doi:10.1136/bmjopen-2021-052602engBellosta-López, P.Domenech-Garcia, V.Palsson, T.S.Christensen, S.W.Silva, P.D.B.Langella, F.Berjano, P.Jensen, P.S.Riis, A.Baroncini, A.Blasco-Abadía, J.Jiménez-Sánchez, C.Calvo, S.Jaén-Carrillo, D.Herrero, P.Hoegh, M.European knowledge alliance for innovative measures in prevention of work-related musculoskeletal pain disorders (Prevent4Work Project): Protocol for an international mixed-methods longitudinal studyART-2021-127045Introduction Work-related musculoskeletal (MSK) pain is a highly prevalent condition and one of the main contributors to disability and loss of work capacity. Current approaches to the management and prevention of work-related MSK pain do not consistently integrate current evidence-based knowledge and seem to be outdated. The Prevent4Work (P4W) Project aims to collect and spread evidence-based information to improve the management and prevention of work-related MSK pain. P4W will longitudinally investigate (1) risk factors associated with the prevalence of work-related MSK pain, (2) predictive factors for new events of work-related MSK pain in the short term and (3) the modification of pain beliefs after participating in evidence-based e-learning courses. Methods and analysis This project employs a mixed-methods design with international cohorts of workers from Spain, Italy and Denmark. All participants will be assessed using self-reported variables at baseline (ie, cross-sectional design) with follow-up after 3 and 6 months (ie, prospective-predictive design). Throughout the first phase (0-3 months), all participants will be offered to self-enrol in e-learning courses on work-related MSK pain. Changes in pain beliefs (if any) will be assessed. The dataset will include sociodemographic characteristics, physical and psychological job demands, lifestyle-related factors, MSK pain history and pain beliefs. At baseline, all participants will additionally complete the P4W questionnaire developed to detect populations at high risk of suffering work-related MSK pain. Descriptive statistics, binary logistic regression, and analysis of variance will be used to identify the significant factors that influence the history of work-related MSK pain, evaluate the short-term prediction capacity of the P4W questionnaire, and investigate whether workers'' participation in e-learning courses will modify their pain beliefs. Ethics and dissemination The study received ethical approval from the Ethical Committee of San Jorge University (USJ011-19/20). The results will be made available via peer-reviewed publications, international conferences and P4W official channels.2021http://zaguan.unizar.es/record/13119810.1136/bmjopen-2021-052602http://zaguan.unizar.es/record/131198oai:zaguan.unizar.es:131198info:eu-repo/grantAgreement/ES/FPI/CPB09-2018info:eu-repo/grantAgreement/ES/MCIU/FPU19-05237BMJ Open 11, 9 (2021), e052602 [6 pp.]by-nchttp://creativecommons.org/licenses/by-nc/3.0/es/info:eu-repo/semantics/openAccess