This again is a simple one, so we'll just kind of leave the demonstration simple as well. Let's move over to manage survey participants. This will allow us to do a little testing. There are actually multiple ways to invite participants into a REDCap survey project. We're going to choose the easiest one which is just having a public link or a common link that anyone wanting to participate in the survey could be emailed or have it sort of hanging off a website. If you can get to that link then you can take the survey. Other ways you can choose include inviting participants and having only those individuals able to participate in the survey. Again, this one is pretty simple and so we'll just leave it simple in the demo. Here in the public survey link you see that I've got a public survey URL that gets rendered out for me. I'll just copy that one to the clipboard. Let's open another page here and I'll pretend that I just got that one by email, or that I just linked off of it from another web page. Now let's play around again with this survey. I'll say that I'm male. My age, man I'm really old today. I try to leave that field and it says, hey, you should have provided an integer. Please try again. So it would nag me. Until I put an integer in. If I put in something like 40, it says, okay, let's go. But if I choose something like 4, it'll come back and it'll tell me again, hey you said that you should be, this number should be between 5 and 110 in the setup. So you can see, it's not only checking for the type integer, it's also checking for the range. If I try to submit, without putting in information, about one of these required fields, it will come up and say hey, you need to provide a value for do you like ice cream. So I'll say no. And then I can submit. And I get that message that we set at the end of the survey. Now let's just try it again. This time we'll check out that branching logic. If I choose yes here for, do you like ice cream? Now, I'd get the chocolate. What is your favorite ice cream flavor? And also get the option to specify on this Click and Drag bar. How much I like ice cream. I'm a big fan. Okay, so we've tested the survey. We can now go in and start looking at the data. Let's go down to, actually let's choose one of the add edit records here. We've got two responses coming in for that particular survey. This is the last one that we put in. You'll notice that I can't edit these at this point. So we treat surveys a little differently than we treat case report forms, in that unless you absolutely specify that you want to break the glass. And if you have the user rights level to break the glass and it's survey information, it's going to allow you to see it but it won't allow you to edit it. Again, REDCap is not going to hold your data hostage and so you can set it up so that you can change those values. But again remember that everything that's done in REDCap and should be in any electronic data capture system is going to be logged. So we can look at the data individually as we're seeing here. The other thing we could look at is using the export tool. So we mentioned this in our earlier demo, where could export all of the data. We could do it in several different ways. Sometimes in survey research, especially if we're doing information where people are putting in, just typing in free text information, it makes sense to sort of render those out in PDF so that they're a little bit more readable. But in this case we'll just export. We'll do the display advanced options. Here are our questions. We'll say, give us everything that we have. And we'll not worry about de-identification. We'll hit submit. And at this point, again as before in our earlier example, we don't really know, REDCap doesn't know which statistics package we're going to be using. But it is pretty smart and it knows the metadata or the data dictionary information about your study, as well as, whatever data have been collected. And so we could choose as before, options to be able to download the script files for the statistics packages that upload the data, and get it rendered out ready for analysis. In this case we won't do that, we'll just kind of look at the data as it's coming in. We'll look at it in Excel. So here I see the data as its output with labels. I've got two entries. First one I answered no to the ice cream like question, and in that case it didn't give me the option of answering the last two. In the second case I answered yes. You'll recall that my answer was chocolate on my favorite. And I chose the very right-hand side of that slider scale, which codes over to 100. If I prefer the raw data, I can just choose the other icon here and open it up. You'll see that in this case, I don't have the chocolate label. I have the actual coded variables that were entered. Now, in most cases, you're not really going to want to analyze your datasets in Excel. But again, you've got these great features that allow you to download the data and the script files into the different statistics packages. And so, really if you add enough test data in, you know what the data is going to come out looking like. You've tested it. You can go ahead, and we often recommend that individual research teams, go ahead and start writing out the analysis scripts before collecting the data. With only this test data, that allows you really to sort of go from front to back data entry all the way over to data analysis, in a testing phase before you launch the survey or launch the study. So let's go back up and let's add a few more records, and then we'll look at one other way to review the data before we go live. Here I'll say that this is a gender. She is 30. She loves, she's sort of on the fence about ice cream. And let's again go to another record here, we're just reloading that same survey. We've got another female that doesn't care for ice cream. And we'll go one more time with a male that is a little bit older. Okay, so now we've got a little more test data in, and we're ready to go. We can go in now and play around with the graphical data view and stats. This really is sort of univariate analysis of data for any particular case report form or in this case, a survey. It's really not meant to be a statistical package again we really like statistical packages for analysis. But this is more or less a quick sanity check and a summary of the universal data for your particular instrument. After choosing the instrument that we are interested in viewing, we can just scroll down the page, and you can see that the test data that we've collected already, this is populating the graphical views that we're seeing. So anytime we have a categorical value like, the gender question, it's going to be shown here by default, as a bar chart. Any time I have a numerical value, like the age, or later on, that visual analog scale, it's going to show on this jitter plot. We can see the individual variables as well as the median. And again, for these univariate variables, we're going to do some quick stats on it to show the min/max/mean standard deviation and in core and in median. Again it's not really meant to be a stats package but for surveys especially for quick surveys like this one you can a pretty good feel of things just by viewing these sorts of screens. So again there is a categorical value on, do you like ice cream, what is your favorite ice cream, with our test data everything splits right down the middle. And then finally that, do you like ice cream question. So that is the graphical data view and descriptive stats module. Let's now go back into the project setup, and we'll just finish things out. So at this point on this simple project, we've done a lot of the heavy lifting of the work that needs to be done. We've worked through the main project settings, simple study, one survey. We've worked through the data collection instrument. Even gone through and tested. We know there are no identifiers there. We could look at the additional customizations, but again for this simple example project we really don't need to make any of the rest of the customizations live. Same with Project Bookmarks. We might look at just one quick thing under user rights that gets activated in the case of survey studies. Clicking on this end user. You'll notice that for the data entry forms, in this case surveys, one survey, any time we see a survey there when I am editing user rights within REDCap, at least we can have the option not only of read-write or no access. But they're also could be these special edit survey responses. If we initiated that here, I as a user would be able to sort of edit surveys after they came in. But again there would be this warning. There would also be this historical record of any of those changes that were made. Otherwise it looks just like what we're accustomed to with our last example. Okay so going back to the project set up again we could add users if we like but here we don't really need to and we'll say that we've tested the project thoroughly. At this point really if we're just doing a simple survey where we're going to email out the link as we've kind of copied and done here, in this example, we're really ready to go. Maybe one thing that we should do before we send it to folks, or send it to our colleagues to do further testing perhaps. We would just go to the other functionality and I would typically always erase all data there. That way we're getting rid of our pilot data. We're really sort of making the project clean at this point, it's ready to go. On this training server we're not allowed to move this into production but otherwise really we'd be ready. If we were thoroughly confident in our survey instrument. The next stage, if we were doing a survey where we were going to post a single URL that would allow anyone to take the survey. Whether that be by email or by posting it on a project website or what have you. We could just copy the link to clipboard we could just paste that into an email message and then send it to our intended recipients. They would then click on that link and then they would be able to go and take the survey. This is the method that you should use in your last assignment to publish your survey. We've gone through now a very quick hands-on demonstration of creating a REDCap survey project. Coding up a survey itself. Testing the survey by entering data. Reviewing those test data several different ways. Deleting the test data. Really, there's a lot more that we haven't explored than we have explored. But I think this gives a decent overview of how to do a simple survey type study in this REDCap platform.