Cindy and Itzel provide us with a student perspective of their time at the Global Evidence Summit. It was the first meeting of Cochrane, the Campbell Collaboration, the Guidelines International Network (G-I-N), the International Society for Evidence-based Health Care and the Joanna Briggs Institute, which took place in September 2017. “…for our luck, it was our very first time attending a Colloquium. This event took place in the beautiful city of Cape Town, South Africa, the land of the first heart transplant”.
This blog follows on from Ammar’s previous post on meta-analysis, and provides further details on the history, value and implementation of this approach.
The Global Evidence Summit took place between 13th and 17th September 2017 in Cape Town, South Africa. The event saw over 1400 delegates from 77 countries gather to discuss how to use evidence to improve lives. Heidi Gardner (a PhD student in Applied Health Sciences) blogs on her thoughts, experience, tips and hope for the future after attending the Summit.
This is the fifteenth blog in a series of 34 blogs explaining 34 key concepts we need to be able to understand to think critically about treatment claims.
This blog explains how randomized allocation helps to ensure that the groups have similar characteristics. However, people sometimes do not receive or take the allocated treatments. The characteristics of such people often differ from those who do take the treatment as allocated. Therefore, excluding from the analysis people who did not receive the allocated treatment may mean that like is no longer being compared with like.
This blog provides an introduction to sample size and power; what it is, why it’s important to consider when designing a study, and how to carry out a power calculation.
This is the fourteenth blog in a series of 34 blogs explaining 34 key concepts we need to be able to understand to think critically about treatment claims.
This blog explains that if people in the treatment comparison groups differ in ways other than the treatments being compared, the apparent effects of the treatments might reflect those differences rather than actual treatment effects. A method such as allocating people to different treatments by assigning them random numbers (the equivalent of flipping a coin) is the best way to ensure that the groups being compared are similar in terms of both measured and unmeasured characteristics.
This blogs provides an overview of linear regression. It is suitable for those with little to no experience of this type of analysis. This is not a guide on how to conduct your own analysis, but instead will serve as a taster to some of the key terms and principles of regression.
This is the thirteenth blog in a series of 34 blogs explaining 34 key concepts we need to be able to understand to think critically about treatment claims.
This blog explains that if a treatment is not compared to something else, it is not possible to know what would happen without the treatment, so it is difficult to attribute outcomes to the treatment.
This is the twelfth in a series of 34 blogs explaining 34 key concepts we need to be able to understand to think critically about treatment claims.
This blog explains that large treatment effects (where everyone or nearly everyone treated experiences a benefit or a harm) are easy to detect without fair comparisons, but few treatments have effects that are so large that fair comparisons are not needed.
This is the eleventh in a series of 34 blogs explaining 34 key concepts we need to be able to understand to think critically about treatment claims.
This blog explains that treatments that should work in theory often do not work in practice, or may turn out to be harmful. An explanation of how or why a treatment might work does not prove that it works or that it is safe.
A pyramid has expressed the idea of hierarchy of medical evidence for so long, that not all evidence is the same. Systematic reviews and meta-analyses have been placed at the top of this pyramid for several good reasons. However, there are several counterarguments to this placement. This blog discusses a new, amended version of the pyramid, proposed in 2016.
A pilot study is a small scale preliminary study conducted in order to evaluate feasibility of the key steps in a future, full-scale project. Pilot studies can teach researchers about any amendments they will need to make to the design of the future study, in order to minimise waste of time and resources.
This is the tenth in a series of 34 blogs explaining 34 key concepts we need to be able to understand to think critically about treatment claims.
This blog explains that hope can be a good thing, but sometimes people in need or desperation hope that treatments will work and assume they cannot do any harm. Similarly, fear can lead people to use treatments that may not work and can cause harm. As a result, they may waste time and money on treatments that have never been shown to be useful, or may actually cause harm.
Debiasing is about trying to account for and eliminate the influence of biases on our decision-making. This blog discusses effective debiasing techniques.
This blog is a Portuguese translation of a blog discussing the problem of evidence-based medicine, with thanks to Cochrane Brazil Evidence Based Medicine is useful for informing healthcare professionals what works, what doesn’t, and helping to determine if the benefits outweigh the harms, but it’s far from perfect. This blog explores some of the issues.