European knowledge alliance for innovative measures in prevention of work-related musculoskeletal pain disorders (Prevent4Work Project): protocol for an international mixed-methods longitudinal study

Bellosta-López, Pablo; Domenech-Garcia, Victor; Palsson, Thorvaldur Skuli; Christensen, Steffan Wittrup; Silva, Priscila de Brito; Langella, Francesco; Berjano, Pedro; Jensen, Palle Schlott; Riis, Allan; Baroncini, Alice; Blasco-Abadía, Julia; Jiménez-Sánchez, Carolina; Calvo, Sandra; Jaén-Carrillo, Diego; Herrero, Pablo; Hoegh, Morten

INTRODUCTION: 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and prevention of work-related MSK pain do not consistently integrate current evidence-based knowledge and seem to be outdated.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.