Many of you don't know that my day job is in the NHS. When I'm not writing articles about just how many aircraft certain carriers happen to have, I'm in a hospital.

I've worked in the NHS in various roles for 12 years now, currently I'm on a 'covid ward'. Actually that's a bit misleading, we no longer have dedicated 'covid wards' most wards now deal with it. That luxury no longer exists.
Since March I've been terrified of going to work due to a virus various halfwits like to claim doesn't exist and it's made all that worse wearing the PPE, the place feels like an oven. I probably sweat more water than I have the time to drink.
Things in the hospital started to get better in the middle of last year but that didn't last long. Things are ramping back up to where they were at the height of the pandemic.
I'm not worried though because my colleagues, from cleaners to doctors and from nurses to porters still know what they're doing. The building is getting scrubbed, patients are getting treated and staff still have a smile for each other despite the immense pressure.
That's actually something I'm proud of, the NHS is a team effort. All the staff no matter their role just make it 'work'.
NHS staff are still doing their jobs despite howls of 'tHe hoSpiTals r eMPty!!!'' from people with absolutely no comprehension of what is actually happening, cries of 'hoax!' from others with as much medical knowledge as a bruised pear.
People love to say 'they have time to make all of those tiktok videos' and that honestly exhausts me. People taking time on their break to boost their own morale, shocking eh?
Why am I tweeting this? I see the end of this approaching. Staff are getting vaccinated, the public will soon follow. Self-testing kits are now being deployed to staff again with the public to follow.
We're nearly there and I cannot wait for that day. I can't wait for a nice pint with friends after my shift and I see that day fast approaching. I'm happy.
For clarity, I'm not a doctor and I'm not a nurse. I'm a member of support staff and I've worked in a number of roles unrelated to patient care for those 12 years.

More from Health

Before we get too far into 2021, I thought I’d write a thread recapping some of the research that came out of my lab in 2020. Most of this work was led by my talented team of graduate students, Kerrianne Morrison, @kmdebrabander, and @DesiRJones.

Back in January, a news story was published about Kerrianne’s study showing improved social interaction outcomes for autistic adults when paired with another autistic partner.

A detailed thread about the study and a link to the paper can be found here (feel free to DM me your email address if you’d like a copy of the full paper for this study or any of our studies):


Another paper published early in 2020 (it appeared a few months earlier online) showed that traditional standalone tasks of social cognition are less predictive of functional and social skills among autistic adults than commonly assumed in autism research.


Next, @kmdebrabander led and published an innovative study about how well autistic and non-autistic adults can predict their own cognitive and social cognitive performance.
You gotta think about this one carefully!

Imagine you go to the doctor and get tested for a rare disease (only 1 in 10,000 people get it.)

The test is 99% effective in detecting both sick and healthy people.

Your test comes back positive.

Are you really sick? Explain below 👇

The most complete answer from every reply so far is from Dr. Lena. Thanks for taking the time and going through


You can get the answer using Bayes' theorem, but let's try to come up with it in a different —maybe more intuitive— way.

👇


Here is what we know:

- Out of 10,000 people, 1 is sick
- Out of 100 sick people, 99 test positive
- Out of 100 healthy people, 99 test negative

Assuming 1 million people take the test (including you):

- 100 of them are sick
- 999,900 of them are healthy

👇

Let's now test both groups, starting with the 100 people sick:

▫️ 99 of them will be diagnosed (correctly) as sick (99%)

▫️ 1 of them is going to be diagnosed (incorrectly) as healthy (1%)

👇

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