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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.

Intensive care programs are very useful for the treatment of chronic low back pain; however, the initial pain intensity reported by patients may affect the degree of improvement following participation in such programs. The authors of this article aimed to determine whether an intensive spine functional restoration program would be as effective for individuals presenting with severe pain as those presenting with mild to moderate pain.

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