Background

Autism spectrum disorder is a neurodevelopmental disorder, with consequences that continue through adulthood: despite good education and motivation, high functioning autism spectrum disorder individuals (HFA) often do not reach employment rates above 50 %, (Vogeley et al., 2013), despite the lack of intellectual disability (IQ>70) and their peak abilities potentially fruitful for many working environments.

Aims

Grounding in the view of mental health as not merely the absence of illness, but encompassing positive psychological dimensions of functioning, the aim of the research is to analyze the behavioral patterns of an HFA group performing a robotic collaborative task. Participants were asked to assemble a mechanic gear together with a cobot for the duration of 5 consecutive days, 3.5 hours a day.

Method

Data collection is ongoing with the aim of recruiting 10 HFA individuals. Two researchers interchangeably participated randomly in three days of data collection, taking unstructured notes of the observed behaviors. Data were processed by coding the annotations according to the SHELLO (Software‐Hardware‐Environment‐Liveware‐Liveware‐Organization) model (Chang & Wang, 2010), that is a conceptual framework which provide a systematic analysis of the human factors involved in complex sociotechnical systems. Inductive coding according to the qualitative content analysis (Mayring, 2000) was conducted to analyze the data.

Results

A group of 6 HFA participants already took part in the experiment. Preliminary evidence outlined behavioral patterns in the organization of the workflow (e.g., systematic strategy of loading the sub-assemblies on the table), in the management of the errors occurring during the task, and in the ability to process multiple operations at the same time, with better outcomes on productivity. The results will be integrated in a sociotechnical systems model, such as the SHELLO, which has been recently used to classify factors affecting physical and mental health of cobot workers (Storm et al., 2022).