Identifying most important predictors for suicidal thoughts and behaviours among healthcare workers active during the Spain COVID-19 pandemic: a machine-learning approach
Por:
Alayo I, Pujol O, Alonso J, Ferrer M, Amigo F, Portillo-Van Diest A, Aragonès E, Aragon Peña A, Asúnsolo Del Barco Á, Campos M, Espuga M, González-Pinto A, Haro JM, López-Fresneña N, Martínez de Salázar AD, Molina JD, Ortí-Lucas RM, Parellada M, Pelayo-Terán JM, Forjaz MJ, Pérez-Zapata A, Pijoan JI, Plana N, Polentinos-Castro E, Puig MT, Rius C, Sanz F, Serra C, Urreta-Barallobre I, Bruffaerts R, Vieta E, Pérez-Solá V, Mortier P and Gemma Vilagut Saiz
Publicada:
8 may 2025
Ahead of Print:
8 may 2025
Resumen:
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.Methods This is a prospective, multicentre cohort study of Spanish HCWs active during the COVID-19 pandemic. A total of 8,996 HCWs participated in the web-based baseline survey (May-July 2020) and 4,809 in the 4-month follow-up survey. A total of 219 predictor variables were derived from the baseline survey. The outcome variable was any STB at the 4-month follow-up. Variable selection was done using an L1 regularized linear Support Vector Classifier (SVC). A random forest model with 5-fold cross-validation was developed, in which the Synthetic Minority Oversampling Technique (SMOTE) and undersampling of the majority class balancing techniques were tested. The model was evaluated by the area under the Receiver Operating Characteristic (AUROC) curve and the area under the precision-recall curve. Shapley's additive explanatory values (SHAP values) were used to evaluate the overall contribution of each variable to the prediction of future STBs. Results were obtained separately by gender.Results The prevalence of STBs in HCWs at the 4-month follow-up was 7.9% (women = 7.8%, men = 8.2%). Thirty-four variables were selected by the L1 regularized linear SVC. The best results were obtained without data balancing techniques: AUROC = 0.87 (0.86 for women and 0.87 for men) and area under the precision-recall curve = 0.50 (0.55 for women and 0.45 for men). Based on SHAP values, the most important baseline predictors for any STB at the 4-month follow-up were the presence of passive suicidal ideation, the number of days in the past 30 days with passive or active suicidal ideation, the number of days in the past 30 days with binge eating episodes, the number of panic attacks (women only) and the frequency of intrusive thoughts (men only).Conclusions Machine learning-based prediction models for STBs in HCWs during the COVID-19 pandemic trained on web-based survey data present high discrimination and classification capacity. Future clinical implementations of this model could enable the early detection of HCWs at the highest risk for developing adverse mental health outcomes.Study registration NCT04556565
Filiaciones:
Alayo I:
Hospital del Mar Research Institute, Barcelona, Spain
Biosistemak Institute for Health Systems Research, Bilbao, Bizkaia, Spain
Red de Investigación en Cronicidad, Atención Primaria y Promoción de la Salud RICAPPS-(RICORS), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
Pujol O:
Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain
Alonso J:
Hospital del Mar Research Institute, Barcelona, Spain
Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
Ferrer M:
Hospital del Mar Research Institute, Barcelona, Spain
Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
Amigo F:
Hospital del Mar Research Institute, Barcelona, Spain
CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
Portillo-Van Diest A:
Hospital del Mar Research Institute, Barcelona, Spain
Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
Aragonès E:
Institut d'Investigació en Atenció Primària IDIAP Jordi Gol, Barcelona, Spain
Atenció Primària Camp de Tarragona, Institut Català de la Salut, Tarragona, Spain
Aragon Peña A:
Epidemiology Unit, Regional Ministry of Health, Community of Madrid, Madrid, Spain
Fundación Investigación e Innovación Biosanitaria de AP, Comunidad de Madrid, Madrid, Spain
Asúnsolo Del Barco Á:
Department of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, University of Alcala, Alcalá de Henares, Spain
Ramón y Cajal Institute of Sanitary Research (IRYCIS), Madrid, Spain
Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, The City University of New York, New York, NY, USA
Campos M:
Service of Prevention of Labor Risks, Medical Emergencies System, Generalitat de Catalunya, Barcelona, Spain
Espuga M:
Occupational Health Service, Hospital Universitari Vall d'Hebron, Barcelona, Spain
González-Pinto A:
