Does graded motor imagery benefit individuals with knee pain: A systematic review and meta-analysis

J Bodyw Mov Ther. 2023 Jul:35:130-139. doi: 10.1016/j.jbmt.2023.05.005. Epub 2023 May 3.

Abstract

Objective: Evaluate how Graded Motor Imagery (GMI) may be used in those with knee pain, if individuals with knee pain present with a central nervous system (CNS) processing deficit, and if GMI is associated with improved outcomes.

Methods: An electronic database search was conducted of PubMed, SPORTDiscus, CINHAL, MEDLINE, Google Scholar, and Sports Medicine Education Index using keywords related to GMI and knee pain. This review was reported following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Out of the 13,224 studies reviewed, 14 studies were included that used GMI for knee pain. Effect sizes were reported with standardized mean differences (SMD).

Results: Individuals with knee osteoarthritis demonstrated poor performance with correctly identifying images of left or right knees, and GMI improved performance. In contrast, individuals with an anterior cruciate ligament injury demonstrated no evidence of CNS processing deficit and mixed outcomes with GMI. Meta-analysis was limited to individuals post total knee arthroplasty showing low certainty that GMI can improve quadriceps force production [SMD 0.64 (0.07,1.22)], but evidence of no effect to reduce pain or improve Timed up and Go performance and self-reported function.

Conclusions: Graded motor imagery may be an effective intervention for individuals with knee osteoarthritis. However, there was limited evidence that GMI was effective for an anterior cruciate ligament injury.

Keywords: Anterior cruciate ligament; Central nervous system; Graded motor imagery; Kinesiophobia; Knee osteoarthritis.

Publication types

  • Meta-Analysis
  • Systematic Review
  • Review

MeSH terms

  • Anterior Cruciate Ligament Injuries*
  • Arthroplasty, Replacement, Knee*
  • Humans
  • Knee Joint / surgery
  • Osteoarthritis, Knee*
  • Pain