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  • 1.
    Nilsson, A.
    et al.
    Uppsala University.
    Lindberg, P.
    Uppsala University.
    Denison, Eva
    Mälardalen University, School of Health, Care and Social Welfare.
    Predicting of pain, disability, and sick leave regarding a non-clinical sample among Swedish nurses2010In: Scandinavian Journal of Pain, ISSN 1877-8860, E-ISSN 1877-8879, Vol. 1, no 3, p. 160-166Article in journal (Refereed)
    Abstract [en]

    Objectives: 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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