title: Useful field of view predicts driving in the presence of distracters.
abstract: OBJECTIVE
  The Useful Field of View (UFOV) test has been shown to be highly effective in predicting crash risk among older adults. An important question which we examined in this study is whether this association is due to the ability of the UFOV to predict difficulties in attention-demanding driving situations that involve either visual or auditory distracters.
  
  
  METHODS
  Participants included 92 community-living adults (mean age 73.6 ± 5.4 years; range 65-88 years) who completed all three subtests of the UFOV involving assessment of visual processing speed (subtest 1), divided attention (subtest 2), and selective attention (subtest 3); driving safety risk was also classified using the UFOV scoring system. Driving performance was assessed separately on a closed-road circuit while driving under three conditions: no distracters, visual distracters, and auditory distracters. Driving outcome measures included road sign recognition, hazard detection, gap perception, time to complete the course, and performance on the distracter tasks.
  
  
  RESULTS
  Those rated as safe on the UFOV (safety rating categories 1 and 2), as well as those responding faster than the recommended cut-off on the selective attention subtest (350 msec), performed significantly better in terms of overall driving performance and also experienced less interference from distracters. Of the three UFOV subtests, the selective attention subtest best predicted overall driving performance in the presence of distracters.
  
  
  CONCLUSIONS
  Older adults who were rated as higher risk on the UFOV, particularly on the selective attention subtest, demonstrated poorest driving performance in the presence of distracters. This finding suggests that the selective attention subtest of the UFOV may be differentially more effective in predicting driving difficulties in situations of divided attention which are commonly associated with crashes.
authors.affiliation: School of Optometry and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia. j.wood@qut.edu.au
authors.forename: Joanne M
authors.initials: JM
authors.lastname: Wood
authors.forename: Alex
authors.initials: A
authors.lastname: Chaparro
authors.forename: Philippe
authors.initials: P
authors.lastname: Lacherez
authors.forename: Louise
authors.initials: L
authors.lastname: Hickson
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control* / Q000706:statistics & numerical data; D000368:Aged; D000369:Aged, 80 and over; D001288:Attention; D001334:Automobile Driving; D004215:Distance Perception / Q000502:physiology*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D015994:Incidence; D008297:Male; D009483:Neuropsychological Tests; D010364:Pattern Recognition, Visual / Q000502:physiology*; D011793:Queensland / Q000453:epidemiology; D012307:Risk Factors; D014794:Visual Fields / Q000502:physiology*