Ranking sports science and medicine interventions impacting team performance: a protocol for a systematic review and meta-analysis of observational studies in elite football
This study protocol describes a systematic method to identify, collect and rank sports science and medicine interventions most associated with optimising team performance in elite football in observational studies. While numerous interventions, such as conditioning or injury prevention programmes, p...
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Veröffentlicht in: | BMJ Open Sport & Exercise Medicine 2024-09, Vol.10 (3), p.e002196 |
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Sprache: | eng |
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Zusammenfassung: | This study protocol describes a systematic method to identify, collect and rank sports science and medicine interventions most associated with optimising team performance in elite football in observational studies. While numerous interventions, such as conditioning or injury prevention programmes, protective equipment, training periodisation, tactical decision-making, supplements, medication and hydration administration, have been associated with football players and team performance enhancement, there is a need to prioritise them to save resources and increase the efficiency of applications. Nevertheless, previous literature has shown that systematic reviews in elite football often need more protocol registration and have limited procedures, synthesis and practical implications directly applicable to the field. Therefore, this protocol outlines a comprehensive process developed following the Cochrane Collaboration and Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement comprising the following stages: (1) research question formulation and preliminary study, (2) eligibility criteria, (3) search strategy, (4) study selection, (5) data collection, (6) data assessment and (7) data synthesis and statistical analysis. It also presents a data quality standard process incorporating human and large language models reviewers and a detailed flow diagram for selecting suitable quantitative synthesis and ranking techniques. It includes meta-regression, pairwise, network, Bayesian or hierarchical meta-analysis options. The project associated and pre-registration of the protocol is available on the Open Science Framework (https://osf.io/tzcxq/). |
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ISSN: | 2055-7647 2055-7647 |
DOI: | 10.1136/bmjsem-2024-002196 |