What we see and do not see – Some further notes on the observation studies…

Doing observation studies is not always as easy as it may seem at first glance, and Diane has already written much interesting stuff in her previous posts on the topic. I agree with her meta-observations, and I just thought I should add some of my views on this topic as well. My experiences are from my two days of observations on the children’s hospital, and the ward for children with tumour and blood diseases. Although the doctors and nurses work with very serious issues, I only experienced a very constructive atmosphere during my two days.

Most of the time when we visit the hospital environment we are there to receive treatment or visiting someone who is. We see a lot of things, and in some way they make sense. We see the blinking numbers on the wards, and we see the different screens used by the nurses and doctors. We see the white coats with blue stripes and don’t think more about that. But when we set out to actually study what is going on in this environment we not only have to see but also interpret the observations into scenarios. Even when we want to study a single system, and its effects on the work, it quickly becomes very evident that the workspace is a very entangled mesh of interactions between people and people and between people and machines. Some of these interactions are very short but nevertheless less important, and they are easy to miss if you are not focused. Some interactions are longer and thus also easier to observe. But in some cases, the more long-term interactions are also easy to miss because they are not continuous and thus have to be observed not only in terms of the shorter sequence as a whole (for instance, see example 2 below). 

So, what do we see during an observation visit? Lots of things, but it soon becomes clear that the things we do not (normally) see, are just as important, if not more. Just to give two quick examples:

    1. In the ward, at every workplace there are two screens for logging into applications, such as Cosmic, and other supportive tools. What is not (easily) seen is the parallell information storage that is widely used by the nurses. After almost a day at the ward, I suddenly realised that all the nurses had a small paper notebook, which they consulted now and then. It was kept in the pockets of the coat but was very difficult to observe. When asked about it, the nurse told me that the notebook was used to keep track of the details about each patient. The notebook seems to be an important but almost externally invisible information carrier. 
  1. Another observation that caught my attention, not because it was evident, but rather because it was not, was the role played by the alarm bell. The alarm has two functions, one that is an emergency call and the other, which is just a call for help with toilet visits or similar. Both are noted on the same display, and with similar sounds (still clearly easy to distinguish). However, the reactions to the alarms are completely different. In the second case, one or two nurses go over to the room, as soon as they are finished with their current tasks. In the first case, the work spaces are emptied within a few seconds. All tasks are interrupted, and almost everyone rushes to the room in question. Since they rush in the middle of a task, the software applications need to be extra supportive and help the nurse getting back into what he or she was doing. This is not something that is easily visible but could be of great importance. 

These two examples show in a clear way that observations can be multilayered and need to be both seen and put into the work context. In the case of the notebook, it was also something that was not really thought of by the nurses; it was so integrated into their work that they never gave it any thought. 

This makes on-site observation studies both important and interesting but also difficult at the same time. How to systematically get at these ”invisible” observations is a difficult matter, and from my experiences, I think it requires a long observation time to find many of them. 

Lars Oestreicher

Senior lecturer at Uppsala University
Lars Oestreicher is a researcher in Human-Computer Interaction/Disability research at Uppsala University. He has a background in Computer Science, with Psychology, Linguistics and Social Science as specialisation.

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