Sample size: A practical introduction

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.

Comparison groups should be similar

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.

Linear regression: a practical introduction

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.

Treatments should be compared fairly

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.

Dramatic treatment effects are rare

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.

Explanations about how treatments work can be wrong

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.

An update to the Evidence-Based Medicine Pyramid: why and how

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.

What is a pilot study?

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.

Hope may lead to unrealistic expectations

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 and its Limitations

Debiasing is about trying to account for and eliminate the influence of biases on our decision-making. This blog discusses effective debiasing techniques.

O problema da Medicina Baseada em Evidências e o que fazer em relação a isso

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.

Earlier is not necessarily better

This is the ninth 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 people often assume that early detection of disease leads to better outcomes. However screening tests can be inaccurate (e.g. misclassifying people who do not have disease as having disease). Screening can also cause harm by labelling people as being sick when they are not and because of side effects of the tests and treatments.