SynthesisSports medicine (Auckland, N.Z.)2025
Guiding Evidence-Based Classification in Para Sporting Populations: A Systematic Review of Impairment Measures and Activity Limitations.
Synthesis in Sports medicine (Auckland, N.Z.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
7 citing papers in PubMed.
- Qualitative investigation evaluating Team USA Paralympic athletes: resources and recommendations for enhancing support systems.BMJ open · 2026Article
- Machine Learning in Adapted Physical Activity: Clinical Applications, Monitoring, and Implementation Pathways for Personalized Exercise in Chronic Conditions: A Narrative Review.Journal of functional morphology and kinesiology · 2026Review
- Sport performance in virtual worlds: a systematic review of sport simulation in neurological paralympic athletes and non-athlete populations.BMC sports science, medicine & rehabilitation · 2026Article
- Pregnancy and postpartum experiences of elite para athletes: a cross-sectional survey.Frontiers in sports and active living · 2026Article
- Public policies for the promotion of paralympic sport in Latin America: a comparative analysis of 10 countries.Frontiers in sports and active living · 2026Article
- From guesswork to guidance: a delphi study on practices of talent identification and development in Para athletics.Frontiers in sports and active living · 2026Article
- Standardised activities in wheelchair rugby, comparison between athletes with coordination impairment and athletes with other impairments.Frontiers in sports and active living · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAs the focus of classification shifts towards an evidence-based approach, it is crucial to establish a robust system that relies on valid and reliable measures of impairment to ensure legitimate and competitive opportunities for all Para athletes. However, the lack of methods that possess the necessary measurement properties for assessing impairments in Para sporting populations presents significant challenges to developing an evidence-based classification system.
objectiveThis review aimed to identify and evaluate measures of impairment and activity limitation measures that have been used to assess eligible impairments in Para sport athletes for potential use in evidence-based classification.
methodsSix electronic databases (MEDLINE, Embase, SPORTDiscus, CINAHL, Scopus, Web of Science) were searched from their earliest record to December 2023.
resultsFifty-one articles were identified, with twenty-one studies focusing on physical impairment measures. Isometric and grip strength emerged as effective measures. Coordination measures, such as tapping tasks, showed variations with performance. Additionally, six studies focused on intellectual impairments, revealing differences between impaired and non-impaired athletes through generic cognitive tests. Vision impairment measures, including visual acuity and visual field assessments, displayed varying associations with performance across sports.
conclusionsAlthough research on evidence-based classification in Para sport is limited, this review provides valuable insights for sports in developing a testing battery that adheres to evidence-based protocols. Ongoing research efforts by sport governing bodies to prioritise research in this area will improve our understanding of the impairment-performance relationship, leading to better decision making and increased credibility in Para sport classification systems.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.