Predictors of the effects of treatment for shoulder pain: protocol of an individual participant data meta-analysis

van der Windt, Danielle A.; Burke, Danielle L.; Babatunde, Opeyemi; Hattle, Miriam; McRobert, Cliona; Littlewood, Chris; Wynne-Jones, Gwenllian; Chesterton, Linda; van der Heijden, Geert J.M.G.; Winters, Jan C.; Rhon, Daniel I.; Bennell, Kim; Roddy, Edward; Heneghan, Carl; Beard, David; Rees, Jonathan L.; Riley, Richard D.

doi:10.1186/s41512-019-0061-x

All Outputs (1)

Predictors of the effects of treatment for shoulder pain: protocol of an individual participant data meta-analysis (2019)
Journal Article
van der Windt, D. A., Burke, D. L., Babatunde, O., Hattle, M., McRobert, C., Littlewood, C., Wynne-Jones, G., Chesterton, L., van der Heijden, G. J., Winters, J. C., Rhon, D. I., Bennell, K., Roddy, E., Heneghan, C., Beard, D., Rees, J. L., & Riley, R. D. (2019). Predictors of the effects of treatment for shoulder pain: protocol of an individual participant data meta-analysis. Diagnostic and Prognostic Research, 15 -?. https://doi.org/10.1186/s41512-019-0061-x

Background
Shoulder pain is one of the most common presentations of musculoskeletal pain with a 1-month population prevalence of between 7 and 26%. The overall prognosis of shoulder pain is highly variable with 40% of patients reporting persistent p... Read More about Predictors of the effects of treatment for shoulder pain: protocol of an individual participant data meta-analysis.