Sex differences in work-related accidents extracted from free text in Spanish using natural language processing

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dc.article.number2746
dc.catalogadorgrr
dc.contributor.authorDunstan Escudero, Jocelyn Mariel
dc.contributor.authorCampaña Herrera, Valentina Andrea
dc.contributor.authorMiranda, Luis
dc.contributor.authorLadron De Guevara Jara, Rocio Helena
dc.contributor.authorPincheira, Pablo
dc.contributor.authorRocco, Victor
dc.contributor.authorMoyano Dávila, Daniela Paz
dc.date.accessioned2025-08-21T15:37:54Z
dc.date.available2025-08-21T15:37:54Z
dc.date.issued2025
dc.date.updated2025-08-17T00:05:47Z
dc.description.abstractEvidence from the global north shows that women and men significantly differ in work accidents and occupational disease rates. However, more data is needed for countries elsewhere. Methods Using natural language processing (NLP), we extracted accident mechanisms from 350,000 admission reports from the largest occupational health provider in Chile. In addition, using the same technique, we normalize occupations written in free text, following the nomenclature from the International Labour Organization (ILO). Results We found that in 57.3% of accidents, a man is affected, while in 42.7% is a woman. The most common occupation for men is operator, while for women, it is related to cleaning duties. The most common form of accident for women is falling from the same height while for men is contact with sharp objects. In this work, we demonstrate the power of NLP in the massive analysis of work-related accidents by reporting the use of large language models with human expert annotation to evaluate mechanisms extraction. Conclusion By sharing our prompts and code, we aim to help other institutions and countries extract crucial information from free text to a controlled vocabulary of ILO. Future work includes the analysis of commuting accidents and occupational diseases.
dc.fechaingreso.objetodigital2025-08-17
dc.format.extent13 páginas
dc.fuente.origenBioMed Central
dc.identifier.doi10.1186/s12889-025-24130-z
dc.identifier.issn1471-2458
dc.identifier.urihttps://doi.org/10.1186/s12889-025-24130-z
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/105244
dc.information.autorucEscuela de Ingeniería; Dunstan Escudero, Jocelyn Mariel; 0000-0001-6726-7242; 1285723
dc.information.autorucEscuela de Ingeniería; Campaña Herrera, Valentina Andrea; 0009-0003-4813-4139; 1068849
dc.information.autorucEscuela de Ingeniería; Ladron De Guevara Jara, Rocio Helena; 0009-0006-4022-6313; 1133216
dc.information.autorucEscuela de Diseño; Moyano Dávila, Daniela Paz; 0000-0002-3454-1070; 206985
dc.issue.numero1
dc.language.isoen
dc.nota.accesocontenido completo
dc.revistaBMC Public Health
dc.rightsacceso abierto
dc.rights.licenseCC BY-NC-ND 4.0 Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.en
dc.subjectOccupational accidents
dc.subjectMechanisms
dc.subjectNatural language processing
dc.subjectSex-differences
dc.subject.ddc300
dc.subject.deweyCiencias socialeses_ES
dc.subject.ods03 Good health and well-being
dc.subject.odspa03 Salud y bienestar
dc.titleSex differences in work-related accidents extracted from free text in Spanish using natural language processing
dc.typeartículo
dc.volumen25
sipa.codpersvinculados1285723
sipa.codpersvinculados1068849
sipa.codpersvinculados1133216
sipa.codpersvinculados206985
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