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Heading in football: a systematic review of descriptors, definitions, and reporting methods used in heading incidence studies.

Kerry PeekAndrew George RossThor Einar AndersenTim MeyerSara DahlenJulia GeorgievaPaula R WilliamsonMichael ClarkeAndreas Serner
Published in: Science & medicine in football (2024)
The primary objective of this systematic review was to describe the number and type of heading descriptors used in all published studies which report on heading incidence in football. The secondary objective was to detail the data collection and reporting methods used in the included studies to present heading incidence data. Eligible studies were identified through searches of five electronic databases: Ovid MEDLINE, CINAHL, EMBASE, SPORTDiscus, and Web of Science, using a combination of free-text keywords (inception to 12th September 2023). Manual searching of reference lists and retrieved systematic reviews was also performed. A descriptive overview and synthesis of the results is presented. From 1620 potentially eligible studies, 71 studies were included, with the following key findings: 1) only 61% of studies defined a header with even fewer (23%) providing an operational definition of a header within the methods; 2) important study and player demographic data including year and country were often not reported; 3) reported heading descriptors and their coding options varied greatly; 4) visual identification of headers was essential when inertial measurement units were used to collect heading incidence data; and 5) there was a lack of standardisation in the reporting methods used in heading incidence studies making comparison between studies challenging. To address these findings, the development of a standardised, internationally supported, operational definition of a header and related heading descriptors should be prioritised. Further recommendations include the development of minimum reporting criteria for heading incidence research.
Keyphrases
  • systematic review
  • case control
  • risk factors
  • electronic health record
  • big data
  • adverse drug
  • public health
  • emergency department
  • meta analyses
  • deep learning
  • artificial intelligence
  • bioinformatics analysis