title: Using canonical commonality analysis to examine the predictive quality of aging and falls efficacy on balance functioning in older adults.
abstract: OBJECTIVE
  The effects of important variables measuring the psychobiological aspects of falls among older adults were considered to determine their utility in predicting balance functioning among older adults. To partition the effects of aging and falls efficacy on balance and leg strength simultaneously, canonical commonality analysis (CCA) was used.
  
  
  METHODS
  CCA is a multivariate technique which decomposes squared semipartial correlation effect sizes into constituent, nonoverlapping segments that describe unique and common explanatory powers of predictor variables. Data from a study conducted to examine the psychobiological and aging influences on unintended falls among physically active older adults were analyzed.
  
  
  RESULTS
  CCA showed balance confidence as measured by the Activities-Specific Balance Confidence Scale (ABC) and age to be noteworthy predictors of balance; yet, age was determined to be more important than balance confidence when predicting balance and leg strength (i.e., balance functioning) simultaneously. In addition, results suggest that data obtained from the ABC better predicted balance functioning among active older adults as compared to the Tinetti Falls Efficacy Scale (FES), a traditional measure used to assess the construct.
  
  
  CONCLUSIONS
  The ABC stands as a viable alternative to consider when assessing falls efficacy among dynamic older adults. Future research would benefit from using CCA to understand how various psychobiological constructs predict fall-related outcomes.
authors.affiliation: Department of Health Education and Behavior, University of Florida, Gainesville, FL 32611, USA. mstellefson@ufl.edu
authors.forename: Michael
authors.initials: M
authors.lastname: Stellefson
authors.forename: John F
authors.initials: JF
authors.lastname: Yannessa
authors.forename: Gregory F
authors.initials: GF
authors.lastname: Martel
mesh_terms: D000058:Accidental Falls / Q000706:statistics & numerical data*; D000367:Age Factors; D000368:Aged; D000375:Aging; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D007866:Leg / Q000502:physiology; D008297:Male; D053580:Muscle Strength; D004856:Postural Balance; D011237:Predictive Value of Tests; D011379:Prognosis; D011594:Psychometrics; D011787:Quality of Health Care; D013223:Statistics as Topic