Mental Health in the Working World
Interaction with machines is an essential component of many occupations. Research into the interaction between people and machines focuses on functional sharing, interface design and use.
Due to increasing automation, human-machine interaction (HMI) now relates to a considerable number of employees. With automation, machines and automats (computer-guided machines) take over functions that were previously carried out by people. The scope of the functions that machines and automats can carry out is wide-ranging and, along with carrying out actions, can also consist of taking over functions in the area of human information processing.
Human-machine interaction is characterised by the fact that it is people who operate the machines. They give the machines tasks, set specific targets and check the working steps and results. The outcome of this interaction can be products, information or energy.
An appropriate sharing of functions between people and machines is important for achieving the given work targets. In addition to this, interfaces must also be designed, for example, input and output provisions. These provisions determine the mental and physical demands on the employees.
A scoping review by the Federal Institute for Occupational Safety and Health summarises the state of scientific knowledge regarding human-machine interaction. It focusses on the characteristics of function sharing, interface design and use, and considers their correlations with (mental) health and well-being. It also describes their relationships with motivation, job satisfaction and performance. In this respect, the degree and the levels of automation are also taken into account. Links to the operator's degree of personal autonomy are also made. The review also reveals research gaps and discusses options for designing this factor.
The scoping review on human-machine interaction is part of the project "Mental Health in the Working World - determining the current state of scientific evidence". The project assesses mental load factors by means of the state of scientific knowledge.
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