Testing balance and fall risk in persons with Parkinson disease, an argument for ecologically valid testing

Parkinsonism Relat Disord. 2011 Mar;17(3):166-71. doi: 10.1016/j.parkreldis.2010.12.007. Epub 2011 Jan 6.


Introduction: Despite clear deficits in postural control, most clinical examination tools lack accuracy in identifying persons with Parkinson disease (PD) who have fallen or are at risk for falls. We assert that this is in part due to the lack of ecological validity of the testing.

Methods: To test this assertion, we examined the responsiveness and predictive validity of the Functional Gait Assessment (FGA), the Pull test, and the Timed up and Go (TUG) during clinically defined ON and OFF medication states. To address responsiveness, ON/OFF medication performance was compared. To address predictive validity, areas under the curve (AUC) of receiver operating characteristic (ROC) curves were compared. Comparisons were made using separate non-parametric tests.

Results: Thirty-six persons (24 male, 12 female) with PD (22 fallers, 14 non-fallers) participated. Only the FGA was able to detect differences between fallers and non-fallers for both ON/OFF medication testing. The predictive validity of the FGA and the TUG for fall identification was higher during OFF medication compared to ON medication testing. The predictive validity of the FGA was higher than the TUG and the Pull test during ON and OFF medication testing.

Discussion: In order to most accurately identify fallers, clinicians should test persons with PD in ecologically relevant conditions and tasks. In this study, interpretation of the OFF medication performance and use of the FGA provided more accurate prediction of those who would fall.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Accidental Falls*
  • Aged
  • Aged, 80 and over
  • Area Under Curve
  • Female
  • Gait / physiology
  • Humans
  • Male
  • Middle Aged
  • Neurologic Examination
  • Parkinson Disease / physiopathology*
  • Postural Balance / physiology*
  • Predictive Value of Tests
  • Psychomotor Performance / physiology*
  • Risk Assessment
  • Risk Factors
  • Statistics, Nonparametric