title: Cognitive abilities that predict success in a computer-based training program.
abstract: OBJECTIVE
  The purposes of this study were (a) to identify cognitive abilities and other factors related to successful completion of training for computer-based tasks that simulated real jobs and (b) to create a brief assessment battery useful in assessing older adults for these kinds of jobs.
  
  
  METHODS
  Participants from three age groups (young, middle-aged, and older) completed a battery of cognitive measures. They then trained on one of three computer-based tasks that simulated actual jobs and were asked to perform the tasks for 3 days. We recorded whether they completed training and whether and how well they did the tasks. In a series of logistic regressions, we evaluated the ability of a subset of cognitive measures drawn from a larger battery to predict participants' ability to successfully complete training and go on to task performance.
  
  
  RESULTS
  Results confirmed theory-based expectations that measures of domain knowledge, crystallized intelligence, memory, and psychomotor speed would predict success in computer-based activities. A brief battery was able to predict older adults' successful completion of training for one task but was less useful for another.
  
  
  CONCLUSIONS
  A brief battery of cognitive measures may be useful in evaluating individuals for job selection. Different measures are related to job-related criteria depending on task and group evaluated, although it was not possible to identify a reduced battery for one task. The specific cognitive abilities related to participants' success have implications for task and interface design for the elderly population.
authors.affiliation: University of Miami Memory Disorders Clinic, 1400 NW 10 Ave. Suite 702, Miami, FL 33136, USA. rownby@med.miami.edu
authors.forename: Raymond L
authors.initials: RL
authors.lastname: Ownby
authors.forename: Sara J
authors.initials: SJ
authors.lastname: Czaja
authors.forename: David
authors.initials: D
authors.lastname: Loewenstein
authors.forename: Mark
authors.initials: M
authors.lastname: Rubert
mesh_terms: D000328:Adult; D000368:Aged; D001076:Aptitude; D003071:Cognition; D003194:Computer-Assisted Instruction; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D008875:Middle Aged; D013647:Task Performance and Analysis; D014584:User-Computer Interface