Understanding Tasks Through the Conceptual Framework of Adherence Engineering

Video

Frank Drews, MS, PhD, professor of cognitive and neural sciences at the University of Utah, Department of Psychology, discusses the steps that are involved in developing a better understanding of tasks through the conceptual framework of adherence engineering.

Frank Drews, MS, PhD, professor of cognitive and neural sciences at the University of Utah, Department of Psychology, discusses the steps that are involved in developing a better understanding of tasks through the new conceptual framework of adherence engineering.

Interview Transcript (slightly modified for readability).

“So I think the very first step is to understand tasks better and to really try to perform task analyses, which requires [researchers] to talk to people who have the expertise to perform those task analyses. To get human factors [engineers] involved is one important step. I think [in] infectious diseases [and] infection prevention and control, there’s a huge opportunity for people like us, human factors engineers and human factors specialists, to come in and to help understand the tasks better. I think the first step [is] to get additional expertise and to think about tasks.

The next step is to ask how feasible our expectations about task performance [are]. How realistic is it to expect a protocol [to be] followed in the clinical context? How much do we evaluate if this protocol is feasible or not and sustainable in its execution or not? So, that’s testing the reality in the context of performance, not only writing a protocol on the desk and saying that people will follow it even with the expertise of a subject matter expert, but really assessing how it can be followed in the clinical context; that’s another thing.

A third thing is that we want to think very hard about the equipment that is being used currently and how the equipment can be used [in a] smarter [way] and how we can ask questions about the usability of the equipment that is currently being used. Often equipment, despite manufacturers’ claims to the opposite, is not high in usability and understanding more about those problems. When equipment is poorly designed, it leads to a performance breakdown, and [we need to understand] more about those contributors to performance breakdowns, and ultimately, increased infections, for example, is [another] important component in all of this.

So, leveraging the expertise that human factors can provide is an important thing that can be done right now. I think the more interesting tasks in the future are trying to get more input on equipment development, trying to standardize certain types of equipment, and develop kits that actually guide people through the tasks they are performing.”

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