In this video you are going to learn what Sensitivity and Specificity are and why those statistical values are important for you as a Physio Hi, welcome back to Phisiotutors Sensitivity and Specificity both influence, how valid or in other words how accurate a clinical test is Validity means to what degree a test measures What is claimed to measure, so for example a valid test for your body weight would be a scale There are a lot of different special tests in the literature to test for the same condition the more accurate a test the better the concepts of sensitivity and specificity will tell you which tests you should use to confirm or exclude an hypothesis Let's start with the basics Let's imagine that we have a couple of people who have a disease marked in red and some that don't With a perfect test we would be able to discover everyone with the disease and also detect the ones that don't have the disease But ones that have the disease and that are correctly diagnosed are called True Positives Which is abbreviated with TP The ones that do not have the pathology and that are correctly diagnosed as healthy are called True Negative Abbreviated with TN This test would then be 100% accurate in real life, however a perfect test does not exist And we will have patients that are diagnosed with the disease, but that are actually healthy called False Positives so for example this one would be False Positive and at the same time you will have patients with the disease, but your test could not detect them and was negative they are called False Negative abbreviated with FN Now let's look at a test that is 100% sensitive Sensitivity is the ability to detect something Imagine an alarm that you have installed at home and that goes off with the tiniest movement so 100% Sensitive test is a test that can detect all people that have the disease so no single Person that has the disease is missed you can imagine that you would want to have the highly sensitive test when you are testing for potentially fatal diseases like cancer Because missing an ill person could potentially lead to the person's death All the persons that tested negatives can be sent home because they definitely do not have the disease So with a 100% sensitive test Abbreviated as SN We do not have any False Negatives therefore if they have a negative test result We can be a 100% sure That they do not have to disease and we can rule them out SNNOUT like in the Snout of an animal in this example here is the mnemonic that you should remember Maybe you have already discovered the problem in the example from before We have two people who are diagnosed as positive, but who are actually healthy If we modify our example a bit, and we now say that for example everyone has a positive test outcome We still have a test that is 100% sensitive The problem now is that a lot of them are falsely diagnosed positive And therefore our test, accuracy will suffer, for this reason we need a test that is more specific So now let's look at a test that is 100% Specific you have to imagine Specificity as the extent to which a positive test result really represents the condition or disease of interest and not some other condition mistaken for it in this case when a test is positive you can be a 100% sure that this person has the disease However like you can see in this example here a specific test can miss people that have the disease So they are going to be sent home with a false negative result in 100% specific test there are no false positives so if a patient has a positive test result You can be a 100% sure that he has a disease in highly specific tests abbreviated as SP You are therefore looking for a positive test result In order to include or confirm your hypothesis Spin like in the spin of a basketball is the mnemonic that you should remember However the trade off of a very specific test is usually that people are falsely diagnosed negative So you will have a few people that are false negatives And that are sent home although they have the disease So ideally you would want to test that has a high sensitivity and a high specificity But unfortunately, this is rarely the case Now let's look at an example to make these two concepts of sensitivity and specificity that we have just discussed more concrete for patients with radicular pain from the lumbosacral area, two commonly used tests to in or exclude this condition out of Straight Leg Raise test and the Cross Straight Leg Raise test According to a review by Vander et al. (2000), the SLR has a sensitivity of 92% and a specificity of 28% and across SLR has a sensitivity of 28% and a specificity of 90% So which test are you going to use to exclude radicular pain from the lumbosacral region The answer is the straight leg raise test remember our mnemonic SNNOUT we are performing a highly sensitive test in order to look for a negative test outcome to rule out a disease if this test is negative. We can be pretty sure that our patient does not have lumbosacral radicular pain To confirm our hypothesis however, we are using the spin rule So we are going to do the Cross Straight Leg Raise test with a high specificity Alright This was our video on sensitivity and specificity if you are still struggling with these two concepts it often helps to gain a better understanding If you know how to calculate these two values you can learn that by a click on a video right next to me Alright, so I hope sensitivity and specificity have become clearer to you if this is the case and this video helped you please give it a like and Don't hesitate to send us questions If something is still unclear. Of course don't forget to subscribe our channel, and I'll see you in the next video. Bye