Identifying most important predictors for suicidal thoughts and behaviours among healthcare workers active during the Spain COVID-19 pandemic: a machine-learning approach - Itxaso Alayo; Oriol Pujol; Jordi Alonso; Montse Ferrer; Franco Amigo; Ana Portillo-Van Diest; Enric Aragonès; Andrés Aragon Peña; Ángel Asúnsolo Del Barco; Mireia Campos; Meritxell Espuga; Ana González-Pinto; et al. (Epidemiology and Psychiatric Sciences)
Abstract Aims Studies conducted during the COVID-19 pandemic found high occurrence of suicidal thoughts and behaviours (STBs) among healthcare workers (HCWs). The current study aimed to (1) develop a machine learning-based prediction model for future STBs using data from a large prospective cohort of Spanish HCWs and (2) identify the most important variables in terms of contribution to the model’s predictive accuracy.