The global spread of the COVID-19 virus has become one of the greatest challenges that humanity has faced in recent years. The unprecedented circumstances of forced isolation and uncertainty that it has imposed on us continue to impact our mental well-being, whether or not we have been directly affected by the virus. Over a period of nearly three years (2017-2020), data was collected from multiple administrations of the Rorschach test, one of the most renowned and extensively studied psychological tests. This study involved the clustering of data, collected through the RAP3 software, to analyze the distinctive trends in data recorded before and after the pandemic. This was achieved through the implementation of the well-established machine learning algorithm, Expectation-Maximization. The proposed solution effectively identifies the key variables that significantly influence the subject’s score and provides a reliable solution. Additionally, the solution offers an intuitive visualization that can assist psychologists in accurately interpreting shifts in trends and response distributions within a large amount of data in the two periods.
2022, CEUR workshop proceedings, Pages 55-63 (volume: 3360)
Analysis pre and post covid-19 pandemic rorschach test data of using em algorithms and gmm models (04b Atto di convegno in volume)
Ponzi Valerio, Russo Samuele, Agata Wajda, Rafa Brociek, Napoli Christian
Gruppo di ricerca: Artificial Intelligence and Robotics