Extracting recurrent scenarios from narrative texts using a Bayesian network: application to serious occupational accidents with movement disturbance.
A probabilistic approach has been developed to extract recurrent serious Occupational Accident with Movement Disturbance (OAMD) scenarios from narrative texts within a prevention framework. Relevant data extracted from 143 accounts was initially coded as logical combinations of generic accident factors. A Bayesian Network (BN)-based model was then built for OAMDs using these data and expert knowledge. A data clustering process was subsequently performed to group the OAMDs into similar classes from generic factor occurrence and pattern standpoints. Finally, the Most Probable Explanation (MPE) was evaluated and identified as the associated recurrent scenario for each class. Using this approach, 8 scenarios were extracted to describe 143 OAMDs in the construction and metallurgy sectors. Their recurrent nature is discussed. Probable generic factor combinations provide a fair representation of particularly serious OAMDs, as described in narrative texts. This work represents a real contribution to raising company awareness of the variety of circumstances, in which these accidents occur, to progressing in the prevention of such accidents and to developing an analysis framework dedicated to this kind of accident.
INRS - Working Life Department, 1 rue de Morvan, 54500 Vandoeuvre les Nancy, France.
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Abdat
INRS - Working Life Department, 1 rue de Morvan, 54500 Vandoeuvre les Nancy, France. Electronic address: sylvie.leclercq@inrs.fr.
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Leclercq
CNAM - Honorary Professor of Occupational Hygiene and Safety, 292 rue Saint-Martin, 75003 Paris, France.
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Cuny
INRS - Library & Literature Watch Division, 65 boulevard Richard Lenoir, 75011 Paris, France.
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Tissot
D000062:Accidents, Occupational / Q000517:prevention & control*; D001499:Bayes Theorem; D060389:Construction Industry; D006801:Humans; D008669:Metallurgy; D015233:Models, Statistical; D009068:Movement; D033262:Narration; D060051:Occupational Injuries / Q000209:etiology* / Q000517:prevention & control; D012307:Risk Factors
Bayesian network; Narrative text; Occupational accident with movement disturbance; Recurrent scenarios