Publication: Correspondence Model Of Occupational Accidents
Loading...
Files
Full text at PDC
Publication Date
2010-12
Advisors (or tutors)
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
Acad Brasileira De Ciencias
Citations
Exportar
Abstract
We present a new generalized model for the diagnosis and prediction of accidents among the Spanish workforce. Based on observational data of the accident rate in all Spanish companies over eleven years (7,519,732 accidents), we classified them in a new risk-injury contingency table (19x19). Through correspondence analysis, we obtained a structure composed of three axes whose combination identifies three separate risk and injury groups, which we used as a general Spanish pattern. The most likely or frequent relationships between the risk and injuries identified in the pattern facilitated the decision-making process in companies at an early stage of risk assessment. Each risk-injury group has its own characteristics, which are understandable within the phenomenological framework of the accident. The main advantages of this model are its potential application to any other country and the feasibility of contrasting different country results. One limiting factor, however, is the need to set a common classification framework for risks and injuries to enhance comparison, a framework that does not exist today. The model aims to manage work-related accidents automatically at any level.
Description
UCM subjects
Unesco subjects
Keywords
Citation
AGUILERA AM. 2001. Tablas de contingencia bidimensionales.
Madrid: La Muralla, Col. Cuadernos de Estadística
15: 23–36.
AGUILERA AM. 2006. Modelización de tablas de contingencia
multidimensionales. Madrid: La Muralla, Col.
Cuadernos de Estadística 33: 25–28.
AMENDOLA A. 2002. Recent paradigms for risk informed
decision making. Safety Sci 40: 17–30.
BARAM M. 2009. Globalization and workplace hazards in
developing nations. Safety Sci 47: 756–766.
BARIL R, BERTHELETTE D AND MASSICOTTE P. 2003.
Early return towork of injuredworkers: multidimensional
patterns of individual and organizational factors. Safety
Sci 41: 277–300.
BECK U. 1999. World risk society. Cambridge: Polity Press.
BENZÉCRI J. 1992. Correspondence analysis handbook.
New York: Marcel Decker.
CONTE JC, CANO F, GARCIA AI AND RUBIO E. 2008.
Interpretación de las relaciones intragrupales de riesgos
y lesiones mediante análisis cluster jerárquico. Rev Mat
Teor Aplic 15: 175–186.
CONTE JC, MARCOS G, GARCIA AI AND RUBIO E. 2007.
Análisis del problema empírico de identificación del
riesgo. Cuad Bioest Aplic Infor 17: 12–25.
DOUGLAS M AND WILDAVSKY A. 1982. Risk and culture.
An essay on the selection of technical and environmental
dangers. Berkeley: University of California Press.
FINE W. 1973. Mathematical evaluations for controlling
hazards. Georgia: Academic Press, Selected Reading in
Safety, p. 1–22.
FRIJTERS A AND SWUSTE P. 2008. Safety assessment in
design and preparation phase. Safety Sci 46: 272–281.
GARCIA AI, CONTE JC, RUBIO E AND PEREZ A. 2009.
Accidente laboral. ACSOM una nueva orientación para
la gestión automática del riesgo. An Sist Sanit Navar
32: 23–34.
GIDDENS A. 1994. Les conséquences de la modernité. Paris:
L’Harmattan.
GREENACRE M AND BLASIUS J. 1994. Correspondence
analysis in social science. Recent developments and applications.
San Diego: Academic Press, p. 141–161.
GULDENMUND FW. 2000. The nature of safety culture: a
review of theory and research. Safety Sci 34: 215–257.
HAIR JF, ANDERSON RE, TATHAM RL AND BLACK WC.
1999. Análisis Multivariante. Madrid: Prentice Hall
Iberia SRL, 5th ed., p. 575–578.
HAMMER W. 1994. Unfallgefährdung und verhütung beim
Gehen, Laufen, Tragen, Schieben und Ziehen im landwirtschaftlichen
Betrieb. Safety Sci 17: 117–143.
HAND D, MANNILA H AND SMITH P. 2001. Principles of
data mining. London: Bradford Book, MIT Press.
JOARISTI L AND LIZASOAIN L. 1999. Análisis de correspondencias.
Madrid: La Muralla, Col. Cuadernos de Estadística
5: 35–52.
KJELLÉN U AND SKLET S. 1995. Integrating analyses of
the risk of occupational accidents into the design process.
Part I: A review of types of acceptance criteria and risk
analysis methods. Safety Sci 18: 215–227.
KÖRVERS P AND SONNEMANS P. 2008. Accidents: A discrepancy
between indicators and facts! Safety Sci 46:
1067–1077.
LAFLAMME L, DÖÖS M AND BACKSTRÖM T. 1991. Identifying
accidents patterns using the FAC and HAC: their
application to accidents at the engine workshops of an
automobile and truck factory. Safety Sci 14: 13–33.
LEVESON N. 2004. A new accident model for engineering
safer systems. Safety Sci 42: 237–270.
NACHREINER F, NICKEL P AND MEYER I. 2006. Human
factors in process control systems: The design of human
machine interfaces. Safety Sci 44: 5–26.
NICHOLSON A. 1998. Analysis of spatial distributions of
accidents. Safety Sci 31: 71–91.
RASMUSSEN J. 1997. Risk management in a dynamic society:
a modelling problem. Safety Sci 27: 183–213.
REAL JE. 2001. Escalamiento multidimensional. Madrid: La
Muralla, Col. Cuadernos de Estadística 14: 8–14.
ROUHIAINEN V. 1992. QUASA: A method for assessing the
quality of safety analysis. Safety Sci 15: 155–172.
RUBIO E. 1983. Estadística para médicos: fundamentos.
Universidad de Zaragoza, Cátedra de Bioestadística,
Facultad de Medicina, p. 119–122.
SARI M, SELCUK S, KARPUZ C AND DUZGUN S. 2009.
Stochastic modelling of accident risks associated with an
underground coal mine in Turkey. Safety Sci 47: 78–87.
SCHROEDER-FRECHETTE K. 1999. Risk. In: CRAIG E AND
FLORIDI L. Routledge Encyclopaedia of Philosophy.
London: Routledge.
VAN DUIJNE F, VAN AKEN D AND SCHOUTEN G. 2008.
Considerations in developing complete and quantified
methods for risk assessment. Safety Sci 46: 245–254.
WILLIAMSON A, FEYER A AND CAIRNS DR. 1996. Industry
differences in accident causation. Safety Sci 24: 1–12.
An Acad