BIOARABA, Hospital Universitario Araba-Santiago, UPV/EHU, Vitoria-Gasteiz, Spain
CIBER Salud Mental (CIBERSAM), Madrid, Spain
Haro JM:
CIBER Salud Mental (CIBERSAM), Madrid, Spain
Parc Sanitari Sant Joan de Déu, Institut de Recerca Sant Joan de Deu (IRSJD), Sant Boi de Llobregat, Barcelona, Spain
López-Fresneña N:
Hospital General Universitario Gregorio Marañón, Madrid, Spain
Martínez de Salázar AD:
UGC Salud Mental, Hospital Universitario Torrecárdenas, Almería, Spain
Molina JD:
CIBER Salud Mental (CIBERSAM), Madrid, Spain
Villaverde Mental Health Center, Clinical Management Area of Psychiatry and Mental Health, Psychiatric Service, Hospital Universitario 12 de Octubre, Madrid, Spain
Research Institute Hospital 12 de Octubre (i+12), Madrid, Spain
Facultad de Medicina, Universidad Francisco de Vitoria, Madrid, Spain
Ortí-Lucas RM:
Servicio de Medicina Preventiva y Calidad Asistencial, Hospital Clínic Universitari de Valencia, Valencia, Spain
Parellada M:
CIBER Salud Mental (CIBERSAM), Madrid, Spain
Hospital General Universitario Gregorio Marañón, Madrid, Spain
Pelayo-Terán JM:
CIBER Salud Mental (CIBERSAM), Madrid, Spain
Servicio de Psiquiatría y Salud Mental, Hospital el Bierzo, Gerencia de Asistencia Sanitaria del Bierzo (GASBI). Gerencia Regional de Salud de Castilla y Leon (SACYL), Ponferrada, León, Spain
Area de Medicina Preventiva y Salud Pública, Departamento de Ciencias Biomédicas, Universidad de León, León, Spain
Forjaz MJ:
Red de Investigación en Cronicidad, Atención Primaria y Promoción de la Salud RICAPPS-(RICORS), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
National Center of Epidemiology, Instituto de Salud Carlos III (ISCIII), Madrid, Spain
Pérez-Zapata A:
Hospital Universitario Príncipe de Asturias, Servicio de Prevención de Riesgos Laborales, Spain
Pijoan JI:
Red de Investigación en Cronicidad, Atención Primaria y Promoción de la Salud RICAPPS-(RICORS), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
Clinical Epidemiology Unit-Hospital Universitario Cruces/ OSI EEC, Biobizkaia Health Research Institute, Barakaldo, Spain
Plana N:
Red de Investigación en Cronicidad, Atención Primaria y Promoción de la Salud RICAPPS-(RICORS), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
Ramón y Cajal University Hospital, IRYCIS, Department of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, University of Alcalá, Alcala de Henares, MAD, Spain
Polentinos-Castro E:
Service of Prevention of Labor Risks, Medical Emergencies System, Generalitat de Catalunya, Barcelona, Spain
Research Unit, Primary Care Management, Madrid Health Service, Madrid, Spain
Department of Medical Specialities and Public Health, King Juan Carlos University, Madrid, Spain
Puig MT:
Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
Department of Epidemiology and Public Health, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain
CIBER Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
Rius C:
CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
Agència de Salut Pública de Barcelona, Barcelona, Spain
Sanz F:
Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra, Barcelona, Spain
Research Progamme on Biomedical Informatics (GRIB), Hospital del Mar Research Institute, Barcelona, Spain
Instituto Nacional de Bioinformatica - ELIXIR-ES, Barcelona, Spain
Serra C:
CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
CiSAL-Centro de Investigación en Salud Laboral, Hospital del Mar Research Institute/University Pompeu Fabra, Barcelona, Spain
Occupational Health Service, Hospital del Mar, Barcelona, Spain
Urreta-Barallobre I:
CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
Osakidetza Basque Health Service, Donostialdea Integrated Health Organisation, Donostia University Hospital, Clinical Epidemiology Unit, San Sebastián, Spain
Biodonostia Health Research Institute, Clinical Epidemiology, San Sebastián, Spain
Bruffaerts R:
Center for Public Health Psychiatry, Universitair Psychiatrisch Centrum, KU Leuven, Leuven, Belgium
Vieta E:
CIBER Salud Mental (CIBERSAM), Madrid, Spain
Institute of Neuroscience, Hospital Clinic, University of Barcelona, IDIBAPS, Barcelona, Spain
Pérez-Solá V:
CIBER Salud Mental (CIBERSAM), Madrid, Spain
Universitat Autònoma de Barcelona (UAB), Barcelona, Spain
Institute of Neuropsychiatry and Addiction (INAD), Parc de Salut Mar, Barcelona, Spain
Mortier P:
Hospital del Mar Research Institute, Barcelona, Spain
CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
Gemma Vilagut Saiz:
Hospital del Mar Research Institute, Barcelona, Spain
CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain
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