Скачать или смотреть Predicting Mental Distress

This document outlines research focused on predicting mental distress in remote IT workers, specifically in Sri Lanka during the COVID-19 pandemic, using machine learning techniques. The authors investigated how various external factors, such as socio-demographic, biological, economic, environmental, occupational, and psychological aspects, influence mental health conditions like depression, anxiety, and stress. The study involved a survey of 481 IT professionals, utilizing established diagnostic scales to categorize mental distress. Several machine learning algorithms were tested, with the CatBoost algorithm demonstrating the highest predictive accuracy at 97.1%. The research aims to develop an automated screening system to identify individuals at high risk for mental distress and facilitate early professional assistance.
Full paper: https://tinyurl.com/c6hujx6h
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