The Combined Attention Systems Test (CAST) is a modification of the ANT-I (Callejas, Lupiáñez, & Tudela, 2004) developed by Lawrence (2018).
This version of the CAST is programmed in Python 3.7 using the KLibs framework. It has been developed and tested on macOS, but should also work with effort on most Windows or Linux systems.
First, you will need to install the KLibs framework by following the instructions here.
Then, you can then download and install the experiment program with the following commands (replacing ~/Downloads with the path to the folder where you would like to put the program folder):
cd ~/Downloads
git clone https://github.com/TheKleinLab/CAST.git
This version of the CAST is a KLibs experiment, meaning that it is run using the klibs command at the terminal (running the 'experiment.py' file using python directly will not work).
To run the experiment, navigate to the CAST folder in Terminal and run klibs run [screensize],
replacing [screensize] with the diagonal size of your display in inches (e.g. klibs run 24 for a 24-inch monitor).
If you just want to test the program out for yourself and skip demographics collection, you can add the -d flag to the end of the command to launch the experiment in development mode.
When using the CAST, participants can be placed into one of two block conditions: the endo-first conditon, where participants complete the endogenous subtest of the CAST first, or the exo-first condition, where they complete the exogenous subtest of the CAST first.
To choose which condition to run, launch the experiment with the --condition or -c flag, followed by either endo or exo. For example, if you wanted to run a participant in the endo-first condition on a computer with a 19-inch monitor, you would run
klibs run 19 --condition endo
If no condition is manually specified, the experiment program defaults to running the exo-first condition.
To export data from the CAST, simply run
klibs export
while in the root of the CAST directory. This will export the trial data for each participant into individual tab-separated text files in the project's ExpAssets/Data subfolder.