU blog of 2023

First of all: Happy New Year!

One of the first message I received this morning was that our editorial ‘Addressing the inequalities in global genetic studies for the advancement of Genetic Epidemiology’ [1] had been published yesterday.  If I had know this in time it would have been the proper last Bournemouth University Research Blog of 2023 published yesterday.  Interestingly, we only submitted the draft editorial on Christmas Day, got it back for revisions on Boxing Day and resubmitted it and had it accepted on December 28th.   It dis, of course, help that both editors-in-chief of the Nepal Journal of Epidemiology are co-authors on this editorial!

 

Prof. Edwin van Teijlingen

Centre for Midwifery & Women’s Health (CMWH)

 

 

Reference:

  1. Sathian, B., van Teijlingen, E., Roy., B., Kabir, R., Banerjee, I., Simkhada, P., Al Hamad, H. (2023) Addressing the
    inequalities in global genetic studies for the advancement of Genetic Epidemiology. Nepal Journal of Epidemiology, 13(4):1292-1293.
    DOI: 10.3126/nje.v13i4.61271

Discovering Causal Relations and Equations from Data

Discovering equations, laws, or invariant principles underpins scientific and technical advancement. Robust model discovery has typically emerged from observing the world and, when possible, performing interventions to falsify models.

Recently, data-driven approaches like classic and deep machine learning are evolving traditional equation discovery methods. These new tools can provide unprecedented advances in computer science, neuroscience, physics, philosophy, and many applied areas.

We have just published a new study discussing concepts and methods on causal and equation discovery, outlining current challenges and promising future lines of research. The work also showcases comprehensive case studies in diverse scientific areas ranging from earth and environmental science to neuroscience.

Our tenet is that discovering fundamental laws and causal relations by observing natural phenomena is revolutionised with the coalescence of observational data and simulations, modern machine learning algorithms and domain knowledge. Exciting times are ahead with many challenges and opportunities to improve our understanding of complex systems.

This study is a collaborative work between eight universities in Europe and the United States (Valencia, Berlin, Tübingen, Jena, Stockholm, New York, and Bournemouth Universities).

Camps-Valls, G., Gerhardus, A., Ninad, U., Varando, G., Martius, G., Balaguer-Ballester, E., Vinuesa, R., Diaz, E., Zanna, L. and Runge, J., 2023. Discovering causal relations and equations from data. Physics Reports, 1044, 1-68 (Impact Factor=30).

 

Paper published on ‘living evidence’

The Nepal Journal of Epidemiology published today carries an article on so-called ‘living evidence’ as an on-going synthesis approach that provides up-to-date rigorous research evidence [1].  This short research methods paper argues that living evidence is particularly useful in rapidly expanding research domains, uncertain existing evidence, and incorporating new research evidence that may impact policy or practice, ensuring that health worker, managers and health-policy makers have access to the best, i.e. the most recent evidence.

The Nepal Journal of Epidemiology is an Open Access journal, and hence freely available to researchers across the globe.  The paper has been co-authored by researchers from the Denmark, Qatar, Mauritius and the UK.

 

Prof. Edwin van Teijlingen

Centre for Midwifery & Women’s Health (CMWH)

 

Reference:

  1. Sathian B., van Teijlingen E., do Nascimento I.J.B., Khatib M.N., Banerjee I., Simkhada P., Kabir R., Al Hamad H. (2023) Need for evidence synthesis for quality control of healthcare decision-making. Nepal Journal of Epidemiology 13(3):1288-1291.  DOI: 10.3126/nje.v13i3.61004