Determination of Dimensionality of the Psychosocial Risk Assessment of Internal, Individual, Double Presence and External Factors in Work Environments-Reference-Cited by-同舟云学术

Determination of Dimensionality of the Psychosocial Risk Assessment of Internal, Individual, Double Presence and External Factors in Work Environments

Published:2018 Issue: Volume: Page:304-313
ISSN:0302-9743
Container-title:Data Mining and Big Data
language:
Short-container-title:

Author:

Viloria Amelec,Bucci Nunziatina,Luna Marisabel,Lis-Gutiérrez Jenny-Paola,Parody Alexander,Bent Darwin Eliecer Solano,López Luz A. Borrero

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-93803-5_29

Reference14 articles.

1. Ministerio de Protección Social: Plan Nacional de Salud Ocupacional 2003–2007. Ministerio de la Protección Social, Bogotá (2004)

2. Oficina Internacional del Trabajo: Factores psicosociales en el trabajo: Naturaleza, incidencia y prevención. Serie de Seguridad, Higiene y Medicina del Trabajo. Número 56. Informe del Comité Mixto OIT-OMS sobre medicina del Trabajo. Novena reunión. Ginebra (1984)

3. Bucci, N., Luna, M.: Modelo de evaluación de riesgos psicosociales determinado por factores internos, individuales, doble presencia y externos para entornos laborales. Universidad Nacional experimental politécnica Antonio José de Sucre, Barquisimeto (2013)

4. Vega, S.: Riesgo psicosocial: el modelo demanda-control-apoyo social (I). Notas Técnicas de Prevención Nº 603, España (2003)

5. Organización Mundial de la Salud: Commission on social determinants of health. A conceptual framework for action on the social determinants of health. (Discussion paper), Geneve (2007)

Cited by 18 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Measuring Acceptance of Adoption Metaverse in eLearning by Using TAM Model;2023 International Conference on Information Technology (ICIT);2023-08-09

2. Towards the Prediction of Students’ Performance Using Educators’ Domain Knowledge;Advances on Intelligent Computing and Data Science;2023

3. Convolutional Neural Networks in the Identification of Benign and Malignant Melanomas;Advances in Intelligent Systems and Computing;2021

4. Classification of Clinical Reports for Supporting Cancer Diagnosis;Advances in Intelligent Systems and Computing;2021

5. Morphometric Characteristics in Discrete Domain for Brain Tumor Recognition;Advances in Intelligent Systems and Computing;2020-08-07