Predicting return to work in a heterogeneous sample of recently injured workers using the brief ÖMPSQ-SF

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Purpose (1) to examine the ability of the Örebro Musculoskeletal Pain Screening Questionnaire-short version (ÖMPSQ-SF) to predict time to return to pre-injury work duties (PID) following a work-related soft tissue injury (regardless of body location); and (2) to examine the appropriateness of 50/100 as a suitable cut-off score for case identification. Methods Injured workers (IW) from six public hospitals in Sydney, Australia, who had taken medically-sanctioned time off work due to their injury, were recruited by insurance case managers within 5–15 days of their injury. Eligible participants (N=213 in total) were administered the ÖMPSQ-SF over the telephone by the case manager. For objective (1) Cox proportional hazards regression analysis was used to predict days to return to PID using the ÖMPSQ-SF. For objective (2) receiver operator characteristic (ROC) analysis was used to determine the ÖMPSQ-SF total score that optimises sensitivity and specificity in detecting whether or not participants had returned to PID within 2–7 weeks. Results The total ÖMPSQ-SF score significantly predicted number of days to return to PID, such that for every 1-point increase in the total ÖMPSQ-SF score the predicted chance of returning to work reduced by 4% (i.e., hazard ratio=0.96), p<0.001. Sensitivity and specificity for the ROC analysis comparing ÖMPSQ-SF total score to return to PID within 2–7 weeks suggested 48 as the optimal cut off (sensitivity=0.65, specificity=0.79). Conclusion The results provide strong support for the use of the ÖMPSQ-SF in an applied setting for identifying those IW likely to have delayed RTW when administered within 15 days of the injury. While a score of 48/100 was the optimal cut point for sensitivity and specificity, pragmatically, 50/100 should be acceptable as a cut-off in future studies of this type.

Abstract

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Acidentes de trabalho - Reabilitação, Acidentes de trabalho - Aspectos psicológicos, Salários

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Screening, Psychosocial factors, Worker’s compensation, Work injury

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https://cris.maastrichtuniversity.nl/ws/files/76002276/Smeets_2019_Predicting_Return_to_Work_in.pdf

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