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Models of Injury Occurrence, Prevention and Prediction

            Methods
            Design and Conceptual Approach
            This contribution was developed as a conceptual and integrative synthe-
            sis of models used to explain injury occurrence, guide injury-prevention
            planning, support implementation in practice, and inform quantita-
            tive estimation of injury risk in sport. The methodological approach is
            descriptive-comparative in nature, with the primary objective of sum-
            marising and contrasting influential conceptual frameworks in order to
            highlight their theoretical assumptions, practical implications, and ap-
            plicability within sport settings.
              Rather than evaluating intervention effectiveness quantitatively, the
            contribution focuses on how different models conceptualise injury cau-
            sation, prevention processes, implementation challenges, and predictive
            approaches to injury risk. This approach was selected because sports-
            injury prevention involves complex interactions among biomechanical,
            behavioural, organisational, and contextual factors that are not ade-
            quately captured through isolated empirical findings alone.

            Literature Search Strategy
            To support the identification of influential models and key conceptual
            papers, targeted literature searches were conducted across several in-
            ternationally recognised scientific databases, including PubMed/MED-
            LINE, Scopus, Web of Science Core Collection, and ScienceDirect. No
            publication-year restrictions were applied in order to include both foun-
            dational theoretical models and more recent developments in sports-
            injury research, implementation science, and risk prediction.
              Search strategies combined terms related to sports injuries, preven-
            tion frameworks, implementation, and predictive modelling. Represen-
            tative search strings included combinations such as:
              • (sport OR athlete OR ‘team sport’) AND (injur* OR ‘sport injur*’)
                AND (model OR framework OR prevention OR implementation OR
                translation)*
              • (TRIPP OR Haddon OR ‘epidemiological model’ OR ‘injury predic-
                tion’ OR ‘risk prediction’ OR ‘logistic regression’ OR ‘injury risk’)
              Boolean operators and database-specific indexing terms were used
            where appropriate to broaden or refine search outputs. In addition to
            database searches, reference lists of influential publications and consen-
            sus statements were manually screened to identify additional relevant
            sources.

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