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- W2068167002 abstract "Low back pain (LBP) is a widespread musculoskeletal condition that frequently occurs in the working-age population (including hospital staff). This study proposes a classification-tree model to predict LBP risk levels in Sacré-Cœur Hospital, Lebanon (as a case study-236 chosen staffs) using various predictor individual and occupational factors. The developed tree model explained 80% of variance in LBP risk levels using standing hours/day (90% in relative importance), job status/sitting hours per day (80% each), body mass index (71%), working days/week (63%), domestic activity hours/week (36%), weight (35%), job dissatisfaction/sitting on ergonomic chairs (30% each), height (28%), gender (27%), sufficient break time (26%), using handling techniques/age (25% each), job stress (24%), marital status/wearing orthopedic insoles/extra professional activity (22% each), practicing prevention measures (20%), children care hours/week (16%), and type of sport activity/sports hours per week, car sitting, and fear of changing work due to LBP (15% each). The overall accuracy of this predictive tree once compared with actual subjects was estimated to be 77%. The proposed tree model can be used by expert physicians in their decision-making for LBP diagnosis among hospital staff." @default.
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- W2068167002 date "2013-08-01" @default.
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- W2068167002 title "The Application of a Classification-Tree Model for Predicting Low Back Pain Prevalence Among Hospital Staff" @default.
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- W2068167002 doi "https://doi.org/10.1080/19338244.2012.663010" @default.
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