title: The application of a classification-tree model for predicting low back pain prevalence among hospital staff.
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.
authors.affiliation: Physiotherapy Service, Sacré-Coeur Hospital, Baabda, Lebanon. fadymendelek@hotmail.com
authors.forename: Fady
authors.initials: F
authors.lastname: Mendelek
authors.forename: Isabelle
authors.initials: I
authors.lastname: Caby
authors.forename: Patrick
authors.initials: P
authors.lastname: Pelayo
authors.forename: Rania Bou
authors.initials: RB
authors.lastname: Kheir
mesh_terms: D000328:Adult; D000368:Aged; D003663:Decision Trees; D005260:Female; D006801:Humans; D007861:Lebanon / Q000453:epidemiology; D017116:Low Back Pain / Q000175:diagnosis* / Q000453:epidemiology* / Q000209:etiology; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D060051:Occupational Injuries / Q000175:diagnosis* / Q000453:epidemiology* / Q000209:etiology; D010564:Personnel, Hospital; D015995:Prevalence; D018570:Risk Assessment; D012307:Risk Factors; D011795:Surveys and Questionnaires; D055815:Young Adult