‘Normal’ checklists are effective whenever there are advantages to standardising performance, time is not critical, the series of tasks is too long to be committed to memory (or there are likely to be interruptions to execution of the task that might interfere with memory retrieval), and the environment enables a physical list to be accessed and used.
Travel checklist. I also have a checklist that I use before I leave on an extended trip. It’s kind of a combo of a to-do list and a routine list. It’s stuff I need to get done, but I use the same list every time. And it’s a DO-CONFIRM checklist: I do my prep from memory but then check the list before I leave to verify that I took care of everything essential. These are the things that I’ve had the most trouble remembering in the past, so they’re on my list:
We may not like to admit it, but many of us can describe a time when we’ve made a mistake during the progress of a study. These mistakes can range from mixing up wires or forgetting to turn on an amplifier to forgetting to collect an essential piece of information that either requires additional processing time or prevents you from analyzing a certain variable altogether. Increased computing power and technological advancements have also made it easier than ever to collect data. We can collect five measures simultaneously in one study and hundreds of trials in no time at all. But where does this leave us now? We must set up all of this equipment and make sure it works together, monitor it as well as our participant or specimen, and somehow sift through all the data post hoc. Even with a detailed lab notebook, its no wonder problems can arise. Even just writing this makes me feel…exposed, as if I’m the only one who struggles with this. It seems so simple, how can I not get it perfect every time? I always thought that I just had to work harder to not miss small steps, but maybe I just needed a different, yet structured, perspective on how to manage such a high volume of complex information.
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