Hoorah! Blogtober day 4, and the resurrection of my Clinical Trials Q&A series.
This is a series where I answer questions about all things trials – this is the third post in this series, previous posts have looked at the first clinical trial, and why you might choose to do a trial in favour of using other study designs (this post explains the concept of randomisation, I’d recommend reading that one if you’re not sure what randomisation is – it’ll help this one make more sense).

This post looks at a concept that’s crucial to the success of trials – blinding.

What is blinding?

Blinding, also referred to as masking, refers to “the concealment of group allocation from one or more individuals involved in the research study“. In practice, that means that if you’re taking part in a trial, you will not know what treatment arm you have been allocated to. Often, your doctor or healthcare professional will not know either.

There are various different types of bias:

Table taken from the European Patients’ Academy

Why is blinding so important?

Blinding serves to avoid bias. Sources of bias can come from participants, clinical staff and/or the trial team that’s interpreting the results.

This is not a bad thing, it’s just a thing. We’re all human, and it’s human nature to be influenced by the things that we know or believe – if we don’t know them then we can’t exert our own biases. Think about it, if you have a headache and you take a pill that says it will make your head feel better, when you do feel better you are likely to attribute it to the actions of that pill. In actual fact your headache might have just lifted of its own accord, but you’re much more likely to believe it was a result of the pill.

This idea translates to clinical trials too – if you take part in a trial that’s aiming to find the best tablets to treat a headache and you are told that you have been allocated a headache-stopping pill, you’re more likely to report that your headaches have reduced since you started taking the pill. If you don’t know what the pill is (maybe it’s a sugar pill that has no medical ability at all, maybe it contains a drug that research think will cure headaches), then you are more likely to report the truth of whether your head is still hurting or not. We are swayed by the information that we have, particularly if that information has the potential to make us feel well or unwell.

Blinding is not only important for participants; clinicians, researchers and the people analysing the trial data can also be influenced by the knowledge of which group a participant has been allocated to. If the person recruiting participants into a trial, or treating people within that trial, knows which group their participants are allocated to, their behaviour may change. These changes are often subtle and completely subconscious, but they could influence the way that the participant views the treatment and therefore influence the results of the trial.

Blinding isn’t always possible

In an ideal world every study would be triple blind – participants, clinicians and researchers would all be blind to the treatment that the participant has been allocated to. The world isn’t ideal though, and lots of the trials that are going on involve complex interventions (i.e. not something as simple as a tablet that you can easily duplicate the look and feel of to ensure allocation remains concealed). Some trials are only able to run if they are single blinded, or completely unblinded- surgical trials for example. Innovative trial designs and techniques are often incorporated in an effort to overcome potential bias in these situations.

Blinding isn’t just important in clinical trials involving humans, lab research involving anything from mice to individual cells can be blinded too! I know that lots of people reading this are involved in laboratory research – if that is you, and you are not currently using blinding to avoid bias in your studies, head to the CAMARADES website.
CAMARADES (Collaborative Approach to Meta-Analysis and Review of Animal Data from Experimental Studies) aims to provide an easily accessible source of methodological support, mentoring, guidance, educational materials and practical assistance to those wishing to embark on systematic review and meta-analysis of data from in vivo studies; that includes providing help and support with things like blinding and randomisation. This resource is a brilliant starting point. If you’re not using techniques like blinding and randomisation in you’re research, you’re not alone. This article from The Scientist earlier this year (original publication here) suggests that more than 95 percent of the preclinical work cited by 109 clinical trial proposals lacked the hallmarks of best practices, such as randomization or blinding. It’s time to change this.