JOURNAL ARTICLE

A RATIONALE FOR ENHANCING CLINICAL OUTCOMES WITH APPLIED KINESIOLOGY.

  • Published In: Australasian College of Nutritional & Environmental Medicine Journal, 2024, v. 43, n. 1. P. 24 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Chetcuti, Trevor 3 of 3

Abstract

Whilst many sports have implemented strength programs as part of training to try to reduce the rate of injury, recent research is indicating neuromuscular control changes may be at the root of many of these problems. With sports that have relatively high rates of injury growing in participation, finding cost-effective and clinically efficient ways of improving the management and prevention of injuries is imperative. Research is starting to question the strength-hypertrophybased rehabilitation model highlighting the need to move toward a neuromuscular control model. However, assessing neuromuscular control can be difficult for the clinician. As such, eccentric exercise approaches based upon theoretical models are often taken to treatment rather than treatment protocols based on individual diagnosed neuro-muscular dysfunction. Functional Manual Muscle testing (fMMT) and Applied Kinesiology may provide a means of effectively assessing these mechanisms, the neurolomuscular interactions between muscles and various receptors and may play a key role in enhancing and advancing the prevention and recovery from injury. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Australasian College of Nutritional & Environmental Medicine Journal. 2024/03, Vol. 43, Issue 1, p24
  • Document Type:Article
  • Subject Area:Complementary and Alternative Medicine
  • Publication Date:2024
  • ISSN:1328-8040
  • Accession Number:180316875
  • Copyright Statement:Copyright of Australasian College of Nutritional & Environmental Medicine Journal is the property of Copyright Agency Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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