Antibiotic resistance, sometimes referred to under the umbrella term antimicrobial resistance (AMR), is a worldwide public health concern.

Antibiotic resistance happens when bacteria adapt and can no longer be killed by antibiotic medicines.

Bacteria evolve through genetic mutations or acquiring resistance genes from other bacteria. This natural process has been accelerated by humans overusing or misusing antibiotics in healthcare, industrial manufacturing, and farming.

As a result, infections caused by antibiotic-resistant bacteria can be more challenging to treat.

Read more resources at the CDC and the World Health Organisation.

The process of capturing and storing carbon dioxide from the atmosphere, typically through natural processes like photosynthesis or through technological methods such as carbon capture and storage (CCS).

Many direct carbon capture methods require significant amounts of energy to operate, potentially offsetting the benefits of capturing carbon dioxide.

Gillick competency allows under 18s to consent to medical treatment without parental permission if they demonstrate sufficient understanding to comprehend the nature and implications of the treatment. Originating from the Gillick v West Norfolk case in 1985, it grants adolescents autonomy in healthcare decisions, particularly regarding sensitive matters like contraception.

Read more from the NSPCC here.

A junior doctor is any qualified doctor who has not yet become a consultant. This ranges from having just graduated to being a senior house officer, which takes about 10 years to complete. Despite the name, often a junior doctor might be the most experienced medical professional on a ward.

The BMA has a helpful guide to all doctors’ titles and an explainer on why junior doctors keep striking.

In January 2024, the NHS and UK government launched the Pharmacy First Scheme. The plan gives community pharmacists greater powers, allowing them to treat and prescribe for seven conditions.

These are as follows: acute otitis media, impetigo, infected insect bites, shingles, sinusitis, sore throat, and uncomplicated urinary tract infections.

The scheme was devised to reduce pressure on GPs by redirecting patients to community pharmacists for non-urgent conditions.

Read more about Pharmacy First here.

A Physician Associate, or PA, is a newly devised medical role. The idea is to have a sort of fast-track healthcare professional to support doctors in the “diagnosis and management of patients”.

PAs have been controversial, as they only have 2 years of training and they earn more than a junior doctor.

Read more here.

When we run a study, for instance, on a new drug, we can’t test it on everyone in the world. Instead, we have to test it on a group of people, or a ‘sample’. If you read a study and see this, (n=59), that means there were fifty nine subjects in the sample. The larger this sample size, the more reliable our test, meaning that the findings are more likely to accurately represent the population as a whole and less likely to result from random chance.

For example, if we wanted to test whether a new antiviral drug could treat coronavirus, we can draw better conclusions if we give it to 1000 people than if we give it to 10. We’d also have more reliable findings if we tested the drug on a whole range of people rather than just one demographic—like white women in their 30s.

This might sound simple enough, but people often make reliability errors in their everyday language. This usually happens when individuals rely too heavily on anecdotal evidence or single case studies. For instance, someone might say, “My friend had a bad reaction to that vaccine,” based on the experience of one person, despite the vaccine having been trialed successfully on thousands of people. Unfortunately, the human brain is prone to placing greater trust in individual stories or personal experiences over statistical data, leading to misconceptions about the reliability of certain treatments or interventions.

When a study talks about the results being "statistically significant," it means they are fairly confident it happened due to specific factors rather than by chance.

When you flip a coin, sometimes you get heads, and sometimes you get tails. If you flip it many times, you'd expect to get heads about half the time. But perhaps you flip the coin 10 times and get heads 9 times—that feels a bit unusual. However, it could still happen by chance.

In scientific studies, researchers use statistics to figure out the chances of their results happening randomly. They compare what they observed to what they would expect to see by random chance alone.

The rule of thumb is as follows: if the chance of getting the result they’ve recorded is less than 5%, then their results are "statistically significant." That means there's only a small probability that what they found happened randomly.

Imagine scientists made a new medicine to reduce blood pressure. They test the medicine on two groups of patients. One group receives the real medicine, and the other receives a fake pill called a "placebo."

After testing, they find that the group taking the real medicine had their blood pressure drop by 20%, while the group taking the placebo only dropped by 5%. Running statistical analysis, they find a result of 0.02, which is like saying there's only a 2% chance that the difference happened by random chance.

So, the scientists can conclude that the difference in blood pressure between the two groups is due to other factors and is not pure coincidence. Because they will have controlled for lots of other factors, they can be pretty confident that the medicine is what made the difference.

The Harvard Business Review and Khan Academy have good resources to understand statistical significance.

Validity is sometimes mixed up with reliability, but it specifically refers to the extent to which a study accurately measures what it claims to measure.

Therefore, something can be reliable while having low validity if it consistently and accurately measures the wrong underlying construct.

For instance, psychologists sometimes measure facial expressions when they want to determine emotional state. However, the extent to which this is a valid measure is contested, as it might not actually signify the emotions someone is feeling.

To summarise, a valid conclusion will be drawn from a study based on accurate, reliable, and relevant data.

Find out more detailed explanations on validity here.

Viruses and bacteria are both tiny organisms that can cause us illnesses, but they have important differences. People often mix them up when talking about infections.

Viruses are much smaller than bacteria, and they are not living cells. They can't survive or multiply on their own. Instead, they invade the cells of other organisms, like humans or animals, and use those “host” cells to multiply.

Bacteria are single-celled organisms that can live and reproduce independently. While some bacteria can cause infections, many are harmless or even useful.

Because of these differences, treatments for viral and bacterial infections are also different. Antibiotics can kill bacteria, but they won't work against viruses.

Read more on the differences between viruses and bacteria at The University of Queensland and The National Library for Medicine

Zoonotic viruses are viruses that an spread from animals to humans. They account for 75% of new diseases.

These viruses naturally reside in animals without causing them harm, but can sometimes infect humans, causing diseases. These infections can occur through various routes, such as direct contact with an infected animal, consumption of contaminated food or water, or through third parties like mosquitoes.

Some well-known examples of zoonotic viruses include Ebola, HIV, Swine Flu, and almost certainly COVID-19.

Read more about zoonoses in our article and at the World Health Organisation.