An AI will be able to detect if you are burnt out

A new method could well make it possible to effectively diagnose burnout. Based on Artificial Intelligence and text analysis, it would distinguish burnout from other syndromes or diseases.

Burnout is an eminently important subject at a time when part of the population seems close to Professional exhaustion. L’Artificial intelligence could it allow us to facilitate the diagnosis of burnout? While many tools and tests exist on Internet to try to answer this question, new method, based on artificial intelligence and the use of automatic natural language processing, could well offer new perspectives. The NLP (Natural Language Processing) is a technology that consists of automatically analyzing sentences formulated by a human in order to make a decision or identify a behaviour.

Between depression, chronic fatigue and burnout

In order to succeed in detecting in texts indicators of burn-out, it is necessary to accumulate a large amount of data. The construction of this model was made through the Reddit platform. The grouping phase consisted of storing anonymous texts about experiences of all kinds with no less than 13,568 samples.

In this cluster of stories, 352 were related to burnout and 979 to depression. The objective for the model is to succeed in automatically detecting which are the sayings related to burnout. This method has achieved a success rate of about 93% in identifying cases of burnout. ” Automatic language processing is effective in detecting burnout while being less time-consuming, which is very promising “, explains Mascha Kurpicz-Briki, professor of data engineering at the Bern University of Applied Sciences, in Biel, Switzerland, in charge of the project.

Support for healthcare professionals

According to High Authority of Health (HAS), burnout is defined as ” an exhaustion physicalemotional and mental that results from prolonged investment in emotionally demanding work situations “. The main symptoms can be physical, emotional or even cognitive with the onset of sleeping troubles, anxiety or emotional fatigue. The World Health Organization (WHO) characterizes it by a feeling of exhaustion.

As promising as the results of the model on these anonymous texts may be, the presence of humans should not be overlooked, according to the authors. Instead of replacing health professionals and mental health specialists, this technology must remain a support. Indeed, the accumulation of data and its analysis in a few movements must support the healthcare professional in his decision-making.

To definitively verify the conclusions around the model, the next step will consist in using this method on real cases representative of the population and no longer on anonymous testimonies.