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Updated: Feb 8, 2026

An Experimental Paradigm for the Prediction of Post-Operative Pain PPOP
Published on: January 27, 2010
Predicting of pain, disability, and sick leave regarding a non-clinical sample among Swedish nurses
Annika Nilsson1, Per Lindberg2, Eva Denison2,3
1Department of Caring Science and Sociology, University of Gävle, Gävle, Sweden.
Objective Health care providers, especially registered nurses (RNs), are a professional group with a high risk of musculoskeletal pain (MSP). This longitudinal study contributes to the literature by describing the prevalence and change in MSP, work-related factors, personal factors, self-reported pain, disability and sick leave (>7 days) among RNs working in a Swedish hospital over a 3-year period. Further, results concerning prediction of pain, disability and sick leave from baseline to a 3-year follow-up are reported. Method In 2003, a convenience sample of 278 RNs (97.5% women, mean age 43 years) completed a questionnaire. In 2006, 244 RNs (88% of the original sample) were located, and 200 (82%) of these completed a second questionnaire. Results Logistic regression analyses revealed that pain, disability and sick leave at baseline best predicted pain, disability, and sick leave at follow-up. The personal factors self-rated health and sleep quality during the last week predicted pain at follow-up, while age, self-rated health, and considering yourself as optimist or pessimist predicted disability at follow-up, however weakly. None of the work-related factors contributed significantly to the regression solution. Conclusions The results support earlier studies showing that a history of pain and disability is predictive of future pain and disability. Attention to individual factors such as personal values may be needed in further research.
Objective Health care providers, especially registered nurses (RNs), are a professional group with a high risk of musculoskeletal pain (MSP). This longitudinal study contributes to the literature by describing the prevalence and change in MSP, work-related factors, personal factors, self-reported pain, disability and sick leave (>7 days) among RNs working in a Swedish hospital over a 3-year period. Further, results concerning prediction of pain, disability and sick leave from baseline to a 3-year follow-up are reported. Method In 2003, a convenience sample of 278 RNs (97.5% women, mean age 43 years) completed a questionnaire. In 2006, 244 RNs (88% of the original sample) were located, and 200 (82%) of these completed a second questionnaire. Results Logistic regression analyses revealed that pain, disability and sick leave at baseline best predicted pain, disability, and sick leave at follow-up. The personal factors self-rated health and sleep quality during the last week predicted pain at follow-up, while age, self-rated health, and considering yourself as optimist or pessimist predicted disability at follow-up, however weakly. None of the work-related factors contributed significantly to the regression solution. Conclusions The results support earlier studies showing that a history of pain and disability is predictive of future pain and disability. Attention to individual factors such as personal values may be needed in further research.
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